Task1NFL.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "5b626a9b-f2f7-4da2-99af-35c12e41f7c8",
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np # linear algebra\n",
    "import pandas as pd # data processing, CSV file I/O (e.g. pd.read_csv)\n",
    "import seaborn as sns\n",
    "import matplotlib.pyplot as plt\n",
    "import matplotlib.patches as patches\n",
    "from matplotlib.patches import Arc\n",
    "from matplotlib import pyplot as plt\n",
    "import matplotlib.patches as mpatches\n",
    "import matplotlib.animation as animation\n",
    "from IPython.display import HTML\n",
    "import warnings\n",
    "warnings.filterwarnings(\"ignore\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "187d85b8-0fa6-4185-8c7f-191a291a71a0",
   "metadata": {},
   "outputs": [],
   "source": [
    "gameData = pd.read_csv('games.csv', dayfirst=False, parse_dates=[3])\n",
    "playsData = pd.read_csv('plays.csv')\n",
    "playersData = pd.read_csv('players.csv')\n",
    "pffData = pd.read_csv('PFFScoutingData.csv')\n",
    "trackingData2018 = pd.read_csv(\"tracking2018.csv\")\n",
    "trackingData2019 = pd.read_csv(\"tracking2019.csv\")\n",
    "trackingData2020 = pd.read_csv(\"tracking2020.csv\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "d9a152ff-553e-44a4-a14c-f6c971af9d5d",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "\u001b[1;30;42m Game Data Columns Datatypes: \u001b[0m\n",
      "Memory Usage for\u001b[1;31;43m float \u001b[0;0mColumns:\u001b[1m 0.00 MB \u001b[0m\n",
      "Memory Usage for\u001b[1;31;43m int \u001b[0;0mColumns:\u001b[1m 0.02 MB \u001b[0m\n",
      "Memory Usage for\u001b[1;31;43m object \u001b[0;0mColumns:\u001b[1m 0.13 MB \u001b[0m\n",
      "\u001b[1mTotal Memory Usage Before Optimization:\u001b[1;30;45m 0.16 MB \u001b[0;0m\n",
      "\n",
      "\u001b[1;30;42m Plays Data Columns Datatypes: \u001b[0m\n",
      "Memory Usage for\u001b[1;31;43m float \u001b[0;0mColumns:\u001b[1m 0.76 MB \u001b[0m\n",
      "Memory Usage for\u001b[1;31;43m int \u001b[0;0mColumns:\u001b[1m 1.52 MB \u001b[0m\n",
      "Memory Usage for\u001b[1;31;43m object \u001b[0;0mColumns:\u001b[1m 11.45 MB \u001b[0m\n",
      "\u001b[1mTotal Memory Usage Before Optimization:\u001b[1;30;45m 13.74 MB \u001b[0;0m\n",
      "\n",
      "\u001b[1;30;42m Players Data Columns Datatypes: \u001b[0m\n",
      "Memory Usage for\u001b[1;31;43m float \u001b[0;0mColumns:\u001b[1m 0.00 MB \u001b[0m\n",
      "Memory Usage for\u001b[1;31;43m int \u001b[0;0mColumns:\u001b[1m 0.04 MB \u001b[0m\n",
      "Memory Usage for\u001b[1;31;43m object \u001b[0;0mColumns:\u001b[1m 0.84 MB \u001b[0m\n",
      "\u001b[1mTotal Memory Usage Before Optimization:\u001b[1;30;45m 0.88 MB \u001b[0;0m\n",
      "\n",
      "\u001b[1;30;42m PFF Data Columns Datatypes: \u001b[0m\n",
      "Memory Usage for\u001b[1;31;43m float \u001b[0;0mColumns:\u001b[1m 0.46 MB \u001b[0m\n",
      "Memory Usage for\u001b[1;31;43m int \u001b[0;0mColumns:\u001b[1m 0.30 MB \u001b[0m\n",
      "Memory Usage for\u001b[1;31;43m object \u001b[0;0mColumns:\u001b[1m 12.29 MB \u001b[0m\n",
      "\u001b[1mTotal Memory Usage Before Optimization:\u001b[1;30;45m 13.06 MB \u001b[0;0m\n",
      "\n",
      "\u001b[1;30;42m Tracking Data 2018 Columns Datatypes: \u001b[0m\n",
      "Memory Usage for\u001b[1;31;43m float \u001b[0;0mColumns:\u001b[1m 877.35 MB \u001b[0m\n",
      "Memory Usage for\u001b[1;31;43m int \u001b[0;0mColumns:\u001b[1m 292.45 MB \u001b[0m\n",
      "Memory Usage for\u001b[1;31;43m object \u001b[0;0mColumns:\u001b[1m 4771.36 MB \u001b[0m\n",
      "\u001b[1mTotal Memory Usage Before Optimization:\u001b[1;30;45m 5941.16 MB \u001b[0;0m\n",
      "\n",
      "\u001b[1;30;42m Tracking Data 2019 Columns Datatypes: \u001b[0m\n",
      "Memory Usage for\u001b[1;31;43m float \u001b[0;0mColumns:\u001b[1m 835.71 MB \u001b[0m\n",
      "Memory Usage for\u001b[1;31;43m int \u001b[0;0mColumns:\u001b[1m 278.57 MB \u001b[0m\n",
      "Memory Usage for\u001b[1;31;43m object \u001b[0;0mColumns:\u001b[1m 4544.09 MB \u001b[0m\n",
      "\u001b[1mTotal Memory Usage Before Optimization:\u001b[1;30;45m 5658.38 MB \u001b[0;0m\n",
      "\n",
      "\u001b[1;30;42m Tracking Data 2020 Datatypes: \u001b[0m\n",
      "Memory Usage for\u001b[1;31;43m float \u001b[0;0mColumns:\u001b[1m 811.73 MB \u001b[0m\n",
      "Memory Usage for\u001b[1;31;43m int \u001b[0;0mColumns:\u001b[1m 270.58 MB \u001b[0m\n",
      "Memory Usage for\u001b[1;31;43m object \u001b[0;0mColumns:\u001b[1m 4415.52 MB \u001b[0m\n",
      "\u001b[1mTotal Memory Usage Before Optimization:\u001b[1;30;45m 5497.83 MB \u001b[0;0m\n"
     ]
    }
   ],
   "source": [
    "def memoryUsagePerDatatype(dataFrame):\n",
    "    types = ['float','int','object']\n",
    "    for type in types:\n",
    "        columns = dataFrame.select_dtypes(include=[type])\n",
    "        memoryUsageInBytes = columns.memory_usage(deep=True).sum()\n",
    "        memoryUsageInMegaBytes=memoryUsageInBytes/1024**2\n",
    "        print(\"Memory Usage for\\033[1;31;43m {} \\033[0;0mColumns:\\033[1m {:03.2f} MB \\033[0m\".format(type,memoryUsageInMegaBytes))\n",
    "\n",
    "        \n",
    "def memoryUsage(dataFrame):\n",
    "    return dataFrame.memory_usage(deep=True).sum()/1024**2\n",
    "\n",
    "\n",
    "print('\\n' + '\\033[1;30;42m' + ' Game Data Columns Datatypes: ' + '\\033[0m')\n",
    "memoryUsagePerDatatype(gameData)\n",
    "print('\\033[1mTotal Memory Usage Before Optimization:\\033[1;30;45m {:.2f} MB \\033[0;0m'.format(memoryUsage(gameData)))\n",
    "print('\\n' + '\\033[1;30;42m' + ' Plays Data Columns Datatypes: ' + '\\033[0m')\n",
    "memoryUsagePerDatatype(playsData)\n",
    "print('\\033[1mTotal Memory Usage Before Optimization:\\033[1;30;45m {:.2f} MB \\033[0;0m'.format(memoryUsage(playsData)))\n",
    "print('\\n' + '\\033[1;30;42m' + ' Players Data Columns Datatypes: ' + '\\033[0m')\n",
    "memoryUsagePerDatatype(playersData)\n",
    "print('\\033[1mTotal Memory Usage Before Optimization:\\033[1;30;45m {:.2f} MB \\033[0;0m'.format(memoryUsage(playersData)))\n",
    "print('\\n' + '\\033[1;30;42m' + ' PFF Data Columns Datatypes: ' + '\\033[0m')\n",
    "memoryUsagePerDatatype(pffData)\n",
    "print('\\033[1mTotal Memory Usage Before Optimization:\\033[1;30;45m {:.2f} MB \\033[0;0m'.format(memoryUsage(pffData)))\n",
    "print('\\n' + '\\033[1;30;42m' + ' Tracking Data 2018 Columns Datatypes: ' + '\\033[0m')\n",
    "memoryUsagePerDatatype(trackingData2018)\n",
    "print('\\033[1mTotal Memory Usage Before Optimization:\\033[1;30;45m {:.2f} MB \\033[0;0m'.format(memoryUsage(trackingData2018)))\n",
    "print('\\n' + '\\033[1;30;42m' + ' Tracking Data 2019 Columns Datatypes: ' + '\\033[0m')\n",
    "memoryUsagePerDatatype(trackingData2019)\n",
    "print('\\033[1mTotal Memory Usage Before Optimization:\\033[1;30;45m {:.2f} MB \\033[0;0m'.format(memoryUsage(trackingData2019)))\n",
    "print('\\n' + '\\033[1;30;42m' + ' Tracking Data 2020 Datatypes: ' + '\\033[0m')\n",
    "memoryUsagePerDatatype(trackingData2020)\n",
    "print('\\033[1mTotal Memory Usage Before Optimization:\\033[1;30;45m {:.2f} MB \\033[0;0m'.format(memoryUsage(trackingData2020)))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "b2ec8a7d-8499-4a7d-be63-5f49a06036bb",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "\u001b[1;30;42m Game Data Compression: \u001b[0m\n",
      "Memory Usage\u001b[1;31;43m Before \u001b[0;0mOptimization of Dataframe is:\u001b[1m 0.04 MB \u001b[0m\n",
      "Memory Usage\u001b[1;31;43m After \u001b[0;0mOptimization is:\u001b[1m 0.03 MB \u001b[0m\n",
      "\u001b[1mCompressed by:\u001b[1;30;45m 21.36 % \u001b[0;0m\n",
      "\n",
      "\u001b[1;30;42m Plays Data Compression: \u001b[0m\n",
      "Memory Usage\u001b[1;31;43m Before \u001b[0;0mOptimization of Dataframe is:\u001b[1m 3.81 MB \u001b[0m\n",
      "Memory Usage\u001b[1;31;43m After \u001b[0;0mOptimization is:\u001b[1m 2.67 MB \u001b[0m\n",
      "\u001b[1mCompressed by:\u001b[1;30;45m 30.00 % \u001b[0;0m\n",
      "\n",
      "\u001b[1;30;42m Playres Data Compression: \u001b[0m\n",
      "Memory Usage\u001b[1;31;43m Before \u001b[0;0mOptimization of Dataframe is:\u001b[1m 0.15 MB \u001b[0m\n",
      "Memory Usage\u001b[1;31;43m After \u001b[0;0mOptimization is:\u001b[1m 0.13 MB \u001b[0m\n",
      "\u001b[1mCompressed by:\u001b[1;30;45m 14.27 % \u001b[0;0m\n",
      "\n",
      "\u001b[1;30;42m Tracking Data 2018 Compression: \u001b[0m\n",
      "Memory Usage\u001b[1;31;43m Before \u001b[0;0mOptimization of Dataframe is:\u001b[1m 1754.70 MB \u001b[0m\n",
      "Memory Usage\u001b[1;31;43m After \u001b[0;0mOptimization is:\u001b[1m 1169.80 MB \u001b[0m\n",
      "\u001b[1mCompressed by:\u001b[1;30;45m 33.33 % \u001b[0;0m\n",
      "\n",
      "\u001b[1;30;42m Tracking Data 2019 Compression: \u001b[0m\n",
      "Memory Usage\u001b[1;31;43m Before \u001b[0;0mOptimization of Dataframe is:\u001b[1m 1671.42 MB \u001b[0m\n",
      "Memory Usage\u001b[1;31;43m After \u001b[0;0mOptimization is:\u001b[1m 1114.28 MB \u001b[0m\n",
      "\u001b[1mCompressed by:\u001b[1;30;45m 33.33 % \u001b[0;0m\n",
      "\n",
      "\u001b[1;30;42m Tracking Data 2020 Compression: \u001b[0m\n",
      "Memory Usage\u001b[1;31;43m Before \u001b[0;0mOptimization of Dataframe is:\u001b[1m 1623.46 MB \u001b[0m\n",
      "Memory Usage\u001b[1;31;43m After \u001b[0;0mOptimization is:\u001b[1m 1082.31 MB \u001b[0m\n",
      "\u001b[1mCompressed by:\u001b[1;30;45m 33.33 % \u001b[0;0m\n"
     ]
    }
   ],
   "source": [
    "def downcast(dataFrame):\n",
    "    startMemoryOptimization = dataFrame.memory_usage().sum() / 1024 ** 2\n",
    "    print('Memory Usage\\033[1;31;43m Before \\033[0;0mOptimization of Dataframe is:\\033[1m {:.2f} MB \\033[0m'.format(startMemoryOptimization))\n",
    "    floatColumns = [c for c in dataFrame if dataFrame[c].dtype in ['float64']]\n",
    "    intColumns = [c for c in dataFrame if dataFrame[c].dtype in ['int64']]\n",
    "    objectColumns = [c for c in dataFrame if dataFrame[c].dtype in ['object']]\n",
    "    dataFrame[floatColumns] = dataFrame[floatColumns].astype(np.float32)\n",
    "    dataFrame[intColumns] = dataFrame[intColumns].astype(np.int32)\n",
    "    for column in dataFrame[objectColumns].columns:\n",
    "        if column =='date':\n",
    "                dataFrame['date'] = pd.to_datetime(dataFrame['date'],format='%Y-%m-%d')\n",
    "                \n",
    "    endMemoryOptimization = dataFrame.memory_usage().sum() / 1024 ** 2\n",
    "    print('Memory Usage\\033[1;31;43m After \\033[0;0mOptimization is:\\033[1m {:.2f} MB \\033[0m'.format(endMemoryOptimization))\n",
    "    print('\\033[1m'+'Compressed by:\\033[1;30;45m {:.2f} % \\033[0;0m'.format(100*(startMemoryOptimization - endMemoryOptimization) / startMemoryOptimization))\n",
    "    return dataFrame\n",
    "\n",
    "\n",
    "print('\\n' + '\\033[1;30;42m' + ' Game Data Compression: ' + '\\033[0m')\n",
    "gameData = downcast(gameData)\n",
    "print('\\n' + '\\033[1;30;42m' + ' Plays Data Compression: ' + '\\033[0m')\n",
    "playsData = downcast(playsData)\n",
    "print('\\n' + '\\033[1;30;42m' + ' Playres Data Compression: ' + '\\033[0m')\n",
    "playersData = downcast(playersData)\n",
    "print('\\n' + '\\033[1;30;42m' + ' Tracking Data 2018 Compression: ' + '\\033[0m')\n",
    "trackingData2018 = downcast(trackingData2018)\n",
    "print('\\n' + '\\033[1;30;42m' + ' Tracking Data 2019 Compression: ' + '\\033[0m')\n",
    "trackingData2019 = downcast(trackingData2019)\n",
    "print('\\n' + '\\033[1;30;42m' + ' Tracking Data 2020 Compression: ' + '\\033[0m')\n",
    "trackingData2020 = downcast(trackingData2020)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "0f55bcfa-8b47-43e9-b5ed-a9e99c15ac00",
   "metadata": {},
   "outputs": [],
   "source": [
    "trackingFull = pd.concat([trackingData2018, trackingData2019, trackingData2020], axis=0)\n",
    "trackingFull.reset_index(drop=True, inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "fdcd8da9-3a58-4a9e-b4d5-4f9ed02b51ca",
   "metadata": {},
   "outputs": [],
   "source": [
    "mergedGameAndPlaysData = gameData.merge(playsData, how='inner', indicator=True)\n",
    "mergedGamePlaysAndTrackingFullData = mergedGameAndPlaysData.merge(trackingFull, how='inner', indicator='exists')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "ee39222d-b300-4ede-8dc1-614b75fa1ac8",
   "metadata": {},
   "outputs": [],
   "source": [
    "task1DataFrame = mergedGameAndPlaysData[['season', 'possessionTeam', 'specialTeamsPlayType','specialTeamsResult']]\n",
    "task1DataFrame[\"Result\"] = task1DataFrame[\"specialTeamsPlayType\"]+ \" - \" + task1DataFrame[\"specialTeamsResult\"].map(str)\n",
    "task1DataFrame.drop(['specialTeamsPlayType','specialTeamsResult'],axis=1, inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "106814fd-e5ea-4650-a787-0439164a47ae",
   "metadata": {},
   "outputs": [],
   "source": [
    "mergedGamePlaysAndTrackingFullData[\"Result\"] = mergedGamePlaysAndTrackingFullData[\"specialTeamsPlayType\"]+ \" - \" + mergedGamePlaysAndTrackingFullData[\"specialTeamsResult\"].map(str)\n",
    "mergedGamePlaysAndTrackingFullData.drop(['specialTeamsPlayType','specialTeamsResult'],axis=1, inplace=True)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "id": "e2cad2c6-c072-4e32-957b-1e36c1eaffca",
   "metadata": {},
   "outputs": [],
   "source": [
    "pd.options.display.max_rows = 99999999"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "3b9aff89-9630-4384-a617-145c77dbe4ea",
   "metadata": {},
   "outputs": [],
   "source": [
    "task1DataFrame = mergedGamePlaysAndTrackingFullData[['gameId','season','week','homeTeamAbbr','visitorTeamAbbr','playId',\n",
    "                                                     'quarter','down','yardsToGo','possessionTeam','Result',\n",
    "                                                     'yardlineNumber','absoluteYardlineNumber','yardlineSide','gameClock','penaltyCodes','preSnapHomeScore',\n",
    "                                                     'preSnapVisitorScore','kickReturnYardage','playResult','event'\n",
    "                                                    ]]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "596f9601-8882-49a5-9a13-9e4c5906b25f",
   "metadata": {},
   "outputs": [],
   "source": [
    "task1DataFrame['penaltyCodes'] = task1DataFrame['penaltyCodes'].replace(np.nan, 0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "8355ee60-b8b7-430c-aa85-fab932bebcfc",
   "metadata": {},
   "outputs": [],
   "source": [
    "task1DataFrame['kickReturnYardage'] = task1DataFrame['kickReturnYardage'].replace(np.nan, 0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "1a21dcb5-d959-475e-9fe4-f907cc0e65de",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Special Play Classification\n",
    "\n",
    "kickoffEvents = ['Kickoff - Touchback','Kickoff - Return','Kickoff - Muffed','Kickoff - Kickoff Team Recovery','Kickoff - Out of Bounds',\n",
    "                 'Kickoff - Fair Catch','Kickoff - Downed']\n",
    "puntEvents = ['Punt - Return','Punt - Touchback','Punt - Fair Catch','Punt - Downed','Punt - Muffed','Punt - Out of Bounds',\n",
    "              'Punt - Non-Special Teams Result','Punt - Blocked Punt']\n",
    "extrapointEvents = ['Extra Point - Kick Attempt Good','Extra Point - Kick Attempt No Good','Extra Point - Non-Special Teams Result',\n",
    "                    'Extra Point - Blocked Kick Attempt']\n",
    "fieldgoalEvents = ['Field Goal - Kick Attempt Good','Field Goal - Kick Attempt No Good','Field Goal - Blocked Kick Attempt',\n",
    "                   'Field Goal - Non-Special Teams Result','Field Goal - Out of Bounds','Field Goal - Downed']\n",
    "\n",
    "task1DataFrameKickoffs = task1DataFrame.loc[task1DataFrame['Result'].isin(kickoffEvents)] \n",
    "task1DataFramePunts = task1DataFrame.loc[task1DataFrame['Result'].isin(puntEvents)]\n",
    "task1DataFrameExtrapoints = task1DataFrame.loc[task1DataFrame['Result'].isin(extrapointEvents)]  \n",
    "task1DataFrameFieldgoals = task1DataFrame.loc[task1DataFrame['Result'].isin(fieldgoalEvents)]        "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "206ac17c-5ba7-4fd4-9d4a-8abb66ece725",
   "metadata": {},
   "outputs": [],
   "source": [
    "task1DataFrameKickoffs.head().T"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "5eff4738-c1d6-4aaa-aa54-ef58f6062212",
   "metadata": {},
   "outputs": [],
   "source": [
    "# ARI Special Plays Data Preparation\n",
    "\n",
    "# Punts\n",
    "puntsARI2018 = task1DataFramePunts[(task1DataFramePunts.season == 2018 ) & (task1DataFramePunts.possessionTeam == 'ARI') \n",
    "                                   & (task1DataFramePunts.penaltyCodes == 0) \n",
    "                                   & (task1DataFramePunts.event != 'None')]\n",
    "puntsARI2019 = task1DataFramePunts[(task1DataFramePunts.season == 2019 ) & (task1DataFramePunts.possessionTeam == 'ARI') \n",
    "                                   & (task1DataFramePunts.penaltyCodes == 0) \n",
    "                                   & (task1DataFramePunts.event != 'None')]\n",
    "puntsARI2020 = task1DataFramePunts[(task1DataFramePunts.season == 2020 ) & (task1DataFramePunts.possessionTeam == 'ARI') \n",
    "                                   & (task1DataFramePunts.penaltyCodes == 0) \n",
    "                                   & (task1DataFramePunts.event != 'None')]\n",
    "\n",
    "# Kickoffs\n",
    "kickoffsARI2018 = task1DataFrameKickoffs[(task1DataFrameKickoffs.season == 2018 ) & (task1DataFrameKickoffs.possessionTeam == 'ARI')\n",
    "                                         & (task1DataFrameKickoffs.penaltyCodes == 0) \n",
    "                                         & (task1DataFrameKickoffs.event != 'None')]\n",
    "kickoffsARI2019 = task1DataFrameKickoffs[(task1DataFrameKickoffs.season == 2019 ) & (task1DataFrameKickoffs.possessionTeam == 'ARI')\n",
    "                                         & (task1DataFrameKickoffs.penaltyCodes == 0) \n",
    "                                         & (task1DataFrameKickoffs.event != 'None')]\n",
    "kickoffsARI2020 = task1DataFrameKickoffs[(task1DataFrameKickoffs.season == 2020 ) & (task1DataFrameKickoffs.possessionTeam == 'ARI')\n",
    "                                         & (task1DataFrameKickoffs.penaltyCodes == 0) \n",
    "                                         & (task1DataFrameKickoffs.event != 'None')]\n",
    "\n",
    "# Extra Points\n",
    "extraPointsARI2018 = task1DataFrameExtrapoints[(task1DataFrameExtrapoints.season == 2018 ) & (task1DataFrameExtrapoints.possessionTeam == 'ARI') \n",
    "                                           & (task1DataFrameExtrapoints.penaltyCodes == 0) \n",
    "                                           & (task1DataFrameExtrapoints.event != 'None')]\n",
    "extraPointsARI2019 = task1DataFrameExtrapoints[(task1DataFrameExtrapoints.season == 2019 ) & (task1DataFrameExtrapoints.possessionTeam == 'ARI') \n",
    "                                           & (task1DataFrameExtrapoints.penaltyCodes == 0) \n",
    "                                           & (task1DataFrameExtrapoints.event != 'None')]\n",
    "extraPointsARI2020 = task1DataFrameExtrapoints[(task1DataFrameExtrapoints.season == 2020 ) & (task1DataFrameExtrapoints.possessionTeam == 'ARI') \n",
    "                                           & (task1DataFrameExtrapoints.penaltyCodes == 0) \n",
    "                                           & (task1DataFrameExtrapoints.event != 'None')]\n",
    "\n",
    "# Field Goals\n",
    "fieldGoalsARI2018 = task1DataFrameFieldgoals[(task1DataFrameFieldgoals.season == 2018 ) & (task1DataFrameFieldgoals.possessionTeam == 'ARI')  \n",
    "                                         & (task1DataFrameFieldgoals.penaltyCodes == 0) \n",
    "                                         & (task1DataFrameFieldgoals.event != 'None')]\n",
    "fieldGoalsARI2019 = task1DataFrameFieldgoals[(task1DataFrameFieldgoals.season == 2019 ) & (task1DataFrameFieldgoals.possessionTeam == 'ARI')  \n",
    "                                         & (task1DataFrameFieldgoals.penaltyCodes == 0) \n",
    "                                         & (task1DataFrameFieldgoals.event != 'None')]\n",
    "fieldGoalsARI2020 = task1DataFrameFieldgoals[(task1DataFrameFieldgoals.season == 2020 ) & (task1DataFrameFieldgoals.possessionTeam == 'ARI')  \n",
    "                                         & (task1DataFrameFieldgoals.penaltyCodes == 0) \n",
    "                                         & (task1DataFrameFieldgoals.event != 'None')]\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "d4db0323-9798-4a1f-813c-a95e25cff0bb",
   "metadata": {},
   "outputs": [],
   "source": [
    "# ATL Special Plays Data Preparation\n",
    "\n",
    "# Punts\n",
    "puntsATL2018 = task1DataFramePunts[(task1DataFramePunts.season == 2018 ) & (task1DataFramePunts.possessionTeam == 'ATL') \n",
    "                                   & (task1DataFramePunts.penaltyCodes == 0) \n",
    "                                   & (task1DataFramePunts.event != 'None')]\n",
    "puntsATL2019 = task1DataFramePunts[(task1DataFramePunts.season == 2019 ) & (task1DataFramePunts.possessionTeam == 'ATL') \n",
    "                                   & (task1DataFramePunts.penaltyCodes == 0) \n",
    "                                   & (task1DataFramePunts.event != 'None')]\n",
    "puntsATL2020 = task1DataFramePunts[(task1DataFramePunts.season == 2020 ) & (task1DataFramePunts.possessionTeam == 'ATL') \n",
    "                                   & (task1DataFramePunts.penaltyCodes == 0) \n",
    "                                   & (task1DataFramePunts.event != 'None')]\n",
    "\n",
    "# Kickoffs\n",
    "kickoffsATL2018 = task1DataFrameKickoffs[(task1DataFrameKickoffs.season == 2018 ) & (task1DataFrameKickoffs.possessionTeam == 'ATL')\n",
    "                                         & (task1DataFrameKickoffs.penaltyCodes == 0) \n",
    "                                         & (task1DataFrameKickoffs.event != 'None')]\n",
    "kickoffsATL2019 = task1DataFrameKickoffs[(task1DataFrameKickoffs.season == 2019 ) & (task1DataFrameKickoffs.possessionTeam == 'ATL')\n",
    "                                         & (task1DataFrameKickoffs.penaltyCodes == 0) \n",
    "                                         & (task1DataFrameKickoffs.event != 'None')]\n",
    "kickoffsATL2020 = task1DataFrameKickoffs[(task1DataFrameKickoffs.season == 2020 ) & (task1DataFrameKickoffs.possessionTeam == 'ATL')\n",
    "                                         & (task1DataFrameKickoffs.penaltyCodes == 0) \n",
    "                                         & (task1DataFrameKickoffs.event != 'None')]\n",
    "\n",
    "# Extra Points\n",
    "extraPointsATL2018 = task1DataFrameExtrapoints[(task1DataFrameExtrapoints.season == 2018 ) & (task1DataFrameExtrapoints.possessionTeam == 'ATL') \n",
    "                                           & (task1DataFrameExtrapoints.penaltyCodes == 0) \n",
    "                                           & (task1DataFrameExtrapoints.event != 'None')]\n",
    "extraPointsATL2019 = task1DataFrameExtrapoints[(task1DataFrameExtrapoints.season == 2019 ) & (task1DataFrameExtrapoints.possessionTeam == 'ATL') \n",
    "                                           & (task1DataFrameExtrapoints.penaltyCodes == 0) \n",
    "                                           & (task1DataFrameExtrapoints.event != 'None')]\n",
    "extraPointsATL2020 = task1DataFrameExtrapoints[(task1DataFrameExtrapoints.season == 2020 ) & (task1DataFrameExtrapoints.possessionTeam == 'ATL') \n",
    "                                           & (task1DataFrameExtrapoints.penaltyCodes == 0) \n",
    "                                           & (task1DataFrameExtrapoints.event != 'None')]\n",
    "\n",
    "# Field Goals\n",
    "fieldGoalsATL2018 = task1DataFrameFieldgoals[(task1DataFrameFieldgoals.season == 2018 ) & (task1DataFrameFieldgoals.possessionTeam == 'ATL')  \n",
    "                                         & (task1DataFrameFieldgoals.penaltyCodes == 0) \n",
    "                                         & (task1DataFrameFieldgoals.event != 'None')]\n",
    "fieldGoalsATL2019 = task1DataFrameFieldgoals[(task1DataFrameFieldgoals.season == 2019 ) & (task1DataFrameFieldgoals.possessionTeam == 'ATL')  \n",
    "                                         & (task1DataFrameFieldgoals.penaltyCodes == 0) \n",
    "                                         & (task1DataFrameFieldgoals.event != 'None')]\n",
    "fieldGoalsATL2020 = task1DataFrameFieldgoals[(task1DataFrameFieldgoals.season == 2020 ) & (task1DataFrameFieldgoals.possessionTeam == 'ATL')  \n",
    "                                         & (task1DataFrameFieldgoals.penaltyCodes == 0) \n",
    "                                         & (task1DataFrameFieldgoals.event != 'None')]\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "e33b31cb-b468-46db-b786-0059f7f46d87",
   "metadata": {},
   "outputs": [],
   "source": [
    "# BAL Special Plays Data Preparation\n",
    "\n",
    "# Punts\n",
    "puntsBAL2018 = task1DataFramePunts[(task1DataFramePunts.season == 2018 ) & (task1DataFramePunts.possessionTeam == 'BAL') \n",
    "                                   & (task1DataFramePunts.penaltyCodes == 0) \n",
    "                                   & (task1DataFramePunts.event != 'None')]\n",
    "puntsBAL2019 = task1DataFramePunts[(task1DataFramePunts.season == 2019 ) & (task1DataFramePunts.possessionTeam == 'BAL') \n",
    "                                   & (task1DataFramePunts.penaltyCodes == 0) \n",
    "                                   & (task1DataFramePunts.event != 'None')]\n",
    "puntsBAL2020 = task1DataFramePunts[(task1DataFramePunts.season == 2020 ) & (task1DataFramePunts.possessionTeam == 'BAL') \n",
    "                                   & (task1DataFramePunts.penaltyCodes == 0) \n",
    "                                   & (task1DataFramePunts.event != 'None')]\n",
    "\n",
    "# Kickoffs\n",
    "kickoffsBAL2018 = task1DataFrameKickoffs[(task1DataFrameKickoffs.season == 2018 ) & (task1DataFrameKickoffs.possessionTeam == 'BAL')\n",
    "                                         & (task1DataFrameKickoffs.penaltyCodes == 0) \n",
    "                                         & (task1DataFrameKickoffs.event != 'None')]\n",
    "kickoffsBAL2019 = task1DataFrameKickoffs[(task1DataFrameKickoffs.season == 2019 ) & (task1DataFrameKickoffs.possessionTeam == 'BAL')\n",
    "                                         & (task1DataFrameKickoffs.penaltyCodes == 0) \n",
    "                                         & (task1DataFrameKickoffs.event != 'None')]\n",
    "kickoffsBAL2020 = task1DataFrameKickoffs[(task1DataFrameKickoffs.season == 2020 ) & (task1DataFrameKickoffs.possessionTeam == 'BAL')\n",
    "                                         & (task1DataFrameKickoffs.penaltyCodes == 0) \n",
    "                                         & (task1DataFrameKickoffs.event != 'None')]\n",
    "\n",
    "# Extra Points\n",
    "extraPointsBAL2018 = task1DataFrameExtrapoints[(task1DataFrameExtrapoints.season == 2018 ) & (task1DataFrameExtrapoints.possessionTeam == 'BAL') \n",
    "                                           & (task1DataFrameExtrapoints.penaltyCodes == 0) \n",
    "                                           & (task1DataFrameExtrapoints.event != 'None')]\n",
    "extraPointsBAL2019 = task1DataFrameExtrapoints[(task1DataFrameExtrapoints.season == 2019 ) & (task1DataFrameExtrapoints.possessionTeam == 'BAL') \n",
    "                                           & (task1DataFrameExtrapoints.penaltyCodes == 0) \n",
    "                                           & (task1DataFrameExtrapoints.event != 'None')]\n",
    "extraPointsBAL2020 = task1DataFrameExtrapoints[(task1DataFrameExtrapoints.season == 2020 ) & (task1DataFrameExtrapoints.possessionTeam == 'BAL') \n",
    "                                           & (task1DataFrameExtrapoints.penaltyCodes == 0) \n",
    "                                           & (task1DataFrameExtrapoints.event != 'None')]\n",
    "\n",
    "# Field Goals\n",
    "fieldGoalsBAL2018 = task1DataFrameFieldgoals[(task1DataFrameFieldgoals.season == 2018 ) & (task1DataFrameFieldgoals.possessionTeam == 'BAL')  \n",
    "                                         & (task1DataFrameFieldgoals.penaltyCodes == 0) \n",
    "                                         & (task1DataFrameFieldgoals.event != 'None')]\n",
    "fieldGoalsBAL2019 = task1DataFrameFieldgoals[(task1DataFrameFieldgoals.season == 2019 ) & (task1DataFrameFieldgoals.possessionTeam == 'BAL')  \n",
    "                                         & (task1DataFrameFieldgoals.penaltyCodes == 0) \n",
    "                                         & (task1DataFrameFieldgoals.event != 'None')]\n",
    "fieldGoalsBAL2020 = task1DataFrameFieldgoals[(task1DataFrameFieldgoals.season == 2020 ) & (task1DataFrameFieldgoals.possessionTeam == 'BAL')  \n",
    "                                         & (task1DataFrameFieldgoals.penaltyCodes == 0) \n",
    "                                         & (task1DataFrameFieldgoals.event != 'None')]\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "3d0a8bc9-75be-4130-b1ee-73aac30c8689",
   "metadata": {},
   "outputs": [],
   "source": [
    "# BUF Special Plays Data Preparation\n",
    "\n",
    "# Punts\n",
    "puntsBUF2018 = task1DataFramePunts[(task1DataFramePunts.season == 2018 ) & (task1DataFramePunts.possessionTeam == 'BUF') \n",
    "                                   & (task1DataFramePunts.penaltyCodes == 0) \n",
    "                                   & (task1DataFramePunts.event != 'None')]\n",
    "puntsBUF2019 = task1DataFramePunts[(task1DataFramePunts.season == 2019 ) & (task1DataFramePunts.possessionTeam == 'BUF') \n",
    "                                   & (task1DataFramePunts.penaltyCodes == 0) \n",
    "                                   & (task1DataFramePunts.event != 'None')]\n",
    "puntsBUF2020 = task1DataFramePunts[(task1DataFramePunts.season == 2020 ) & (task1DataFramePunts.possessionTeam == 'BUF') \n",
    "                                   & (task1DataFramePunts.penaltyCodes == 0) \n",
    "                                   & (task1DataFramePunts.event != 'None')]\n",
    "\n",
    "# Kickoffs\n",
    "kickoffsBUF2018 = task1DataFrameKickoffs[(task1DataFrameKickoffs.season == 2018 ) & (task1DataFrameKickoffs.possessionTeam == 'BUF')\n",
    "                                         & (task1DataFrameKickoffs.penaltyCodes == 0) \n",
    "                                         & (task1DataFrameKickoffs.event != 'None')]\n",
    "kickoffsBUF2019 = task1DataFrameKickoffs[(task1DataFrameKickoffs.season == 2019 ) & (task1DataFrameKickoffs.possessionTeam == 'BUF')\n",
    "                                         & (task1DataFrameKickoffs.penaltyCodes == 0) \n",
    "                                         & (task1DataFrameKickoffs.event != 'None')]\n",
    "kickoffsBUF2020 = task1DataFrameKickoffs[(task1DataFrameKickoffs.season == 2020 ) & (task1DataFrameKickoffs.possessionTeam == 'BUF')\n",
    "                                         & (task1DataFrameKickoffs.penaltyCodes == 0) \n",
    "                                         & (task1DataFrameKickoffs.event != 'None')]\n",
    "\n",
    "# Extra Points\n",
    "extraPointsBUF2018 = task1DataFrameExtrapoints[(task1DataFrameExtrapoints.season == 2018 ) & (task1DataFrameExtrapoints.possessionTeam == 'BUF') \n",
    "                                           & (task1DataFrameExtrapoints.penaltyCodes == 0) \n",
    "                                           & (task1DataFrameExtrapoints.event != 'None')]\n",
    "extraPointsBUF2019 = task1DataFrameExtrapoints[(task1DataFrameExtrapoints.season == 2019 ) & (task1DataFrameExtrapoints.possessionTeam == 'BUF') \n",
    "                                           & (task1DataFrameExtrapoints.penaltyCodes == 0) \n",
    "                                           & (task1DataFrameExtrapoints.event != 'None')]\n",
    "extraPointsBUF2020 = task1DataFrameExtrapoints[(task1DataFrameExtrapoints.season == 2020 ) & (task1DataFrameExtrapoints.possessionTeam == 'BUF') \n",
    "                                           & (task1DataFrameExtrapoints.penaltyCodes == 0) \n",
    "                                           & (task1DataFrameExtrapoints.event != 'None')]\n",
    "\n",
    "# Field Goals\n",
    "fieldGoalsBUF2018 = task1DataFrameFieldgoals[(task1DataFrameFieldgoals.season == 2018 ) & (task1DataFrameFieldgoals.possessionTeam == 'BUF')  \n",
    "                                         & (task1DataFrameFieldgoals.penaltyCodes == 0) \n",
    "                                         & (task1DataFrameFieldgoals.event != 'None')]\n",
    "fieldGoalsBUF2019 = task1DataFrameFieldgoals[(task1DataFrameFieldgoals.season == 2019 ) & (task1DataFrameFieldgoals.possessionTeam == 'BUF')  \n",
    "                                         & (task1DataFrameFieldgoals.penaltyCodes == 0) \n",
    "                                         & (task1DataFrameFieldgoals.event != 'None')]\n",
    "fieldGoalsBUF2020 = task1DataFrameFieldgoals[(task1DataFrameFieldgoals.season == 2020 ) & (task1DataFrameFieldgoals.possessionTeam == 'BUF')  \n",
    "                                         & (task1DataFrameFieldgoals.penaltyCodes == 0) \n",
    "                                         & (task1DataFrameFieldgoals.event != 'None')]\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "b4c77049-fb92-4a6f-b460-3db9502bdc9a",
   "metadata": {},
   "outputs": [],
   "source": [
    "# CAR Special Plays Data Preparation\n",
    "\n",
    "# Punts\n",
    "puntsCAR2018 = task1DataFramePunts[(task1DataFramePunts.season == 2018 ) & (task1DataFramePunts.possessionTeam == 'CAR') \n",
    "                                   & (task1DataFramePunts.penaltyCodes == 0) \n",
    "                                   & (task1DataFramePunts.event != 'None')]\n",
    "puntsCAR2019 = task1DataFramePunts[(task1DataFramePunts.season == 2019 ) & (task1DataFramePunts.possessionTeam == 'CAR') \n",
    "                                   & (task1DataFramePunts.penaltyCodes == 0) \n",
    "                                   & (task1DataFramePunts.event != 'None')]\n",
    "puntsCAR2020 = task1DataFramePunts[(task1DataFramePunts.season == 2020 ) & (task1DataFramePunts.possessionTeam == 'CAR') \n",
    "                                   & (task1DataFramePunts.penaltyCodes == 0) \n",
    "                                   & (task1DataFramePunts.event != 'None')]\n",
    "\n",
    "# Kickoffs\n",
    "kickoffsCAR2018 = task1DataFrameKickoffs[(task1DataFrameKickoffs.season == 2018 ) & (task1DataFrameKickoffs.possessionTeam == 'CAR')\n",
    "                                         & (task1DataFrameKickoffs.penaltyCodes == 0) \n",
    "                                         & (task1DataFrameKickoffs.event != 'None')]\n",
    "kickoffsCAR2019 = task1DataFrameKickoffs[(task1DataFrameKickoffs.season == 2019 ) & (task1DataFrameKickoffs.possessionTeam == 'CAR')\n",
    "                                         & (task1DataFrameKickoffs.penaltyCodes == 0) \n",
    "                                         & (task1DataFrameKickoffs.event != 'None')]\n",
    "kickoffsCAR2020 = task1DataFrameKickoffs[(task1DataFrameKickoffs.season == 2020 ) & (task1DataFrameKickoffs.possessionTeam == 'CAR')\n",
    "                                         & (task1DataFrameKickoffs.penaltyCodes == 0) \n",
    "                                         & (task1DataFrameKickoffs.event != 'None')]\n",
    "\n",
    "# Extra Points\n",
    "extraPointsCAR2018 = task1DataFrameExtrapoints[(task1DataFrameExtrapoints.season == 2018 ) & (task1DataFrameExtrapoints.possessionTeam == 'CAR') \n",
    "                                           & (task1DataFrameExtrapoints.penaltyCodes == 0) \n",
    "                                           & (task1DataFrameExtrapoints.event != 'None')]\n",
    "extraPointsCAR2019 = task1DataFrameExtrapoints[(task1DataFrameExtrapoints.season == 2019 ) & (task1DataFrameExtrapoints.possessionTeam == 'CAR') \n",
    "                                           & (task1DataFrameExtrapoints.penaltyCodes == 0) \n",
    "                                           & (task1DataFrameExtrapoints.event != 'None')]\n",
    "extraPointsCAR2020 = task1DataFrameExtrapoints[(task1DataFrameExtrapoints.season == 2020 ) & (task1DataFrameExtrapoints.possessionTeam == 'CAR') \n",
    "                                           & (task1DataFrameExtrapoints.penaltyCodes == 0) \n",
    "                                           & (task1DataFrameExtrapoints.event != 'None')]\n",
    "\n",
    "# Field Goals\n",
    "fieldGoalsCAR2018 = task1DataFrameFieldgoals[(task1DataFrameFieldgoals.season == 2018 ) & (task1DataFrameFieldgoals.possessionTeam == 'CAR')  \n",
    "                                         & (task1DataFrameFieldgoals.penaltyCodes == 0) \n",
    "                                         & (task1DataFrameFieldgoals.event != 'None')]\n",
    "fieldGoalsCAR2019 = task1DataFrameFieldgoals[(task1DataFrameFieldgoals.season == 2019 ) & (task1DataFrameFieldgoals.possessionTeam == 'CAR')  \n",
    "                                         & (task1DataFrameFieldgoals.penaltyCodes == 0) \n",
    "                                         & (task1DataFrameFieldgoals.event != 'None')]\n",
    "fieldGoalsCAR2020 = task1DataFrameFieldgoals[(task1DataFrameFieldgoals.season == 2020 ) & (task1DataFrameFieldgoals.possessionTeam == 'CAR')  \n",
    "                                         & (task1DataFrameFieldgoals.penaltyCodes == 0) \n",
    "                                         & (task1DataFrameFieldgoals.event != 'None')]\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "8e15e639-894a-4a8f-8648-b3a4bb04aa1b",
   "metadata": {},
   "outputs": [],
   "source": [
    "# CHI Special Plays Data Preparation\n",
    "\n",
    "# Punts\n",
    "puntsCHI2018 = task1DataFramePunts[(task1DataFramePunts.season == 2018 ) & (task1DataFramePunts.possessionTeam == 'CHI') \n",
    "                                   & (task1DataFramePunts.penaltyCodes == 0) \n",
    "                                   & (task1DataFramePunts.event != 'None')]\n",
    "puntsCHI2019 = task1DataFramePunts[(task1DataFramePunts.season == 2019 ) & (task1DataFramePunts.possessionTeam == 'CHI') \n",
    "                                   & (task1DataFramePunts.penaltyCodes == 0) \n",
    "                                   & (task1DataFramePunts.event != 'None')]\n",
    "puntsCHI2020 = task1DataFramePunts[(task1DataFramePunts.season == 2020 ) & (task1DataFramePunts.possessionTeam == 'CHI') \n",
    "                                   & (task1DataFramePunts.penaltyCodes == 0) \n",
    "                                   & (task1DataFramePunts.event != 'None')]\n",
    "\n",
    "# Kickoffs\n",
    "kickoffsCHI2018 = task1DataFrameKickoffs[(task1DataFrameKickoffs.season == 2018 ) & (task1DataFrameKickoffs.possessionTeam == 'CHI')\n",
    "                                         & (task1DataFrameKickoffs.penaltyCodes == 0) \n",
    "                                         & (task1DataFrameKickoffs.event != 'None')]\n",
    "kickoffsCHI2019 = task1DataFrameKickoffs[(task1DataFrameKickoffs.season == 2019 ) & (task1DataFrameKickoffs.possessionTeam == 'CHI')\n",
    "                                         & (task1DataFrameKickoffs.penaltyCodes == 0) \n",
    "                                         & (task1DataFrameKickoffs.event != 'None')]\n",
    "kickoffsCHI2020 = task1DataFrameKickoffs[(task1DataFrameKickoffs.season == 2020 ) & (task1DataFrameKickoffs.possessionTeam == 'CHI')\n",
    "                                         & (task1DataFrameKickoffs.penaltyCodes == 0) \n",
    "                                         & (task1DataFrameKickoffs.event != 'None')]\n",
    "\n",
    "# Extra Points\n",
    "extraPointsCHI2018 = task1DataFrameExtrapoints[(task1DataFrameExtrapoints.season == 2018 ) & (task1DataFrameExtrapoints.possessionTeam == 'CHI') \n",
    "                                           & (task1DataFrameExtrapoints.penaltyCodes == 0) \n",
    "                                           & (task1DataFrameExtrapoints.event != 'None')]\n",
    "extraPointsCHI2019 = task1DataFrameExtrapoints[(task1DataFrameExtrapoints.season == 2019 ) & (task1DataFrameExtrapoints.possessionTeam == 'CHI') \n",
    "                                           & (task1DataFrameExtrapoints.penaltyCodes == 0) \n",
    "                                           & (task1DataFrameExtrapoints.event != 'None')]\n",
    "extraPointsCHI2020 = task1DataFrameExtrapoints[(task1DataFrameExtrapoints.season == 2020 ) & (task1DataFrameExtrapoints.possessionTeam == 'CHI') \n",
    "                                           & (task1DataFrameExtrapoints.penaltyCodes == 0) \n",
    "                                           & (task1DataFrameExtrapoints.event != 'None')]\n",
    "\n",
    "# Field Goals\n",
    "fieldGoalsCHI2018 = task1DataFrameFieldgoals[(task1DataFrameFieldgoals.season == 2018 ) & (task1DataFrameFieldgoals.possessionTeam == 'CHI')  \n",
    "                                         & (task1DataFrameFieldgoals.penaltyCodes == 0) \n",
    "                                         & (task1DataFrameFieldgoals.event != 'None')]\n",
    "fieldGoalsCHI2019 = task1DataFrameFieldgoals[(task1DataFrameFieldgoals.season == 2019 ) & (task1DataFrameFieldgoals.possessionTeam == 'CHI')  \n",
    "                                         & (task1DataFrameFieldgoals.penaltyCodes == 0) \n",
    "                                         & (task1DataFrameFieldgoals.event != 'None')]\n",
    "fieldGoalsCHI2020 = task1DataFrameFieldgoals[(task1DataFrameFieldgoals.season == 2020 ) & (task1DataFrameFieldgoals.possessionTeam == 'CHI')  \n",
    "                                         & (task1DataFrameFieldgoals.penaltyCodes == 0) \n",
    "                                         & (task1DataFrameFieldgoals.event != 'None')]\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "e95e791d-a90d-4cdd-a4e9-59c159007d81",
   "metadata": {},
   "outputs": [],
   "source": [
    "# CLE Special Plays Data Preparation\n",
    "\n",
    "# Punts\n",
    "puntsCLE2018 = task1DataFramePunts[(task1DataFramePunts.season == 2018 ) & (task1DataFramePunts.possessionTeam == 'CLE') \n",
    "                                   & (task1DataFramePunts.penaltyCodes == 0) \n",
    "                                   & (task1DataFramePunts.event != 'None')]\n",
    "puntsCLE2019 = task1DataFramePunts[(task1DataFramePunts.season == 2019 ) & (task1DataFramePunts.possessionTeam == 'CLE') \n",
    "                                   & (task1DataFramePunts.penaltyCodes == 0) \n",
    "                                   & (task1DataFramePunts.event != 'None')]\n",
    "puntsCLE2020 = task1DataFramePunts[(task1DataFramePunts.season == 2020 ) & (task1DataFramePunts.possessionTeam == 'CLE') \n",
    "                                   & (task1DataFramePunts.penaltyCodes == 0) \n",
    "                                   & (task1DataFramePunts.event != 'None')]\n",
    "\n",
    "# Kickoffs\n",
    "kickoffsCLE2018 = task1DataFrameKickoffs[(task1DataFrameKickoffs.season == 2018 ) & (task1DataFrameKickoffs.possessionTeam == 'CLE')\n",
    "                                         & (task1DataFrameKickoffs.penaltyCodes == 0) \n",
    "                                         & (task1DataFrameKickoffs.event != 'None')]\n",
    "kickoffsCLE2019 = task1DataFrameKickoffs[(task1DataFrameKickoffs.season == 2019 ) & (task1DataFrameKickoffs.possessionTeam == 'CLE')\n",
    "                                         & (task1DataFrameKickoffs.penaltyCodes == 0) \n",
    "                                         & (task1DataFrameKickoffs.event != 'None')]\n",
    "kickoffsCLE2020 = task1DataFrameKickoffs[(task1DataFrameKickoffs.season == 2020 ) & (task1DataFrameKickoffs.possessionTeam == 'CLE')\n",
    "                                         & (task1DataFrameKickoffs.penaltyCodes == 0) \n",
    "                                         & (task1DataFrameKickoffs.event != 'None')]\n",
    "\n",
    "# Extra Points\n",
    "extraPointsCLE2018 = task1DataFrameExtrapoints[(task1DataFrameExtrapoints.season == 2018 ) & (task1DataFrameExtrapoints.possessionTeam == 'CLE') \n",
    "                                           & (task1DataFrameExtrapoints.penaltyCodes == 0) \n",
    "                                           & (task1DataFrameExtrapoints.event != 'None')]\n",
    "extraPointsCLE2019 = task1DataFrameExtrapoints[(task1DataFrameExtrapoints.season == 2019 ) & (task1DataFrameExtrapoints.possessionTeam == 'CLE') \n",
    "                                           & (task1DataFrameExtrapoints.penaltyCodes == 0) \n",
    "                                           & (task1DataFrameExtrapoints.event != 'None')]\n",
    "extraPointsCLE2020 = task1DataFrameExtrapoints[(task1DataFrameExtrapoints.season == 2020 ) & (task1DataFrameExtrapoints.possessionTeam == 'CLE') \n",
    "                                           & (task1DataFrameExtrapoints.penaltyCodes == 0) \n",
    "                                           & (task1DataFrameExtrapoints.event != 'None')]\n",
    "\n",
    "# Field Goals\n",
    "fieldGoalsCLE2018 = task1DataFrameFieldgoals[(task1DataFrameFieldgoals.season == 2018 ) & (task1DataFrameFieldgoals.possessionTeam == 'CLE')  \n",
    "                                         & (task1DataFrameFieldgoals.penaltyCodes == 0) \n",
    "                                         & (task1DataFrameFieldgoals.event != 'None')]\n",
    "fieldGoalsCLE2019 = task1DataFrameFieldgoals[(task1DataFrameFieldgoals.season == 2019 ) & (task1DataFrameFieldgoals.possessionTeam == 'CLE')  \n",
    "                                         & (task1DataFrameFieldgoals.penaltyCodes == 0) \n",
    "                                         & (task1DataFrameFieldgoals.event != 'None')]\n",
    "fieldGoalsCLE2020 = task1DataFrameFieldgoals[(task1DataFrameFieldgoals.season == 2020 ) & (task1DataFrameFieldgoals.possessionTeam == 'CLE')  \n",
    "                                         & (task1DataFrameFieldgoals.penaltyCodes == 0) \n",
    "                                         & (task1DataFrameFieldgoals.event != 'None')]\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "ee3a64c9-7843-4e9d-a113-b1da406f7c60",
   "metadata": {},
   "outputs": [],
   "source": [
    "# CIN Special Plays Data Preparation\n",
    "\n",
    "# Punts\n",
    "puntsCIN2018 = task1DataFramePunts[(task1DataFramePunts.season == 2018 ) & (task1DataFramePunts.possessionTeam == 'CIN') \n",
    "                                   & (task1DataFramePunts.penaltyCodes == 0) \n",
    "                                   & (task1DataFramePunts.event != 'None')]\n",
    "puntsCIN2019 = task1DataFramePunts[(task1DataFramePunts.season == 2019 ) & (task1DataFramePunts.possessionTeam == 'CIN') \n",
    "                                   & (task1DataFramePunts.penaltyCodes == 0) \n",
    "                                   & (task1DataFramePunts.event != 'None')]\n",
    "puntsCIN2020 = task1DataFramePunts[(task1DataFramePunts.season == 2020 ) & (task1DataFramePunts.possessionTeam == 'CIN') \n",
    "                                   & (task1DataFramePunts.penaltyCodes == 0) \n",
    "                                   & (task1DataFramePunts.event != 'None')]\n",
    "\n",
    "# Kickoffs\n",
    "kickoffsCIN2018 = task1DataFrameKickoffs[(task1DataFrameKickoffs.season == 2018 ) & (task1DataFrameKickoffs.possessionTeam == 'CIN')\n",
    "                                         & (task1DataFrameKickoffs.penaltyCodes == 0) \n",
    "                                         & (task1DataFrameKickoffs.event != 'None')]\n",
    "kickoffsCIN2019 = task1DataFrameKickoffs[(task1DataFrameKickoffs.season == 2019 ) & (task1DataFrameKickoffs.possessionTeam == 'CIN')\n",
    "                                         & (task1DataFrameKickoffs.penaltyCodes == 0) \n",
    "                                         & (task1DataFrameKickoffs.event != 'None')]\n",
    "kickoffsCIN2020 = task1DataFrameKickoffs[(task1DataFrameKickoffs.season == 2020 ) & (task1DataFrameKickoffs.possessionTeam == 'CIN')\n",
    "                                         & (task1DataFrameKickoffs.penaltyCodes == 0) \n",
    "                                         & (task1DataFrameKickoffs.event != 'None')]\n",
    "\n",
    "# Extra Points\n",
    "extraPointsCIN2018 = task1DataFrameExtrapoints[(task1DataFrameExtrapoints.season == 2018 ) & (task1DataFrameExtrapoints.possessionTeam == 'CIN') \n",
    "                                           & (task1DataFrameExtrapoints.penaltyCodes == 0) \n",
    "                                           & (task1DataFrameExtrapoints.event != 'None')]\n",
    "extraPointsCIN2019 = task1DataFrameExtrapoints[(task1DataFrameExtrapoints.season == 2019 ) & (task1DataFrameExtrapoints.possessionTeam == 'CIN') \n",
    "                                           & (task1DataFrameExtrapoints.penaltyCodes == 0) \n",
    "                                           & (task1DataFrameExtrapoints.event != 'None')]\n",
    "extraPointsCIN2020 = task1DataFrameExtrapoints[(task1DataFrameExtrapoints.season == 2020 ) & (task1DataFrameExtrapoints.possessionTeam == 'CIN') \n",
    "                                           & (task1DataFrameExtrapoints.penaltyCodes == 0) \n",
    "                                           & (task1DataFrameExtrapoints.event != 'None')]\n",
    "\n",
    "# Field Goals\n",
    "fieldGoalsCIN2018 = task1DataFrameFieldgoals[(task1DataFrameFieldgoals.season == 2018 ) & (task1DataFrameFieldgoals.possessionTeam == 'CIN')  \n",
    "                                         & (task1DataFrameFieldgoals.penaltyCodes == 0) \n",
    "                                         & (task1DataFrameFieldgoals.event != 'None')]\n",
    "fieldGoalsCIN2019 = task1DataFrameFieldgoals[(task1DataFrameFieldgoals.season == 2019 ) & (task1DataFrameFieldgoals.possessionTeam == 'CIN')  \n",
    "                                         & (task1DataFrameFieldgoals.penaltyCodes == 0) \n",
    "                                         & (task1DataFrameFieldgoals.event != 'None')]\n",
    "fieldGoalsCIN2020 = task1DataFrameFieldgoals[(task1DataFrameFieldgoals.season == 2020 ) & (task1DataFrameFieldgoals.possessionTeam == 'CIN')  \n",
    "                                         & (task1DataFrameFieldgoals.penaltyCodes == 0) \n",
    "                                         & (task1DataFrameFieldgoals.event != 'None')]\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "c29d3c26-40df-4b94-b759-6b7d93927578",
   "metadata": {},
   "outputs": [],
   "source": [
    "# DAL Special Plays Data Preparation\n",
    "\n",
    "# Punts\n",
    "puntsDAL2018 = task1DataFramePunts[(task1DataFramePunts.season == 2018 ) & (task1DataFramePunts.possessionTeam == 'DAL') \n",
    "                                   & (task1DataFramePunts.penaltyCodes == 0) \n",
    "                                   & (task1DataFramePunts.event != 'None')]\n",
    "puntsDAL2019 = task1DataFramePunts[(task1DataFramePunts.season == 2019 ) & (task1DataFramePunts.possessionTeam == 'DAL') \n",
    "                                   & (task1DataFramePunts.penaltyCodes == 0) \n",
    "                                   & (task1DataFramePunts.event != 'None')]\n",
    "puntsDAL2020 = task1DataFramePunts[(task1DataFramePunts.season == 2020 ) & (task1DataFramePunts.possessionTeam == 'DAL') \n",
    "                                   & (task1DataFramePunts.penaltyCodes == 0) \n",
    "                                   & (task1DataFramePunts.event != 'None')]\n",
    "\n",
    "# Kickoffs\n",
    "kickoffsDAL2018 = task1DataFrameKickoffs[(task1DataFrameKickoffs.season == 2018 ) & (task1DataFrameKickoffs.possessionTeam == 'DAL')\n",
    "                                         & (task1DataFrameKickoffs.penaltyCodes == 0) \n",
    "                                         & (task1DataFrameKickoffs.event != 'None')]\n",
    "kickoffsDAL2019 = task1DataFrameKickoffs[(task1DataFrameKickoffs.season == 2019 ) & (task1DataFrameKickoffs.possessionTeam == 'DAL')\n",
    "                                         & (task1DataFrameKickoffs.penaltyCodes == 0) \n",
    "                                         & (task1DataFrameKickoffs.event != 'None')]\n",
    "kickoffsDAL2020 = task1DataFrameKickoffs[(task1DataFrameKickoffs.season == 2020 ) & (task1DataFrameKickoffs.possessionTeam == 'DAL')\n",
    "                                         & (task1DataFrameKickoffs.penaltyCodes == 0) \n",
    "                                         & (task1DataFrameKickoffs.event != 'None')]\n",
    "\n",
    "# Extra Points\n",
    "extraPointsDAL2018 = task1DataFrameExtrapoints[(task1DataFrameExtrapoints.season == 2018 ) & (task1DataFrameExtrapoints.possessionTeam == 'DAL') \n",
    "                                           & (task1DataFrameExtrapoints.penaltyCodes == 0) \n",
    "                                           & (task1DataFrameExtrapoints.event != 'None')]\n",
    "extraPointsDAL2019 = task1DataFrameExtrapoints[(task1DataFrameExtrapoints.season == 2019 ) & (task1DataFrameExtrapoints.possessionTeam == 'DAL') \n",
    "                                           & (task1DataFrameExtrapoints.penaltyCodes == 0) \n",
    "                                           & (task1DataFrameExtrapoints.event != 'None')]\n",
    "extraPointsDAL2020 = task1DataFrameExtrapoints[(task1DataFrameExtrapoints.season == 2020 ) & (task1DataFrameExtrapoints.possessionTeam == 'DAL') \n",
    "                                           & (task1DataFrameExtrapoints.penaltyCodes == 0) \n",
    "                                           & (task1DataFrameExtrapoints.event != 'None')]\n",
    "\n",
    "# Field Goals\n",
    "fieldGoalsDAL2018 = task1DataFrameFieldgoals[(task1DataFrameFieldgoals.season == 2018 ) & (task1DataFrameFieldgoals.possessionTeam == 'DAL')  \n",
    "                                         & (task1DataFrameFieldgoals.penaltyCodes == 0) \n",
    "                                         & (task1DataFrameFieldgoals.event != 'None')]\n",
    "fieldGoalsDAL2019 = task1DataFrameFieldgoals[(task1DataFrameFieldgoals.season == 2019 ) & (task1DataFrameFieldgoals.possessionTeam == 'DAL')  \n",
    "                                         & (task1DataFrameFieldgoals.penaltyCodes == 0) \n",
    "                                         & (task1DataFrameFieldgoals.event != 'None')]\n",
    "fieldGoalsDAL2020 = task1DataFrameFieldgoals[(task1DataFrameFieldgoals.season == 2020 ) & (task1DataFrameFieldgoals.possessionTeam == 'DAL')  \n",
    "                                         & (task1DataFrameFieldgoals.penaltyCodes == 0) \n",
    "                                         & (task1DataFrameFieldgoals.event != 'None')]\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "6b392b24-981c-4d49-a588-3bbebeb5f4d4",
   "metadata": {},
   "outputs": [],
   "source": [
    "extraPointsDAL2018.to_csv(r'/Users/kushtrivedi/Desktop/NFL/Dallas/DAL_ExtraPoint_2018.csv', index=False)\n",
    "extraPointsDAL2019.to_csv(r'/Users/kushtrivedi/Desktop/NFL/Dallas/DAL_ExtraPoint_2019.csv', index=False)\n",
    "extraPointsDAL2020.to_csv(r'/Users/kushtrivedi/Desktop/NFL/Dallas/DAL_ExtraPoint_2020.csv', index=False)\n",
    "\n",
    "fieldGoalsDAL2018.to_csv(r'/Users/kushtrivedi/Desktop/NFL/Dallas/DAL_FiledGoals_2018.csv', index=False)\n",
    "fieldGoalsDAL2019.to_csv(r'/Users/kushtrivedi/Desktop/NFL/Dallas/DAL_FiledGoals_2019.csv', index=False)\n",
    "fieldGoalsDAL2020.to_csv(r'/Users/kushtrivedi/Desktop/NFL/Dallas/DAL_FiledGoals_2020.csv', index=False)\n",
    "\n",
    "kickoffsDAL2018.to_csv(r'/Users/kushtrivedi/Desktop/NFL/Dallas/DAL_Kickoffs_2018.csv', index=False)\n",
    "kickoffsDAL2019.to_csv(r'/Users/kushtrivedi/Desktop/NFL/Dallas/DAL_Kickoffs_2019.csv', index=False)\n",
    "kickoffsDAL2020.to_csv(r'/Users/kushtrivedi/Desktop/NFL/Dallas/DAL_Kickoffs_2020.csv', index=False)\n",
    "\n",
    "puntsDAL2018.to_csv(r'/Users/kushtrivedi/Desktop/NFL/Dallas/DAL_Punts_2018.csv', index=False)\n",
    "puntsDAL2019.to_csv(r'/Users/kushtrivedi/Desktop/NFL/Dallas/DAL_Punts_2019.csv', index=False)\n",
    "puntsDAL2020.to_csv(r'/Users/kushtrivedi/Desktop/NFL/Dallas/DAL_Punts_2020.csv', index=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "dd527456-3348-440a-a9ba-85ec57472e52",
   "metadata": {},
   "outputs": [],
   "source": [
    "# DEN Special Plays Data Preparation\n",
    "\n",
    "# Punts\n",
    "puntsDEN2018 = task1DataFramePunts[(task1DataFramePunts.season == 2018 ) & (task1DataFramePunts.possessionTeam == 'DEN') \n",
    "                                   & (task1DataFramePunts.penaltyCodes == 0) \n",
    "                                   & (task1DataFramePunts.event != 'None')]\n",
    "puntsDEN2019 = task1DataFramePunts[(task1DataFramePunts.season == 2019 ) & (task1DataFramePunts.possessionTeam == 'DEN') \n",
    "                                   & (task1DataFramePunts.penaltyCodes == 0) \n",
    "                                   & (task1DataFramePunts.event != 'None')]\n",
    "puntsDEN2020 = task1DataFramePunts[(task1DataFramePunts.season == 2020 ) & (task1DataFramePunts.possessionTeam == 'DEN') \n",
    "                                   & (task1DataFramePunts.penaltyCodes == 0) \n",
    "                                   & (task1DataFramePunts.event != 'None')]\n",
    "\n",
    "# Kickoffs\n",
    "kickoffsDEN2018 = task1DataFrameKickoffs[(task1DataFrameKickoffs.season == 2018 ) & (task1DataFrameKickoffs.possessionTeam == 'DEN')\n",
    "                                         & (task1DataFrameKickoffs.penaltyCodes == 0) \n",
    "                                         & (task1DataFrameKickoffs.event != 'None')]\n",
    "kickoffsDEN2019 = task1DataFrameKickoffs[(task1DataFrameKickoffs.season == 2019 ) & (task1DataFrameKickoffs.possessionTeam == 'DEN')\n",
    "                                         & (task1DataFrameKickoffs.penaltyCodes == 0) \n",
    "                                         & (task1DataFrameKickoffs.event != 'None')]\n",
    "kickoffsDEN2020 = task1DataFrameKickoffs[(task1DataFrameKickoffs.season == 2020 ) & (task1DataFrameKickoffs.possessionTeam == 'DEN')\n",
    "                                         & (task1DataFrameKickoffs.penaltyCodes == 0) \n",
    "                                         & (task1DataFrameKickoffs.event != 'None')]\n",
    "\n",
    "# Extra Points\n",
    "extraPointsDEN2018 = task1DataFrameExtrapoints[(task1DataFrameExtrapoints.season == 2018 ) & (task1DataFrameExtrapoints.possessionTeam == 'DEN') \n",
    "                                           & (task1DataFrameExtrapoints.penaltyCodes == 0) \n",
    "                                           & (task1DataFrameExtrapoints.event != 'None')]\n",
    "extraPointsDEN2019 = task1DataFrameExtrapoints[(task1DataFrameExtrapoints.season == 2019 ) & (task1DataFrameExtrapoints.possessionTeam == 'DEN') \n",
    "                                           & (task1DataFrameExtrapoints.penaltyCodes == 0) \n",
    "                                           & (task1DataFrameExtrapoints.event != 'None')]\n",
    "extraPointsDEN2020 = task1DataFrameExtrapoints[(task1DataFrameExtrapoints.season == 2020 ) & (task1DataFrameExtrapoints.possessionTeam == 'DEN') \n",
    "                                           & (task1DataFrameExtrapoints.penaltyCodes == 0) \n",
    "                                           & (task1DataFrameExtrapoints.event != 'None')]\n",
    "\n",
    "# Field Goals\n",
    "fieldGoalsDEN2018 = task1DataFrameFieldgoals[(task1DataFrameFieldgoals.season == 2018 ) & (task1DataFrameFieldgoals.possessionTeam == 'DEN')  \n",
    "                                         & (task1DataFrameFieldgoals.penaltyCodes == 0) \n",
    "                                         & (task1DataFrameFieldgoals.event != 'None')]\n",
    "fieldGoalsDEN2019 = task1DataFrameFieldgoals[(task1DataFrameFieldgoals.season == 2019 ) & (task1DataFrameFieldgoals.possessionTeam == 'DEN')  \n",
    "                                         & (task1DataFrameFieldgoals.penaltyCodes == 0) \n",
    "                                         & (task1DataFrameFieldgoals.event != 'None')]\n",
    "fieldGoalsDEN2020 = task1DataFrameFieldgoals[(task1DataFrameFieldgoals.season == 2020 ) & (task1DataFrameFieldgoals.possessionTeam == 'DEN')  \n",
    "                                         & (task1DataFrameFieldgoals.penaltyCodes == 0) \n",
    "                                         & (task1DataFrameFieldgoals.event != 'None')]\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "47bbf0f9-b432-4e75-8207-d19d2d68abd7",
   "metadata": {},
   "outputs": [],
   "source": [
    "# DET Special Plays Data Preparation\n",
    "\n",
    "# Punts\n",
    "puntsDET2018 = task1DataFramePunts[(task1DataFramePunts.season == 2018 ) & (task1DataFramePunts.possessionTeam == 'DET') \n",
    "                                   & (task1DataFramePunts.penaltyCodes == 0) \n",
    "                                   & (task1DataFramePunts.event != 'None')]\n",
    "puntsDET2019 = task1DataFramePunts[(task1DataFramePunts.season == 2019 ) & (task1DataFramePunts.possessionTeam == 'DET') \n",
    "                                   & (task1DataFramePunts.penaltyCodes == 0) \n",
    "                                   & (task1DataFramePunts.event != 'None')]\n",
    "puntsDET2020 = task1DataFramePunts[(task1DataFramePunts.season == 2020 ) & (task1DataFramePunts.possessionTeam == 'DET') \n",
    "                                   & (task1DataFramePunts.penaltyCodes == 0) \n",
    "                                   & (task1DataFramePunts.event != 'None')]\n",
    "\n",
    "# Kickoffs\n",
    "kickoffsDET2018 = task1DataFrameKickoffs[(task1DataFrameKickoffs.season == 2018 ) & (task1DataFrameKickoffs.possessionTeam == 'DET')\n",
    "                                         & (task1DataFrameKickoffs.penaltyCodes == 0) \n",
    "                                         & (task1DataFrameKickoffs.event != 'None')]\n",
    "kickoffsDET2019 = task1DataFrameKickoffs[(task1DataFrameKickoffs.season == 2019 ) & (task1DataFrameKickoffs.possessionTeam == 'DET')\n",
    "                                         & (task1DataFrameKickoffs.penaltyCodes == 0) \n",
    "                                         & (task1DataFrameKickoffs.event != 'None')]\n",
    "kickoffsDET2020 = task1DataFrameKickoffs[(task1DataFrameKickoffs.season == 2020 ) & (task1DataFrameKickoffs.possessionTeam == 'DET')\n",
    "                                         & (task1DataFrameKickoffs.penaltyCodes == 0) \n",
    "                                         & (task1DataFrameKickoffs.event != 'None')]\n",
    "\n",
    "# Extra Points\n",
    "extraPointsDET2018 = task1DataFrameExtrapoints[(task1DataFrameExtrapoints.season == 2018 ) & (task1DataFrameExtrapoints.possessionTeam == 'DET') \n",
    "                                           & (task1DataFrameExtrapoints.penaltyCodes == 0) \n",
    "                                           & (task1DataFrameExtrapoints.event != 'None')]\n",
    "extraPointsDET2019 = task1DataFrameExtrapoints[(task1DataFrameExtrapoints.season == 2019 ) & (task1DataFrameExtrapoints.possessionTeam == 'DET') \n",
    "                                           & (task1DataFrameExtrapoints.penaltyCodes == 0) \n",
    "                                           & (task1DataFrameExtrapoints.event != 'None')]\n",
    "extraPointsDET2020 = task1DataFrameExtrapoints[(task1DataFrameExtrapoints.season == 2020 ) & (task1DataFrameExtrapoints.possessionTeam == 'DET') \n",
    "                                           & (task1DataFrameExtrapoints.penaltyCodes == 0) \n",
    "                                           & (task1DataFrameExtrapoints.event != 'None')]\n",
    "\n",
    "# Field Goals\n",
    "fieldGoalsDET2018 = task1DataFrameFieldgoals[(task1DataFrameFieldgoals.season == 2018 ) & (task1DataFrameFieldgoals.possessionTeam == 'DET')  \n",
    "                                         & (task1DataFrameFieldgoals.penaltyCodes == 0) \n",
    "                                         & (task1DataFrameFieldgoals.event != 'None')]\n",
    "fieldGoalsDET2019 = task1DataFrameFieldgoals[(task1DataFrameFieldgoals.season == 2019 ) & (task1DataFrameFieldgoals.possessionTeam == 'DET')  \n",
    "                                         & (task1DataFrameFieldgoals.penaltyCodes == 0) \n",
    "                                         & (task1DataFrameFieldgoals.event != 'None')]\n",
    "fieldGoalsDET2020 = task1DataFrameFieldgoals[(task1DataFrameFieldgoals.season == 2020 ) & (task1DataFrameFieldgoals.possessionTeam == 'DET')  \n",
    "                                         & (task1DataFrameFieldgoals.penaltyCodes == 0) \n",
    "                                         & (task1DataFrameFieldgoals.event != 'None')]\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "b0b0719f-8341-4026-918d-0f622a3688e0",
   "metadata": {},
   "outputs": [],
   "source": [
    "# GB Special Plays Data Preparation\n",
    "\n",
    "# Punts\n",
    "puntsGB2018 = task1DataFramePunts[(task1DataFramePunts.season == 2018 ) & (task1DataFramePunts.possessionTeam == 'GB') \n",
    "                                   & (task1DataFramePunts.penaltyCodes == 0) \n",
    "                                   & (task1DataFramePunts.event != 'None')]\n",
    "puntsGB2019 = task1DataFramePunts[(task1DataFramePunts.season == 2019 ) & (task1DataFramePunts.possessionTeam == 'GB') \n",
    "                                   & (task1DataFramePunts.penaltyCodes == 0) \n",
    "                                   & (task1DataFramePunts.event != 'None')]\n",
    "puntsGB2020 = task1DataFramePunts[(task1DataFramePunts.season == 2020 ) & (task1DataFramePunts.possessionTeam == 'GB') \n",
    "                                   & (task1DataFramePunts.penaltyCodes == 0) \n",
    "                                   & (task1DataFramePunts.event != 'None')]\n",
    "\n",
    "# Kickoffs\n",
    "kickoffsGB2018 = task1DataFrameKickoffs[(task1DataFrameKickoffs.season == 2018 ) & (task1DataFrameKickoffs.possessionTeam == 'GB')\n",
    "                                         & (task1DataFrameKickoffs.penaltyCodes == 0) \n",
    "                                         & (task1DataFrameKickoffs.event != 'None')]\n",
    "kickoffsGB2019 = task1DataFrameKickoffs[(task1DataFrameKickoffs.season == 2019 ) & (task1DataFrameKickoffs.possessionTeam == 'GB')\n",
    "                                         & (task1DataFrameKickoffs.penaltyCodes == 0) \n",
    "                                         & (task1DataFrameKickoffs.event != 'None')]\n",
    "kickoffsGB2020 = task1DataFrameKickoffs[(task1DataFrameKickoffs.season == 2020 ) & (task1DataFrameKickoffs.possessionTeam == 'GB')\n",
    "                                         & (task1DataFrameKickoffs.penaltyCodes == 0) \n",
    "                                         & (task1DataFrameKickoffs.event != 'None')]\n",
    "\n",
    "# Extra Points\n",
    "extraPointsGB2018 = task1DataFrameExtrapoints[(task1DataFrameExtrapoints.season == 2018 ) & (task1DataFrameExtrapoints.possessionTeam == 'GB') \n",
    "                                           & (task1DataFrameExtrapoints.penaltyCodes == 0) \n",
    "                                           & (task1DataFrameExtrapoints.event != 'None')]\n",
    "extraPointsGB2019 = task1DataFrameExtrapoints[(task1DataFrameExtrapoints.season == 2019 ) & (task1DataFrameExtrapoints.possessionTeam == 'GB') \n",
    "                                           & (task1DataFrameExtrapoints.penaltyCodes == 0) \n",
    "                                           & (task1DataFrameExtrapoints.event != 'None')]\n",
    "extraPointsGB2020 = task1DataFrameExtrapoints[(task1DataFrameExtrapoints.season == 2020 ) & (task1DataFrameExtrapoints.possessionTeam == 'GB') \n",
    "                                           & (task1DataFrameExtrapoints.penaltyCodes == 0) \n",
    "                                           & (task1DataFrameExtrapoints.event != 'None')]\n",
    "\n",
    "# Field Goals\n",
    "fieldGoalsGB2018 = task1DataFrameFieldgoals[(task1DataFrameFieldgoals.season == 2018 ) & (task1DataFrameFieldgoals.possessionTeam == 'GB')  \n",
    "                                         & (task1DataFrameFieldgoals.penaltyCodes == 0) \n",
    "                                         & (task1DataFrameFieldgoals.event != 'None')]\n",
    "fieldGoalsGB2019 = task1DataFrameFieldgoals[(task1DataFrameFieldgoals.season == 2019 ) & (task1DataFrameFieldgoals.possessionTeam == 'GB')  \n",
    "                                         & (task1DataFrameFieldgoals.penaltyCodes == 0) \n",
    "                                         & (task1DataFrameFieldgoals.event != 'None')]\n",
    "fieldGoalsGB2020 = task1DataFrameFieldgoals[(task1DataFrameFieldgoals.season == 2020 ) & (task1DataFrameFieldgoals.possessionTeam == 'GB')  \n",
    "                                         & (task1DataFrameFieldgoals.penaltyCodes == 0) \n",
    "                                         & (task1DataFrameFieldgoals.event != 'None')]\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "7114e5f4-0768-47e0-a9d6-a1fffce0bc7d",
   "metadata": {},
   "outputs": [],
   "source": [
    "extraPointsGB2018.to_csv(r'/Users/kushtrivedi/Desktop/NFL/GreenBay/GB_ExtraPoint_2018.csv', index=False)\n",
    "extraPointsGB2019.to_csv(r'/Users/kushtrivedi/Desktop/NFL/GreenBay/GB_ExtraPoint_2019.csv', index=False)\n",
    "extraPointsGB2020.to_csv(r'/Users/kushtrivedi/Desktop/NFL/GreenBay/GB_ExtraPoint_2020.csv', index=False)\n",
    "\n",
    "fieldGoalsGB2018.to_csv(r'/Users/kushtrivedi/Desktop/NFL/GreenBay/GB_FiledGoals_2018.csv', index=False)\n",
    "fieldGoalsGB2019.to_csv(r'/Users/kushtrivedi/Desktop/NFL/GreenBay/GB_FiledGoals_2019.csv', index=False)\n",
    "fieldGoalsGB2020.to_csv(r'/Users/kushtrivedi/Desktop/NFL/GreenBay/GB_FiledGoals_2020.csv', index=False)\n",
    "\n",
    "kickoffsGB2018.to_csv(r'/Users/kushtrivedi/Desktop/NFL/GreenBay/GB_Kickoffs_2018.csv', index=False)\n",
    "kickoffsGB2019.to_csv(r'/Users/kushtrivedi/Desktop/NFL/GreenBay/GB_Kickoffs_2019.csv', index=False)\n",
    "kickoffsGB2020.to_csv(r'/Users/kushtrivedi/Desktop/NFL/GreenBay/GB_Kickoffs_2020.csv', index=False)\n",
    "\n",
    "puntsGB2018.to_csv(r'/Users/kushtrivedi/Desktop/NFL/GreenBay/GB_Punts_2018.csv', index=False)\n",
    "puntsGB2019.to_csv(r'/Users/kushtrivedi/Desktop/NFL/GreenBay/GB_Punts_2019.csv', index=False)\n",
    "puntsGB2020.to_csv(r'/Users/kushtrivedi/Desktop/NFL/GreenBay/GB_Punts_2020.csv', index=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "5444fdd3-c2ba-4ab0-862b-52dfa4889d72",
   "metadata": {},
   "outputs": [],
   "source": [
    "# HOU Special Plays Data Preparation\n",
    "\n",
    "# Punts\n",
    "puntsHOU2018 = task1DataFramePunts[(task1DataFramePunts.season == 2018 ) & (task1DataFramePunts.possessionTeam == 'HOU') \n",
    "                                   & (task1DataFramePunts.penaltyCodes == 0) \n",
    "                                   & (task1DataFramePunts.event != 'None')]\n",
    "puntsHOU2019 = task1DataFramePunts[(task1DataFramePunts.season == 2019 ) & (task1DataFramePunts.possessionTeam == 'HOU') \n",
    "                                   & (task1DataFramePunts.penaltyCodes == 0) \n",
    "                                   & (task1DataFramePunts.event != 'None')]\n",
    "puntsHOU2020 = task1DataFramePunts[(task1DataFramePunts.season == 2020 ) & (task1DataFramePunts.possessionTeam == 'HOU') \n",
    "                                   & (task1DataFramePunts.penaltyCodes == 0) \n",
    "                                   & (task1DataFramePunts.event != 'None')]\n",
    "\n",
    "# Kickoffs\n",
    "kickoffsHOU2018 = task1DataFrameKickoffs[(task1DataFrameKickoffs.season == 2018 ) & (task1DataFrameKickoffs.possessionTeam == 'HOU')\n",
    "                                         & (task1DataFrameKickoffs.penaltyCodes == 0) \n",
    "                                         & (task1DataFrameKickoffs.event != 'None')]\n",
    "kickoffsHOU2019 = task1DataFrameKickoffs[(task1DataFrameKickoffs.season == 2019 ) & (task1DataFrameKickoffs.possessionTeam == 'HOU')\n",
    "                                         & (task1DataFrameKickoffs.penaltyCodes == 0) \n",
    "                                         & (task1DataFrameKickoffs.event != 'None')]\n",
    "kickoffsHOU2020 = task1DataFrameKickoffs[(task1DataFrameKickoffs.season == 2020 ) & (task1DataFrameKickoffs.possessionTeam == 'HOU')\n",
    "                                         & (task1DataFrameKickoffs.penaltyCodes == 0) \n",
    "                                         & (task1DataFrameKickoffs.event != 'None')]\n",
    "\n",
    "# Extra Points\n",
    "extraPointsHOU2018 = task1DataFrameExtrapoints[(task1DataFrameExtrapoints.season == 2018 ) & (task1DataFrameExtrapoints.possessionTeam == 'HOU') \n",
    "                                           & (task1DataFrameExtrapoints.penaltyCodes == 0) \n",
    "                                           & (task1DataFrameExtrapoints.event != 'None')]\n",
    "extraPointsHOU2019 = task1DataFrameExtrapoints[(task1DataFrameExtrapoints.season == 2019 ) & (task1DataFrameExtrapoints.possessionTeam == 'HOU') \n",
    "                                           & (task1DataFrameExtrapoints.penaltyCodes == 0) \n",
    "                                           & (task1DataFrameExtrapoints.event != 'None')]\n",
    "extraPointsHOU2020 = task1DataFrameExtrapoints[(task1DataFrameExtrapoints.season == 2020 ) & (task1DataFrameExtrapoints.possessionTeam == 'HOU') \n",
    "                                           & (task1DataFrameExtrapoints.penaltyCodes == 0) \n",
    "                                           & (task1DataFrameExtrapoints.event != 'None')]\n",
    "\n",
    "# Field Goals\n",
    "fieldGoalsHOU2018 = task1DataFrameFieldgoals[(task1DataFrameFieldgoals.season == 2018 ) & (task1DataFrameFieldgoals.possessionTeam == 'HOU')  \n",
    "                                         & (task1DataFrameFieldgoals.penaltyCodes == 0) \n",
    "                                         & (task1DataFrameFieldgoals.event != 'None')]\n",
    "fieldGoalsHOU2019 = task1DataFrameFieldgoals[(task1DataFrameFieldgoals.season == 2019 ) & (task1DataFrameFieldgoals.possessionTeam == 'HOU')  \n",
    "                                         & (task1DataFrameFieldgoals.penaltyCodes == 0) \n",
    "                                         & (task1DataFrameFieldgoals.event != 'None')]\n",
    "fieldGoalsHOU2020 = task1DataFrameFieldgoals[(task1DataFrameFieldgoals.season == 2020 ) & (task1DataFrameFieldgoals.possessionTeam == 'HOU')  \n",
    "                                         & (task1DataFrameFieldgoals.penaltyCodes == 0) \n",
    "                                         & (task1DataFrameFieldgoals.event != 'None')]\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "d7a14f67-f8d0-4326-9fb7-3ca400ea6430",
   "metadata": {},
   "outputs": [],
   "source": [
    "# IND Special Plays Data Preparation\n",
    "\n",
    "# Punts\n",
    "puntsIND2018 = task1DataFramePunts[(task1DataFramePunts.season == 2018 ) & (task1DataFramePunts.possessionTeam == 'IND') \n",
    "                                   & (task1DataFramePunts.penaltyCodes == 0) \n",
    "                                   & (task1DataFramePunts.event != 'None')]\n",
    "puntsIND2019 = task1DataFramePunts[(task1DataFramePunts.season == 2019 ) & (task1DataFramePunts.possessionTeam == 'IND') \n",
    "                                   & (task1DataFramePunts.penaltyCodes == 0) \n",
    "                                   & (task1DataFramePunts.event != 'None')]\n",
    "puntsIND2020 = task1DataFramePunts[(task1DataFramePunts.season == 2020 ) & (task1DataFramePunts.possessionTeam == 'IND') \n",
    "                                   & (task1DataFramePunts.penaltyCodes == 0) \n",
    "                                   & (task1DataFramePunts.event != 'None')]\n",
    "\n",
    "# Kickoffs\n",
    "kickoffsIND2018 = task1DataFrameKickoffs[(task1DataFrameKickoffs.season == 2018 ) & (task1DataFrameKickoffs.possessionTeam == 'IND')\n",
    "                                         & (task1DataFrameKickoffs.penaltyCodes == 0) \n",
    "                                         & (task1DataFrameKickoffs.event != 'None')]\n",
    "kickoffsIND2019 = task1DataFrameKickoffs[(task1DataFrameKickoffs.season == 2019 ) & (task1DataFrameKickoffs.possessionTeam == 'IND')\n",
    "                                         & (task1DataFrameKickoffs.penaltyCodes == 0) \n",
    "                                         & (task1DataFrameKickoffs.event != 'None')]\n",
    "kickoffsIND2020 = task1DataFrameKickoffs[(task1DataFrameKickoffs.season == 2020 ) & (task1DataFrameKickoffs.possessionTeam == 'IND')\n",
    "                                         & (task1DataFrameKickoffs.penaltyCodes == 0) \n",
    "                                         & (task1DataFrameKickoffs.event != 'None')]\n",
    "\n",
    "# Extra Points\n",
    "extraPointsIND2018 = task1DataFrameExtrapoints[(task1DataFrameExtrapoints.season == 2018 ) & (task1DataFrameExtrapoints.possessionTeam == 'IND') \n",
    "                                           & (task1DataFrameExtrapoints.penaltyCodes == 0) \n",
    "                                           & (task1DataFrameExtrapoints.event != 'None')]\n",
    "extraPointsIND2019 = task1DataFrameExtrapoints[(task1DataFrameExtrapoints.season == 2019 ) & (task1DataFrameExtrapoints.possessionTeam == 'IND') \n",
    "                                           & (task1DataFrameExtrapoints.penaltyCodes == 0) \n",
    "                                           & (task1DataFrameExtrapoints.event != 'None')]\n",
    "extraPointsIND2020 = task1DataFrameExtrapoints[(task1DataFrameExtrapoints.season == 2020 ) & (task1DataFrameExtrapoints.possessionTeam == 'IND') \n",
    "                                           & (task1DataFrameExtrapoints.penaltyCodes == 0) \n",
    "                                           & (task1DataFrameExtrapoints.event != 'None')]\n",
    "\n",
    "# Field Goals\n",
    "fieldGoalsIND2018 = task1DataFrameFieldgoals[(task1DataFrameFieldgoals.season == 2018 ) & (task1DataFrameFieldgoals.possessionTeam == 'IND')  \n",
    "                                         & (task1DataFrameFieldgoals.penaltyCodes == 0) \n",
    "                                         & (task1DataFrameFieldgoals.event != 'None')]\n",
    "fieldGoalsIND2019 = task1DataFrameFieldgoals[(task1DataFrameFieldgoals.season == 2019 ) & (task1DataFrameFieldgoals.possessionTeam == 'IND')  \n",
    "                                         & (task1DataFrameFieldgoals.penaltyCodes == 0) \n",
    "                                         & (task1DataFrameFieldgoals.event != 'None')]\n",
    "fieldGoalsIND2020 = task1DataFrameFieldgoals[(task1DataFrameFieldgoals.season == 2020 ) & (task1DataFrameFieldgoals.possessionTeam == 'IND')  \n",
    "                                         & (task1DataFrameFieldgoals.penaltyCodes == 0) \n",
    "                                         & (task1DataFrameFieldgoals.event != 'None')]\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "e0f86d74-c941-4042-9418-50f7b2b6ee5a",
   "metadata": {},
   "outputs": [],
   "source": [
    "# JAX Special Plays Data Preparation\n",
    "\n",
    "# Punts\n",
    "puntsJAX2018 = task1DataFramePunts[(task1DataFramePunts.season == 2018 ) & (task1DataFramePunts.possessionTeam == 'JAX') \n",
    "                                   & (task1DataFramePunts.penaltyCodes == 0) \n",
    "                                   & (task1DataFramePunts.event != 'None')]\n",
    "puntsJAX2019 = task1DataFramePunts[(task1DataFramePunts.season == 2019 ) & (task1DataFramePunts.possessionTeam == 'JAX') \n",
    "                                   & (task1DataFramePunts.penaltyCodes == 0) \n",
    "                                   & (task1DataFramePunts.event != 'None')]\n",
    "puntsJAX2020 = task1DataFramePunts[(task1DataFramePunts.season == 2020 ) & (task1DataFramePunts.possessionTeam == 'JAX') \n",
    "                                   & (task1DataFramePunts.penaltyCodes == 0) \n",
    "                                   & (task1DataFramePunts.event != 'None')]\n",
    "\n",
    "# Kickoffs\n",
    "kickoffsJAX2018 = task1DataFrameKickoffs[(task1DataFrameKickoffs.season == 2018 ) & (task1DataFrameKickoffs.possessionTeam == 'JAX')\n",
    "                                         & (task1DataFrameKickoffs.penaltyCodes == 0) \n",
    "                                         & (task1DataFrameKickoffs.event != 'None')]\n",
    "kickoffsJAX2019 = task1DataFrameKickoffs[(task1DataFrameKickoffs.season == 2019 ) & (task1DataFrameKickoffs.possessionTeam == 'JAX')\n",
    "                                         & (task1DataFrameKickoffs.penaltyCodes == 0) \n",
    "                                         & (task1DataFrameKickoffs.event != 'None')]\n",
    "kickoffsJAX2020 = task1DataFrameKickoffs[(task1DataFrameKickoffs.season == 2020 ) & (task1DataFrameKickoffs.possessionTeam == 'JAX')\n",
    "                                         & (task1DataFrameKickoffs.penaltyCodes == 0) \n",
    "                                         & (task1DataFrameKickoffs.event != 'None')]\n",
    "\n",
    "# Extra Points\n",
    "extraPointsJAX2018 = task1DataFrameExtrapoints[(task1DataFrameExtrapoints.season == 2018 ) & (task1DataFrameExtrapoints.possessionTeam == 'JAX') \n",
    "                                           & (task1DataFrameExtrapoints.penaltyCodes == 0) \n",
    "                                           & (task1DataFrameExtrapoints.event != 'None')]\n",
    "extraPointsJAX2019 = task1DataFrameExtrapoints[(task1DataFrameExtrapoints.season == 2019 ) & (task1DataFrameExtrapoints.possessionTeam == 'JAX') \n",
    "                                           & (task1DataFrameExtrapoints.penaltyCodes == 0) \n",
    "                                           & (task1DataFrameExtrapoints.event != 'None')]\n",
    "extraPointsJAX2020 = task1DataFrameExtrapoints[(task1DataFrameExtrapoints.season == 2020 ) & (task1DataFrameExtrapoints.possessionTeam == 'JAX') \n",
    "                                           & (task1DataFrameExtrapoints.penaltyCodes == 0) \n",
    "                                           & (task1DataFrameExtrapoints.event != 'None')]\n",
    "\n",
    "# Field Goals\n",
    "fieldGoalsJAX2018 = task1DataFrameFieldgoals[(task1DataFrameFieldgoals.season == 2018 ) & (task1DataFrameFieldgoals.possessionTeam == 'JAX')  \n",
    "                                         & (task1DataFrameFieldgoals.penaltyCodes == 0) \n",
    "                                         & (task1DataFrameFieldgoals.event != 'None')]\n",
    "fieldGoalsJAX2019 = task1DataFrameFieldgoals[(task1DataFrameFieldgoals.season == 2019 ) & (task1DataFrameFieldgoals.possessionTeam == 'JAX')  \n",
    "                                         & (task1DataFrameFieldgoals.penaltyCodes == 0) \n",
    "                                         & (task1DataFrameFieldgoals.event != 'None')]\n",
    "fieldGoalsJAX2020 = task1DataFrameFieldgoals[(task1DataFrameFieldgoals.season == 2020 ) & (task1DataFrameFieldgoals.possessionTeam == 'JAX')  \n",
    "                                         & (task1DataFrameFieldgoals.penaltyCodes == 0) \n",
    "                                         & (task1DataFrameFieldgoals.event != 'None')]\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "44224fa7-6d3d-494a-8034-27dd299c4c3c",
   "metadata": {},
   "outputs": [],
   "source": [
    "# KC Special Plays Data Preparation\n",
    "\n",
    "# Punts\n",
    "puntsKC2018 = task1DataFramePunts[(task1DataFramePunts.season == 2018 ) & (task1DataFramePunts.possessionTeam == 'KC') \n",
    "                                   & (task1DataFramePunts.penaltyCodes == 0) \n",
    "                                   & (task1DataFramePunts.event != 'None')]\n",
    "puntsKC2019 = task1DataFramePunts[(task1DataFramePunts.season == 2019 ) & (task1DataFramePunts.possessionTeam == 'KC') \n",
    "                                   & (task1DataFramePunts.penaltyCodes == 0) \n",
    "                                   & (task1DataFramePunts.event != 'None')]\n",
    "puntsKC2020 = task1DataFramePunts[(task1DataFramePunts.season == 2020 ) & (task1DataFramePunts.possessionTeam == 'KC') \n",
    "                                   & (task1DataFramePunts.penaltyCodes == 0) \n",
    "                                   & (task1DataFramePunts.event != 'None')]\n",
    "\n",
    "# Kickoffs\n",
    "kickoffsKC2018 = task1DataFrameKickoffs[(task1DataFrameKickoffs.season == 2018 ) & (task1DataFrameKickoffs.possessionTeam == 'KC')\n",
    "                                         & (task1DataFrameKickoffs.penaltyCodes == 0) \n",
    "                                         & (task1DataFrameKickoffs.event != 'None')]\n",
    "kickoffsKC2019 = task1DataFrameKickoffs[(task1DataFrameKickoffs.season == 2019 ) & (task1DataFrameKickoffs.possessionTeam == 'KC')\n",
    "                                         & (task1DataFrameKickoffs.penaltyCodes == 0) \n",
    "                                         & (task1DataFrameKickoffs.event != 'None')]\n",
    "kickoffsKC2020 = task1DataFrameKickoffs[(task1DataFrameKickoffs.season == 2020 ) & (task1DataFrameKickoffs.possessionTeam == 'KC')\n",
    "                                         & (task1DataFrameKickoffs.penaltyCodes == 0) \n",
    "                                         & (task1DataFrameKickoffs.event != 'None')]\n",
    "\n",
    "# Extra Points\n",
    "extraPointsKC2018 = task1DataFrameExtrapoints[(task1DataFrameExtrapoints.season == 2018 ) & (task1DataFrameExtrapoints.possessionTeam == 'KC') \n",
    "                                           & (task1DataFrameExtrapoints.penaltyCodes == 0) \n",
    "                                           & (task1DataFrameExtrapoints.event != 'None')]\n",
    "extraPointsKC2019 = task1DataFrameExtrapoints[(task1DataFrameExtrapoints.season == 2019 ) & (task1DataFrameExtrapoints.possessionTeam == 'KC') \n",
    "                                           & (task1DataFrameExtrapoints.penaltyCodes == 0) \n",
    "                                           & (task1DataFrameExtrapoints.event != 'None')]\n",
    "extraPointsKC2020 = task1DataFrameExtrapoints[(task1DataFrameExtrapoints.season == 2020 ) & (task1DataFrameExtrapoints.possessionTeam == 'KC') \n",
    "                                           & (task1DataFrameExtrapoints.penaltyCodes == 0) \n",
    "                                           & (task1DataFrameExtrapoints.event != 'None')]\n",
    "\n",
    "# Field Goals\n",
    "fieldGoalsKC2018 = task1DataFrameFieldgoals[(task1DataFrameFieldgoals.season == 2018 ) & (task1DataFrameFieldgoals.possessionTeam == 'KC')  \n",
    "                                         & (task1DataFrameFieldgoals.penaltyCodes == 0) \n",
    "                                         & (task1DataFrameFieldgoals.event != 'None')]\n",
    "fieldGoalsKC2019 = task1DataFrameFieldgoals[(task1DataFrameFieldgoals.season == 2019 ) & (task1DataFrameFieldgoals.possessionTeam == 'KC')  \n",
    "                                         & (task1DataFrameFieldgoals.penaltyCodes == 0) \n",
    "                                         & (task1DataFrameFieldgoals.event != 'None')]\n",
    "fieldGoalsKC2020 = task1DataFrameFieldgoals[(task1DataFrameFieldgoals.season == 2020 ) & (task1DataFrameFieldgoals.possessionTeam == 'KC')  \n",
    "                                         & (task1DataFrameFieldgoals.penaltyCodes == 0) \n",
    "                                         & (task1DataFrameFieldgoals.event != 'None')]\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "ef5c4d00-a9bf-488d-8492-8f835a52e0a4",
   "metadata": {},
   "outputs": [],
   "source": [
    "kickoffsKC2020.head(100).T"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "45b94e43-19c3-4035-b901-62c0f64d5892",
   "metadata": {},
   "outputs": [],
   "source": [
    "extraPointsKC2018.to_csv(r'/Users/kushtrivedi/Desktop/NFL/KansasCity/KC_ExtraPoint_2018.csv', index=False)\n",
    "extraPointsKC2019.to_csv(r'/Users/kushtrivedi/Desktop/NFL/KansasCity/KC_ExtraPoint_2019.csv', index=False)\n",
    "extraPointsKC2020.to_csv(r'/Users/kushtrivedi/Desktop/NFL/KansasCity/KC_ExtraPoint_2020.csv', index=False)\n",
    "\n",
    "fieldGoalsKC2018.to_csv(r'/Users/kushtrivedi/Desktop/NFL/KansasCity/KC_FiledGoals_2018.csv', index=False)\n",
    "fieldGoalsKC2019.to_csv(r'/Users/kushtrivedi/Desktop/NFL/KansasCity/KC_FiledGoals_2019.csv', index=False)\n",
    "fieldGoalsKC2020.to_csv(r'/Users/kushtrivedi/Desktop/NFL/KansasCity/KC_FiledGoals_2020.csv', index=False)\n",
    "\n",
    "kickoffsKC2018.to_csv(r'/Users/kushtrivedi/Desktop/NFL/KansasCity/KC_Kickoffs_2018.csv', index=False)\n",
    "kickoffsKC2019.to_csv(r'/Users/kushtrivedi/Desktop/NFL/KansasCity/KC_Kickoffs_2019.csv', index=False)\n",
    "kickoffsKC2020.to_csv(r'/Users/kushtrivedi/Desktop/NFL/KansasCity/KC_Kickoffs_2020.csv', index=False)\n",
    "\n",
    "puntsKC2018.to_csv(r'/Users/kushtrivedi/Desktop/NFL/KansasCity/KC_Punts_2018.csv', index=False)\n",
    "puntsKC2019.to_csv(r'/Users/kushtrivedi/Desktop/NFL/KansasCity/KC_Punts_2019.csv', index=False)\n",
    "puntsKC2020.to_csv(r'/Users/kushtrivedi/Desktop/NFL/KansasCity/KC_Punts_2020.csv', index=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "61068fa8-bfc4-4123-a943-c0e46b829abf",
   "metadata": {},
   "outputs": [],
   "source": [
    "# LA Special Plays Data Preparation\n",
    "\n",
    "# Punts\n",
    "puntsLA2018 = task1DataFramePunts[(task1DataFramePunts.season == 2018 ) & (task1DataFramePunts.possessionTeam == 'LA') \n",
    "                                   & (task1DataFramePunts.penaltyCodes == 0) \n",
    "                                   & (task1DataFramePunts.event != 'None')]\n",
    "puntsLA2019 = task1DataFramePunts[(task1DataFramePunts.season == 2019 ) & (task1DataFramePunts.possessionTeam == 'LA') \n",
    "                                   & (task1DataFramePunts.penaltyCodes == 0) \n",
    "                                   & (task1DataFramePunts.event != 'None')]\n",
    "puntsLA2020 = task1DataFramePunts[(task1DataFramePunts.season == 2020 ) & (task1DataFramePunts.possessionTeam == 'LA') \n",
    "                                   & (task1DataFramePunts.penaltyCodes == 0) \n",
    "                                   & (task1DataFramePunts.event != 'None')]\n",
    "\n",
    "# Kickoffs\n",
    "kickoffsLA2018 = task1DataFrameKickoffs[(task1DataFrameKickoffs.season == 2018 ) & (task1DataFrameKickoffs.possessionTeam == 'LA')\n",
    "                                         & (task1DataFrameKickoffs.penaltyCodes == 0) \n",
    "                                         & (task1DataFrameKickoffs.event != 'None')]\n",
    "kickoffsLA2019 = task1DataFrameKickoffs[(task1DataFrameKickoffs.season == 2019 ) & (task1DataFrameKickoffs.possessionTeam == 'LA')\n",
    "                                         & (task1DataFrameKickoffs.penaltyCodes == 0) \n",
    "                                         & (task1DataFrameKickoffs.event != 'None')]\n",
    "kickoffsLA2020 = task1DataFrameKickoffs[(task1DataFrameKickoffs.season == 2020 ) & (task1DataFrameKickoffs.possessionTeam == 'LA')\n",
    "                                         & (task1DataFrameKickoffs.penaltyCodes == 0) \n",
    "                                         & (task1DataFrameKickoffs.event != 'None')]\n",
    "\n",
    "# Extra Points\n",
    "extraPointsLA2018 = task1DataFrameExtrapoints[(task1DataFrameExtrapoints.season == 2018 ) & (task1DataFrameExtrapoints.possessionTeam == 'LA') \n",
    "                                           & (task1DataFrameExtrapoints.penaltyCodes == 0) \n",
    "                                           & (task1DataFrameExtrapoints.event != 'None')]\n",
    "extraPointsLA2019 = task1DataFrameExtrapoints[(task1DataFrameExtrapoints.season == 2019 ) & (task1DataFrameExtrapoints.possessionTeam == 'LA') \n",
    "                                           & (task1DataFrameExtrapoints.penaltyCodes == 0) \n",
    "                                           & (task1DataFrameExtrapoints.event != 'None')]\n",
    "extraPointsLA2020 = task1DataFrameExtrapoints[(task1DataFrameExtrapoints.season == 2020 ) & (task1DataFrameExtrapoints.possessionTeam == 'LA') \n",
    "                                           & (task1DataFrameExtrapoints.penaltyCodes == 0) \n",
    "                                           & (task1DataFrameExtrapoints.event != 'None')]\n",
    "\n",
    "# Field Goals\n",
    "fieldGoalsLA2018 = task1DataFrameFieldgoals[(task1DataFrameFieldgoals.season == 2018 ) & (task1DataFrameFieldgoals.possessionTeam == 'LA')  \n",
    "                                         & (task1DataFrameFieldgoals.penaltyCodes == 0) \n",
    "                                         & (task1DataFrameFieldgoals.event != 'None')]\n",
    "fieldGoalsLA2019 = task1DataFrameFieldgoals[(task1DataFrameFieldgoals.season == 2019 ) & (task1DataFrameFieldgoals.possessionTeam == 'LA')  \n",
    "                                         & (task1DataFrameFieldgoals.penaltyCodes == 0) \n",
    "                                         & (task1DataFrameFieldgoals.event != 'None')]\n",
    "fieldGoalsLA2020 = task1DataFrameFieldgoals[(task1DataFrameFieldgoals.season == 2020 ) & (task1DataFrameFieldgoals.possessionTeam == 'LA')  \n",
    "                                         & (task1DataFrameFieldgoals.penaltyCodes == 0) \n",
    "                                         & (task1DataFrameFieldgoals.event != 'None')]\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "c98ed348-8589-4ecc-bf65-85dc72ab5ca9",
   "metadata": {},
   "outputs": [],
   "source": [
    "extraPointsLA2018.to_csv(r'/Users/kushtrivedi/Desktop/NFL/LosAngeles/LA_ExtraPoint_2018.csv', index=False)\n",
    "extraPointsLA2019.to_csv(r'/Users/kushtrivedi/Desktop/NFL/LosAngeles/LA_ExtraPoint_2019.csv', index=False)\n",
    "extraPointsLA2020.to_csv(r'/Users/kushtrivedi/Desktop/NFL/LosAngeles/LA_ExtraPoint_2020.csv', index=False)\n",
    "\n",
    "fieldGoalsLA2018.to_csv(r'/Users/kushtrivedi/Desktop/NFL/LosAngeles/LA_FiledGoals_2018.csv', index=False)\n",
    "fieldGoalsLA2019.to_csv(r'/Users/kushtrivedi/Desktop/NFL/LosAngeles/LA_FiledGoals_2019.csv', index=False)\n",
    "fieldGoalsLA2020.to_csv(r'/Users/kushtrivedi/Desktop/NFL/LosAngeles/LA_FiledGoals_2020.csv', index=False)\n",
    "\n",
    "kickoffsLA2018.to_csv(r'/Users/kushtrivedi/Desktop/NFL/LosAngeles/LA_Kickoffs_2018.csv', index=False)\n",
    "kickoffsLA2019.to_csv(r'/Users/kushtrivedi/Desktop/NFL/LosAngeles/LA_Kickoffs_2019.csv', index=False)\n",
    "kickoffsLA2020.to_csv(r'/Users/kushtrivedi/Desktop/NFL/LosAngeles/LA_Kickoffs_2020.csv', index=False)\n",
    "\n",
    "puntsLA2018.to_csv(r'/Users/kushtrivedi/Desktop/NFL/LosAngeles/LA_Punts_2018.csv', index=False)\n",
    "puntsLA2019.to_csv(r'/Users/kushtrivedi/Desktop/NFL/LosAngeles/LA_Punts_2019.csv', index=False)\n",
    "puntsLA2020.to_csv(r'/Users/kushtrivedi/Desktop/NFL/LosAngeles/LA_Punts_2020.csv', index=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "8ad05960-4cf6-476a-b29c-7e5567b9bc3a",
   "metadata": {},
   "outputs": [],
   "source": [
    "# LAC Special Plays Data Preparation\n",
    "\n",
    "# Punts\n",
    "puntsLAC2018 = task1DataFramePunts[(task1DataFramePunts.season == 2018 ) & (task1DataFramePunts.possessionTeam == 'LAC') \n",
    "                                   & (task1DataFramePunts.penaltyCodes == 0) \n",
    "                                   & (task1DataFramePunts.event != 'None')]\n",
    "puntsLAC2019 = task1DataFramePunts[(task1DataFramePunts.season == 2019 ) & (task1DataFramePunts.possessionTeam == 'LAC') \n",
    "                                   & (task1DataFramePunts.penaltyCodes == 0) \n",
    "                                   & (task1DataFramePunts.event != 'None')]\n",
    "puntsLAC2020 = task1DataFramePunts[(task1DataFramePunts.season == 2020 ) & (task1DataFramePunts.possessionTeam == 'LAC') \n",
    "                                   & (task1DataFramePunts.penaltyCodes == 0) \n",
    "                                   & (task1DataFramePunts.event != 'None')]\n",
    "\n",
    "# Kickoffs\n",
    "kickoffsLAC2018 = task1DataFrameKickoffs[(task1DataFrameKickoffs.season == 2018 ) & (task1DataFrameKickoffs.possessionTeam == 'LAC')\n",
    "                                         & (task1DataFrameKickoffs.penaltyCodes == 0) \n",
    "                                         & (task1DataFrameKickoffs.event != 'None')]\n",
    "kickoffsLAC2019 = task1DataFrameKickoffs[(task1DataFrameKickoffs.season == 2019 ) & (task1DataFrameKickoffs.possessionTeam == 'LAC')\n",
    "                                         & (task1DataFrameKickoffs.penaltyCodes == 0) \n",
    "                                         & (task1DataFrameKickoffs.event != 'None')]\n",
    "kickoffsLAC2020 = task1DataFrameKickoffs[(task1DataFrameKickoffs.season == 2020 ) & (task1DataFrameKickoffs.possessionTeam == 'LAC')\n",
    "                                         & (task1DataFrameKickoffs.penaltyCodes == 0) \n",
    "                                         & (task1DataFrameKickoffs.event != 'None')]\n",
    "\n",
    "# Extra Points\n",
    "extraPointsLAC2018 = task1DataFrameExtrapoints[(task1DataFrameExtrapoints.season == 2018 ) & (task1DataFrameExtrapoints.possessionTeam == 'LAC') \n",
    "                                           & (task1DataFrameExtrapoints.penaltyCodes == 0) \n",
    "                                           & (task1DataFrameExtrapoints.event != 'None')]\n",
    "extraPointsLAC2019 = task1DataFrameExtrapoints[(task1DataFrameExtrapoints.season == 2019 ) & (task1DataFrameExtrapoints.possessionTeam == 'LAC') \n",
    "                                           & (task1DataFrameExtrapoints.penaltyCodes == 0) \n",
    "                                           & (task1DataFrameExtrapoints.event != 'None')]\n",
    "extraPointsLAC2020 = task1DataFrameExtrapoints[(task1DataFrameExtrapoints.season == 2020 ) & (task1DataFrameExtrapoints.possessionTeam == 'LAC') \n",
    "                                           & (task1DataFrameExtrapoints.penaltyCodes == 0) \n",
    "                                           & (task1DataFrameExtrapoints.event != 'None')]\n",
    "\n",
    "# Field Goals\n",
    "fieldGoalsLAC2018 = task1DataFrameFieldgoals[(task1DataFrameFieldgoals.season == 2018 ) & (task1DataFrameFieldgoals.possessionTeam == 'LAC')  \n",
    "                                         & (task1DataFrameFieldgoals.penaltyCodes == 0) \n",
    "                                         & (task1DataFrameFieldgoals.event != 'None')]\n",
    "fieldGoalsLAC2019 = task1DataFrameFieldgoals[(task1DataFrameFieldgoals.season == 2019 ) & (task1DataFrameFieldgoals.possessionTeam == 'LAC')  \n",
    "                                         & (task1DataFrameFieldgoals.penaltyCodes == 0) \n",
    "                                         & (task1DataFrameFieldgoals.event != 'None')]\n",
    "fieldGoalsLAC2020 = task1DataFrameFieldgoals[(task1DataFrameFieldgoals.season == 2020 ) & (task1DataFrameFieldgoals.possessionTeam == 'LAC')  \n",
    "                                         & (task1DataFrameFieldgoals.penaltyCodes == 0) \n",
    "                                         & (task1DataFrameFieldgoals.event != 'None')]\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "085b366c-3461-42c9-8e9c-f5ee13373200",
   "metadata": {},
   "outputs": [],
   "source": [
    "# MIA Special Plays Data Preparation\n",
    "\n",
    "# Punts\n",
    "puntsMIA2018 = task1DataFramePunts[(task1DataFramePunts.season == 2018 ) & (task1DataFramePunts.possessionTeam == 'MIA') \n",
    "                                   & (task1DataFramePunts.penaltyCodes == 0) \n",
    "                                   & (task1DataFramePunts.event != 'None')]\n",
    "puntsMIA2019 = task1DataFramePunts[(task1DataFramePunts.season == 2019 ) & (task1DataFramePunts.possessionTeam == 'MIA') \n",
    "                                   & (task1DataFramePunts.penaltyCodes == 0) \n",
    "                                   & (task1DataFramePunts.event != 'None')]\n",
    "puntsMIA2020 = task1DataFramePunts[(task1DataFramePunts.season == 2020 ) & (task1DataFramePunts.possessionTeam == 'MIA') \n",
    "                                   & (task1DataFramePunts.penaltyCodes == 0) \n",
    "                                   & (task1DataFramePunts.event != 'None')]\n",
    "\n",
    "# Kickoffs\n",
    "kickoffsMIA2018 = task1DataFrameKickoffs[(task1DataFrameKickoffs.season == 2018 ) & (task1DataFrameKickoffs.possessionTeam == 'MIA')\n",
    "                                         & (task1DataFrameKickoffs.penaltyCodes == 0) \n",
    "                                         & (task1DataFrameKickoffs.event != 'None')]\n",
    "kickoffsMIA2019 = task1DataFrameKickoffs[(task1DataFrameKickoffs.season == 2019 ) & (task1DataFrameKickoffs.possessionTeam == 'MIA')\n",
    "                                         & (task1DataFrameKickoffs.penaltyCodes == 0) \n",
    "                                         & (task1DataFrameKickoffs.event != 'None')]\n",
    "kickoffsMIA2020 = task1DataFrameKickoffs[(task1DataFrameKickoffs.season == 2020 ) & (task1DataFrameKickoffs.possessionTeam == 'MIA')\n",
    "                                         & (task1DataFrameKickoffs.penaltyCodes == 0) \n",
    "                                         & (task1DataFrameKickoffs.event != 'None')]\n",
    "\n",
    "# Extra Points\n",
    "extraPointsMIA2018 = task1DataFrameExtrapoints[(task1DataFrameExtrapoints.season == 2018 ) & (task1DataFrameExtrapoints.possessionTeam == 'MIA') \n",
    "                                           & (task1DataFrameExtrapoints.penaltyCodes == 0) \n",
    "                                           & (task1DataFrameExtrapoints.event != 'None')]\n",
    "extraPointsMIA2019 = task1DataFrameExtrapoints[(task1DataFrameExtrapoints.season == 2019 ) & (task1DataFrameExtrapoints.possessionTeam == 'MIA') \n",
    "                                           & (task1DataFrameExtrapoints.penaltyCodes == 0) \n",
    "                                           & (task1DataFrameExtrapoints.event != 'None')]\n",
    "extraPointsMIA2020 = task1DataFrameExtrapoints[(task1DataFrameExtrapoints.season == 2020 ) & (task1DataFrameExtrapoints.possessionTeam == 'MIA') \n",
    "                                           & (task1DataFrameExtrapoints.penaltyCodes == 0) \n",
    "                                           & (task1DataFrameExtrapoints.event != 'None')]\n",
    "\n",
    "# Field Goals\n",
    "fieldGoalsMIA2018 = task1DataFrameFieldgoals[(task1DataFrameFieldgoals.season == 2018 ) & (task1DataFrameFieldgoals.possessionTeam == 'MIA')  \n",
    "                                         & (task1DataFrameFieldgoals.penaltyCodes == 0) \n",
    "                                         & (task1DataFrameFieldgoals.event != 'None')]\n",
    "fieldGoalsMIA2019 = task1DataFrameFieldgoals[(task1DataFrameFieldgoals.season == 2019 ) & (task1DataFrameFieldgoals.possessionTeam == 'MIA')  \n",
    "                                         & (task1DataFrameFieldgoals.penaltyCodes == 0) \n",
    "                                         & (task1DataFrameFieldgoals.event != 'None')]\n",
    "fieldGoalsMIA2020 = task1DataFrameFieldgoals[(task1DataFrameFieldgoals.season == 2020 ) & (task1DataFrameFieldgoals.possessionTeam == 'MIA')  \n",
    "                                         & (task1DataFrameFieldgoals.penaltyCodes == 0) \n",
    "                                         & (task1DataFrameFieldgoals.event != 'None')]\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "61afdfad-19cb-4c42-ae37-a8668128f9f7",
   "metadata": {},
   "outputs": [],
   "source": [
    "# MIN Special Plays Data Preparation\n",
    "\n",
    "# Punts\n",
    "puntsMIN2018 = task1DataFramePunts[(task1DataFramePunts.season == 2018 ) & (task1DataFramePunts.possessionTeam == 'MIN') \n",
    "                                   & (task1DataFramePunts.penaltyCodes == 0) \n",
    "                                   & (task1DataFramePunts.event != 'None')]\n",
    "puntsMIN2019 = task1DataFramePunts[(task1DataFramePunts.season == 2019 ) & (task1DataFramePunts.possessionTeam == 'MIN') \n",
    "                                   & (task1DataFramePunts.penaltyCodes == 0) \n",
    "                                   & (task1DataFramePunts.event != 'None')]\n",
    "puntsMIN2020 = task1DataFramePunts[(task1DataFramePunts.season == 2020 ) & (task1DataFramePunts.possessionTeam == 'MIN') \n",
    "                                   & (task1DataFramePunts.penaltyCodes == 0) \n",
    "                                   & (task1DataFramePunts.event != 'None')]\n",
    "\n",
    "# Kickoffs\n",
    "kickoffsMIN2018 = task1DataFrameKickoffs[(task1DataFrameKickoffs.season == 2018 ) & (task1DataFrameKickoffs.possessionTeam == 'MIN')\n",
    "                                         & (task1DataFrameKickoffs.penaltyCodes == 0) \n",
    "                                         & (task1DataFrameKickoffs.event != 'None')]\n",
    "kickoffsMIN2019 = task1DataFrameKickoffs[(task1DataFrameKickoffs.season == 2019 ) & (task1DataFrameKickoffs.possessionTeam == 'MIN')\n",
    "                                         & (task1DataFrameKickoffs.penaltyCodes == 0) \n",
    "                                         & (task1DataFrameKickoffs.event != 'None')]\n",
    "kickoffsMIN2020 = task1DataFrameKickoffs[(task1DataFrameKickoffs.season == 2020 ) & (task1DataFrameKickoffs.possessionTeam == 'MIN')\n",
    "                                         & (task1DataFrameKickoffs.penaltyCodes == 0) \n",
    "                                         & (task1DataFrameKickoffs.event != 'None')]\n",
    "\n",
    "# Extra Points\n",
    "extraPointsMIN2018 = task1DataFrameExtrapoints[(task1DataFrameExtrapoints.season == 2018 ) & (task1DataFrameExtrapoints.possessionTeam == 'MIN') \n",
    "                                           & (task1DataFrameExtrapoints.penaltyCodes == 0) \n",
    "                                           & (task1DataFrameExtrapoints.event != 'None')]\n",
    "extraPointsMIN2019 = task1DataFrameExtrapoints[(task1DataFrameExtrapoints.season == 2019 ) & (task1DataFrameExtrapoints.possessionTeam == 'MIN') \n",
    "                                           & (task1DataFrameExtrapoints.penaltyCodes == 0) \n",
    "                                           & (task1DataFrameExtrapoints.event != 'None')]\n",
    "extraPointsMIN2020 = task1DataFrameExtrapoints[(task1DataFrameExtrapoints.season == 2020 ) & (task1DataFrameExtrapoints.possessionTeam == 'MIN') \n",
    "                                           & (task1DataFrameExtrapoints.penaltyCodes == 0) \n",
    "                                           & (task1DataFrameExtrapoints.event != 'None')]\n",
    "\n",
    "# Field Goals\n",
    "fieldGoalsMIN2018 = task1DataFrameFieldgoals[(task1DataFrameFieldgoals.season == 2018 ) & (task1DataFrameFieldgoals.possessionTeam == 'MIN')  \n",
    "                                         & (task1DataFrameFieldgoals.penaltyCodes == 0) \n",
    "                                         & (task1DataFrameFieldgoals.event != 'None')]\n",
    "fieldGoalsMIN2019 = task1DataFrameFieldgoals[(task1DataFrameFieldgoals.season == 2019 ) & (task1DataFrameFieldgoals.possessionTeam == 'MIN')  \n",
    "                                         & (task1DataFrameFieldgoals.penaltyCodes == 0) \n",
    "                                         & (task1DataFrameFieldgoals.event != 'None')]\n",
    "fieldGoalsMIN2020 = task1DataFrameFieldgoals[(task1DataFrameFieldgoals.season == 2020 ) & (task1DataFrameFieldgoals.possessionTeam == 'MIN')  \n",
    "                                         & (task1DataFrameFieldgoals.penaltyCodes == 0) \n",
    "                                         & (task1DataFrameFieldgoals.event != 'None')]\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "9730dccb-1fac-4afc-a6eb-2c673bc14cf3",
   "metadata": {},
   "outputs": [],
   "source": [
    "# NE Special Plays Data Preparation\n",
    "\n",
    "# Punts\n",
    "puntsNE2018 = task1DataFramePunts[(task1DataFramePunts.season == 2018 ) & (task1DataFramePunts.possessionTeam == 'NE') \n",
    "                                   & (task1DataFramePunts.penaltyCodes == 0) \n",
    "                                   & (task1DataFramePunts.event != 'None')]\n",
    "puntsNE2019 = task1DataFramePunts[(task1DataFramePunts.season == 2019 ) & (task1DataFramePunts.possessionTeam == 'NE') \n",
    "                                   & (task1DataFramePunts.penaltyCodes == 0) \n",
    "                                   & (task1DataFramePunts.event != 'None')]\n",
    "puntsNE2020 = task1DataFramePunts[(task1DataFramePunts.season == 2020 ) & (task1DataFramePunts.possessionTeam == 'NE') \n",
    "                                   & (task1DataFramePunts.penaltyCodes == 0) \n",
    "                                   & (task1DataFramePunts.event != 'None')]\n",
    "\n",
    "# Kickoffs\n",
    "kickoffsNE2018 = task1DataFrameKickoffs[(task1DataFrameKickoffs.season == 2018 ) & (task1DataFrameKickoffs.possessionTeam == 'NE')\n",
    "                                         & (task1DataFrameKickoffs.penaltyCodes == 0) \n",
    "                                         & (task1DataFrameKickoffs.event != 'None')]\n",
    "kickoffsNE2019 = task1DataFrameKickoffs[(task1DataFrameKickoffs.season == 2019 ) & (task1DataFrameKickoffs.possessionTeam == 'NE')\n",
    "                                         & (task1DataFrameKickoffs.penaltyCodes == 0) \n",
    "                                         & (task1DataFrameKickoffs.event != 'None')]\n",
    "kickoffsNE2020 = task1DataFrameKickoffs[(task1DataFrameKickoffs.season == 2020 ) & (task1DataFrameKickoffs.possessionTeam == 'NE')\n",
    "                                         & (task1DataFrameKickoffs.penaltyCodes == 0) \n",
    "                                         & (task1DataFrameKickoffs.event != 'None')]\n",
    "\n",
    "# Extra Points\n",
    "extraPointsNE2018 = task1DataFrameExtrapoints[(task1DataFrameExtrapoints.season == 2018 ) & (task1DataFrameExtrapoints.possessionTeam == 'NE') \n",
    "                                           & (task1DataFrameExtrapoints.penaltyCodes == 0) \n",
    "                                           & (task1DataFrameExtrapoints.event != 'None')]\n",
    "extraPointsNE2019 = task1DataFrameExtrapoints[(task1DataFrameExtrapoints.season == 2019 ) & (task1DataFrameExtrapoints.possessionTeam == 'NE') \n",
    "                                           & (task1DataFrameExtrapoints.penaltyCodes == 0) \n",
    "                                           & (task1DataFrameExtrapoints.event != 'None')]\n",
    "extraPointsNE2020 = task1DataFrameExtrapoints[(task1DataFrameExtrapoints.season == 2020 ) & (task1DataFrameExtrapoints.possessionTeam == 'NE') \n",
    "                                           & (task1DataFrameExtrapoints.penaltyCodes == 0) \n",
    "                                           & (task1DataFrameExtrapoints.event != 'None')]\n",
    "\n",
    "# Field Goals\n",
    "fieldGoalsNE2018 = task1DataFrameFieldgoals[(task1DataFrameFieldgoals.season == 2018 ) & (task1DataFrameFieldgoals.possessionTeam == 'NE')  \n",
    "                                         & (task1DataFrameFieldgoals.penaltyCodes == 0) \n",
    "                                         & (task1DataFrameFieldgoals.event != 'None')]\n",
    "fieldGoalsNE2019 = task1DataFrameFieldgoals[(task1DataFrameFieldgoals.season == 2019 ) & (task1DataFrameFieldgoals.possessionTeam == 'NE')  \n",
    "                                         & (task1DataFrameFieldgoals.penaltyCodes == 0) \n",
    "                                         & (task1DataFrameFieldgoals.event != 'None')]\n",
    "fieldGoalsNE2020 = task1DataFrameFieldgoals[(task1DataFrameFieldgoals.season == 2020 ) & (task1DataFrameFieldgoals.possessionTeam == 'NE')  \n",
    "                                         & (task1DataFrameFieldgoals.penaltyCodes == 0) \n",
    "                                         & (task1DataFrameFieldgoals.event != 'None')]\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "6c98379b-c2eb-4e3a-a4c5-e7cd14340b3b",
   "metadata": {},
   "outputs": [],
   "source": [
    "# NO Special Plays Data Preparation\n",
    "\n",
    "# Punts\n",
    "puntsNO2018 = task1DataFramePunts[(task1DataFramePunts.season == 2018 ) & (task1DataFramePunts.possessionTeam == 'NO') \n",
    "                                   & (task1DataFramePunts.penaltyCodes == 0) \n",
    "                                   & (task1DataFramePunts.event != 'None')]\n",
    "puntsNO2019 = task1DataFramePunts[(task1DataFramePunts.season == 2019 ) & (task1DataFramePunts.possessionTeam == 'NO') \n",
    "                                   & (task1DataFramePunts.penaltyCodes == 0) \n",
    "                                   & (task1DataFramePunts.event != 'None')]\n",
    "puntsNO2020 = task1DataFramePunts[(task1DataFramePunts.season == 2020 ) & (task1DataFramePunts.possessionTeam == 'NO') \n",
    "                                   & (task1DataFramePunts.penaltyCodes == 0) \n",
    "                                   & (task1DataFramePunts.event != 'None')]\n",
    "\n",
    "# Kickoffs\n",
    "kickoffsNO2018 = task1DataFrameKickoffs[(task1DataFrameKickoffs.season == 2018 ) & (task1DataFrameKickoffs.possessionTeam == 'NO')\n",
    "                                         & (task1DataFrameKickoffs.penaltyCodes == 0) \n",
    "                                         & (task1DataFrameKickoffs.event != 'None')]\n",
    "kickoffsNO2019 = task1DataFrameKickoffs[(task1DataFrameKickoffs.season == 2019 ) & (task1DataFrameKickoffs.possessionTeam == 'NO')\n",
    "                                         & (task1DataFrameKickoffs.penaltyCodes == 0) \n",
    "                                         & (task1DataFrameKickoffs.event != 'None')]\n",
    "kickoffsNO2020 = task1DataFrameKickoffs[(task1DataFrameKickoffs.season == 2020 ) & (task1DataFrameKickoffs.possessionTeam == 'NO')\n",
    "                                         & (task1DataFrameKickoffs.penaltyCodes == 0) \n",
    "                                         & (task1DataFrameKickoffs.event != 'None')]\n",
    "\n",
    "# Extra Points\n",
    "extraPointsNO2018 = task1DataFrameExtrapoints[(task1DataFrameExtrapoints.season == 2018 ) & (task1DataFrameExtrapoints.possessionTeam == 'NO') \n",
    "                                           & (task1DataFrameExtrapoints.penaltyCodes == 0) \n",
    "                                           & (task1DataFrameExtrapoints.event != 'None')]\n",
    "extraPointsNO2019 = task1DataFrameExtrapoints[(task1DataFrameExtrapoints.season == 2019 ) & (task1DataFrameExtrapoints.possessionTeam == 'NO') \n",
    "                                           & (task1DataFrameExtrapoints.penaltyCodes == 0) \n",
    "                                           & (task1DataFrameExtrapoints.event != 'None')]\n",
    "extraPointsNO2020 = task1DataFrameExtrapoints[(task1DataFrameExtrapoints.season == 2020 ) & (task1DataFrameExtrapoints.possessionTeam == 'NO') \n",
    "                                           & (task1DataFrameExtrapoints.penaltyCodes == 0) \n",
    "                                           & (task1DataFrameExtrapoints.event != 'None')]\n",
    "\n",
    "# Field Goals\n",
    "fieldGoalsNO2018 = task1DataFrameFieldgoals[(task1DataFrameFieldgoals.season == 2018 ) & (task1DataFrameFieldgoals.possessionTeam == 'NO')  \n",
    "                                         & (task1DataFrameFieldgoals.penaltyCodes == 0) \n",
    "                                         & (task1DataFrameFieldgoals.event != 'None')]\n",
    "fieldGoalsNO2019 = task1DataFrameFieldgoals[(task1DataFrameFieldgoals.season == 2019 ) & (task1DataFrameFieldgoals.possessionTeam == 'NO')  \n",
    "                                         & (task1DataFrameFieldgoals.penaltyCodes == 0) \n",
    "                                         & (task1DataFrameFieldgoals.event != 'None')]\n",
    "fieldGoalsNO2020 = task1DataFrameFieldgoals[(task1DataFrameFieldgoals.season == 2020 ) & (task1DataFrameFieldgoals.possessionTeam == 'NO')  \n",
    "                                         & (task1DataFrameFieldgoals.penaltyCodes == 0) \n",
    "                                         & (task1DataFrameFieldgoals.event != 'None')]\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "d2bc3495-c329-4551-97af-34a3388a9bc5",
   "metadata": {},
   "outputs": [],
   "source": [
    "# NYG Special Plays Data Preparation\n",
    "\n",
    "# Punts\n",
    "puntsNYG2018 = task1DataFramePunts[(task1DataFramePunts.season == 2018 ) & (task1DataFramePunts.possessionTeam == 'NYG') \n",
    "                                   & (task1DataFramePunts.penaltyCodes == 0) \n",
    "                                   & (task1DataFramePunts.event != 'None')]\n",
    "puntsNYG2019 = task1DataFramePunts[(task1DataFramePunts.season == 2019 ) & (task1DataFramePunts.possessionTeam == 'NYG') \n",
    "                                   & (task1DataFramePunts.penaltyCodes == 0) \n",
    "                                   & (task1DataFramePunts.event != 'None')]\n",
    "puntsNYG2020 = task1DataFramePunts[(task1DataFramePunts.season == 2020 ) & (task1DataFramePunts.possessionTeam == 'NYG') \n",
    "                                   & (task1DataFramePunts.penaltyCodes == 0) \n",
    "                                   & (task1DataFramePunts.event != 'None')]\n",
    "\n",
    "# Kickoffs\n",
    "kickoffsNYG2018 = task1DataFrameKickoffs[(task1DataFrameKickoffs.season == 2018 ) & (task1DataFrameKickoffs.possessionTeam == 'NYG')\n",
    "                                         & (task1DataFrameKickoffs.penaltyCodes == 0) \n",
    "                                         & (task1DataFrameKickoffs.event != 'None')]\n",
    "kickoffsNYG2019 = task1DataFrameKickoffs[(task1DataFrameKickoffs.season == 2019 ) & (task1DataFrameKickoffs.possessionTeam == 'NYG')\n",
    "                                         & (task1DataFrameKickoffs.penaltyCodes == 0) \n",
    "                                         & (task1DataFrameKickoffs.event != 'None')]\n",
    "kickoffsNYG2020 = task1DataFrameKickoffs[(task1DataFrameKickoffs.season == 2020 ) & (task1DataFrameKickoffs.possessionTeam == 'NYG')\n",
    "                                         & (task1DataFrameKickoffs.penaltyCodes == 0) \n",
    "                                         & (task1DataFrameKickoffs.event != 'None')]\n",
    "\n",
    "# Extra Points\n",
    "extraPointsNYG2018 = task1DataFrameExtrapoints[(task1DataFrameExtrapoints.season == 2018 ) & (task1DataFrameExtrapoints.possessionTeam == 'NYG') \n",
    "                                           & (task1DataFrameExtrapoints.penaltyCodes == 0) \n",
    "                                           & (task1DataFrameExtrapoints.event != 'None')]\n",
    "extraPointsNYG2019 = task1DataFrameExtrapoints[(task1DataFrameExtrapoints.season == 2019 ) & (task1DataFrameExtrapoints.possessionTeam == 'NYG') \n",
    "                                           & (task1DataFrameExtrapoints.penaltyCodes == 0) \n",
    "                                           & (task1DataFrameExtrapoints.event != 'None')]\n",
    "extraPointsNYG2020 = task1DataFrameExtrapoints[(task1DataFrameExtrapoints.season == 2020 ) & (task1DataFrameExtrapoints.possessionTeam == 'NYG') \n",
    "                                           & (task1DataFrameExtrapoints.penaltyCodes == 0) \n",
    "                                           & (task1DataFrameExtrapoints.event != 'None')]\n",
    "\n",
    "# Field Goals\n",
    "fieldGoalsNYG2018 = task1DataFrameFieldgoals[(task1DataFrameFieldgoals.season == 2018 ) & (task1DataFrameFieldgoals.possessionTeam == 'NYG')  \n",
    "                                         & (task1DataFrameFieldgoals.penaltyCodes == 0) \n",
    "                                         & (task1DataFrameFieldgoals.event != 'None')]\n",
    "fieldGoalsNYG2019 = task1DataFrameFieldgoals[(task1DataFrameFieldgoals.season == 2019 ) & (task1DataFrameFieldgoals.possessionTeam == 'NYG')  \n",
    "                                         & (task1DataFrameFieldgoals.penaltyCodes == 0) \n",
    "                                         & (task1DataFrameFieldgoals.event != 'None')]\n",
    "fieldGoalsNYG2020 = task1DataFrameFieldgoals[(task1DataFrameFieldgoals.season == 2020 ) & (task1DataFrameFieldgoals.possessionTeam == 'NYG')  \n",
    "                                         & (task1DataFrameFieldgoals.penaltyCodes == 0) \n",
    "                                         & (task1DataFrameFieldgoals.event != 'None')]\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "9bcd5b33-30aa-421d-be55-233f5d23cf96",
   "metadata": {},
   "outputs": [],
   "source": [
    "# NYJ Special Plays Data Preparation\n",
    "\n",
    "# Punts\n",
    "puntsNYJ2018 = task1DataFramePunts[(task1DataFramePunts.season == 2018 ) & (task1DataFramePunts.possessionTeam == 'NYJ') \n",
    "                                   & (task1DataFramePunts.penaltyCodes == 0) \n",
    "                                   & (task1DataFramePunts.event != 'None')]\n",
    "puntsNYJ2019 = task1DataFramePunts[(task1DataFramePunts.season == 2019 ) & (task1DataFramePunts.possessionTeam == 'NYJ') \n",
    "                                   & (task1DataFramePunts.penaltyCodes == 0) \n",
    "                                   & (task1DataFramePunts.event != 'None')]\n",
    "puntsNYJ2020 = task1DataFramePunts[(task1DataFramePunts.season == 2020 ) & (task1DataFramePunts.possessionTeam == 'NYJ') \n",
    "                                   & (task1DataFramePunts.penaltyCodes == 0) \n",
    "                                   & (task1DataFramePunts.event != 'None')]\n",
    "\n",
    "# Kickoffs\n",
    "kickoffsNYJ2018 = task1DataFrameKickoffs[(task1DataFrameKickoffs.season == 2018 ) & (task1DataFrameKickoffs.possessionTeam == 'NYJ')\n",
    "                                         & (task1DataFrameKickoffs.penaltyCodes == 0) \n",
    "                                         & (task1DataFrameKickoffs.event != 'None')]\n",
    "kickoffsNYJ2019 = task1DataFrameKickoffs[(task1DataFrameKickoffs.season == 2019 ) & (task1DataFrameKickoffs.possessionTeam == 'NYJ')\n",
    "                                         & (task1DataFrameKickoffs.penaltyCodes == 0) \n",
    "                                         & (task1DataFrameKickoffs.event != 'None')]\n",
    "kickoffsNYJ2020 = task1DataFrameKickoffs[(task1DataFrameKickoffs.season == 2020 ) & (task1DataFrameKickoffs.possessionTeam == 'NYJ')\n",
    "                                         & (task1DataFrameKickoffs.penaltyCodes == 0) \n",
    "                                         & (task1DataFrameKickoffs.event != 'None')]\n",
    "\n",
    "# Extra Points\n",
    "extraPointsNYJ2018 = task1DataFrameExtrapoints[(task1DataFrameExtrapoints.season == 2018 ) & (task1DataFrameExtrapoints.possessionTeam == 'NYJ') \n",
    "                                           & (task1DataFrameExtrapoints.penaltyCodes == 0) \n",
    "                                           & (task1DataFrameExtrapoints.event != 'None')]\n",
    "extraPointsNYJ2019 = task1DataFrameExtrapoints[(task1DataFrameExtrapoints.season == 2019 ) & (task1DataFrameExtrapoints.possessionTeam == 'NYJ') \n",
    "                                           & (task1DataFrameExtrapoints.penaltyCodes == 0) \n",
    "                                           & (task1DataFrameExtrapoints.event != 'None')]\n",
    "extraPointsNYJ2020 = task1DataFrameExtrapoints[(task1DataFrameExtrapoints.season == 2020 ) & (task1DataFrameExtrapoints.possessionTeam == 'NYJ') \n",
    "                                           & (task1DataFrameExtrapoints.penaltyCodes == 0) \n",
    "                                           & (task1DataFrameExtrapoints.event != 'None')]\n",
    "\n",
    "# Field Goals\n",
    "fieldGoalsNYJ2018 = task1DataFrameFieldgoals[(task1DataFrameFieldgoals.season == 2018 ) & (task1DataFrameFieldgoals.possessionTeam == 'NYJ')  \n",
    "                                         & (task1DataFrameFieldgoals.penaltyCodes == 0) \n",
    "                                         & (task1DataFrameFieldgoals.event != 'None')]\n",
    "fieldGoalsNYJ2019 = task1DataFrameFieldgoals[(task1DataFrameFieldgoals.season == 2019 ) & (task1DataFrameFieldgoals.possessionTeam == 'NYJ')  \n",
    "                                         & (task1DataFrameFieldgoals.penaltyCodes == 0) \n",
    "                                         & (task1DataFrameFieldgoals.event != 'None')]\n",
    "fieldGoalsNYJ2020 = task1DataFrameFieldgoals[(task1DataFrameFieldgoals.season == 2020 ) & (task1DataFrameFieldgoals.possessionTeam == 'NYJ')  \n",
    "                                         & (task1DataFrameFieldgoals.penaltyCodes == 0) \n",
    "                                         & (task1DataFrameFieldgoals.event != 'None')]\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "af8a67bf-fec9-440b-a1ca-ae3955322df2",
   "metadata": {},
   "outputs": [],
   "source": [
    "# OAK Special Plays Data Preparation\n",
    "\n",
    "# Punts\n",
    "puntsOAK2018 = task1DataFramePunts[(task1DataFramePunts.season == 2018 ) & (task1DataFramePunts.possessionTeam == 'OAK') \n",
    "                                   & (task1DataFramePunts.penaltyCodes == 0) \n",
    "                                   & (task1DataFramePunts.event != 'None')]\n",
    "puntsOAK2019 = task1DataFramePunts[(task1DataFramePunts.season == 2019 ) & (task1DataFramePunts.possessionTeam == 'OAK') \n",
    "                                   & (task1DataFramePunts.penaltyCodes == 0) \n",
    "                                   & (task1DataFramePunts.event != 'None')]\n",
    "puntsOAK2020 = task1DataFramePunts[(task1DataFramePunts.season == 2020 ) & (task1DataFramePunts.possessionTeam == 'LV') \n",
    "                                   & (task1DataFramePunts.penaltyCodes == 0) \n",
    "                                   & (task1DataFramePunts.event != 'None')]\n",
    "\n",
    "# Kickoffs\n",
    "kickoffsOAK2018 = task1DataFrameKickoffs[(task1DataFrameKickoffs.season == 2018 ) & (task1DataFrameKickoffs.possessionTeam == 'OAK')\n",
    "                                         & (task1DataFrameKickoffs.penaltyCodes == 0) \n",
    "                                         & (task1DataFrameKickoffs.event != 'None')]\n",
    "kickoffsOAK2019 = task1DataFrameKickoffs[(task1DataFrameKickoffs.season == 2019 ) & (task1DataFrameKickoffs.possessionTeam == 'OAK')\n",
    "                                         & (task1DataFrameKickoffs.penaltyCodes == 0) \n",
    "                                         & (task1DataFrameKickoffs.event != 'None')]\n",
    "kickoffsOAK2020 = task1DataFrameKickoffs[(task1DataFrameKickoffs.season == 2020 ) & (task1DataFrameKickoffs.possessionTeam == 'LV')\n",
    "                                         & (task1DataFrameKickoffs.penaltyCodes == 0) \n",
    "                                         & (task1DataFrameKickoffs.event != 'None')]\n",
    "\n",
    "# Extra Points\n",
    "extraPointsOAK2018 = task1DataFrameExtrapoints[(task1DataFrameExtrapoints.season == 2018 ) & (task1DataFrameExtrapoints.possessionTeam == 'OAK') \n",
    "                                           & (task1DataFrameExtrapoints.penaltyCodes == 0) \n",
    "                                           & (task1DataFrameExtrapoints.event != 'None')]\n",
    "extraPointsOAK2019 = task1DataFrameExtrapoints[(task1DataFrameExtrapoints.season == 2019 ) & (task1DataFrameExtrapoints.possessionTeam == 'OAK') \n",
    "                                           & (task1DataFrameExtrapoints.penaltyCodes == 0) \n",
    "                                           & (task1DataFrameExtrapoints.event != 'None')]\n",
    "extraPointsOAK2020 = task1DataFrameExtrapoints[(task1DataFrameExtrapoints.season == 2020 ) & (task1DataFrameExtrapoints.possessionTeam == 'LV') \n",
    "                                           & (task1DataFrameExtrapoints.penaltyCodes == 0) \n",
    "                                           & (task1DataFrameExtrapoints.event != 'None')]\n",
    "\n",
    "# Field Goals\n",
    "fieldGoalsOAK2018 = task1DataFrameFieldgoals[(task1DataFrameFieldgoals.season == 2018 ) & (task1DataFrameFieldgoals.possessionTeam == 'OAK')  \n",
    "                                         & (task1DataFrameFieldgoals.penaltyCodes == 0) \n",
    "                                         & (task1DataFrameFieldgoals.event != 'None')]\n",
    "fieldGoalsOAK2019 = task1DataFrameFieldgoals[(task1DataFrameFieldgoals.season == 2019 ) & (task1DataFrameFieldgoals.possessionTeam == 'OAK')  \n",
    "                                         & (task1DataFrameFieldgoals.penaltyCodes == 0) \n",
    "                                         & (task1DataFrameFieldgoals.event != 'None')]\n",
    "fieldGoalsOAK2020 = task1DataFrameFieldgoals[(task1DataFrameFieldgoals.season == 2020 ) & (task1DataFrameFieldgoals.possessionTeam == 'LV')  \n",
    "                                         & (task1DataFrameFieldgoals.penaltyCodes == 0) \n",
    "                                         & (task1DataFrameFieldgoals.event != 'None')]\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "0bc6b763-1478-4ff5-9ddf-b6cdcd6d3252",
   "metadata": {},
   "outputs": [],
   "source": [
    "# PHI Special Plays Data Preparation\n",
    "\n",
    "# Punts\n",
    "puntsPHI2018 = task1DataFramePunts[(task1DataFramePunts.season == 2018 ) & (task1DataFramePunts.possessionTeam == 'PHI') \n",
    "                                   & (task1DataFramePunts.penaltyCodes == 0) \n",
    "                                   & (task1DataFramePunts.event != 'None')]\n",
    "puntsPHI2019 = task1DataFramePunts[(task1DataFramePunts.season == 2019 ) & (task1DataFramePunts.possessionTeam == 'PHI') \n",
    "                                   & (task1DataFramePunts.penaltyCodes == 0) \n",
    "                                   & (task1DataFramePunts.event != 'None')]\n",
    "puntsPHI2020 = task1DataFramePunts[(task1DataFramePunts.season == 2020 ) & (task1DataFramePunts.possessionTeam == 'PHI') \n",
    "                                   & (task1DataFramePunts.penaltyCodes == 0) \n",
    "                                   & (task1DataFramePunts.event != 'None')]\n",
    "\n",
    "# Kickoffs\n",
    "kickoffsPHI2018 = task1DataFrameKickoffs[(task1DataFrameKickoffs.season == 2018 ) & (task1DataFrameKickoffs.possessionTeam == 'PHI')\n",
    "                                         & (task1DataFrameKickoffs.penaltyCodes == 0) \n",
    "                                         & (task1DataFrameKickoffs.event != 'None')]\n",
    "kickoffsPHI2019 = task1DataFrameKickoffs[(task1DataFrameKickoffs.season == 2019 ) & (task1DataFrameKickoffs.possessionTeam == 'PHI')\n",
    "                                         & (task1DataFrameKickoffs.penaltyCodes == 0) \n",
    "                                         & (task1DataFrameKickoffs.event != 'None')]\n",
    "kickoffsPHI2020 = task1DataFrameKickoffs[(task1DataFrameKickoffs.season == 2020 ) & (task1DataFrameKickoffs.possessionTeam == 'PHI')\n",
    "                                         & (task1DataFrameKickoffs.penaltyCodes == 0) \n",
    "                                         & (task1DataFrameKickoffs.event != 'None')]\n",
    "\n",
    "# Extra Points\n",
    "extraPointsPHI2018 = task1DataFrameExtrapoints[(task1DataFrameExtrapoints.season == 2018 ) & (task1DataFrameExtrapoints.possessionTeam == 'PHI') \n",
    "                                           & (task1DataFrameExtrapoints.penaltyCodes == 0) \n",
    "                                           & (task1DataFrameExtrapoints.event != 'None')]\n",
    "extraPointsPHI2019 = task1DataFrameExtrapoints[(task1DataFrameExtrapoints.season == 2019 ) & (task1DataFrameExtrapoints.possessionTeam == 'PHI') \n",
    "                                           & (task1DataFrameExtrapoints.penaltyCodes == 0) \n",
    "                                           & (task1DataFrameExtrapoints.event != 'None')]\n",
    "extraPointsPHI2020 = task1DataFrameExtrapoints[(task1DataFrameExtrapoints.season == 2020 ) & (task1DataFrameExtrapoints.possessionTeam == 'PHI') \n",
    "                                           & (task1DataFrameExtrapoints.penaltyCodes == 0) \n",
    "                                           & (task1DataFrameExtrapoints.event != 'None')]\n",
    "\n",
    "# Field Goals\n",
    "fieldGoalsPHI2018 = task1DataFrameFieldgoals[(task1DataFrameFieldgoals.season == 2018 ) & (task1DataFrameFieldgoals.possessionTeam == 'PHI')  \n",
    "                                         & (task1DataFrameFieldgoals.penaltyCodes == 0) \n",
    "                                         & (task1DataFrameFieldgoals.event != 'None')]\n",
    "fieldGoalsPHI2019 = task1DataFrameFieldgoals[(task1DataFrameFieldgoals.season == 2019 ) & (task1DataFrameFieldgoals.possessionTeam == 'PHI')  \n",
    "                                         & (task1DataFrameFieldgoals.penaltyCodes == 0) \n",
    "                                         & (task1DataFrameFieldgoals.event != 'None')]\n",
    "fieldGoalsPHI2020 = task1DataFrameFieldgoals[(task1DataFrameFieldgoals.season == 2020 ) & (task1DataFrameFieldgoals.possessionTeam == 'PHI')  \n",
    "                                         & (task1DataFrameFieldgoals.penaltyCodes == 0) \n",
    "                                         & (task1DataFrameFieldgoals.event != 'None')]\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "89322d37-55ec-431a-9ab4-8af5fd1f136e",
   "metadata": {},
   "outputs": [],
   "source": [
    "# PIT Special Plays Data Preparation\n",
    "\n",
    "# Punts\n",
    "puntsPIT2018 = task1DataFramePunts[(task1DataFramePunts.season == 2018 ) & (task1DataFramePunts.possessionTeam == 'PIT') \n",
    "                                   & (task1DataFramePunts.penaltyCodes == 0) \n",
    "                                   & (task1DataFramePunts.event != 'None')]\n",
    "puntsPIT2019 = task1DataFramePunts[(task1DataFramePunts.season == 2019 ) & (task1DataFramePunts.possessionTeam == 'PIT') \n",
    "                                   & (task1DataFramePunts.penaltyCodes == 0) \n",
    "                                   & (task1DataFramePunts.event != 'None')]\n",
    "puntsPIT2020 = task1DataFramePunts[(task1DataFramePunts.season == 2020 ) & (task1DataFramePunts.possessionTeam == 'PIT') \n",
    "                                   & (task1DataFramePunts.penaltyCodes == 0) \n",
    "                                   & (task1DataFramePunts.event != 'None')]\n",
    "\n",
    "# Kickoffs\n",
    "kickoffsPIT2018 = task1DataFrameKickoffs[(task1DataFrameKickoffs.season == 2018 ) & (task1DataFrameKickoffs.possessionTeam == 'PIT')\n",
    "                                         & (task1DataFrameKickoffs.penaltyCodes == 0) \n",
    "                                         & (task1DataFrameKickoffs.event != 'None')]\n",
    "kickoffsPIT2019 = task1DataFrameKickoffs[(task1DataFrameKickoffs.season == 2019 ) & (task1DataFrameKickoffs.possessionTeam == 'PIT')\n",
    "                                         & (task1DataFrameKickoffs.penaltyCodes == 0) \n",
    "                                         & (task1DataFrameKickoffs.event != 'None')]\n",
    "kickoffsPIT2020 = task1DataFrameKickoffs[(task1DataFrameKickoffs.season == 2020 ) & (task1DataFrameKickoffs.possessionTeam == 'PIT')\n",
    "                                         & (task1DataFrameKickoffs.penaltyCodes == 0) \n",
    "                                         & (task1DataFrameKickoffs.event != 'None')]\n",
    "\n",
    "# Extra Points\n",
    "extraPointsPIT2018 = task1DataFrameExtrapoints[(task1DataFrameExtrapoints.season == 2018 ) & (task1DataFrameExtrapoints.possessionTeam == 'PIT') \n",
    "                                           & (task1DataFrameExtrapoints.penaltyCodes == 0) \n",
    "                                           & (task1DataFrameExtrapoints.event != 'None')]\n",
    "extraPointsPIT2019 = task1DataFrameExtrapoints[(task1DataFrameExtrapoints.season == 2019 ) & (task1DataFrameExtrapoints.possessionTeam == 'PIT') \n",
    "                                           & (task1DataFrameExtrapoints.penaltyCodes == 0) \n",
    "                                           & (task1DataFrameExtrapoints.event != 'None')]\n",
    "extraPointsPIT2020 = task1DataFrameExtrapoints[(task1DataFrameExtrapoints.season == 2020 ) & (task1DataFrameExtrapoints.possessionTeam == 'PIT') \n",
    "                                           & (task1DataFrameExtrapoints.penaltyCodes == 0) \n",
    "                                           & (task1DataFrameExtrapoints.event != 'None')]\n",
    "\n",
    "# Field Goals\n",
    "fieldGoalsPIT2018 = task1DataFrameFieldgoals[(task1DataFrameFieldgoals.season == 2018 ) & (task1DataFrameFieldgoals.possessionTeam == 'PIT')  \n",
    "                                         & (task1DataFrameFieldgoals.penaltyCodes == 0) \n",
    "                                         & (task1DataFrameFieldgoals.event != 'None')]\n",
    "fieldGoalsPIT2019 = task1DataFrameFieldgoals[(task1DataFrameFieldgoals.season == 2019 ) & (task1DataFrameFieldgoals.possessionTeam == 'PIT')  \n",
    "                                         & (task1DataFrameFieldgoals.penaltyCodes == 0) \n",
    "                                         & (task1DataFrameFieldgoals.event != 'None')]\n",
    "fieldGoalsPIT2020 = task1DataFrameFieldgoals[(task1DataFrameFieldgoals.season == 2020 ) & (task1DataFrameFieldgoals.possessionTeam == 'PIT')  \n",
    "                                         & (task1DataFrameFieldgoals.penaltyCodes == 0) \n",
    "                                         & (task1DataFrameFieldgoals.event != 'None')]\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "8d23f942-5404-4cdb-916b-b907db307d84",
   "metadata": {},
   "outputs": [],
   "source": [
    "# SEA Special Plays Data Preparation\n",
    "\n",
    "# Punts\n",
    "puntsSEA2018 = task1DataFramePunts[(task1DataFramePunts.season == 2018 ) & (task1DataFramePunts.possessionTeam == 'SEA') \n",
    "                                   & (task1DataFramePunts.penaltyCodes == 0) \n",
    "                                   & (task1DataFramePunts.event != 'None')]\n",
    "puntsSEA2019 = task1DataFramePunts[(task1DataFramePunts.season == 2019 ) & (task1DataFramePunts.possessionTeam == 'SEA') \n",
    "                                   & (task1DataFramePunts.penaltyCodes == 0) \n",
    "                                   & (task1DataFramePunts.event != 'None')]\n",
    "puntsSEA2020 = task1DataFramePunts[(task1DataFramePunts.season == 2020 ) & (task1DataFramePunts.possessionTeam == 'SEA') \n",
    "                                   & (task1DataFramePunts.penaltyCodes == 0) \n",
    "                                   & (task1DataFramePunts.event != 'None')]\n",
    "\n",
    "# Kickoffs\n",
    "kickoffsSEA2018 = task1DataFrameKickoffs[(task1DataFrameKickoffs.season == 2018 ) & (task1DataFrameKickoffs.possessionTeam == 'SEA')\n",
    "                                         & (task1DataFrameKickoffs.penaltyCodes == 0) \n",
    "                                         & (task1DataFrameKickoffs.event != 'None')]\n",
    "kickoffsSEA2019 = task1DataFrameKickoffs[(task1DataFrameKickoffs.season == 2019 ) & (task1DataFrameKickoffs.possessionTeam == 'SEA')\n",
    "                                         & (task1DataFrameKickoffs.penaltyCodes == 0) \n",
    "                                         & (task1DataFrameKickoffs.event != 'None')]\n",
    "kickoffsSEA2020 = task1DataFrameKickoffs[(task1DataFrameKickoffs.season == 2020 ) & (task1DataFrameKickoffs.possessionTeam == 'SEA')\n",
    "                                         & (task1DataFrameKickoffs.penaltyCodes == 0) \n",
    "                                         & (task1DataFrameKickoffs.event != 'None')]\n",
    "\n",
    "# Extra Points\n",
    "extraPointsSEA2018 = task1DataFrameExtrapoints[(task1DataFrameExtrapoints.season == 2018 ) & (task1DataFrameExtrapoints.possessionTeam == 'SEA') \n",
    "                                           & (task1DataFrameExtrapoints.penaltyCodes == 0) \n",
    "                                           & (task1DataFrameExtrapoints.event != 'None')]\n",
    "extraPointsSEA2019 = task1DataFrameExtrapoints[(task1DataFrameExtrapoints.season == 2019 ) & (task1DataFrameExtrapoints.possessionTeam == 'SEA') \n",
    "                                           & (task1DataFrameExtrapoints.penaltyCodes == 0) \n",
    "                                           & (task1DataFrameExtrapoints.event != 'None')]\n",
    "extraPointsSEA2020 = task1DataFrameExtrapoints[(task1DataFrameExtrapoints.season == 2020 ) & (task1DataFrameExtrapoints.possessionTeam == 'SEA') \n",
    "                                           & (task1DataFrameExtrapoints.penaltyCodes == 0) \n",
    "                                           & (task1DataFrameExtrapoints.event != 'None')]\n",
    "\n",
    "# Field Goals\n",
    "fieldGoalsSEA2018 = task1DataFrameFieldgoals[(task1DataFrameFieldgoals.season == 2018 ) & (task1DataFrameFieldgoals.possessionTeam == 'SEA')  \n",
    "                                         & (task1DataFrameFieldgoals.penaltyCodes == 0) \n",
    "                                         & (task1DataFrameFieldgoals.event != 'None')]\n",
    "fieldGoalsSEA2019 = task1DataFrameFieldgoals[(task1DataFrameFieldgoals.season == 2019 ) & (task1DataFrameFieldgoals.possessionTeam == 'SEA')  \n",
    "                                         & (task1DataFrameFieldgoals.penaltyCodes == 0) \n",
    "                                         & (task1DataFrameFieldgoals.event != 'None')]\n",
    "fieldGoalsSEA2020 = task1DataFrameFieldgoals[(task1DataFrameFieldgoals.season == 2020 ) & (task1DataFrameFieldgoals.possessionTeam == 'SEA')  \n",
    "                                         & (task1DataFrameFieldgoals.penaltyCodes == 0) \n",
    "                                         & (task1DataFrameFieldgoals.event != 'None')]\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "0c9161af-a054-4f10-9daf-66c1fbfc4354",
   "metadata": {},
   "outputs": [],
   "source": [
    "# SF Special Plays Data Preparation\n",
    "\n",
    "# Punts\n",
    "puntsSF2018 = task1DataFramePunts[(task1DataFramePunts.season == 2018 ) & (task1DataFramePunts.possessionTeam == 'SF') \n",
    "                                   & (task1DataFramePunts.penaltyCodes == 0) \n",
    "                                   & (task1DataFramePunts.event != 'None')]\n",
    "puntsSF2019 = task1DataFramePunts[(task1DataFramePunts.season == 2019 ) & (task1DataFramePunts.possessionTeam == 'SF') \n",
    "                                   & (task1DataFramePunts.penaltyCodes == 0) \n",
    "                                   & (task1DataFramePunts.event != 'None')]\n",
    "puntsSF2020 = task1DataFramePunts[(task1DataFramePunts.season == 2020 ) & (task1DataFramePunts.possessionTeam == 'SF') \n",
    "                                   & (task1DataFramePunts.penaltyCodes == 0) \n",
    "                                   & (task1DataFramePunts.event != 'None')]\n",
    "\n",
    "# Kickoffs\n",
    "kickoffsSF2018 = task1DataFrameKickoffs[(task1DataFrameKickoffs.season == 2018 ) & (task1DataFrameKickoffs.possessionTeam == 'SF')\n",
    "                                         & (task1DataFrameKickoffs.penaltyCodes == 0) \n",
    "                                         & (task1DataFrameKickoffs.event != 'None')]\n",
    "kickoffsSF2019 = task1DataFrameKickoffs[(task1DataFrameKickoffs.season == 2019 ) & (task1DataFrameKickoffs.possessionTeam == 'SF')\n",
    "                                         & (task1DataFrameKickoffs.penaltyCodes == 0) \n",
    "                                         & (task1DataFrameKickoffs.event != 'None')]\n",
    "kickoffsSF2020 = task1DataFrameKickoffs[(task1DataFrameKickoffs.season == 2020 ) & (task1DataFrameKickoffs.possessionTeam == 'SF')\n",
    "                                         & (task1DataFrameKickoffs.penaltyCodes == 0) \n",
    "                                         & (task1DataFrameKickoffs.event != 'None')]\n",
    "\n",
    "# Extra Points\n",
    "extraPointsSF2018 = task1DataFrameExtrapoints[(task1DataFrameExtrapoints.season == 2018 ) & (task1DataFrameExtrapoints.possessionTeam == 'SF') \n",
    "                                           & (task1DataFrameExtrapoints.penaltyCodes == 0) \n",
    "                                           & (task1DataFrameExtrapoints.event != 'None')]\n",
    "extraPointsSF2019 = task1DataFrameExtrapoints[(task1DataFrameExtrapoints.season == 2019 ) & (task1DataFrameExtrapoints.possessionTeam == 'SF') \n",
    "                                           & (task1DataFrameExtrapoints.penaltyCodes == 0) \n",
    "                                           & (task1DataFrameExtrapoints.event != 'None')]\n",
    "extraPointsSF2020 = task1DataFrameExtrapoints[(task1DataFrameExtrapoints.season == 2020 ) & (task1DataFrameExtrapoints.possessionTeam == 'SF') \n",
    "                                           & (task1DataFrameExtrapoints.penaltyCodes == 0) \n",
    "                                           & (task1DataFrameExtrapoints.event != 'None')]\n",
    "\n",
    "# Field Goals\n",
    "fieldGoalsSF2018 = task1DataFrameFieldgoals[(task1DataFrameFieldgoals.season == 2018 ) & (task1DataFrameFieldgoals.possessionTeam == 'SF')  \n",
    "                                         & (task1DataFrameFieldgoals.penaltyCodes == 0) \n",
    "                                         & (task1DataFrameFieldgoals.event != 'None')]\n",
    "fieldGoalsSF2019 = task1DataFrameFieldgoals[(task1DataFrameFieldgoals.season == 2019 ) & (task1DataFrameFieldgoals.possessionTeam == 'SF')  \n",
    "                                         & (task1DataFrameFieldgoals.penaltyCodes == 0) \n",
    "                                         & (task1DataFrameFieldgoals.event != 'None')]\n",
    "fieldGoalsSF2020 = task1DataFrameFieldgoals[(task1DataFrameFieldgoals.season == 2020 ) & (task1DataFrameFieldgoals.possessionTeam == 'SF')  \n",
    "                                         & (task1DataFrameFieldgoals.penaltyCodes == 0) \n",
    "                                         & (task1DataFrameFieldgoals.event != 'None')]\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "d1ef0a4c-9dd8-45cc-9287-114860390231",
   "metadata": {},
   "outputs": [],
   "source": [
    "# TB Special Plays Data Preparation\n",
    "\n",
    "# Punts\n",
    "puntsTB2018 = task1DataFramePunts[(task1DataFramePunts.season == 2018 ) & (task1DataFramePunts.possessionTeam == 'TB') \n",
    "                                   & (task1DataFramePunts.penaltyCodes == 0) \n",
    "                                   & (task1DataFramePunts.event != 'None')]\n",
    "puntsTB2019 = task1DataFramePunts[(task1DataFramePunts.season == 2019 ) & (task1DataFramePunts.possessionTeam == 'TB') \n",
    "                                   & (task1DataFramePunts.penaltyCodes == 0) \n",
    "                                   & (task1DataFramePunts.event != 'None')]\n",
    "puntsTB2020 = task1DataFramePunts[(task1DataFramePunts.season == 2020 ) & (task1DataFramePunts.possessionTeam == 'TB') \n",
    "                                   & (task1DataFramePunts.penaltyCodes == 0) \n",
    "                                   & (task1DataFramePunts.event != 'None')]\n",
    "\n",
    "# Kickoffs\n",
    "kickoffsTB2018 = task1DataFrameKickoffs[(task1DataFrameKickoffs.season == 2018 ) & (task1DataFrameKickoffs.possessionTeam == 'TB')\n",
    "                                         & (task1DataFrameKickoffs.penaltyCodes == 0) \n",
    "                                         & (task1DataFrameKickoffs.event != 'None')]\n",
    "kickoffsTB2019 = task1DataFrameKickoffs[(task1DataFrameKickoffs.season == 2019 ) & (task1DataFrameKickoffs.possessionTeam == 'TB')\n",
    "                                         & (task1DataFrameKickoffs.penaltyCodes == 0) \n",
    "                                         & (task1DataFrameKickoffs.event != 'None')]\n",
    "kickoffsTB2020 = task1DataFrameKickoffs[(task1DataFrameKickoffs.season == 2020 ) & (task1DataFrameKickoffs.possessionTeam == 'TB')\n",
    "                                         & (task1DataFrameKickoffs.penaltyCodes == 0) \n",
    "                                         & (task1DataFrameKickoffs.event != 'None')]\n",
    "\n",
    "# Extra Points\n",
    "extraPointsTB2018 = task1DataFrameExtrapoints[(task1DataFrameExtrapoints.season == 2018 ) & (task1DataFrameExtrapoints.possessionTeam == 'TB') \n",
    "                                           & (task1DataFrameExtrapoints.penaltyCodes == 0) \n",
    "                                           & (task1DataFrameExtrapoints.event != 'None')]\n",
    "extraPointsTB2019 = task1DataFrameExtrapoints[(task1DataFrameExtrapoints.season == 2019 ) & (task1DataFrameExtrapoints.possessionTeam == 'TB') \n",
    "                                           & (task1DataFrameExtrapoints.penaltyCodes == 0) \n",
    "                                           & (task1DataFrameExtrapoints.event != 'None')]\n",
    "extraPointsTB2020 = task1DataFrameExtrapoints[(task1DataFrameExtrapoints.season == 2020 ) & (task1DataFrameExtrapoints.possessionTeam == 'TB') \n",
    "                                           & (task1DataFrameExtrapoints.penaltyCodes == 0) \n",
    "                                           & (task1DataFrameExtrapoints.event != 'None')]\n",
    "\n",
    "# Field Goals\n",
    "fieldGoalsTB2018 = task1DataFrameFieldgoals[(task1DataFrameFieldgoals.season == 2018 ) & (task1DataFrameFieldgoals.possessionTeam == 'TB')  \n",
    "                                         & (task1DataFrameFieldgoals.penaltyCodes == 0) \n",
    "                                         & (task1DataFrameFieldgoals.event != 'None')]\n",
    "fieldGoalsTB2019 = task1DataFrameFieldgoals[(task1DataFrameFieldgoals.season == 2019 ) & (task1DataFrameFieldgoals.possessionTeam == 'TB')  \n",
    "                                         & (task1DataFrameFieldgoals.penaltyCodes == 0) \n",
    "                                         & (task1DataFrameFieldgoals.event != 'None')]\n",
    "fieldGoalsTB2020 = task1DataFrameFieldgoals[(task1DataFrameFieldgoals.season == 2020 ) & (task1DataFrameFieldgoals.possessionTeam == 'TB')  \n",
    "                                         & (task1DataFrameFieldgoals.penaltyCodes == 0) \n",
    "                                         & (task1DataFrameFieldgoals.event != 'None')]\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "07715ce7-5b70-4f96-b3af-f87023509730",
   "metadata": {},
   "outputs": [],
   "source": [
    "extraPointsTB2018.to_csv(r'/Users/kushtrivedi/Desktop/NFL/TampaBay/TB_ExtraPoint_2018.csv', index=False)\n",
    "extraPointsTB2019.to_csv(r'/Users/kushtrivedi/Desktop/NFL/TampaBay/TB_ExtraPoint_2019.csv', index=False)\n",
    "extraPointsTB2020.to_csv(r'/Users/kushtrivedi/Desktop/NFL/TampaBay/TB_ExtraPoint_2020.csv', index=False)\n",
    "\n",
    "fieldGoalsTB2018.to_csv(r'/Users/kushtrivedi/Desktop/NFL/TampaBay/TB_FiledGoals_2018.csv', index=False)\n",
    "fieldGoalsTB2019.to_csv(r'/Users/kushtrivedi/Desktop/NFL/TampaBay/TB_FiledGoals_2019.csv', index=False)\n",
    "fieldGoalsTB2020.to_csv(r'/Users/kushtrivedi/Desktop/NFL/TampaBay/TB_FiledGoals_2020.csv', index=False)\n",
    "\n",
    "kickoffsTB2018.to_csv(r'/Users/kushtrivedi/Desktop/NFL/TampaBay/TB_Kickoffs_2018.csv', index=False)\n",
    "kickoffsTB2019.to_csv(r'/Users/kushtrivedi/Desktop/NFL/TampaBay/TB_Kickoffs_2019.csv', index=False)\n",
    "kickoffsTB2020.to_csv(r'/Users/kushtrivedi/Desktop/NFL/TampaBay/TB_Kickoffs_2020.csv', index=False)\n",
    "\n",
    "puntsTB2018.to_csv(r'/Users/kushtrivedi/Desktop/NFL/TampaBay/TB_Punts_2018.csv', index=False)\n",
    "puntsTB2019.to_csv(r'/Users/kushtrivedi/Desktop/NFL/TampaBay/TB_Punts_2019.csv', index=False)\n",
    "puntsTB2020.to_csv(r'/Users/kushtrivedi/Desktop/NFL/TampaBay/TB_Punts_2020.csv', index=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "20841dd4-8554-4b5b-b8b1-340bd448f47e",
   "metadata": {},
   "outputs": [],
   "source": [
    "# TEN Special Plays Data Preparation\n",
    "\n",
    "# Punts\n",
    "puntsTEN2018 = task1DataFramePunts[(task1DataFramePunts.season == 2018 ) & (task1DataFramePunts.possessionTeam == 'TEN') \n",
    "                                   & (task1DataFramePunts.penaltyCodes == 0) \n",
    "                                   & (task1DataFramePunts.event != 'None')]\n",
    "puntsTEN2019 = task1DataFramePunts[(task1DataFramePunts.season == 2019 ) & (task1DataFramePunts.possessionTeam == 'TEN') \n",
    "                                   & (task1DataFramePunts.penaltyCodes == 0) \n",
    "                                   & (task1DataFramePunts.event != 'None')]\n",
    "puntsTEN2020 = task1DataFramePunts[(task1DataFramePunts.season == 2020 ) & (task1DataFramePunts.possessionTeam == 'TEN') \n",
    "                                   & (task1DataFramePunts.penaltyCodes == 0) \n",
    "                                   & (task1DataFramePunts.event != 'None')]\n",
    "\n",
    "# Kickoffs\n",
    "kickoffsTEN2018 = task1DataFrameKickoffs[(task1DataFrameKickoffs.season == 2018 ) & (task1DataFrameKickoffs.possessionTeam == 'TEN')\n",
    "                                         & (task1DataFrameKickoffs.penaltyCodes == 0) \n",
    "                                         & (task1DataFrameKickoffs.event != 'None')]\n",
    "kickoffsTEN2019 = task1DataFrameKickoffs[(task1DataFrameKickoffs.season == 2019 ) & (task1DataFrameKickoffs.possessionTeam == 'TEN')\n",
    "                                         & (task1DataFrameKickoffs.penaltyCodes == 0) \n",
    "                                         & (task1DataFrameKickoffs.event != 'None')]\n",
    "kickoffsTEN2020 = task1DataFrameKickoffs[(task1DataFrameKickoffs.season == 2020 ) & (task1DataFrameKickoffs.possessionTeam == 'TEN')\n",
    "                                         & (task1DataFrameKickoffs.penaltyCodes == 0) \n",
    "                                         & (task1DataFrameKickoffs.event != 'None')]\n",
    "\n",
    "# Extra Points\n",
    "extraPointsTEN2018 = task1DataFrameExtrapoints[(task1DataFrameExtrapoints.season == 2018 ) & (task1DataFrameExtrapoints.possessionTeam == 'TEN') \n",
    "                                           & (task1DataFrameExtrapoints.penaltyCodes == 0) \n",
    "                                           & (task1DataFrameExtrapoints.event != 'None')]\n",
    "extraPointsTEN2019 = task1DataFrameExtrapoints[(task1DataFrameExtrapoints.season == 2019 ) & (task1DataFrameExtrapoints.possessionTeam == 'TEN') \n",
    "                                           & (task1DataFrameExtrapoints.penaltyCodes == 0) \n",
    "                                           & (task1DataFrameExtrapoints.event != 'None')]\n",
    "extraPointsTEN2020 = task1DataFrameExtrapoints[(task1DataFrameExtrapoints.season == 2020 ) & (task1DataFrameExtrapoints.possessionTeam == 'TEN') \n",
    "                                           & (task1DataFrameExtrapoints.penaltyCodes == 0) \n",
    "                                           & (task1DataFrameExtrapoints.event != 'None')]\n",
    "\n",
    "# Field Goals\n",
    "fieldGoalsTEN2018 = task1DataFrameFieldgoals[(task1DataFrameFieldgoals.season == 2018 ) & (task1DataFrameFieldgoals.possessionTeam == 'TEN')  \n",
    "                                         & (task1DataFrameFieldgoals.penaltyCodes == 0) \n",
    "                                         & (task1DataFrameFieldgoals.event != 'None')]\n",
    "fieldGoalsTEN2019 = task1DataFrameFieldgoals[(task1DataFrameFieldgoals.season == 2019 ) & (task1DataFrameFieldgoals.possessionTeam == 'TEN')  \n",
    "                                         & (task1DataFrameFieldgoals.penaltyCodes == 0) \n",
    "                                         & (task1DataFrameFieldgoals.event != 'None')]\n",
    "fieldGoalsTEN2020 = task1DataFrameFieldgoals[(task1DataFrameFieldgoals.season == 2020 ) & (task1DataFrameFieldgoals.possessionTeam == 'TEN')  \n",
    "                                         & (task1DataFrameFieldgoals.penaltyCodes == 0) \n",
    "                                         & (task1DataFrameFieldgoals.event != 'None')]\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "a387c0b9-7ccf-4a0a-8c08-e7233288a7cf",
   "metadata": {},
   "outputs": [],
   "source": [
    "extraPointsTEN2018.to_csv(r'/Users/kushtrivedi/Desktop/NFL/Tennessee/TEN_ExtraPoint_2018.csv', index=False)\n",
    "extraPointsTEN2019.to_csv(r'/Users/kushtrivedi/Desktop/NFL/Tennessee/TEN_ExtraPoint_2019.csv', index=False)\n",
    "extraPointsTEN2020.to_csv(r'/Users/kushtrivedi/Desktop/NFL/Tennessee/TEN_ExtraPoint_2020.csv', index=False)\n",
    "\n",
    "fieldGoalsTEN2018.to_csv(r'/Users/kushtrivedi/Desktop/NFL/Tennessee/TEN_FiledGoals_2018.csv', index=False)\n",
    "fieldGoalsTEN2019.to_csv(r'/Users/kushtrivedi/Desktop/NFL/Tennessee/TEN_FiledGoals_2019.csv', index=False)\n",
    "fieldGoalsTEN2020.to_csv(r'/Users/kushtrivedi/Desktop/NFL/Tennessee/TEN_FiledGoals_2020.csv', index=False)\n",
    "\n",
    "kickoffsTEN2018.to_csv(r'/Users/kushtrivedi/Desktop/NFL/Tennessee/TEN_Kickoffs_2018.csv', index=False)\n",
    "kickoffsTEN2019.to_csv(r'/Users/kushtrivedi/Desktop/NFL/Tennessee/TEN_Kickoffs_2019.csv', index=False)\n",
    "kickoffsTEN2020.to_csv(r'/Users/kushtrivedi/Desktop/NFL/Tennessee/TEN_Kickoffs_2020.csv', index=False)\n",
    "\n",
    "puntsTEN2018.to_csv(r'/Users/kushtrivedi/Desktop/NFL/Tennessee/TEN_Punts_2018.csv', index=False)\n",
    "puntsTEN2019.to_csv(r'/Users/kushtrivedi/Desktop/NFL/Tennessee/TEN_Punts_2019.csv', index=False)\n",
    "puntsTEN2020.to_csv(r'/Users/kushtrivedi/Desktop/NFL/Tennessee/TEN_Punts_2020.csv', index=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "63b7978d-a301-4c1b-b243-538ffefcfc27",
   "metadata": {},
   "outputs": [],
   "source": [
    "# WAS Special Plays Data Preparation\n",
    "\n",
    "# Punts\n",
    "puntsWAS2018 = task1DataFramePunts[(task1DataFramePunts.season == 2018 ) & (task1DataFramePunts.possessionTeam == 'WAS') \n",
    "                                   & (task1DataFramePunts.penaltyCodes == 0) \n",
    "                                   & (task1DataFramePunts.event != 'None')]\n",
    "puntsWAS2019 = task1DataFramePunts[(task1DataFramePunts.season == 2019 ) & (task1DataFramePunts.possessionTeam == 'WAS') \n",
    "                                   & (task1DataFramePunts.penaltyCodes == 0) \n",
    "                                   & (task1DataFramePunts.event != 'None')]\n",
    "puntsWAS2020 = task1DataFramePunts[(task1DataFramePunts.season == 2020 ) & (task1DataFramePunts.possessionTeam == 'WAS') \n",
    "                                   & (task1DataFramePunts.penaltyCodes == 0) \n",
    "                                   & (task1DataFramePunts.event != 'None')]\n",
    "\n",
    "# Kickoffs\n",
    "kickoffsWAS2018 = task1DataFrameKickoffs[(task1DataFrameKickoffs.season == 2018 ) & (task1DataFrameKickoffs.possessionTeam == 'WAS')\n",
    "                                         & (task1DataFrameKickoffs.penaltyCodes == 0) \n",
    "                                         & (task1DataFrameKickoffs.event != 'None')]\n",
    "kickoffsWAS2019 = task1DataFrameKickoffs[(task1DataFrameKickoffs.season == 2019 ) & (task1DataFrameKickoffs.possessionTeam == 'WAS')\n",
    "                                         & (task1DataFrameKickoffs.penaltyCodes == 0) \n",
    "                                         & (task1DataFrameKickoffs.event != 'None')]\n",
    "kickoffsWAS2020 = task1DataFrameKickoffs[(task1DataFrameKickoffs.season == 2020 ) & (task1DataFrameKickoffs.possessionTeam == 'WAS')\n",
    "                                         & (task1DataFrameKickoffs.penaltyCodes == 0) \n",
    "                                         & (task1DataFrameKickoffs.event != 'None')]\n",
    "\n",
    "# Extra Points\n",
    "extraPointsWAS2018 = task1DataFrameExtrapoints[(task1DataFrameExtrapoints.season == 2018 ) & (task1DataFrameExtrapoints.possessionTeam == 'WAS') \n",
    "                                           & (task1DataFrameExtrapoints.penaltyCodes == 0) \n",
    "                                           & (task1DataFrameExtrapoints.event != 'None')]\n",
    "extraPointsWAS2019 = task1DataFrameExtrapoints[(task1DataFrameExtrapoints.season == 2019 ) & (task1DataFrameExtrapoints.possessionTeam == 'WAS') \n",
    "                                           & (task1DataFrameExtrapoints.penaltyCodes == 0) \n",
    "                                           & (task1DataFrameExtrapoints.event != 'None')]\n",
    "extraPointsWAS2020 = task1DataFrameExtrapoints[(task1DataFrameExtrapoints.season == 2020 ) & (task1DataFrameExtrapoints.possessionTeam == 'WAS') \n",
    "                                           & (task1DataFrameExtrapoints.penaltyCodes == 0) \n",
    "                                           & (task1DataFrameExtrapoints.event != 'None')]\n",
    "\n",
    "# Field Goals\n",
    "fieldGoalsWAS2018 = task1DataFrameFieldgoals[(task1DataFrameFieldgoals.season == 2018 ) & (task1DataFrameFieldgoals.possessionTeam == 'WAS')  \n",
    "                                         & (task1DataFrameFieldgoals.penaltyCodes == 0) \n",
    "                                         & (task1DataFrameFieldgoals.event != 'None')]\n",
    "fieldGoalsWAS2019 = task1DataFrameFieldgoals[(task1DataFrameFieldgoals.season == 2019 ) & (task1DataFrameFieldgoals.possessionTeam == 'WAS')  \n",
    "                                         & (task1DataFrameFieldgoals.penaltyCodes == 0) \n",
    "                                         & (task1DataFrameFieldgoals.event != 'None')]\n",
    "fieldGoalsWAS2020 = task1DataFrameFieldgoals[(task1DataFrameFieldgoals.season == 2020 ) & (task1DataFrameFieldgoals.possessionTeam == 'WAS')  \n",
    "                                         & (task1DataFrameFieldgoals.penaltyCodes == 0) \n",
    "                                         & (task1DataFrameFieldgoals.event != 'None')]\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "bf3ebd68-40b3-4b5c-8ba9-5bb42ab6c76b",
   "metadata": {},
   "outputs": [],
   "source": [
    "# ARI Special Plays Data Frames\n",
    "\n",
    "# Punt Frames\n",
    "ARIPuntsSeries2018 = puntsARI2018.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo','yardlineSide','Result','gameClock',\n",
    "                                   'yardlineNumber','playResult','preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr',\n",
    "                                   'week'],as_index=True).size()\n",
    "ARIPuntsFrame2018 = pd.DataFrame(ARIPuntsSeries2018)\n",
    "\n",
    "ARIPuntsSeries2019 = puntsARI2019.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo','yardlineSide','Result','gameClock',\n",
    "                                           'yardlineNumber','playResult','preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr',\n",
    "                                           'week'],as_index=True).size()\n",
    "ARIPuntsFrame2019 = pd.DataFrame(ARIPuntsSeries2019)\n",
    "\n",
    "ARIPuntsSeries2020 = puntsARI2020.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo','yardlineSide','Result','gameClock',\n",
    "                                           'yardlineNumber','playResult','preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr',\n",
    "                                           'week'],as_index=True).size()\n",
    "ARIPuntsFrame2020 = pd.DataFrame(ARIPuntsSeries2020)\n",
    "\n",
    "\n",
    "# Kickoff Frames\n",
    "ARIKickoffsSeries2018 = kickoffsARI2018.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo','yardlineSide','Result','gameClock',\n",
    "                                                 'yardlineNumber','playResult','preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr',\n",
    "                                                 'visitorTeamAbbr','week'],as_index=True).size()\n",
    "ARIKickoffsFrame2018 = pd.DataFrame(ARIKickoffsSeries2018)\n",
    "\n",
    "ARIKickoffsSeries2019 = kickoffsARI2019.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo','yardlineSide','Result','gameClock',\n",
    "                                                 'yardlineNumber','playResult','preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr',\n",
    "                                                 'visitorTeamAbbr','week'],as_index=True).size()\n",
    "ARIKickoffsFrame2019 = pd.DataFrame(ARIKickoffsSeries2019)\n",
    "\n",
    "ARIKickoffsSeries2020 = kickoffsARI2020.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo','yardlineSide','Result','gameClock',\n",
    "                                                 'yardlineNumber','playResult','preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr',\n",
    "                                                 'visitorTeamAbbr','week'],as_index=True).size()\n",
    "ARIKickoffsFrame2020 = pd.DataFrame(ARIKickoffsSeries2020)\n",
    "\n",
    "\n",
    "# Extra Points\n",
    "ARIExtraPointsSeries2018 = extraPointsARI2018.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo','yardlineSide','Result','gameClock',\n",
    "                                               'yardlineNumber','playResult','preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr',\n",
    "                                               'week'],as_index=True).size()\n",
    "ARIExtraPointsFrame2018 = pd.DataFrame(ARIExtraPointsSeries2018)\n",
    "ARIExtraPointsSeries2019 = extraPointsARI2019.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo','yardlineSide','Result','gameClock',\n",
    "                                               'yardlineNumber','playResult','preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr',\n",
    "                                               'week'],as_index=True).size()\n",
    "ARIExtraPointsFrame2019 = pd.DataFrame(ARIExtraPointsSeries2019)\n",
    "ARIExtraPointsSeries2020 = extraPointsARI2020.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo','yardlineSide','Result','gameClock',\n",
    "                                               'yardlineNumber','playResult','preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr',\n",
    "                                               'week'],as_index=True).size()\n",
    "ARIExtraPointsFrame2020 = pd.DataFrame(ARIExtraPointsSeries2020)\n",
    "\n",
    "\n",
    "# Field Goals\n",
    "ARIFiledGoalsSeries2018 = fieldGoalsARI2018.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo',\n",
    "                                               'yardlineSide','Result','gameClock','yardlineNumber','playResult',\n",
    "                                               'preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr','week']\n",
    "                                              ,as_index=True).size()\n",
    "ARIFiledGoalsFrame2018 = pd.DataFrame(ARIFiledGoalsSeries2018)\n",
    "ARIFiledGoalsSeries2019 = fieldGoalsARI2019.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo',\n",
    "                                               'yardlineSide','Result','gameClock','yardlineNumber','playResult',\n",
    "                                               'preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr','week']\n",
    "                                              ,as_index=True).size()\n",
    "ARIFiledGoalsFrame2019 = pd.DataFrame(ARIFiledGoalsSeries2019)\n",
    "ARIFiledGoalsSeries2020 = fieldGoalsARI2020.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo',\n",
    "                                               'yardlineSide','Result','gameClock','yardlineNumber','playResult',\n",
    "                                               'preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr','week']\n",
    "                                              ,as_index=True).size()\n",
    "ARIFiledGoalsFrame2020 = pd.DataFrame(ARIFiledGoalsSeries2020)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "34143f4a-e1be-42ad-97b8-457cdd6bc9a4",
   "metadata": {},
   "outputs": [],
   "source": [
    "# ATL Special Plays Data Frames\n",
    "\n",
    "# Punt Frames\n",
    "ATLPuntsSeries2018 = puntsATL2018.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo','yardlineSide','Result','gameClock',\n",
    "                                   'yardlineNumber','playResult','preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr',\n",
    "                                   'week'],as_index=True).size()\n",
    "ATLPuntsFrame2018 = pd.DataFrame(ATLPuntsSeries2018)\n",
    "\n",
    "ATLPuntsSeries2019 = puntsATL2019.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo','yardlineSide','Result','gameClock',\n",
    "                                           'yardlineNumber','playResult','preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr',\n",
    "                                           'week'],as_index=True).size()\n",
    "ATLPuntsFrame2019 = pd.DataFrame(ATLPuntsSeries2019)\n",
    "\n",
    "ATLPuntsSeries2020 = puntsATL2020.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo','yardlineSide','Result','gameClock',\n",
    "                                           'yardlineNumber','playResult','preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr',\n",
    "                                           'week'],as_index=True).size()\n",
    "ATLPuntsFrame2020 = pd.DataFrame(ATLPuntsSeries2020)\n",
    "\n",
    "\n",
    "# Kickoff Frames\n",
    "ATLKickoffsSeries2018 = kickoffsATL2018.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo','yardlineSide','Result','gameClock',\n",
    "                                                 'yardlineNumber','playResult','preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr',\n",
    "                                                 'visitorTeamAbbr','week'],as_index=True).size()\n",
    "ATLKickoffsFrame2018 = pd.DataFrame(ATLKickoffsSeries2018)\n",
    "\n",
    "ATLKickoffsSeries2019 = kickoffsATL2019.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo','yardlineSide','Result','gameClock',\n",
    "                                                 'yardlineNumber','playResult','preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr',\n",
    "                                                 'visitorTeamAbbr','week'],as_index=True).size()\n",
    "ATLKickoffsFrame2019 = pd.DataFrame(ATLKickoffsSeries2019)\n",
    "\n",
    "ATLKickoffsSeries2020 = kickoffsATL2020.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo','yardlineSide','Result','gameClock',\n",
    "                                                 'yardlineNumber','playResult','preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr',\n",
    "                                                 'visitorTeamAbbr','week'],as_index=True).size()\n",
    "ATLKickoffsFrame2020 = pd.DataFrame(ATLKickoffsSeries2020)\n",
    "\n",
    "\n",
    "# Extra Points\n",
    "ATLExtraPointsSeries2018 = extraPointsATL2018.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo','yardlineSide','Result','gameClock',\n",
    "                                               'yardlineNumber','playResult','preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr',\n",
    "                                               'week'],as_index=True).size()\n",
    "ATLExtraPointsFrame2018 = pd.DataFrame(ATLExtraPointsSeries2018)\n",
    "ATLExtraPointsSeries2019 = extraPointsATL2019.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo','yardlineSide','Result','gameClock',\n",
    "                                               'yardlineNumber','playResult','preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr',\n",
    "                                               'week'],as_index=True).size()\n",
    "ATLExtraPointsFrame2019 = pd.DataFrame(ATLExtraPointsSeries2019)\n",
    "ATLExtraPointsSeries2020 = extraPointsATL2020.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo','yardlineSide','Result','gameClock',\n",
    "                                               'yardlineNumber','playResult','preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr',\n",
    "                                               'week'],as_index=True).size()\n",
    "ATLExtraPointsFrame2020 = pd.DataFrame(ATLExtraPointsSeries2020)\n",
    "\n",
    "\n",
    "# Field Goals\n",
    "ATLFiledGoalsSeries2018 = fieldGoalsATL2018.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo',\n",
    "                                               'yardlineSide','Result','gameClock','yardlineNumber','playResult',\n",
    "                                               'preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr','week']\n",
    "                                              ,as_index=True).size()\n",
    "ATLFiledGoalsFrame2018 = pd.DataFrame(ATLFiledGoalsSeries2018)\n",
    "ATLFiledGoalsSeries2019 = fieldGoalsATL2019.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo',\n",
    "                                               'yardlineSide','Result','gameClock','yardlineNumber','playResult',\n",
    "                                               'preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr','week']\n",
    "                                              ,as_index=True).size()\n",
    "ATLFiledGoalsFrame2019 = pd.DataFrame(ATLFiledGoalsSeries2019)\n",
    "ATLFiledGoalsSeries2020 = fieldGoalsATL2020.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo',\n",
    "                                               'yardlineSide','Result','gameClock','yardlineNumber','playResult',\n",
    "                                               'preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr','week']\n",
    "                                              ,as_index=True).size()\n",
    "ATLFiledGoalsFrame2020 = pd.DataFrame(ATLFiledGoalsSeries2020)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "1300344d-6612-429b-aef9-316f705ebe89",
   "metadata": {},
   "outputs": [],
   "source": [
    "# BAL Special Plays Data Frames\n",
    "\n",
    "# Punt Frames\n",
    "BALPuntsSeries2018 = puntsBAL2018.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo','yardlineSide','Result','gameClock',\n",
    "                                   'yardlineNumber','playResult','preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr',\n",
    "                                   'week'],as_index=True).size()\n",
    "BALPuntsFrame2018 = pd.DataFrame(BALPuntsSeries2018)\n",
    "\n",
    "BALPuntsSeries2019 = puntsBAL2019.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo','yardlineSide','Result','gameClock',\n",
    "                                           'yardlineNumber','playResult','preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr',\n",
    "                                           'week'],as_index=True).size()\n",
    "BALPuntsFrame2019 = pd.DataFrame(BALPuntsSeries2019)\n",
    "\n",
    "BALPuntsSeries2020 = puntsBAL2020.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo','yardlineSide','Result','gameClock',\n",
    "                                           'yardlineNumber','playResult','preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr',\n",
    "                                           'week'],as_index=True).size()\n",
    "BALPuntsFrame2020 = pd.DataFrame(BALPuntsSeries2020)\n",
    "\n",
    "\n",
    "# Kickoff Frames\n",
    "BALKickoffsSeries2018 = kickoffsBAL2018.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo','yardlineSide','Result','gameClock',\n",
    "                                                 'yardlineNumber','playResult','preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr',\n",
    "                                                 'visitorTeamAbbr','week'],as_index=True).size()\n",
    "BALKickoffsFrame2018 = pd.DataFrame(BALKickoffsSeries2018)\n",
    "\n",
    "BALKickoffsSeries2019 = kickoffsBAL2019.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo','yardlineSide','Result','gameClock',\n",
    "                                                 'yardlineNumber','playResult','preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr',\n",
    "                                                 'visitorTeamAbbr','week'],as_index=True).size()\n",
    "BALKickoffsFrame2019 = pd.DataFrame(BALKickoffsSeries2019)\n",
    "\n",
    "BALKickoffsSeries2020 = kickoffsBAL2020.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo','yardlineSide','Result','gameClock',\n",
    "                                                 'yardlineNumber','playResult','preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr',\n",
    "                                                 'visitorTeamAbbr','week'],as_index=True).size()\n",
    "BALKickoffsFrame2020 = pd.DataFrame(BALKickoffsSeries2020)\n",
    "\n",
    "\n",
    "# Extra Points\n",
    "BALExtraPointsSeries2018 = extraPointsBAL2018.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo','yardlineSide','Result','gameClock',\n",
    "                                               'yardlineNumber','playResult','preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr',\n",
    "                                               'week'],as_index=True).size()\n",
    "BALExtraPointsFrame2018 = pd.DataFrame(BALExtraPointsSeries2018)\n",
    "BALExtraPointsSeries2019 = extraPointsBAL2019.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo','yardlineSide','Result','gameClock',\n",
    "                                               'yardlineNumber','playResult','preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr',\n",
    "                                               'week'],as_index=True).size()\n",
    "BALExtraPointsFrame2019 = pd.DataFrame(BALExtraPointsSeries2019)\n",
    "BALExtraPointsSeries2020 = extraPointsBAL2020.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo','yardlineSide','Result','gameClock',\n",
    "                                               'yardlineNumber','playResult','preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr',\n",
    "                                               'week'],as_index=True).size()\n",
    "BALExtraPointsFrame2020 = pd.DataFrame(BALExtraPointsSeries2020)\n",
    "\n",
    "\n",
    "# Field Goals\n",
    "BALFiledGoalsSeries2018 = fieldGoalsBAL2018.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo',\n",
    "                                               'yardlineSide','Result','gameClock','yardlineNumber','playResult',\n",
    "                                               'preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr','week']\n",
    "                                              ,as_index=True).size()\n",
    "BALFiledGoalsFrame2018 = pd.DataFrame(BALFiledGoalsSeries2018)\n",
    "BALFiledGoalsSeries2019 = fieldGoalsBAL2019.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo',\n",
    "                                               'yardlineSide','Result','gameClock','yardlineNumber','playResult',\n",
    "                                               'preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr','week']\n",
    "                                              ,as_index=True).size()\n",
    "BALFiledGoalsFrame2019 = pd.DataFrame(BALFiledGoalsSeries2019)\n",
    "BALFiledGoalsSeries2020 = fieldGoalsBAL2020.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo',\n",
    "                                               'yardlineSide','Result','gameClock','yardlineNumber','playResult',\n",
    "                                               'preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr','week']\n",
    "                                              ,as_index=True).size()\n",
    "BALFiledGoalsFrame2020 = pd.DataFrame(BALFiledGoalsSeries2020)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "4df50737-dfad-46b2-9f79-38cb0e0352eb",
   "metadata": {},
   "outputs": [],
   "source": [
    "# BUF Special Plays Data Frames\n",
    "\n",
    "# Punt Frames\n",
    "BUFPuntsSeries2018 = puntsBUF2018.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo','yardlineSide','Result','gameClock',\n",
    "                                   'yardlineNumber','playResult','preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr',\n",
    "                                   'week'],as_index=True).size()\n",
    "BUFPuntsFrame2018 = pd.DataFrame(BUFPuntsSeries2018)\n",
    "\n",
    "BUFPuntsSeries2019 = puntsBUF2019.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo','yardlineSide','Result','gameClock',\n",
    "                                           'yardlineNumber','playResult','preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr',\n",
    "                                           'week'],as_index=True).size()\n",
    "BUFPuntsFrame2019 = pd.DataFrame(BUFPuntsSeries2019)\n",
    "\n",
    "BUFPuntsSeries2020 = puntsBUF2020.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo','yardlineSide','Result','gameClock',\n",
    "                                           'yardlineNumber','playResult','preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr',\n",
    "                                           'week'],as_index=True).size()\n",
    "BUFPuntsFrame2020 = pd.DataFrame(BUFPuntsSeries2020)\n",
    "\n",
    "\n",
    "# Kickoff Frames\n",
    "BUFKickoffsSeries2018 = kickoffsBUF2018.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo','yardlineSide','Result','gameClock',\n",
    "                                                 'yardlineNumber','playResult','preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr',\n",
    "                                                 'visitorTeamAbbr','week'],as_index=True).size()\n",
    "BUFKickoffsFrame2018 = pd.DataFrame(BUFKickoffsSeries2018)\n",
    "\n",
    "BUFKickoffsSeries2019 = kickoffsBUF2019.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo','yardlineSide','Result','gameClock',\n",
    "                                                 'yardlineNumber','playResult','preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr',\n",
    "                                                 'visitorTeamAbbr','week'],as_index=True).size()\n",
    "BUFKickoffsFrame2019 = pd.DataFrame(BUFKickoffsSeries2019)\n",
    "\n",
    "BUFKickoffsSeries2020 = kickoffsBUF2020.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo','yardlineSide','Result','gameClock',\n",
    "                                                 'yardlineNumber','playResult','preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr',\n",
    "                                                 'visitorTeamAbbr','week'],as_index=True).size()\n",
    "BUFKickoffsFrame2020 = pd.DataFrame(BUFKickoffsSeries2020)\n",
    "\n",
    "\n",
    "# Extra Points\n",
    "BUFExtraPointsSeries2018 = extraPointsBUF2018.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo','yardlineSide','Result','gameClock',\n",
    "                                               'yardlineNumber','playResult','preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr',\n",
    "                                               'week'],as_index=True).size()\n",
    "BUFExtraPointsFrame2018 = pd.DataFrame(BUFExtraPointsSeries2018)\n",
    "BUFExtraPointsSeries2019 = extraPointsBUF2019.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo','yardlineSide','Result','gameClock',\n",
    "                                               'yardlineNumber','playResult','preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr',\n",
    "                                               'week'],as_index=True).size()\n",
    "BUFExtraPointsFrame2019 = pd.DataFrame(BUFExtraPointsSeries2019)\n",
    "BUFExtraPointsSeries2020 = extraPointsBUF2020.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo','yardlineSide','Result','gameClock',\n",
    "                                               'yardlineNumber','playResult','preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr',\n",
    "                                               'week'],as_index=True).size()\n",
    "BUFExtraPointsFrame2020 = pd.DataFrame(BUFExtraPointsSeries2020)\n",
    "\n",
    "\n",
    "# Field Goals\n",
    "BUFFiledGoalsSeries2018 = fieldGoalsBUF2018.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo',\n",
    "                                               'yardlineSide','Result','gameClock','yardlineNumber','playResult',\n",
    "                                               'preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr','week']\n",
    "                                              ,as_index=True).size()\n",
    "BUFFiledGoalsFrame2018 = pd.DataFrame(BUFFiledGoalsSeries2018)\n",
    "BUFFiledGoalsSeries2019 = fieldGoalsBUF2019.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo',\n",
    "                                               'yardlineSide','Result','gameClock','yardlineNumber','playResult',\n",
    "                                               'preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr','week']\n",
    "                                              ,as_index=True).size()\n",
    "BUFFiledGoalsFrame2019 = pd.DataFrame(BUFFiledGoalsSeries2019)\n",
    "BUFFiledGoalsSeries2020 = fieldGoalsBUF2020.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo',\n",
    "                                               'yardlineSide','Result','gameClock','yardlineNumber','playResult',\n",
    "                                               'preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr','week']\n",
    "                                              ,as_index=True).size()\n",
    "BUFFiledGoalsFrame2020 = pd.DataFrame(BUFFiledGoalsSeries2020)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "d63fd45f-564b-4632-9b1f-9890caffc75e",
   "metadata": {},
   "outputs": [],
   "source": [
    "# CAR Special Plays Data Frames\n",
    "\n",
    "# Punt Frames\n",
    "CARPuntsSeries2018 = puntsCAR2018.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo','yardlineSide','Result','gameClock',\n",
    "                                   'yardlineNumber','playResult','preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr',\n",
    "                                   'week'],as_index=True).size()\n",
    "CARPuntsFrame2018 = pd.DataFrame(CARPuntsSeries2018)\n",
    "\n",
    "CARPuntsSeries2019 = puntsCAR2019.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo','yardlineSide','Result','gameClock',\n",
    "                                           'yardlineNumber','playResult','preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr',\n",
    "                                           'week'],as_index=True).size()\n",
    "CARPuntsFrame2019 = pd.DataFrame(CARPuntsSeries2019)\n",
    "\n",
    "CARPuntsSeries2020 = puntsCAR2020.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo','yardlineSide','Result','gameClock',\n",
    "                                           'yardlineNumber','playResult','preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr',\n",
    "                                           'week'],as_index=True).size()\n",
    "CARPuntsFrame2020 = pd.DataFrame(CARPuntsSeries2020)\n",
    "\n",
    "\n",
    "# Kickoff Frames\n",
    "CARKickoffsSeries2018 = kickoffsCAR2018.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo','yardlineSide','Result','gameClock',\n",
    "                                                 'yardlineNumber','playResult','preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr',\n",
    "                                                 'visitorTeamAbbr','week'],as_index=True).size()\n",
    "CARKickoffsFrame2018 = pd.DataFrame(CARKickoffsSeries2018)\n",
    "\n",
    "CARKickoffsSeries2019 = kickoffsCAR2019.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo','yardlineSide','Result','gameClock',\n",
    "                                                 'yardlineNumber','playResult','preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr',\n",
    "                                                 'visitorTeamAbbr','week'],as_index=True).size()\n",
    "CARKickoffsFrame2019 = pd.DataFrame(CARKickoffsSeries2019)\n",
    "\n",
    "CARKickoffsSeries2020 = kickoffsCAR2020.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo','yardlineSide','Result','gameClock',\n",
    "                                                 'yardlineNumber','playResult','preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr',\n",
    "                                                 'visitorTeamAbbr','week'],as_index=True).size()\n",
    "CARKickoffsFrame2020 = pd.DataFrame(CARKickoffsSeries2020)\n",
    "\n",
    "\n",
    "# Extra Points\n",
    "CARExtraPointsSeries2018 = extraPointsCAR2018.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo','yardlineSide','Result','gameClock',\n",
    "                                               'yardlineNumber','playResult','preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr',\n",
    "                                               'week'],as_index=True).size()\n",
    "CARExtraPointsFrame2018 = pd.DataFrame(CARExtraPointsSeries2018)\n",
    "CARExtraPointsSeries2019 = extraPointsCAR2019.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo','yardlineSide','Result','gameClock',\n",
    "                                               'yardlineNumber','playResult','preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr',\n",
    "                                               'week'],as_index=True).size()\n",
    "CARExtraPointsFrame2019 = pd.DataFrame(CARExtraPointsSeries2019)\n",
    "CARExtraPointsSeries2020 = extraPointsCAR2020.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo','yardlineSide','Result','gameClock',\n",
    "                                               'yardlineNumber','playResult','preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr',\n",
    "                                               'week'],as_index=True).size()\n",
    "CARExtraPointsFrame2020 = pd.DataFrame(CARExtraPointsSeries2020)\n",
    "\n",
    "\n",
    "# Field Goals\n",
    "CARFiledGoalsSeries2018 = fieldGoalsCAR2018.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo',\n",
    "                                               'yardlineSide','Result','gameClock','yardlineNumber','playResult',\n",
    "                                               'preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr','week']\n",
    "                                              ,as_index=True).size()\n",
    "CARFiledGoalsFrame2018 = pd.DataFrame(CARFiledGoalsSeries2018)\n",
    "CARFiledGoalsSeries2019 = fieldGoalsCAR2019.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo',\n",
    "                                               'yardlineSide','Result','gameClock','yardlineNumber','playResult',\n",
    "                                               'preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr','week']\n",
    "                                              ,as_index=True).size()\n",
    "CARFiledGoalsFrame2019 = pd.DataFrame(CARFiledGoalsSeries2019)\n",
    "CARFiledGoalsSeries2020 = fieldGoalsCAR2020.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo',\n",
    "                                               'yardlineSide','Result','gameClock','yardlineNumber','playResult',\n",
    "                                               'preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr','week']\n",
    "                                              ,as_index=True).size()\n",
    "CARFiledGoalsFrame2020 = pd.DataFrame(CARFiledGoalsSeries2020)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "7cc5d300-5f0a-4174-92bc-61147d7dcdaf",
   "metadata": {},
   "outputs": [],
   "source": [
    "# CHI Special Plays Data Frames\n",
    "\n",
    "# Punt Frames\n",
    "CHIPuntsSeries2018 = puntsCHI2018.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo','yardlineSide','Result','gameClock',\n",
    "                                   'yardlineNumber','playResult','preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr',\n",
    "                                   'week'],as_index=True).size()\n",
    "CHIPuntsFrame2018 = pd.DataFrame(CHIPuntsSeries2018)\n",
    "\n",
    "CHIPuntsSeries2019 = puntsCHI2019.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo','yardlineSide','Result','gameClock',\n",
    "                                           'yardlineNumber','playResult','preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr',\n",
    "                                           'week'],as_index=True).size()\n",
    "CHIPuntsFrame2019 = pd.DataFrame(CHIPuntsSeries2019)\n",
    "\n",
    "CHIPuntsSeries2020 = puntsCHI2020.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo','yardlineSide','Result','gameClock',\n",
    "                                           'yardlineNumber','playResult','preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr',\n",
    "                                           'week'],as_index=True).size()\n",
    "CHIPuntsFrame2020 = pd.DataFrame(CHIPuntsSeries2020)\n",
    "\n",
    "\n",
    "# Kickoff Frames\n",
    "CHIKickoffsSeries2018 = kickoffsCHI2018.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo','yardlineSide','Result','gameClock',\n",
    "                                                 'yardlineNumber','playResult','preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr',\n",
    "                                                 'visitorTeamAbbr','week'],as_index=True).size()\n",
    "CHIKickoffsFrame2018 = pd.DataFrame(CHIKickoffsSeries2018)\n",
    "\n",
    "CHIKickoffsSeries2019 = kickoffsCHI2019.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo','yardlineSide','Result','gameClock',\n",
    "                                                 'yardlineNumber','playResult','preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr',\n",
    "                                                 'visitorTeamAbbr','week'],as_index=True).size()\n",
    "CHIKickoffsFrame2019 = pd.DataFrame(CHIKickoffsSeries2019)\n",
    "\n",
    "CHIKickoffsSeries2020 = kickoffsCHI2020.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo','yardlineSide','Result','gameClock',\n",
    "                                                 'yardlineNumber','playResult','preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr',\n",
    "                                                 'visitorTeamAbbr','week'],as_index=True).size()\n",
    "CHIKickoffsFrame2020 = pd.DataFrame(CHIKickoffsSeries2020)\n",
    "\n",
    "\n",
    "# Extra Points\n",
    "CHIExtraPointsSeries2018 = extraPointsCHI2018.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo','yardlineSide','Result','gameClock',\n",
    "                                               'yardlineNumber','playResult','preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr',\n",
    "                                               'week'],as_index=True).size()\n",
    "CHIExtraPointsFrame2018 = pd.DataFrame(CHIExtraPointsSeries2018)\n",
    "CHIExtraPointsSeries2019 = extraPointsCHI2019.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo','yardlineSide','Result','gameClock',\n",
    "                                               'yardlineNumber','playResult','preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr',\n",
    "                                               'week'],as_index=True).size()\n",
    "CHIExtraPointsFrame2019 = pd.DataFrame(CHIExtraPointsSeries2019)\n",
    "CHIExtraPointsSeries2020 = extraPointsCHI2020.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo','yardlineSide','Result','gameClock',\n",
    "                                               'yardlineNumber','playResult','preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr',\n",
    "                                               'week'],as_index=True).size()\n",
    "CHIExtraPointsFrame2020 = pd.DataFrame(CHIExtraPointsSeries2020)\n",
    "\n",
    "\n",
    "# Field Goals\n",
    "CHIFiledGoalsSeries2018 = fieldGoalsCHI2018.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo',\n",
    "                                               'yardlineSide','Result','gameClock','yardlineNumber','playResult',\n",
    "                                               'preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr','week']\n",
    "                                              ,as_index=True).size()\n",
    "CHIFiledGoalsFrame2018 = pd.DataFrame(CHIFiledGoalsSeries2018)\n",
    "CHIFiledGoalsSeries2019 = fieldGoalsCHI2019.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo',\n",
    "                                               'yardlineSide','Result','gameClock','yardlineNumber','playResult',\n",
    "                                               'preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr','week']\n",
    "                                              ,as_index=True).size()\n",
    "CHIFiledGoalsFrame2019 = pd.DataFrame(CHIFiledGoalsSeries2019)\n",
    "CHIFiledGoalsSeries2020 = fieldGoalsCHI2020.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo',\n",
    "                                               'yardlineSide','Result','gameClock','yardlineNumber','playResult',\n",
    "                                               'preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr','week']\n",
    "                                              ,as_index=True).size()\n",
    "CHIFiledGoalsFrame2020 = pd.DataFrame(CHIFiledGoalsSeries2020)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "29d061f2-472e-4fb7-9045-fbc710221ab1",
   "metadata": {},
   "outputs": [],
   "source": [
    "# CIN Special Plays Data Frames\n",
    "\n",
    "# Punt Frames\n",
    "CINPuntsSeries2018 = puntsCIN2018.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo','yardlineSide','Result','gameClock',\n",
    "                                   'yardlineNumber','playResult','preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr',\n",
    "                                   'week'],as_index=True).size()\n",
    "CINPuntsFrame2018 = pd.DataFrame(CINPuntsSeries2018)\n",
    "\n",
    "CINPuntsSeries2019 = puntsCIN2019.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo','yardlineSide','Result','gameClock',\n",
    "                                           'yardlineNumber','playResult','preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr',\n",
    "                                           'week'],as_index=True).size()\n",
    "CINPuntsFrame2019 = pd.DataFrame(CINPuntsSeries2019)\n",
    "\n",
    "CINPuntsSeries2020 = puntsCIN2020.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo','yardlineSide','Result','gameClock',\n",
    "                                           'yardlineNumber','playResult','preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr',\n",
    "                                           'week'],as_index=True).size()\n",
    "CINPuntsFrame2020 = pd.DataFrame(CINPuntsSeries2020)\n",
    "\n",
    "\n",
    "# Kickoff Frames\n",
    "CINKickoffsSeries2018 = kickoffsCIN2018.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo','yardlineSide','Result','gameClock',\n",
    "                                                 'yardlineNumber','playResult','preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr',\n",
    "                                                 'visitorTeamAbbr','week'],as_index=True).size()\n",
    "CINKickoffsFrame2018 = pd.DataFrame(CINKickoffsSeries2018)\n",
    "\n",
    "CINKickoffsSeries2019 = kickoffsCIN2019.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo','yardlineSide','Result','gameClock',\n",
    "                                                 'yardlineNumber','playResult','preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr',\n",
    "                                                 'visitorTeamAbbr','week'],as_index=True).size()\n",
    "CINKickoffsFrame2019 = pd.DataFrame(CINKickoffsSeries2019)\n",
    "\n",
    "CINKickoffsSeries2020 = kickoffsCIN2020.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo','yardlineSide','Result','gameClock',\n",
    "                                                 'yardlineNumber','playResult','preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr',\n",
    "                                                 'visitorTeamAbbr','week'],as_index=True).size()\n",
    "CINKickoffsFrame2020 = pd.DataFrame(CINKickoffsSeries2020)\n",
    "\n",
    "\n",
    "# Extra Points\n",
    "CINExtraPointsSeries2018 = extraPointsCIN2018.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo','yardlineSide','Result','gameClock',\n",
    "                                               'yardlineNumber','playResult','preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr',\n",
    "                                               'week'],as_index=True).size()\n",
    "CINExtraPointsFrame2018 = pd.DataFrame(CINExtraPointsSeries2018)\n",
    "CINExtraPointsSeries2019 = extraPointsCIN2019.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo','yardlineSide','Result','gameClock',\n",
    "                                               'yardlineNumber','playResult','preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr',\n",
    "                                               'week'],as_index=True).size()\n",
    "CINExtraPointsFrame2019 = pd.DataFrame(CINExtraPointsSeries2019)\n",
    "CINExtraPointsSeries2020 = extraPointsCIN2020.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo','yardlineSide','Result','gameClock',\n",
    "                                               'yardlineNumber','playResult','preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr',\n",
    "                                               'week'],as_index=True).size()\n",
    "CINExtraPointsFrame2020 = pd.DataFrame(CINExtraPointsSeries2020)\n",
    "\n",
    "\n",
    "# Field Goals\n",
    "CINFiledGoalsSeries2018 = fieldGoalsCIN2018.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo',\n",
    "                                               'yardlineSide','Result','gameClock','yardlineNumber','playResult',\n",
    "                                               'preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr','week']\n",
    "                                              ,as_index=True).size()\n",
    "CINFiledGoalsFrame2018 = pd.DataFrame(CINFiledGoalsSeries2018)\n",
    "CINFiledGoalsSeries2019 = fieldGoalsCIN2019.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo',\n",
    "                                               'yardlineSide','Result','gameClock','yardlineNumber','playResult',\n",
    "                                               'preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr','week']\n",
    "                                              ,as_index=True).size()\n",
    "CINFiledGoalsFrame2019 = pd.DataFrame(CINFiledGoalsSeries2019)\n",
    "CINFiledGoalsSeries2020 = fieldGoalsCIN2020.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo',\n",
    "                                               'yardlineSide','Result','gameClock','yardlineNumber','playResult',\n",
    "                                               'preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr','week']\n",
    "                                              ,as_index=True).size()\n",
    "CINFiledGoalsFrame2020 = pd.DataFrame(CINFiledGoalsSeries2020)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "da21273d-836d-4fa4-a6f7-d76958356eff",
   "metadata": {},
   "outputs": [],
   "source": [
    "# CLE Special Plays Data Frames\n",
    "\n",
    "# Punt Frames\n",
    "CLEPuntsSeries2018 = puntsCLE2018.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo','yardlineSide','Result','gameClock',\n",
    "                                   'yardlineNumber','playResult','preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr',\n",
    "                                   'week'],as_index=True).size()\n",
    "CLEPuntsFrame2018 = pd.DataFrame(CLEPuntsSeries2018)\n",
    "\n",
    "CLEPuntsSeries2019 = puntsCLE2019.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo','yardlineSide','Result','gameClock',\n",
    "                                           'yardlineNumber','playResult','preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr',\n",
    "                                           'week'],as_index=True).size()\n",
    "CLEPuntsFrame2019 = pd.DataFrame(CLEPuntsSeries2019)\n",
    "\n",
    "CLEPuntsSeries2020 = puntsCLE2020.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo','yardlineSide','Result','gameClock',\n",
    "                                           'yardlineNumber','playResult','preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr',\n",
    "                                           'week'],as_index=True).size()\n",
    "CLEPuntsFrame2020 = pd.DataFrame(CLEPuntsSeries2020)\n",
    "\n",
    "\n",
    "# Kickoff Frames\n",
    "CLEKickoffsSeries2018 = kickoffsCLE2018.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo','yardlineSide','Result','gameClock',\n",
    "                                                 'yardlineNumber','playResult','preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr',\n",
    "                                                 'visitorTeamAbbr','week'],as_index=True).size()\n",
    "CLEKickoffsFrame2018 = pd.DataFrame(CLEKickoffsSeries2018)\n",
    "\n",
    "CLEKickoffsSeries2019 = kickoffsCLE2019.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo','yardlineSide','Result','gameClock',\n",
    "                                                 'yardlineNumber','playResult','preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr',\n",
    "                                                 'visitorTeamAbbr','week'],as_index=True).size()\n",
    "CLEKickoffsFrame2019 = pd.DataFrame(CLEKickoffsSeries2019)\n",
    "\n",
    "CLEKickoffsSeries2020 = kickoffsCLE2020.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo','yardlineSide','Result','gameClock',\n",
    "                                                 'yardlineNumber','playResult','preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr',\n",
    "                                                 'visitorTeamAbbr','week'],as_index=True).size()\n",
    "CLEKickoffsFrame2020 = pd.DataFrame(CLEKickoffsSeries2020)\n",
    "\n",
    "\n",
    "# Extra Points\n",
    "CLEExtraPointsSeries2018 = extraPointsCLE2018.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo','yardlineSide','Result','gameClock',\n",
    "                                               'yardlineNumber','playResult','preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr',\n",
    "                                               'week'],as_index=True).size()\n",
    "CLEExtraPointsFrame2018 = pd.DataFrame(CLEExtraPointsSeries2018)\n",
    "CLEExtraPointsSeries2019 = extraPointsCLE2019.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo','yardlineSide','Result','gameClock',\n",
    "                                               'yardlineNumber','playResult','preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr',\n",
    "                                               'week'],as_index=True).size()\n",
    "CLEExtraPointsFrame2019 = pd.DataFrame(CLEExtraPointsSeries2019)\n",
    "CLEExtraPointsSeries2020 = extraPointsCLE2020.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo','yardlineSide','Result','gameClock',\n",
    "                                               'yardlineNumber','playResult','preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr',\n",
    "                                               'week'],as_index=True).size()\n",
    "CLEExtraPointsFrame2020 = pd.DataFrame(CLEExtraPointsSeries2020)\n",
    "\n",
    "\n",
    "# Field Goals\n",
    "CLEFiledGoalsSeries2018 = fieldGoalsCLE2018.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo',\n",
    "                                               'yardlineSide','Result','gameClock','yardlineNumber','playResult',\n",
    "                                               'preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr','week']\n",
    "                                              ,as_index=True).size()\n",
    "CLEFiledGoalsFrame2018 = pd.DataFrame(CLEFiledGoalsSeries2018)\n",
    "CLEFiledGoalsSeries2019 = fieldGoalsCLE2019.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo',\n",
    "                                               'yardlineSide','Result','gameClock','yardlineNumber','playResult',\n",
    "                                               'preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr','week']\n",
    "                                              ,as_index=True).size()\n",
    "CLEFiledGoalsFrame2019 = pd.DataFrame(CLEFiledGoalsSeries2019)\n",
    "CLEFiledGoalsSeries2020 = fieldGoalsCLE2020.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo',\n",
    "                                               'yardlineSide','Result','gameClock','yardlineNumber','playResult',\n",
    "                                               'preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr','week']\n",
    "                                              ,as_index=True).size()\n",
    "CLEFiledGoalsFrame2020 = pd.DataFrame(CLEFiledGoalsSeries2020)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "bbe1a7db-0130-45ea-90d9-bf443ea009a9",
   "metadata": {},
   "outputs": [],
   "source": [
    "# DAL Special Plays Data Frames\n",
    "\n",
    "# Punt Frames\n",
    "DALPuntsSeries2018 = puntsDAL2018.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo','yardlineSide','Result','gameClock',\n",
    "                                   'yardlineNumber','playResult','preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr',\n",
    "                                   'week'],as_index=True).size()\n",
    "DALPuntsFrame2018 = pd.DataFrame(DALPuntsSeries2018)\n",
    "\n",
    "DALPuntsSeries2019 = puntsDAL2019.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo','yardlineSide','Result','gameClock',\n",
    "                                           'yardlineNumber','playResult','preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr',\n",
    "                                           'week'],as_index=True).size()\n",
    "DALPuntsFrame2019 = pd.DataFrame(DALPuntsSeries2019)\n",
    "\n",
    "DALPuntsSeries2020 = puntsDAL2020.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo','yardlineSide','Result','gameClock',\n",
    "                                           'yardlineNumber','playResult','preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr',\n",
    "                                           'week'],as_index=True).size()\n",
    "DALPuntsFrame2020 = pd.DataFrame(DALPuntsSeries2020)\n",
    "\n",
    "\n",
    "# Kickoff Frames\n",
    "DALKickoffsSeries2018 = kickoffsDAL2018.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo','yardlineSide','Result','gameClock',\n",
    "                                                 'yardlineNumber','playResult','preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr',\n",
    "                                                 'visitorTeamAbbr','week'],as_index=True).size()\n",
    "DALKickoffsFrame2018 = pd.DataFrame(DALKickoffsSeries2018)\n",
    "\n",
    "DALKickoffsSeries2019 = kickoffsDAL2019.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo','yardlineSide','Result','gameClock',\n",
    "                                                 'yardlineNumber','playResult','preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr',\n",
    "                                                 'visitorTeamAbbr','week'],as_index=True).size()\n",
    "DALKickoffsFrame2019 = pd.DataFrame(DALKickoffsSeries2019)\n",
    "\n",
    "DALKickoffsSeries2020 = kickoffsDAL2020.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo','yardlineSide','Result','gameClock',\n",
    "                                                 'yardlineNumber','playResult','preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr',\n",
    "                                                 'visitorTeamAbbr','week'],as_index=True).size()\n",
    "DALKickoffsFrame2020 = pd.DataFrame(DALKickoffsSeries2020)\n",
    "\n",
    "\n",
    "# Extra Points\n",
    "DALExtraPointsSeries2018 = extraPointsDAL2018.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo','yardlineSide','Result','gameClock',\n",
    "                                               'yardlineNumber','playResult','preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr',\n",
    "                                               'week'],as_index=True).size()\n",
    "DALExtraPointsFrame2018 = pd.DataFrame(DALExtraPointsSeries2018)\n",
    "DALExtraPointsSeries2019 = extraPointsDAL2019.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo','yardlineSide','Result','gameClock',\n",
    "                                               'yardlineNumber','playResult','preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr',\n",
    "                                               'week'],as_index=True).size()\n",
    "DALExtraPointsFrame2019 = pd.DataFrame(DALExtraPointsSeries2019)\n",
    "DALExtraPointsSeries2020 = extraPointsDAL2020.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo','yardlineSide','Result','gameClock',\n",
    "                                               'yardlineNumber','playResult','preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr',\n",
    "                                               'week'],as_index=True).size()\n",
    "DALExtraPointsFrame2020 = pd.DataFrame(DALExtraPointsSeries2020)\n",
    "\n",
    "\n",
    "# Field Goals\n",
    "DALFiledGoalsSeries2018 = fieldGoalsDAL2018.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo',\n",
    "                                               'yardlineSide','Result','gameClock','yardlineNumber','playResult',\n",
    "                                               'preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr','week']\n",
    "                                              ,as_index=True).size()\n",
    "DALFiledGoalsFrame2018 = pd.DataFrame(DALFiledGoalsSeries2018)\n",
    "DALFiledGoalsSeries2019 = fieldGoalsDAL2019.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo',\n",
    "                                               'yardlineSide','Result','gameClock','yardlineNumber','playResult',\n",
    "                                               'preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr','week']\n",
    "                                              ,as_index=True).size()\n",
    "DALFiledGoalsFrame2019 = pd.DataFrame(DALFiledGoalsSeries2019)\n",
    "DALFiledGoalsSeries2020 = fieldGoalsDAL2020.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo',\n",
    "                                               'yardlineSide','Result','gameClock','yardlineNumber','playResult',\n",
    "                                               'preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr','week']\n",
    "                                              ,as_index=True).size()\n",
    "DALFiledGoalsFrame2020 = pd.DataFrame(DALFiledGoalsSeries2020)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "69c4189a-1f0a-4275-a33e-861b026b59f5",
   "metadata": {},
   "outputs": [],
   "source": [
    "# DEN Special Plays Data Frames\n",
    "\n",
    "# Punt Frames\n",
    "DENPuntsSeries2018 = puntsDEN2018.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo','yardlineSide','Result','gameClock',\n",
    "                                   'yardlineNumber','playResult','preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr',\n",
    "                                   'week'],as_index=True).size()\n",
    "DENPuntsFrame2018 = pd.DataFrame(DENPuntsSeries2018)\n",
    "\n",
    "DENPuntsSeries2019 = puntsDEN2019.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo','yardlineSide','Result','gameClock',\n",
    "                                           'yardlineNumber','playResult','preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr',\n",
    "                                           'week'],as_index=True).size()\n",
    "DENPuntsFrame2019 = pd.DataFrame(DENPuntsSeries2019)\n",
    "\n",
    "DENPuntsSeries2020 = puntsDEN2020.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo','yardlineSide','Result','gameClock',\n",
    "                                           'yardlineNumber','playResult','preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr',\n",
    "                                           'week'],as_index=True).size()\n",
    "DENPuntsFrame2020 = pd.DataFrame(DENPuntsSeries2020)\n",
    "\n",
    "\n",
    "# Kickoff Frames\n",
    "DENKickoffsSeries2018 = kickoffsDEN2018.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo','yardlineSide','Result','gameClock',\n",
    "                                                 'yardlineNumber','playResult','preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr',\n",
    "                                                 'visitorTeamAbbr','week'],as_index=True).size()\n",
    "DENKickoffsFrame2018 = pd.DataFrame(DENKickoffsSeries2018)\n",
    "\n",
    "DENKickoffsSeries2019 = kickoffsDEN2019.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo','yardlineSide','Result','gameClock',\n",
    "                                                 'yardlineNumber','playResult','preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr',\n",
    "                                                 'visitorTeamAbbr','week'],as_index=True).size()\n",
    "DENKickoffsFrame2019 = pd.DataFrame(DENKickoffsSeries2019)\n",
    "\n",
    "DENKickoffsSeries2020 = kickoffsDEN2020.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo','yardlineSide','Result','gameClock',\n",
    "                                                 'yardlineNumber','playResult','preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr',\n",
    "                                                 'visitorTeamAbbr','week'],as_index=True).size()\n",
    "DENKickoffsFrame2020 = pd.DataFrame(DENKickoffsSeries2020)\n",
    "\n",
    "\n",
    "# Extra Points\n",
    "DENExtraPointsSeries2018 = extraPointsDEN2018.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo','yardlineSide','Result','gameClock',\n",
    "                                               'yardlineNumber','playResult','preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr',\n",
    "                                               'week'],as_index=True).size()\n",
    "DENExtraPointsFrame2018 = pd.DataFrame(DENExtraPointsSeries2018)\n",
    "DENExtraPointsSeries2019 = extraPointsDEN2019.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo','yardlineSide','Result','gameClock',\n",
    "                                               'yardlineNumber','playResult','preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr',\n",
    "                                               'week'],as_index=True).size()\n",
    "DENExtraPointsFrame2019 = pd.DataFrame(DENExtraPointsSeries2019)\n",
    "DENExtraPointsSeries2020 = extraPointsDEN2020.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo','yardlineSide','Result','gameClock',\n",
    "                                               'yardlineNumber','playResult','preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr',\n",
    "                                               'week'],as_index=True).size()\n",
    "DENExtraPointsFrame2020 = pd.DataFrame(DENExtraPointsSeries2020)\n",
    "\n",
    "\n",
    "# Field Goals\n",
    "DENFiledGoalsSeries2018 = fieldGoalsDEN2018.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo',\n",
    "                                               'yardlineSide','Result','gameClock','yardlineNumber','playResult',\n",
    "                                               'preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr','week']\n",
    "                                              ,as_index=True).size()\n",
    "DENFiledGoalsFrame2018 = pd.DataFrame(DENFiledGoalsSeries2018)\n",
    "DENFiledGoalsSeries2019 = fieldGoalsDEN2019.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo',\n",
    "                                               'yardlineSide','Result','gameClock','yardlineNumber','playResult',\n",
    "                                               'preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr','week']\n",
    "                                              ,as_index=True).size()\n",
    "DENFiledGoalsFrame2019 = pd.DataFrame(DENFiledGoalsSeries2019)\n",
    "DENFiledGoalsSeries2020 = fieldGoalsDEN2020.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo',\n",
    "                                               'yardlineSide','Result','gameClock','yardlineNumber','playResult',\n",
    "                                               'preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr','week']\n",
    "                                              ,as_index=True).size()\n",
    "DENFiledGoalsFrame2020 = pd.DataFrame(DENFiledGoalsSeries2020)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "ed8d00d3-87a8-4806-bb62-5448ce412cab",
   "metadata": {},
   "outputs": [],
   "source": [
    "# DET Special Plays Data Frames\n",
    "\n",
    "# Punt Frames\n",
    "DETPuntsSeries2018 = puntsDET2018.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo','yardlineSide','Result','gameClock',\n",
    "                                   'yardlineNumber','playResult','preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr',\n",
    "                                   'week'],as_index=True).size()\n",
    "DETPuntsFrame2018 = pd.DataFrame(DETPuntsSeries2018)\n",
    "\n",
    "DETPuntsSeries2019 = puntsDET2019.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo','yardlineSide','Result','gameClock',\n",
    "                                           'yardlineNumber','playResult','preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr',\n",
    "                                           'week'],as_index=True).size()\n",
    "DETPuntsFrame2019 = pd.DataFrame(DETPuntsSeries2019)\n",
    "\n",
    "DETPuntsSeries2020 = puntsDET2020.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo','yardlineSide','Result','gameClock',\n",
    "                                           'yardlineNumber','playResult','preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr',\n",
    "                                           'week'],as_index=True).size()\n",
    "DETPuntsFrame2020 = pd.DataFrame(DETPuntsSeries2020)\n",
    "\n",
    "\n",
    "# Kickoff Frames\n",
    "DETKickoffsSeries2018 = kickoffsDET2018.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo','yardlineSide','Result','gameClock',\n",
    "                                                 'yardlineNumber','playResult','preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr',\n",
    "                                                 'visitorTeamAbbr','week'],as_index=True).size()\n",
    "DETKickoffsFrame2018 = pd.DataFrame(DETKickoffsSeries2018)\n",
    "\n",
    "DETKickoffsSeries2019 = kickoffsDET2019.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo','yardlineSide','Result','gameClock',\n",
    "                                                 'yardlineNumber','playResult','preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr',\n",
    "                                                 'visitorTeamAbbr','week'],as_index=True).size()\n",
    "DETKickoffsFrame2019 = pd.DataFrame(DETKickoffsSeries2019)\n",
    "\n",
    "DETKickoffsSeries2020 = kickoffsDET2020.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo','yardlineSide','Result','gameClock',\n",
    "                                                 'yardlineNumber','playResult','preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr',\n",
    "                                                 'visitorTeamAbbr','week'],as_index=True).size()\n",
    "DETKickoffsFrame2020 = pd.DataFrame(DETKickoffsSeries2020)\n",
    "\n",
    "\n",
    "# Extra Points\n",
    "DETExtraPointsSeries2018 = extraPointsDET2018.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo','yardlineSide','Result','gameClock',\n",
    "                                               'yardlineNumber','playResult','preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr',\n",
    "                                               'week'],as_index=True).size()\n",
    "DETExtraPointsFrame2018 = pd.DataFrame(DETExtraPointsSeries2018)\n",
    "DETExtraPointsSeries2019 = extraPointsDET2019.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo','yardlineSide','Result','gameClock',\n",
    "                                               'yardlineNumber','playResult','preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr',\n",
    "                                               'week'],as_index=True).size()\n",
    "DETExtraPointsFrame2019 = pd.DataFrame(DETExtraPointsSeries2019)\n",
    "DETExtraPointsSeries2020 = extraPointsDET2020.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo','yardlineSide','Result','gameClock',\n",
    "                                               'yardlineNumber','playResult','preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr',\n",
    "                                               'week'],as_index=True).size()\n",
    "DETExtraPointsFrame2020 = pd.DataFrame(DETExtraPointsSeries2020)\n",
    "\n",
    "\n",
    "# Field Goals\n",
    "DETFiledGoalsSeries2018 = fieldGoalsDET2018.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo',\n",
    "                                               'yardlineSide','Result','gameClock','yardlineNumber','playResult',\n",
    "                                               'preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr','week']\n",
    "                                              ,as_index=True).size()\n",
    "DETFiledGoalsFrame2018 = pd.DataFrame(DETFiledGoalsSeries2018)\n",
    "DETFiledGoalsSeries2019 = fieldGoalsDET2019.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo',\n",
    "                                               'yardlineSide','Result','gameClock','yardlineNumber','playResult',\n",
    "                                               'preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr','week']\n",
    "                                              ,as_index=True).size()\n",
    "DETFiledGoalsFrame2019 = pd.DataFrame(DETFiledGoalsSeries2019)\n",
    "DETFiledGoalsSeries2020 = fieldGoalsDET2020.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo',\n",
    "                                               'yardlineSide','Result','gameClock','yardlineNumber','playResult',\n",
    "                                               'preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr','week']\n",
    "                                              ,as_index=True).size()\n",
    "DETFiledGoalsFrame2020 = pd.DataFrame(DETFiledGoalsSeries2020)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "e180ae9e-a94f-4c71-bf06-926e670449c4",
   "metadata": {},
   "outputs": [],
   "source": [
    "# GB Special Plays Data Frames\n",
    "\n",
    "# Punt Frames\n",
    "GBPuntsSeries2018 = puntsGB2018.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo','yardlineSide','Result','gameClock',\n",
    "                                   'yardlineNumber','playResult','preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr',\n",
    "                                   'week'],as_index=True).size()\n",
    "GBPuntsFrame2018 = pd.DataFrame(GBPuntsSeries2018)\n",
    "\n",
    "GBPuntsSeries2019 = puntsGB2019.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo','yardlineSide','Result','gameClock',\n",
    "                                           'yardlineNumber','playResult','preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr',\n",
    "                                           'week'],as_index=True).size()\n",
    "GBPuntsFrame2019 = pd.DataFrame(GBPuntsSeries2019)\n",
    "\n",
    "GBPuntsSeries2020 = puntsGB2020.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo','yardlineSide','Result','gameClock',\n",
    "                                           'yardlineNumber','playResult','preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr',\n",
    "                                           'week'],as_index=True).size()\n",
    "GBPuntsFrame2020 = pd.DataFrame(GBPuntsSeries2020)\n",
    "\n",
    "\n",
    "# Kickoff Frames\n",
    "GBKickoffsSeries2018 = kickoffsGB2018.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo','yardlineSide','Result','gameClock',\n",
    "                                                 'yardlineNumber','playResult','preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr',\n",
    "                                                 'visitorTeamAbbr','week'],as_index=True).size()\n",
    "GBKickoffsFrame2018 = pd.DataFrame(GBKickoffsSeries2018)\n",
    "\n",
    "GBKickoffsSeries2019 = kickoffsGB2019.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo','yardlineSide','Result','gameClock',\n",
    "                                                 'yardlineNumber','playResult','preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr',\n",
    "                                                 'visitorTeamAbbr','week'],as_index=True).size()\n",
    "GBKickoffsFrame2019 = pd.DataFrame(GBKickoffsSeries2019)\n",
    "\n",
    "GBKickoffsSeries2020 = kickoffsGB2020.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo','yardlineSide','Result','gameClock',\n",
    "                                                 'yardlineNumber','playResult','preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr',\n",
    "                                                 'visitorTeamAbbr','week'],as_index=True).size()\n",
    "GBKickoffsFrame2020 = pd.DataFrame(GBKickoffsSeries2020)\n",
    "\n",
    "\n",
    "# Extra Points\n",
    "GBExtraPointsSeries2018 = extraPointsGB2018.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo','yardlineSide','Result','gameClock',\n",
    "                                               'yardlineNumber','playResult','preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr',\n",
    "                                               'week'],as_index=True).size()\n",
    "GBExtraPointsFrame2018 = pd.DataFrame(GBExtraPointsSeries2018)\n",
    "GBExtraPointsSeries2019 = extraPointsGB2019.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo','yardlineSide','Result','gameClock',\n",
    "                                               'yardlineNumber','playResult','preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr',\n",
    "                                               'week'],as_index=True).size()\n",
    "GBExtraPointsFrame2019 = pd.DataFrame(GBExtraPointsSeries2019)\n",
    "GBExtraPointsSeries2020 = extraPointsGB2020.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo','yardlineSide','Result','gameClock',\n",
    "                                               'yardlineNumber','playResult','preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr',\n",
    "                                               'week'],as_index=True).size()\n",
    "GBExtraPointsFrame2020 = pd.DataFrame(GBExtraPointsSeries2020)\n",
    "\n",
    "\n",
    "# Field Goals\n",
    "GBFiledGoalsSeries2018 = fieldGoalsGB2018.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo',\n",
    "                                               'yardlineSide','Result','gameClock','yardlineNumber','playResult',\n",
    "                                               'preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr','week']\n",
    "                                              ,as_index=True).size()\n",
    "GBFiledGoalsFrame2018 = pd.DataFrame(GBFiledGoalsSeries2018)\n",
    "GBFiledGoalsSeries2019 = fieldGoalsGB2019.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo',\n",
    "                                               'yardlineSide','Result','gameClock','yardlineNumber','playResult',\n",
    "                                               'preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr','week']\n",
    "                                              ,as_index=True).size()\n",
    "GBFiledGoalsFrame2019 = pd.DataFrame(GBFiledGoalsSeries2019)\n",
    "GBFiledGoalsSeries2020 = fieldGoalsGB2020.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo',\n",
    "                                               'yardlineSide','Result','gameClock','yardlineNumber','playResult',\n",
    "                                               'preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr','week']\n",
    "                                              ,as_index=True).size()\n",
    "GBFiledGoalsFrame2020 = pd.DataFrame(GBFiledGoalsSeries2020)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "65bf9296-837f-4b10-a6c9-c99ccceabffe",
   "metadata": {},
   "outputs": [],
   "source": [
    "# HOU Special Plays Data Frames\n",
    "\n",
    "# Punt Frames\n",
    "HOUPuntsSeries2018 = puntsHOU2018.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo','yardlineSide','Result','gameClock',\n",
    "                                   'yardlineNumber','playResult','preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr',\n",
    "                                   'week'],as_index=True).size()\n",
    "HOUPuntsFrame2018 = pd.DataFrame(HOUPuntsSeries2018)\n",
    "\n",
    "HOUPuntsSeries2019 = puntsHOU2019.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo','yardlineSide','Result','gameClock',\n",
    "                                           'yardlineNumber','playResult','preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr',\n",
    "                                           'week'],as_index=True).size()\n",
    "HOUPuntsFrame2019 = pd.DataFrame(HOUPuntsSeries2019)\n",
    "\n",
    "HOUPuntsSeries2020 = puntsHOU2020.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo','yardlineSide','Result','gameClock',\n",
    "                                           'yardlineNumber','playResult','preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr',\n",
    "                                           'week'],as_index=True).size()\n",
    "HOUPuntsFrame2020 = pd.DataFrame(HOUPuntsSeries2020)\n",
    "\n",
    "\n",
    "# Kickoff Frames\n",
    "HOUKickoffsSeries2018 = kickoffsHOU2018.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo','yardlineSide','Result','gameClock',\n",
    "                                                 'yardlineNumber','playResult','preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr',\n",
    "                                                 'visitorTeamAbbr','week'],as_index=True).size()\n",
    "HOUKickoffsFrame2018 = pd.DataFrame(HOUKickoffsSeries2018)\n",
    "\n",
    "HOUKickoffsSeries2019 = kickoffsHOU2019.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo','yardlineSide','Result','gameClock',\n",
    "                                                 'yardlineNumber','playResult','preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr',\n",
    "                                                 'visitorTeamAbbr','week'],as_index=True).size()\n",
    "HOUKickoffsFrame2019 = pd.DataFrame(HOUKickoffsSeries2019)\n",
    "\n",
    "HOUKickoffsSeries2020 = kickoffsHOU2020.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo','yardlineSide','Result','gameClock',\n",
    "                                                 'yardlineNumber','playResult','preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr',\n",
    "                                                 'visitorTeamAbbr','week'],as_index=True).size()\n",
    "HOUKickoffsFrame2020 = pd.DataFrame(HOUKickoffsSeries2020)\n",
    "\n",
    "\n",
    "# Extra Points\n",
    "HOUExtraPointsSeries2018 = extraPointsHOU2018.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo','yardlineSide','Result','gameClock',\n",
    "                                               'yardlineNumber','playResult','preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr',\n",
    "                                               'week'],as_index=True).size()\n",
    "HOUExtraPointsFrame2018 = pd.DataFrame(HOUExtraPointsSeries2018)\n",
    "HOUExtraPointsSeries2019 = extraPointsHOU2019.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo','yardlineSide','Result','gameClock',\n",
    "                                               'yardlineNumber','playResult','preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr',\n",
    "                                               'week'],as_index=True).size()\n",
    "HOUExtraPointsFrame2019 = pd.DataFrame(HOUExtraPointsSeries2019)\n",
    "HOUExtraPointsSeries2020 = extraPointsHOU2020.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo','yardlineSide','Result','gameClock',\n",
    "                                               'yardlineNumber','playResult','preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr',\n",
    "                                               'week'],as_index=True).size()\n",
    "HOUExtraPointsFrame2020 = pd.DataFrame(HOUExtraPointsSeries2020)\n",
    "\n",
    "\n",
    "# Field Goals\n",
    "HOUFiledGoalsSeries2018 = fieldGoalsHOU2018.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo',\n",
    "                                               'yardlineSide','Result','gameClock','yardlineNumber','playResult',\n",
    "                                               'preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr','week']\n",
    "                                              ,as_index=True).size()\n",
    "HOUFiledGoalsFrame2018 = pd.DataFrame(HOUFiledGoalsSeries2018)\n",
    "HOUFiledGoalsSeries2019 = fieldGoalsHOU2019.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo',\n",
    "                                               'yardlineSide','Result','gameClock','yardlineNumber','playResult',\n",
    "                                               'preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr','week']\n",
    "                                              ,as_index=True).size()\n",
    "HOUFiledGoalsFrame2019 = pd.DataFrame(HOUFiledGoalsSeries2019)\n",
    "HOUFiledGoalsSeries2020 = fieldGoalsHOU2020.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo',\n",
    "                                               'yardlineSide','Result','gameClock','yardlineNumber','playResult',\n",
    "                                               'preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr','week']\n",
    "                                              ,as_index=True).size()\n",
    "HOUFiledGoalsFrame2020 = pd.DataFrame(HOUFiledGoalsSeries2020)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "de3fe789-53bc-466c-8a21-1b59c1bbc4c0",
   "metadata": {},
   "outputs": [],
   "source": [
    "# IND Special Plays Data Frames\n",
    "\n",
    "# Punt Frames\n",
    "INDPuntsSeries2018 = puntsIND2018.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo','yardlineSide','Result','gameClock',\n",
    "                                   'yardlineNumber','playResult','preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr',\n",
    "                                   'week'],as_index=True).size()\n",
    "INDPuntsFrame2018 = pd.DataFrame(INDPuntsSeries2018)\n",
    "\n",
    "INDPuntsSeries2019 = puntsIND2019.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo','yardlineSide','Result','gameClock',\n",
    "                                           'yardlineNumber','playResult','preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr',\n",
    "                                           'week'],as_index=True).size()\n",
    "INDPuntsFrame2019 = pd.DataFrame(INDPuntsSeries2019)\n",
    "\n",
    "INDPuntsSeries2020 = puntsIND2020.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo','yardlineSide','Result','gameClock',\n",
    "                                           'yardlineNumber','playResult','preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr',\n",
    "                                           'week'],as_index=True).size()\n",
    "INDPuntsFrame2020 = pd.DataFrame(INDPuntsSeries2020)\n",
    "\n",
    "\n",
    "# Kickoff Frames\n",
    "INDKickoffsSeries2018 = kickoffsIND2018.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo','yardlineSide','Result','gameClock',\n",
    "                                                 'yardlineNumber','playResult','preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr',\n",
    "                                                 'visitorTeamAbbr','week'],as_index=True).size()\n",
    "INDKickoffsFrame2018 = pd.DataFrame(INDKickoffsSeries2018)\n",
    "\n",
    "INDKickoffsSeries2019 = kickoffsIND2019.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo','yardlineSide','Result','gameClock',\n",
    "                                                 'yardlineNumber','playResult','preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr',\n",
    "                                                 'visitorTeamAbbr','week'],as_index=True).size()\n",
    "INDKickoffsFrame2019 = pd.DataFrame(INDKickoffsSeries2019)\n",
    "\n",
    "INDKickoffsSeries2020 = kickoffsIND2020.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo','yardlineSide','Result','gameClock',\n",
    "                                                 'yardlineNumber','playResult','preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr',\n",
    "                                                 'visitorTeamAbbr','week'],as_index=True).size()\n",
    "INDKickoffsFrame2020 = pd.DataFrame(INDKickoffsSeries2020)\n",
    "\n",
    "\n",
    "# Extra Points\n",
    "INDExtraPointsSeries2018 = extraPointsIND2018.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo','yardlineSide','Result','gameClock',\n",
    "                                               'yardlineNumber','playResult','preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr',\n",
    "                                               'week'],as_index=True).size()\n",
    "INDExtraPointsFrame2018 = pd.DataFrame(INDExtraPointsSeries2018)\n",
    "INDExtraPointsSeries2019 = extraPointsIND2019.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo','yardlineSide','Result','gameClock',\n",
    "                                               'yardlineNumber','playResult','preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr',\n",
    "                                               'week'],as_index=True).size()\n",
    "INDExtraPointsFrame2019 = pd.DataFrame(INDExtraPointsSeries2019)\n",
    "INDExtraPointsSeries2020 = extraPointsIND2020.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo','yardlineSide','Result','gameClock',\n",
    "                                               'yardlineNumber','playResult','preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr',\n",
    "                                               'week'],as_index=True).size()\n",
    "INDExtraPointsFrame2020 = pd.DataFrame(INDExtraPointsSeries2020)\n",
    "\n",
    "\n",
    "# Field Goals\n",
    "INDFiledGoalsSeries2018 = fieldGoalsIND2018.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo',\n",
    "                                               'yardlineSide','Result','gameClock','yardlineNumber','playResult',\n",
    "                                               'preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr','week']\n",
    "                                              ,as_index=True).size()\n",
    "INDFiledGoalsFrame2018 = pd.DataFrame(INDFiledGoalsSeries2018)\n",
    "INDFiledGoalsSeries2019 = fieldGoalsIND2019.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo',\n",
    "                                               'yardlineSide','Result','gameClock','yardlineNumber','playResult',\n",
    "                                               'preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr','week']\n",
    "                                              ,as_index=True).size()\n",
    "INDFiledGoalsFrame2019 = pd.DataFrame(INDFiledGoalsSeries2019)\n",
    "INDFiledGoalsSeries2020 = fieldGoalsIND2020.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo',\n",
    "                                               'yardlineSide','Result','gameClock','yardlineNumber','playResult',\n",
    "                                               'preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr','week']\n",
    "                                              ,as_index=True).size()\n",
    "INDFiledGoalsFrame2020 = pd.DataFrame(INDFiledGoalsSeries2020)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "63ddde6e-4d55-4537-8711-448fbcdc0c41",
   "metadata": {},
   "outputs": [],
   "source": [
    "# JAX Special Plays Data Frames\n",
    "\n",
    "# Punt Frames\n",
    "JAXPuntsSeries2018 = puntsJAX2018.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo','yardlineSide','Result','gameClock',\n",
    "                                   'yardlineNumber','playResult','preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr',\n",
    "                                   'week'],as_index=True).size()\n",
    "JAXPuntsFrame2018 = pd.DataFrame(JAXPuntsSeries2018)\n",
    "\n",
    "JAXPuntsSeries2019 = puntsJAX2019.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo','yardlineSide','Result','gameClock',\n",
    "                                           'yardlineNumber','playResult','preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr',\n",
    "                                           'week'],as_index=True).size()\n",
    "JAXPuntsFrame2019 = pd.DataFrame(JAXPuntsSeries2019)\n",
    "\n",
    "JAXPuntsSeries2020 = puntsJAX2020.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo','yardlineSide','Result','gameClock',\n",
    "                                           'yardlineNumber','playResult','preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr',\n",
    "                                           'week'],as_index=True).size()\n",
    "JAXPuntsFrame2020 = pd.DataFrame(JAXPuntsSeries2020)\n",
    "\n",
    "\n",
    "# Kickoff Frames\n",
    "JAXKickoffsSeries2018 = kickoffsJAX2018.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo','yardlineSide','Result','gameClock',\n",
    "                                                 'yardlineNumber','playResult','preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr',\n",
    "                                                 'visitorTeamAbbr','week'],as_index=True).size()\n",
    "JAXKickoffsFrame2018 = pd.DataFrame(JAXKickoffsSeries2018)\n",
    "\n",
    "JAXKickoffsSeries2019 = kickoffsJAX2019.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo','yardlineSide','Result','gameClock',\n",
    "                                                 'yardlineNumber','playResult','preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr',\n",
    "                                                 'visitorTeamAbbr','week'],as_index=True).size()\n",
    "JAXKickoffsFrame2019 = pd.DataFrame(JAXKickoffsSeries2019)\n",
    "\n",
    "JAXKickoffsSeries2020 = kickoffsJAX2020.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo','yardlineSide','Result','gameClock',\n",
    "                                                 'yardlineNumber','playResult','preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr',\n",
    "                                                 'visitorTeamAbbr','week'],as_index=True).size()\n",
    "JAXKickoffsFrame2020 = pd.DataFrame(JAXKickoffsSeries2020)\n",
    "\n",
    "\n",
    "# Extra Points\n",
    "JAXExtraPointsSeries2018 = extraPointsJAX2018.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo','yardlineSide','Result','gameClock',\n",
    "                                               'yardlineNumber','playResult','preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr',\n",
    "                                               'week'],as_index=True).size()\n",
    "JAXExtraPointsFrame2018 = pd.DataFrame(JAXExtraPointsSeries2018)\n",
    "JAXExtraPointsSeries2019 = extraPointsJAX2019.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo','yardlineSide','Result','gameClock',\n",
    "                                               'yardlineNumber','playResult','preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr',\n",
    "                                               'week'],as_index=True).size()\n",
    "JAXExtraPointsFrame2019 = pd.DataFrame(JAXExtraPointsSeries2019)\n",
    "JAXExtraPointsSeries2020 = extraPointsJAX2020.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo','yardlineSide','Result','gameClock',\n",
    "                                               'yardlineNumber','playResult','preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr',\n",
    "                                               'week'],as_index=True).size()\n",
    "JAXExtraPointsFrame2020 = pd.DataFrame(JAXExtraPointsSeries2020)\n",
    "\n",
    "\n",
    "# Field Goals\n",
    "JAXFiledGoalsSeries2018 = fieldGoalsJAX2018.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo',\n",
    "                                               'yardlineSide','Result','gameClock','yardlineNumber','playResult',\n",
    "                                               'preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr','week']\n",
    "                                              ,as_index=True).size()\n",
    "JAXFiledGoalsFrame2018 = pd.DataFrame(JAXFiledGoalsSeries2018)\n",
    "JAXFiledGoalsSeries2019 = fieldGoalsJAX2019.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo',\n",
    "                                               'yardlineSide','Result','gameClock','yardlineNumber','playResult',\n",
    "                                               'preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr','week']\n",
    "                                              ,as_index=True).size()\n",
    "JAXFiledGoalsFrame2019 = pd.DataFrame(JAXFiledGoalsSeries2019)\n",
    "JAXFiledGoalsSeries2020 = fieldGoalsJAX2020.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo',\n",
    "                                               'yardlineSide','Result','gameClock','yardlineNumber','playResult',\n",
    "                                               'preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr','week']\n",
    "                                              ,as_index=True).size()\n",
    "JAXFiledGoalsFrame2020 = pd.DataFrame(JAXFiledGoalsSeries2020)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "5a588f61-aaf7-416b-99a5-f2e64c70cbcb",
   "metadata": {},
   "outputs": [],
   "source": [
    "# KC Special Plays Data Frames\n",
    "\n",
    "# Punt Frames\n",
    "KCPuntsSeries2018 = puntsKC2018.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo','yardlineSide','Result','gameClock',\n",
    "                                   'yardlineNumber','playResult','preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr',\n",
    "                                   'week'],as_index=True).size()\n",
    "KCPuntsFrame2018 = pd.DataFrame(KCPuntsSeries2018)\n",
    "\n",
    "KCPuntsSeries2019 = puntsKC2019.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo','yardlineSide','Result','gameClock',\n",
    "                                           'yardlineNumber','playResult','preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr',\n",
    "                                           'week'],as_index=True).size()\n",
    "KCPuntsFrame2019 = pd.DataFrame(KCPuntsSeries2019)\n",
    "\n",
    "KCPuntsSeries2020 = puntsKC2020.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo','yardlineSide','Result','gameClock',\n",
    "                                           'yardlineNumber','playResult','preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr',\n",
    "                                           'week'],as_index=True).size()\n",
    "KCPuntsFrame2020 = pd.DataFrame(KCPuntsSeries2020)\n",
    "\n",
    "\n",
    "# Kickoff Frames\n",
    "KCKickoffsSeries2018 = kickoffsKC2018.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo','yardlineSide','Result','gameClock',\n",
    "                                                 'yardlineNumber','playResult','preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr',\n",
    "                                                 'visitorTeamAbbr','week'],as_index=True).size()\n",
    "KCKickoffsFrame2018 = pd.DataFrame(KCKickoffsSeries2018)\n",
    "\n",
    "KCKickoffsSeries2019 = kickoffsKC2019.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo','yardlineSide','Result','gameClock',\n",
    "                                                 'yardlineNumber','playResult','preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr',\n",
    "                                                 'visitorTeamAbbr','week'],as_index=True).size()\n",
    "KCKickoffsFrame2019 = pd.DataFrame(KCKickoffsSeries2019)\n",
    "\n",
    "KCKickoffsSeries2020 = kickoffsKC2020.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo','yardlineSide','Result','gameClock',\n",
    "                                                 'yardlineNumber','playResult','preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr',\n",
    "                                                 'visitorTeamAbbr','week'],as_index=True).size()\n",
    "KCKickoffsFrame2020 = pd.DataFrame(KCKickoffsSeries2020)\n",
    "\n",
    "\n",
    "# Extra Points\n",
    "KCExtraPointsSeries2018 = extraPointsKC2018.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo','yardlineSide','Result','gameClock',\n",
    "                                               'yardlineNumber','playResult','preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr',\n",
    "                                               'week'],as_index=True).size()\n",
    "KCExtraPointsFrame2018 = pd.DataFrame(KCExtraPointsSeries2018)\n",
    "KCExtraPointsSeries2019 = extraPointsKC2019.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo','yardlineSide','Result','gameClock',\n",
    "                                               'yardlineNumber','playResult','preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr',\n",
    "                                               'week'],as_index=True).size()\n",
    "KCExtraPointsFrame2019 = pd.DataFrame(KCExtraPointsSeries2019)\n",
    "KCExtraPointsSeries2020 = extraPointsKC2020.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo','yardlineSide','Result','gameClock',\n",
    "                                               'yardlineNumber','playResult','preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr',\n",
    "                                               'week'],as_index=True).size()\n",
    "KCExtraPointsFrame2020 = pd.DataFrame(KCExtraPointsSeries2020)\n",
    "\n",
    "\n",
    "# Field Goals\n",
    "KCFiledGoalsSeries2018 = fieldGoalsKC2018.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo',\n",
    "                                               'yardlineSide','Result','gameClock','yardlineNumber','playResult',\n",
    "                                               'preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr','week']\n",
    "                                              ,as_index=True).size()\n",
    "KCFiledGoalsFrame2018 = pd.DataFrame(KCFiledGoalsSeries2018)\n",
    "KCFiledGoalsSeries2019 = fieldGoalsKC2019.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo',\n",
    "                                               'yardlineSide','Result','gameClock','yardlineNumber','playResult',\n",
    "                                               'preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr','week']\n",
    "                                              ,as_index=True).size()\n",
    "KCFiledGoalsFrame2019 = pd.DataFrame(KCFiledGoalsSeries2019)\n",
    "KCFiledGoalsSeries2020 = fieldGoalsKC2020.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo',\n",
    "                                               'yardlineSide','Result','gameClock','yardlineNumber','playResult',\n",
    "                                               'preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr','week']\n",
    "                                              ,as_index=True).size()\n",
    "KCFiledGoalsFrame2020 = pd.DataFrame(KCFiledGoalsSeries2020)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "8eebd4e1-c21f-4bd2-9b60-c9d8b4aac06b",
   "metadata": {},
   "outputs": [],
   "source": [
    "# LA Special Plays Data Frames\n",
    "\n",
    "# Punt Frames\n",
    "LAPuntsSeries2018 = puntsLA2018.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo','yardlineSide','Result','gameClock',\n",
    "                                   'yardlineNumber','playResult','preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr',\n",
    "                                   'week'],as_index=True).size()\n",
    "LAPuntsFrame2018 = pd.DataFrame(LAPuntsSeries2018)\n",
    "\n",
    "LAPuntsSeries2019 = puntsLA2019.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo','yardlineSide','Result','gameClock',\n",
    "                                           'yardlineNumber','playResult','preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr',\n",
    "                                           'week'],as_index=True).size()\n",
    "LAPuntsFrame2019 = pd.DataFrame(LAPuntsSeries2019)\n",
    "\n",
    "LAPuntsSeries2020 = puntsLA2020.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo','yardlineSide','Result','gameClock',\n",
    "                                           'yardlineNumber','playResult','preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr',\n",
    "                                           'week'],as_index=True).size()\n",
    "LAPuntsFrame2020 = pd.DataFrame(LAPuntsSeries2020)\n",
    "\n",
    "\n",
    "# Kickoff Frames\n",
    "LAKickoffsSeries2018 = kickoffsLA2018.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo','yardlineSide','Result','gameClock',\n",
    "                                                 'yardlineNumber','playResult','preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr',\n",
    "                                                 'visitorTeamAbbr','week'],as_index=True).size()\n",
    "LAKickoffsFrame2018 = pd.DataFrame(LAKickoffsSeries2018)\n",
    "\n",
    "LAKickoffsSeries2019 = kickoffsLA2019.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo','yardlineSide','Result','gameClock',\n",
    "                                                 'yardlineNumber','playResult','preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr',\n",
    "                                                 'visitorTeamAbbr','week'],as_index=True).size()\n",
    "LAKickoffsFrame2019 = pd.DataFrame(LAKickoffsSeries2019)\n",
    "\n",
    "LAKickoffsSeries2020 = kickoffsLA2020.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo','yardlineSide','Result','gameClock',\n",
    "                                                 'yardlineNumber','playResult','preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr',\n",
    "                                                 'visitorTeamAbbr','week'],as_index=True).size()\n",
    "LAKickoffsFrame2020 = pd.DataFrame(LAKickoffsSeries2020)\n",
    "\n",
    "\n",
    "# Extra Points\n",
    "LAExtraPointsSeries2018 = extraPointsLA2018.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo','yardlineSide','Result','gameClock',\n",
    "                                               'yardlineNumber','playResult','preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr',\n",
    "                                               'week'],as_index=True).size()\n",
    "LAExtraPointsFrame2018 = pd.DataFrame(LAExtraPointsSeries2018)\n",
    "LAExtraPointsSeries2019 = extraPointsLA2019.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo','yardlineSide','Result','gameClock',\n",
    "                                               'yardlineNumber','playResult','preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr',\n",
    "                                               'week'],as_index=True).size()\n",
    "LAExtraPointsFrame2019 = pd.DataFrame(LAExtraPointsSeries2019)\n",
    "LAExtraPointsSeries2020 = extraPointsLA2020.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo','yardlineSide','Result','gameClock',\n",
    "                                               'yardlineNumber','playResult','preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr',\n",
    "                                               'week'],as_index=True).size()\n",
    "LAExtraPointsFrame2020 = pd.DataFrame(LAExtraPointsSeries2020)\n",
    "\n",
    "\n",
    "# Field Goals\n",
    "LAFiledGoalsSeries2018 = fieldGoalsLA2018.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo',\n",
    "                                               'yardlineSide','Result','gameClock','yardlineNumber','playResult',\n",
    "                                               'preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr','week']\n",
    "                                              ,as_index=True).size()\n",
    "LAFiledGoalsFrame2018 = pd.DataFrame(LAFiledGoalsSeries2018)\n",
    "LAFiledGoalsSeries2019 = fieldGoalsLA2019.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo',\n",
    "                                               'yardlineSide','Result','gameClock','yardlineNumber','playResult',\n",
    "                                               'preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr','week']\n",
    "                                              ,as_index=True).size()\n",
    "LAFiledGoalsFrame2019 = pd.DataFrame(LAFiledGoalsSeries2019)\n",
    "LAFiledGoalsSeries2020 = fieldGoalsLA2020.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo',\n",
    "                                               'yardlineSide','Result','gameClock','yardlineNumber','playResult',\n",
    "                                               'preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr','week']\n",
    "                                              ,as_index=True).size()\n",
    "LAFiledGoalsFrame2020 = pd.DataFrame(LAFiledGoalsSeries2020)\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "077dfeda-dba0-47b5-9500-ea61a9ebe6cb",
   "metadata": {},
   "outputs": [],
   "source": [
    "# LAC Special Plays Data Frames\n",
    "\n",
    "# Punt Frames\n",
    "LACPuntsSeries2018 = puntsLAC2018.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo','yardlineSide','Result','gameClock',\n",
    "                                   'yardlineNumber','playResult','preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr',\n",
    "                                   'week'],as_index=True).size()\n",
    "LACPuntsFrame2018 = pd.DataFrame(LACPuntsSeries2018)\n",
    "\n",
    "LACPuntsSeries2019 = puntsLAC2019.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo','yardlineSide','Result','gameClock',\n",
    "                                           'yardlineNumber','playResult','preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr',\n",
    "                                           'week'],as_index=True).size()\n",
    "LACPuntsFrame2019 = pd.DataFrame(LACPuntsSeries2019)\n",
    "\n",
    "LACPuntsSeries2020 = puntsLAC2020.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo','yardlineSide','Result','gameClock',\n",
    "                                           'yardlineNumber','playResult','preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr',\n",
    "                                           'week'],as_index=True).size()\n",
    "LACPuntsFrame2020 = pd.DataFrame(LACPuntsSeries2020)\n",
    "\n",
    "\n",
    "# Kickoff Frames\n",
    "LACKickoffsSeries2018 = kickoffsLAC2018.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo','yardlineSide','Result','gameClock',\n",
    "                                                 'yardlineNumber','playResult','preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr',\n",
    "                                                 'visitorTeamAbbr','week'],as_index=True).size()\n",
    "LACKickoffsFrame2018 = pd.DataFrame(LACKickoffsSeries2018)\n",
    "\n",
    "LACKickoffsSeries2019 = kickoffsLAC2019.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo','yardlineSide','Result','gameClock',\n",
    "                                                 'yardlineNumber','playResult','preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr',\n",
    "                                                 'visitorTeamAbbr','week'],as_index=True).size()\n",
    "LACKickoffsFrame2019 = pd.DataFrame(LACKickoffsSeries2019)\n",
    "\n",
    "LACKickoffsSeries2020 = kickoffsLAC2020.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo','yardlineSide','Result','gameClock',\n",
    "                                                 'yardlineNumber','playResult','preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr',\n",
    "                                                 'visitorTeamAbbr','week'],as_index=True).size()\n",
    "LACKickoffsFrame2020 = pd.DataFrame(LACKickoffsSeries2020)\n",
    "\n",
    "\n",
    "# Extra Points\n",
    "LACExtraPointsSeries2018 = extraPointsLAC2018.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo','yardlineSide','Result','gameClock',\n",
    "                                               'yardlineNumber','playResult','preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr',\n",
    "                                               'week'],as_index=True).size()\n",
    "LACExtraPointsFrame2018 = pd.DataFrame(LACExtraPointsSeries2018)\n",
    "LACExtraPointsSeries2019 = extraPointsLAC2019.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo','yardlineSide','Result','gameClock',\n",
    "                                               'yardlineNumber','playResult','preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr',\n",
    "                                               'week'],as_index=True).size()\n",
    "LACExtraPointsFrame2019 = pd.DataFrame(LACExtraPointsSeries2019)\n",
    "LACExtraPointsSeries2020 = extraPointsLAC2020.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo','yardlineSide','Result','gameClock',\n",
    "                                               'yardlineNumber','playResult','preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr',\n",
    "                                               'week'],as_index=True).size()\n",
    "LACExtraPointsFrame2020 = pd.DataFrame(LACExtraPointsSeries2020)\n",
    "\n",
    "\n",
    "# Field Goals\n",
    "LACFiledGoalsSeries2018 = fieldGoalsLAC2018.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo',\n",
    "                                               'yardlineSide','Result','gameClock','yardlineNumber','playResult',\n",
    "                                               'preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr','week']\n",
    "                                              ,as_index=True).size()\n",
    "LACFiledGoalsFrame2018 = pd.DataFrame(LACFiledGoalsSeries2018)\n",
    "LACFiledGoalsSeries2019 = fieldGoalsLAC2019.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo',\n",
    "                                               'yardlineSide','Result','gameClock','yardlineNumber','playResult',\n",
    "                                               'preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr','week']\n",
    "                                              ,as_index=True).size()\n",
    "LACFiledGoalsFrame2019 = pd.DataFrame(LACFiledGoalsSeries2019)\n",
    "LACFiledGoalsSeries2020 = fieldGoalsLAC2020.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo',\n",
    "                                               'yardlineSide','Result','gameClock','yardlineNumber','playResult',\n",
    "                                               'preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr','week']\n",
    "                                              ,as_index=True).size()\n",
    "LACFiledGoalsFrame2020 = pd.DataFrame(LACFiledGoalsSeries2020)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "90f850f6-1e03-4612-b4d1-af999a142a41",
   "metadata": {},
   "outputs": [],
   "source": [
    "# MIA Special Plays Data Frames\n",
    "\n",
    "# Punt Frames\n",
    "MIAPuntsSeries2018 = puntsMIA2018.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo','yardlineSide','Result','gameClock',\n",
    "                                   'yardlineNumber','playResult','preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr',\n",
    "                                   'week'],as_index=True).size()\n",
    "MIAPuntsFrame2018 = pd.DataFrame(MIAPuntsSeries2018)\n",
    "\n",
    "MIAPuntsSeries2019 = puntsMIA2019.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo','yardlineSide','Result','gameClock',\n",
    "                                           'yardlineNumber','playResult','preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr',\n",
    "                                           'week'],as_index=True).size()\n",
    "MIAPuntsFrame2019 = pd.DataFrame(MIAPuntsSeries2019)\n",
    "\n",
    "MIAPuntsSeries2020 = puntsMIA2020.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo','yardlineSide','Result','gameClock',\n",
    "                                           'yardlineNumber','playResult','preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr',\n",
    "                                           'week'],as_index=True).size()\n",
    "MIAPuntsFrame2020 = pd.DataFrame(MIAPuntsSeries2020)\n",
    "\n",
    "\n",
    "# Kickoff Framesa\n",
    "MIAKickoffsSeries2018 = kickoffsMIA2018.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo','yardlineSide','Result','gameClock',\n",
    "                                                 'yardlineNumber','playResult','preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr',\n",
    "                                                 'visitorTeamAbbr','week'],as_index=True).size()\n",
    "MIAKickoffsFrame2018 = pd.DataFrame(MIAKickoffsSeries2018)\n",
    "\n",
    "MIAKickoffsSeries2019 = kickoffsMIA2019.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo','yardlineSide','Result','gameClock',\n",
    "                                                 'yardlineNumber','playResult','preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr',\n",
    "                                                 'visitorTeamAbbr','week'],as_index=True).size()\n",
    "MIAKickoffsFrame2019 = pd.DataFrame(MIAKickoffsSeries2019)\n",
    "\n",
    "MIAKickoffsSeries2020 = kickoffsMIA2020.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo','yardlineSide','Result','gameClock',\n",
    "                                                 'yardlineNumber','playResult','preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr',\n",
    "                                                 'visitorTeamAbbr','week'],as_index=True).size()\n",
    "MIAKickoffsFrame2020 = pd.DataFrame(MIAKickoffsSeries2020)\n",
    "\n",
    "\n",
    "# Extra Points\n",
    "MIAExtraPointsSeries2018 = extraPointsMIA2018.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo','yardlineSide','Result','gameClock',\n",
    "                                               'yardlineNumber','playResult','preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr',\n",
    "                                               'week'],as_index=True).size()\n",
    "MIAExtraPointsFrame2018 = pd.DataFrame(MIAExtraPointsSeries2018)\n",
    "MIAExtraPointsSeries2019 = extraPointsMIA2019.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo','yardlineSide','Result','gameClock',\n",
    "                                               'yardlineNumber','playResult','preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr',\n",
    "                                               'week'],as_index=True).size()\n",
    "MIAExtraPointsFrame2019 = pd.DataFrame(MIAExtraPointsSeries2019)\n",
    "MIAExtraPointsSeries2020 = extraPointsMIA2020.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo','yardlineSide','Result','gameClock',\n",
    "                                               'yardlineNumber','playResult','preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr',\n",
    "                                               'week'],as_index=True).size()\n",
    "MIAExtraPointsFrame2020 = pd.DataFrame(MIAExtraPointsSeries2020)\n",
    "\n",
    "\n",
    "# Field Goals\n",
    "MIAFiledGoalsSeries2018 = fieldGoalsMIA2018.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo',\n",
    "                                               'yardlineSide','Result','gameClock','yardlineNumber','playResult',\n",
    "                                               'preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr','week']\n",
    "                                              ,as_index=True).size()\n",
    "MIAFiledGoalsFrame2018 = pd.DataFrame(MIAFiledGoalsSeries2018)\n",
    "MIAFiledGoalsSeries2019 = fieldGoalsMIA2019.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo',\n",
    "                                               'yardlineSide','Result','gameClock','yardlineNumber','playResult',\n",
    "                                               'preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr','week']\n",
    "                                              ,as_index=True).size()\n",
    "MIAFiledGoalsFrame2019 = pd.DataFrame(MIAFiledGoalsSeries2019)\n",
    "MIAFiledGoalsSeries2020 = fieldGoalsMIA2020.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo',\n",
    "                                               'yardlineSide','Result','gameClock','yardlineNumber','playResult',\n",
    "                                               'preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr','week']\n",
    "                                              ,as_index=True).size()\n",
    "MIAFiledGoalsFrame2020 = pd.DataFrame(MIAFiledGoalsSeries2020)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "279bdb87-a13c-4408-a5ca-f324cf09198e",
   "metadata": {},
   "outputs": [],
   "source": [
    "# MIN Special Plays Data Frames\n",
    "\n",
    "# Punt Frames\n",
    "MINPuntsSeries2018 = puntsMIN2018.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo','yardlineSide','Result','gameClock',\n",
    "                                   'yardlineNumber','playResult','preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr',\n",
    "                                   'week'],as_index=True).size()\n",
    "MINPuntsFrame2018 = pd.DataFrame(MINPuntsSeries2018)\n",
    "\n",
    "MINPuntsSeries2019 = puntsMIN2019.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo','yardlineSide','Result','gameClock',\n",
    "                                           'yardlineNumber','playResult','preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr',\n",
    "                                           'week'],as_index=True).size()\n",
    "MINPuntsFrame2019 = pd.DataFrame(MINPuntsSeries2019)\n",
    "\n",
    "MINPuntsSeries2020 = puntsMIN2020.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo','yardlineSide','Result','gameClock',\n",
    "                                           'yardlineNumber','playResult','preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr',\n",
    "                                           'week'],as_index=True).size()\n",
    "MINPuntsFrame2020 = pd.DataFrame(MINPuntsSeries2020)\n",
    "\n",
    "\n",
    "# Kickoff Frames\n",
    "MINKickoffsSeries2018 = kickoffsMIN2018.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo','yardlineSide','Result','gameClock',\n",
    "                                                 'yardlineNumber','playResult','preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr',\n",
    "                                                 'visitorTeamAbbr','week'],as_index=True).size()\n",
    "MINKickoffsFrame2018 = pd.DataFrame(MINKickoffsSeries2018)\n",
    "\n",
    "MINKickoffsSeries2019 = kickoffsMIN2019.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo','yardlineSide','Result','gameClock',\n",
    "                                                 'yardlineNumber','playResult','preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr',\n",
    "                                                 'visitorTeamAbbr','week'],as_index=True).size()\n",
    "MINKickoffsFrame2019 = pd.DataFrame(MINKickoffsSeries2019)\n",
    "\n",
    "MINKickoffsSeries2020 = kickoffsMIN2020.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo','yardlineSide','Result','gameClock',\n",
    "                                                 'yardlineNumber','playResult','preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr',\n",
    "                                                 'visitorTeamAbbr','week'],as_index=True).size()\n",
    "MINKickoffsFrame2020 = pd.DataFrame(MINKickoffsSeries2020)\n",
    "\n",
    "\n",
    "# Extra Points\n",
    "MINExtraPointsSeries2018 = extraPointsMIN2018.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo','yardlineSide','Result','gameClock',\n",
    "                                               'yardlineNumber','playResult','preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr',\n",
    "                                               'week'],as_index=True).size()\n",
    "MINExtraPointsFrame2018 = pd.DataFrame(MINExtraPointsSeries2018)\n",
    "MINExtraPointsSeries2019 = extraPointsMIN2019.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo','yardlineSide','Result','gameClock',\n",
    "                                               'yardlineNumber','playResult','preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr',\n",
    "                                               'week'],as_index=True).size()\n",
    "MINExtraPointsFrame2019 = pd.DataFrame(MINExtraPointsSeries2019)\n",
    "MINExtraPointsSeries2020 = extraPointsMIN2020.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo','yardlineSide','Result','gameClock',\n",
    "                                               'yardlineNumber','playResult','preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr',\n",
    "                                               'week'],as_index=True).size()\n",
    "MINExtraPointsFrame2020 = pd.DataFrame(MINExtraPointsSeries2020)\n",
    "\n",
    "\n",
    "# Field Goals\n",
    "MINFiledGoalsSeries2018 = fieldGoalsMIN2018.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo',\n",
    "                                               'yardlineSide','Result','gameClock','yardlineNumber','playResult',\n",
    "                                               'preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr','week']\n",
    "                                              ,as_index=True).size()\n",
    "MINFiledGoalsFrame2018 = pd.DataFrame(MINFiledGoalsSeries2018)\n",
    "MINFiledGoalsSeries2019 = fieldGoalsMIN2019.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo',\n",
    "                                               'yardlineSide','Result','gameClock','yardlineNumber','playResult',\n",
    "                                               'preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr','week']\n",
    "                                              ,as_index=True).size()\n",
    "MINFiledGoalsFrame2019 = pd.DataFrame(MINFiledGoalsSeries2019)\n",
    "MINFiledGoalsSeries2020 = fieldGoalsMIN2020.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo',\n",
    "                                               'yardlineSide','Result','gameClock','yardlineNumber','playResult',\n",
    "                                               'preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr','week']\n",
    "                                              ,as_index=True).size()\n",
    "MINFiledGoalsFrame2020 = pd.DataFrame(MINFiledGoalsSeries2020)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "2d61ed9d-e43d-4f52-a6fe-b050af57469a",
   "metadata": {},
   "outputs": [],
   "source": [
    "# NE Special Plays Data Frames\n",
    "\n",
    "# Punt Frames\n",
    "NEPuntsSeries2018 = puntsNE2018.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo','yardlineSide','Result','gameClock',\n",
    "                                   'yardlineNumber','playResult','preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr',\n",
    "                                   'week'],as_index=True).size()\n",
    "NEPuntsFrame2018 = pd.DataFrame(NEPuntsSeries2018)\n",
    "\n",
    "NEPuntsSeries2019 = puntsNE2019.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo','yardlineSide','Result','gameClock',\n",
    "                                           'yardlineNumber','playResult','preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr',\n",
    "                                           'week'],as_index=True).size()\n",
    "NEPuntsFrame2019 = pd.DataFrame(NEPuntsSeries2019)\n",
    "\n",
    "NEPuntsSeries2020 = puntsNE2020.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo','yardlineSide','Result','gameClock',\n",
    "                                           'yardlineNumber','playResult','preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr',\n",
    "                                           'week'],as_index=True).size()\n",
    "NEPuntsFrame2020 = pd.DataFrame(NEPuntsSeries2020)\n",
    "\n",
    "\n",
    "# Kickoff Frames\n",
    "NEKickoffsSeries2018 = kickoffsNE2018.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo','yardlineSide','Result','gameClock',\n",
    "                                                 'yardlineNumber','playResult','preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr',\n",
    "                                                 'visitorTeamAbbr','week'],as_index=True).size()\n",
    "NEKickoffsFrame2018 = pd.DataFrame(NEKickoffsSeries2018)\n",
    "\n",
    "NEKickoffsSeries2019 = kickoffsNE2019.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo','yardlineSide','Result','gameClock',\n",
    "                                                 'yardlineNumber','playResult','preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr',\n",
    "                                                 'visitorTeamAbbr','week'],as_index=True).size()\n",
    "NEKickoffsFrame2019 = pd.DataFrame(NEKickoffsSeries2019)\n",
    "\n",
    "NEKickoffsSeries2020 = kickoffsNE2020.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo','yardlineSide','Result','gameClock',\n",
    "                                                 'yardlineNumber','playResult','preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr',\n",
    "                                                 'visitorTeamAbbr','week'],as_index=True).size()\n",
    "NEKickoffsFrame2020 = pd.DataFrame(NEKickoffsSeries2020)\n",
    "\n",
    "\n",
    "# Extra Points\n",
    "NEExtraPointsSeries2018 = extraPointsNE2018.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo','yardlineSide','Result','gameClock',\n",
    "                                               'yardlineNumber','playResult','preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr',\n",
    "                                               'week'],as_index=True).size()\n",
    "NEExtraPointsFrame2018 = pd.DataFrame(NEExtraPointsSeries2018)\n",
    "NEExtraPointsSeries2019 = extraPointsNE2019.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo','yardlineSide','Result','gameClock',\n",
    "                                               'yardlineNumber','playResult','preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr',\n",
    "                                               'week'],as_index=True).size()\n",
    "NEExtraPointsFrame2019 = pd.DataFrame(NEExtraPointsSeries2019)\n",
    "NEExtraPointsSeries2020 = extraPointsNE2020.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo','yardlineSide','Result','gameClock',\n",
    "                                               'yardlineNumber','playResult','preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr',\n",
    "                                               'week'],as_index=True).size()\n",
    "NEExtraPointsFrame2020 = pd.DataFrame(NEExtraPointsSeries2020)\n",
    "\n",
    "\n",
    "# Field Goals\n",
    "NEFiledGoalsSeries2018 = fieldGoalsNE2018.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo',\n",
    "                                               'yardlineSide','Result','gameClock','yardlineNumber','playResult',\n",
    "                                               'preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr','week']\n",
    "                                              ,as_index=True).size()\n",
    "NEFiledGoalsFrame2018 = pd.DataFrame(NEFiledGoalsSeries2018)\n",
    "NEFiledGoalsSeries2019 = fieldGoalsNE2019.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo',\n",
    "                                               'yardlineSide','Result','gameClock','yardlineNumber','playResult',\n",
    "                                               'preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr','week']\n",
    "                                              ,as_index=True).size()\n",
    "NEFiledGoalsFrame2019 = pd.DataFrame(NEFiledGoalsSeries2019)\n",
    "NEFiledGoalsSeries2020 = fieldGoalsNE2020.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo',\n",
    "                                               'yardlineSide','Result','gameClock','yardlineNumber','playResult',\n",
    "                                               'preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr','week']\n",
    "                                              ,as_index=True).size()\n",
    "NEFiledGoalsFrame2020 = pd.DataFrame(NEFiledGoalsSeries2020)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "31cadc4a-6037-4488-8c28-e459bb269c9f",
   "metadata": {},
   "outputs": [],
   "source": [
    "# NO Special Plays Data Frames\n",
    "\n",
    "# Punt Frames\n",
    "NOPuntsSeries2018 = puntsNO2018.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo','yardlineSide','Result','gameClock',\n",
    "                                   'yardlineNumber','playResult','preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr',\n",
    "                                   'week'],as_index=True).size()\n",
    "NOPuntsFrame2018 = pd.DataFrame(NOPuntsSeries2018)\n",
    "\n",
    "NOPuntsSeries2019 = puntsNO2019.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo','yardlineSide','Result','gameClock',\n",
    "                                           'yardlineNumber','playResult','preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr',\n",
    "                                           'week'],as_index=True).size()\n",
    "NOPuntsFrame2019 = pd.DataFrame(NOPuntsSeries2019)\n",
    "\n",
    "NOPuntsSeries2020 = puntsNO2020.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo','yardlineSide','Result','gameClock',\n",
    "                                           'yardlineNumber','playResult','preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr',\n",
    "                                           'week'],as_index=True).size()\n",
    "NOPuntsFrame2020 = pd.DataFrame(NOPuntsSeries2020)\n",
    "\n",
    "\n",
    "# Kickoff Frames\n",
    "NOKickoffsSeries2018 = kickoffsNO2018.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo','yardlineSide','Result','gameClock',\n",
    "                                                 'yardlineNumber','playResult','preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr',\n",
    "                                                 'visitorTeamAbbr','week'],as_index=True).size()\n",
    "NOKickoffsFrame2018 = pd.DataFrame(NOKickoffsSeries2018)\n",
    "\n",
    "NOKickoffsSeries2019 = kickoffsNO2019.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo','yardlineSide','Result','gameClock',\n",
    "                                                 'yardlineNumber','playResult','preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr',\n",
    "                                                 'visitorTeamAbbr','week'],as_index=True).size()\n",
    "NOKickoffsFrame2019 = pd.DataFrame(NOKickoffsSeries2019)\n",
    "\n",
    "NOKickoffsSeries2020 = kickoffsNO2020.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo','yardlineSide','Result','gameClock',\n",
    "                                                 'yardlineNumber','playResult','preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr',\n",
    "                                                 'visitorTeamAbbr','week'],as_index=True).size()\n",
    "NOKickoffsFrame2020 = pd.DataFrame(NOKickoffsSeries2020)\n",
    "\n",
    "\n",
    "# Extra Points\n",
    "NOExtraPointsSeries2018 = extraPointsNO2018.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo','yardlineSide','Result','gameClock',\n",
    "                                               'yardlineNumber','playResult','preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr',\n",
    "                                               'week'],as_index=True).size()\n",
    "NOExtraPointsFrame2018 = pd.DataFrame(NOExtraPointsSeries2018)\n",
    "NOExtraPointsSeries2019 = extraPointsNO2019.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo','yardlineSide','Result','gameClock',\n",
    "                                               'yardlineNumber','playResult','preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr',\n",
    "                                               'week'],as_index=True).size()\n",
    "NOExtraPointsFrame2019 = pd.DataFrame(NOExtraPointsSeries2019)\n",
    "NOExtraPointsSeries2020 = extraPointsNO2020.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo','yardlineSide','Result','gameClock',\n",
    "                                               'yardlineNumber','playResult','preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr',\n",
    "                                               'week'],as_index=True).size()\n",
    "NOExtraPointsFrame2020 = pd.DataFrame(NOExtraPointsSeries2020)\n",
    "\n",
    "\n",
    "# Field Goals\n",
    "NOFiledGoalsSeries2018 = fieldGoalsNO2018.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo',\n",
    "                                               'yardlineSide','Result','gameClock','yardlineNumber','playResult',\n",
    "                                               'preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr','week']\n",
    "                                              ,as_index=True).size()\n",
    "NOFiledGoalsFrame2018 = pd.DataFrame(NOFiledGoalsSeries2018)\n",
    "NOFiledGoalsSeries2019 = fieldGoalsNO2019.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo',\n",
    "                                               'yardlineSide','Result','gameClock','yardlineNumber','playResult',\n",
    "                                               'preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr','week']\n",
    "                                              ,as_index=True).size()\n",
    "NOFiledGoalsFrame2019 = pd.DataFrame(NOFiledGoalsSeries2019)\n",
    "NOFiledGoalsSeries2020 = fieldGoalsNO2020.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo',\n",
    "                                               'yardlineSide','Result','gameClock','yardlineNumber','playResult',\n",
    "                                               'preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr','week']\n",
    "                                              ,as_index=True).size()\n",
    "NOFiledGoalsFrame2020 = pd.DataFrame(NOFiledGoalsSeries2020)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "5e576904-a7fd-4dbc-902c-f734c1559089",
   "metadata": {},
   "outputs": [],
   "source": [
    "# NYG Special Plays Data Frames\n",
    "\n",
    "# Punt Frames\n",
    "NYGPuntsSeries2018 = puntsNYG2018.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo','yardlineSide','Result','gameClock',\n",
    "                                   'yardlineNumber','playResult','preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr',\n",
    "                                   'week'],as_index=True).size()\n",
    "NYGPuntsFrame2018 = pd.DataFrame(NYGPuntsSeries2018)\n",
    "\n",
    "NYGPuntsSeries2019 = puntsNYG2019.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo','yardlineSide','Result','gameClock',\n",
    "                                           'yardlineNumber','playResult','preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr',\n",
    "                                           'week'],as_index=True).size()\n",
    "NYGPuntsFrame2019 = pd.DataFrame(NYGPuntsSeries2019)\n",
    "\n",
    "NYGPuntsSeries2020 = puntsNYG2020.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo','yardlineSide','Result','gameClock',\n",
    "                                           'yardlineNumber','playResult','preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr',\n",
    "                                           'week'],as_index=True).size()\n",
    "NYGPuntsFrame2020 = pd.DataFrame(NYGPuntsSeries2020)\n",
    "\n",
    "\n",
    "# Kickoff Frames\n",
    "NYGKickoffsSeries2018 = kickoffsNYG2018.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo','yardlineSide','Result','gameClock',\n",
    "                                                 'yardlineNumber','playResult','preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr',\n",
    "                                                 'visitorTeamAbbr','week'],as_index=True).size()\n",
    "NYGKickoffsFrame2018 = pd.DataFrame(NYGKickoffsSeries2018)\n",
    "\n",
    "NYGKickoffsSeries2019 = kickoffsNYG2019.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo','yardlineSide','Result','gameClock',\n",
    "                                                 'yardlineNumber','playResult','preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr',\n",
    "                                                 'visitorTeamAbbr','week'],as_index=True).size()\n",
    "NYGKickoffsFrame2019 = pd.DataFrame(NYGKickoffsSeries2019)\n",
    "\n",
    "NYGKickoffsSeries2020 = kickoffsNYG2020.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo','yardlineSide','Result','gameClock',\n",
    "                                                 'yardlineNumber','playResult','preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr',\n",
    "                                                 'visitorTeamAbbr','week'],as_index=True).size()\n",
    "NYGKickoffsFrame2020 = pd.DataFrame(NYGKickoffsSeries2020)\n",
    "\n",
    "\n",
    "# Extra Points\n",
    "NYGExtraPointsSeries2018 = extraPointsNYG2018.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo','yardlineSide','Result','gameClock',\n",
    "                                               'yardlineNumber','playResult','preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr',\n",
    "                                               'week'],as_index=True).size()\n",
    "NYGExtraPointsFrame2018 = pd.DataFrame(NYGExtraPointsSeries2018)\n",
    "NYGExtraPointsSeries2019 = extraPointsNYG2019.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo','yardlineSide','Result','gameClock',\n",
    "                                               'yardlineNumber','playResult','preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr',\n",
    "                                               'week'],as_index=True).size()\n",
    "NYGExtraPointsFrame2019 = pd.DataFrame(NYGExtraPointsSeries2019)\n",
    "NYGExtraPointsSeries2020 = extraPointsNYG2020.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo','yardlineSide','Result','gameClock',\n",
    "                                               'yardlineNumber','playResult','preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr',\n",
    "                                               'week'],as_index=True).size()\n",
    "NYGExtraPointsFrame2020 = pd.DataFrame(NYGExtraPointsSeries2020)\n",
    "\n",
    "\n",
    "# Field Goals\n",
    "NYGFiledGoalsSeries2018 = fieldGoalsNYG2018.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo',\n",
    "                                               'yardlineSide','Result','gameClock','yardlineNumber','playResult',\n",
    "                                               'preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr','week']\n",
    "                                              ,as_index=True).size()\n",
    "NYGFiledGoalsFrame2018 = pd.DataFrame(NYGFiledGoalsSeries2018)\n",
    "NYGFiledGoalsSeries2019 = fieldGoalsNYG2019.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo',\n",
    "                                               'yardlineSide','Result','gameClock','yardlineNumber','playResult',\n",
    "                                               'preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr','week']\n",
    "                                              ,as_index=True).size()\n",
    "NYGFiledGoalsFrame2019 = pd.DataFrame(NYGFiledGoalsSeries2019)\n",
    "NYGFiledGoalsSeries2020 = fieldGoalsNYG2020.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo',\n",
    "                                               'yardlineSide','Result','gameClock','yardlineNumber','playResult',\n",
    "                                               'preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr','week']\n",
    "                                              ,as_index=True).size()\n",
    "NYGFiledGoalsFrame2020 = pd.DataFrame(NYGFiledGoalsSeries2020)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "75829705-5cf2-40b8-a333-7a9573ee3760",
   "metadata": {},
   "outputs": [],
   "source": [
    "# NYJ Special Plays Data Frames\n",
    "\n",
    "# Punt Frames\n",
    "NYJPuntsSeries2018 = puntsNYJ2018.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo','yardlineSide','Result','gameClock',\n",
    "                                   'yardlineNumber','playResult','preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr',\n",
    "                                   'week'],as_index=True).size()\n",
    "NYJPuntsFrame2018 = pd.DataFrame(NYJPuntsSeries2018)\n",
    "\n",
    "NYJPuntsSeries2019 = puntsNYJ2019.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo','yardlineSide','Result','gameClock',\n",
    "                                           'yardlineNumber','playResult','preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr',\n",
    "                                           'week'],as_index=True).size()\n",
    "NYJPuntsFrame2019 = pd.DataFrame(NYJPuntsSeries2019)\n",
    "\n",
    "NYJPuntsSeries2020 = puntsNYJ2020.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo','yardlineSide','Result','gameClock',\n",
    "                                           'yardlineNumber','playResult','preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr',\n",
    "                                           'week'],as_index=True).size()\n",
    "NYJPuntsFrame2020 = pd.DataFrame(NYJPuntsSeries2020)\n",
    "\n",
    "\n",
    "# Kickoff Frames\n",
    "NYJKickoffsSeries2018 = kickoffsNYJ2018.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo','yardlineSide','Result','gameClock',\n",
    "                                                 'yardlineNumber','playResult','preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr',\n",
    "                                                 'visitorTeamAbbr','week'],as_index=True).size()\n",
    "NYJKickoffsFrame2018 = pd.DataFrame(NYJKickoffsSeries2018)\n",
    "\n",
    "NYJKickoffsSeries2019 = kickoffsNYJ2019.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo','yardlineSide','Result','gameClock',\n",
    "                                                 'yardlineNumber','playResult','preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr',\n",
    "                                                 'visitorTeamAbbr','week'],as_index=True).size()\n",
    "NYJKickoffsFrame2019 = pd.DataFrame(NYJKickoffsSeries2019)\n",
    "\n",
    "NYJKickoffsSeries2020 = kickoffsNYJ2020.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo','yardlineSide','Result','gameClock',\n",
    "                                                 'yardlineNumber','playResult','preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr',\n",
    "                                                 'visitorTeamAbbr','week'],as_index=True).size()\n",
    "NYJKickoffsFrame2020 = pd.DataFrame(NYJKickoffsSeries2020)\n",
    "\n",
    "\n",
    "# Extra Points\n",
    "NYJExtraPointsSeries2018 = extraPointsNYJ2018.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo','yardlineSide','Result','gameClock',\n",
    "                                               'yardlineNumber','playResult','preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr',\n",
    "                                               'week'],as_index=True).size()\n",
    "NYJExtraPointsFrame2018 = pd.DataFrame(NYJExtraPointsSeries2018)\n",
    "NYJExtraPointsSeries2019 = extraPointsNYJ2019.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo','yardlineSide','Result','gameClock',\n",
    "                                               'yardlineNumber','playResult','preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr',\n",
    "                                               'week'],as_index=True).size()\n",
    "NYJExtraPointsFrame2019 = pd.DataFrame(NYJExtraPointsSeries2019)\n",
    "NYJExtraPointsSeries2020 = extraPointsNYJ2020.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo','yardlineSide','Result','gameClock',\n",
    "                                               'yardlineNumber','playResult','preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr',\n",
    "                                               'week'],as_index=True).size()\n",
    "NYJExtraPointsFrame2020 = pd.DataFrame(NYJExtraPointsSeries2020)\n",
    "\n",
    "\n",
    "# Field Goals\n",
    "NYJFiledGoalsSeries2018 = fieldGoalsNYJ2018.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo',\n",
    "                                               'yardlineSide','Result','gameClock','yardlineNumber','playResult',\n",
    "                                               'preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr','week']\n",
    "                                              ,as_index=True).size()\n",
    "NYJFiledGoalsFrame2018 = pd.DataFrame(NYJFiledGoalsSeries2018)\n",
    "NYJFiledGoalsSeries2019 = fieldGoalsNYJ2019.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo',\n",
    "                                               'yardlineSide','Result','gameClock','yardlineNumber','playResult',\n",
    "                                               'preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr','week']\n",
    "                                              ,as_index=True).size()\n",
    "NYJFiledGoalsFrame2019 = pd.DataFrame(NYJFiledGoalsSeries2019)\n",
    "NYJFiledGoalsSeries2020 = fieldGoalsNYJ2020.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo',\n",
    "                                               'yardlineSide','Result','gameClock','yardlineNumber','playResult',\n",
    "                                               'preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr','week']\n",
    "                                              ,as_index=True).size()\n",
    "NYJFiledGoalsFrame2020 = pd.DataFrame(NYJFiledGoalsSeries2020)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "bdf39cf8-5f2f-4471-a364-7b3c650493f3",
   "metadata": {},
   "outputs": [],
   "source": [
    "# OAK Special Plays Data Frames\n",
    "\n",
    "# Punt Frames\n",
    "OAKPuntsSeries2018 = puntsOAK2018.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo','yardlineSide','Result','gameClock',\n",
    "                                   'yardlineNumber','playResult','preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr',\n",
    "                                   'week'],as_index=True).size()\n",
    "OAKPuntsFrame2018 = pd.DataFrame(OAKPuntsSeries2018)\n",
    "\n",
    "OAKPuntsSeries2019 = puntsOAK2019.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo','yardlineSide','Result','gameClock',\n",
    "                                           'yardlineNumber','playResult','preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr',\n",
    "                                           'week'],as_index=True).size()\n",
    "OAKPuntsFrame2019 = pd.DataFrame(OAKPuntsSeries2019)\n",
    "\n",
    "OAKPuntsSeries2020 = puntsOAK2020.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo','yardlineSide','Result','gameClock',\n",
    "                                           'yardlineNumber','playResult','preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr',\n",
    "                                           'week'],as_index=True).size()\n",
    "OAKPuntsFrame2020 = pd.DataFrame(OAKPuntsSeries2020)\n",
    "\n",
    "\n",
    "# Kickoff Frames\n",
    "OAKKickoffsSeries2018 = kickoffsOAK2018.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo','yardlineSide','Result','gameClock',\n",
    "                                                 'yardlineNumber','playResult','preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr',\n",
    "                                                 'visitorTeamAbbr','week'],as_index=True).size()\n",
    "OAKKickoffsFrame2018 = pd.DataFrame(OAKKickoffsSeries2018)\n",
    "\n",
    "OAKKickoffsSeries2019 = kickoffsOAK2019.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo','yardlineSide','Result','gameClock',\n",
    "                                                 'yardlineNumber','playResult','preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr',\n",
    "                                                 'visitorTeamAbbr','week'],as_index=True).size()\n",
    "OAKKickoffsFrame2019 = pd.DataFrame(OAKKickoffsSeries2019)\n",
    "\n",
    "OAKKickoffsSeries2020 = kickoffsOAK2020.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo','yardlineSide','Result','gameClock',\n",
    "                                                 'yardlineNumber','playResult','preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr',\n",
    "                                                 'visitorTeamAbbr','week'],as_index=True).size()\n",
    "OAKKickoffsFrame2020 = pd.DataFrame(OAKKickoffsSeries2020)\n",
    "\n",
    "\n",
    "# Extra Points\n",
    "OAKExtraPointsSeries2018 = extraPointsOAK2018.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo','yardlineSide','Result','gameClock',\n",
    "                                               'yardlineNumber','playResult','preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr',\n",
    "                                               'week'],as_index=True).size()\n",
    "OAKExtraPointsFrame2018 = pd.DataFrame(OAKExtraPointsSeries2018)\n",
    "OAKExtraPointsSeries2019 = extraPointsOAK2019.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo','yardlineSide','Result','gameClock',\n",
    "                                               'yardlineNumber','playResult','preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr',\n",
    "                                               'week'],as_index=True).size()\n",
    "OAKExtraPointsFrame2019 = pd.DataFrame(OAKExtraPointsSeries2019)\n",
    "OAKExtraPointsSeries2020 = extraPointsOAK2020.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo','yardlineSide','Result','gameClock',\n",
    "                                               'yardlineNumber','playResult','preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr',\n",
    "                                               'week'],as_index=True).size()\n",
    "OAKExtraPointsFrame2020 = pd.DataFrame(OAKExtraPointsSeries2020)\n",
    "\n",
    "\n",
    "# Field Goals\n",
    "OAKFiledGoalsSeries2018 = fieldGoalsOAK2018.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo',\n",
    "                                               'yardlineSide','Result','gameClock','yardlineNumber','playResult',\n",
    "                                               'preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr','week']\n",
    "                                              ,as_index=True).size()\n",
    "OAKFiledGoalsFrame2018 = pd.DataFrame(OAKFiledGoalsSeries2018)\n",
    "OAKFiledGoalsSeries2019 = fieldGoalsOAK2019.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo',\n",
    "                                               'yardlineSide','Result','gameClock','yardlineNumber','playResult',\n",
    "                                               'preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr','week']\n",
    "                                              ,as_index=True).size()\n",
    "OAKFiledGoalsFrame2019 = pd.DataFrame(OAKFiledGoalsSeries2019)\n",
    "OAKFiledGoalsSeries2020 = fieldGoalsOAK2020.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo',\n",
    "                                               'yardlineSide','Result','gameClock','yardlineNumber','playResult',\n",
    "                                               'preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr','week']\n",
    "                                              ,as_index=True).size()\n",
    "OAKFiledGoalsFrame2020 = pd.DataFrame(OAKFiledGoalsSeries2020)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "ae9d090e-856d-47f0-a66b-8520b967d145",
   "metadata": {},
   "outputs": [],
   "source": [
    "# PHI Special Plays Data Frames\n",
    "\n",
    "# Punt Frames\n",
    "PHIPuntsSeries2018 = puntsPHI2018.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo','yardlineSide','Result','gameClock',\n",
    "                                   'yardlineNumber','playResult','preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr',\n",
    "                                   'week'],as_index=True).size()\n",
    "PHIPuntsFrame2018 = pd.DataFrame(PHIPuntsSeries2018)\n",
    "\n",
    "PHIPuntsSeries2019 = puntsPHI2019.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo','yardlineSide','Result','gameClock',\n",
    "                                           'yardlineNumber','playResult','preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr',\n",
    "                                           'week'],as_index=True).size()\n",
    "PHIPuntsFrame2019 = pd.DataFrame(PHIPuntsSeries2019)\n",
    "\n",
    "PHIPuntsSeries2020 = puntsPHI2020.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo','yardlineSide','Result','gameClock',\n",
    "                                           'yardlineNumber','playResult','preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr',\n",
    "                                           'week'],as_index=True).size()\n",
    "PHIPuntsFrame2020 = pd.DataFrame(PHIPuntsSeries2020)\n",
    "\n",
    "\n",
    "# Kickoff Frames\n",
    "PHIKickoffsSeries2018 = kickoffsPHI2018.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo','yardlineSide','Result','gameClock',\n",
    "                                                 'yardlineNumber','playResult','preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr',\n",
    "                                                 'visitorTeamAbbr','week'],as_index=True).size()\n",
    "PHIKickoffsFrame2018 = pd.DataFrame(PHIKickoffsSeries2018)\n",
    "\n",
    "PHIKickoffsSeries2019 = kickoffsPHI2019.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo','yardlineSide','Result','gameClock',\n",
    "                                                 'yardlineNumber','playResult','preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr',\n",
    "                                                 'visitorTeamAbbr','week'],as_index=True).size()\n",
    "PHIKickoffsFrame2019 = pd.DataFrame(PHIKickoffsSeries2019)\n",
    "\n",
    "PHIKickoffsSeries2020 = kickoffsPHI2020.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo','yardlineSide','Result','gameClock',\n",
    "                                                 'yardlineNumber','playResult','preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr',\n",
    "                                                 'visitorTeamAbbr','week'],as_index=True).size()\n",
    "PHIKickoffsFrame2020 = pd.DataFrame(PHIKickoffsSeries2020)\n",
    "\n",
    "\n",
    "# Extra Points\n",
    "PHIExtraPointsSeries2018 = extraPointsPHI2018.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo','yardlineSide','Result','gameClock',\n",
    "                                               'yardlineNumber','playResult','preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr',\n",
    "                                               'week'],as_index=True).size()\n",
    "PHIExtraPointsFrame2018 = pd.DataFrame(PHIExtraPointsSeries2018)\n",
    "PHIExtraPointsSeries2019 = extraPointsPHI2019.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo','yardlineSide','Result','gameClock',\n",
    "                                               'yardlineNumber','playResult','preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr',\n",
    "                                               'week'],as_index=True).size()\n",
    "PHIExtraPointsFrame2019 = pd.DataFrame(PHIExtraPointsSeries2019)\n",
    "PHIExtraPointsSeries2020 = extraPointsPHI2020.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo','yardlineSide','Result','gameClock',\n",
    "                                               'yardlineNumber','playResult','preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr',\n",
    "                                               'week'],as_index=True).size()\n",
    "PHIExtraPointsFrame2020 = pd.DataFrame(PHIExtraPointsSeries2020)\n",
    "\n",
    "\n",
    "# Field Goals\n",
    "PHIFiledGoalsSeries2018 = fieldGoalsPHI2018.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo',\n",
    "                                               'yardlineSide','Result','gameClock','yardlineNumber','playResult',\n",
    "                                               'preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr','week']\n",
    "                                              ,as_index=True).size()\n",
    "PHIFiledGoalsFrame2018 = pd.DataFrame(PHIFiledGoalsSeries2018)\n",
    "PHIFiledGoalsSeries2019 = fieldGoalsPHI2019.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo',\n",
    "                                               'yardlineSide','Result','gameClock','yardlineNumber','playResult',\n",
    "                                               'preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr','week']\n",
    "                                              ,as_index=True).size()\n",
    "PHIFiledGoalsFrame2019 = pd.DataFrame(PHIFiledGoalsSeries2019)\n",
    "PHIFiledGoalsSeries2020 = fieldGoalsPHI2020.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo',\n",
    "                                               'yardlineSide','Result','gameClock','yardlineNumber','playResult',\n",
    "                                               'preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr','week']\n",
    "                                              ,as_index=True).size()\n",
    "PHIFiledGoalsFrame2020 = pd.DataFrame(PHIFiledGoalsSeries2020)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "9c03a79a-1542-4fe5-bf66-c41b3d87eec9",
   "metadata": {},
   "outputs": [],
   "source": [
    "# PIT Special Plays Data Frames\n",
    "\n",
    "# Punt Frames\n",
    "PITPuntsSeries2018 = puntsPIT2018.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo','yardlineSide','Result','gameClock',\n",
    "                                   'yardlineNumber','playResult','preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr',\n",
    "                                   'week'],as_index=True).size()\n",
    "PITPuntsFrame2018 = pd.DataFrame(PITPuntsSeries2018)\n",
    "\n",
    "PITPuntsSeries2019 = puntsPIT2019.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo','yardlineSide','Result','gameClock',\n",
    "                                           'yardlineNumber','playResult','preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr',\n",
    "                                           'week'],as_index=True).size()\n",
    "PITPuntsFrame2019 = pd.DataFrame(PITPuntsSeries2019)\n",
    "\n",
    "PITPuntsSeries2020 = puntsPIT2020.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo','yardlineSide','Result','gameClock',\n",
    "                                           'yardlineNumber','playResult','preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr',\n",
    "                                           'week'],as_index=True).size()\n",
    "PITPuntsFrame2020 = pd.DataFrame(PITPuntsSeries2020)\n",
    "\n",
    "\n",
    "# Kickoff Frames\n",
    "PITKickoffsSeries2018 = kickoffsPIT2018.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo','yardlineSide','Result','gameClock',\n",
    "                                                 'yardlineNumber','playResult','preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr',\n",
    "                                                 'visitorTeamAbbr','week'],as_index=True).size()\n",
    "PITKickoffsFrame2018 = pd.DataFrame(PITKickoffsSeries2018)\n",
    "\n",
    "PITKickoffsSeries2019 = kickoffsPIT2019.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo','yardlineSide','Result','gameClock',\n",
    "                                                 'yardlineNumber','playResult','preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr',\n",
    "                                                 'visitorTeamAbbr','week'],as_index=True).size()\n",
    "PITKickoffsFrame2019 = pd.DataFrame(PITKickoffsSeries2019)\n",
    "\n",
    "PITKickoffsSeries2020 = kickoffsPIT2020.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo','yardlineSide','Result','gameClock',\n",
    "                                                 'yardlineNumber','playResult','preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr',\n",
    "                                                 'visitorTeamAbbr','week'],as_index=True).size()\n",
    "PITKickoffsFrame2020 = pd.DataFrame(PITKickoffsSeries2020)\n",
    "\n",
    "\n",
    "# Extra Points\n",
    "PITExtraPointsSeries2018 = extraPointsPIT2018.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo','yardlineSide','Result','gameClock',\n",
    "                                               'yardlineNumber','playResult','preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr',\n",
    "                                               'week'],as_index=True).size()\n",
    "PITExtraPointsFrame2018 = pd.DataFrame(PITExtraPointsSeries2018)\n",
    "PITExtraPointsSeries2019 = extraPointsPIT2019.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo','yardlineSide','Result','gameClock',\n",
    "                                               'yardlineNumber','playResult','preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr',\n",
    "                                               'week'],as_index=True).size()\n",
    "PITExtraPointsFrame2019 = pd.DataFrame(PITExtraPointsSeries2019)\n",
    "PITExtraPointsSeries2020 = extraPointsPIT2020.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo','yardlineSide','Result','gameClock',\n",
    "                                               'yardlineNumber','playResult','preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr',\n",
    "                                               'week'],as_index=True).size()\n",
    "PITExtraPointsFrame2020 = pd.DataFrame(PITExtraPointsSeries2020)\n",
    "\n",
    "\n",
    "# Field Goals\n",
    "PITFiledGoalsSeries2018 = fieldGoalsPIT2018.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo',\n",
    "                                               'yardlineSide','Result','gameClock','yardlineNumber','playResult',\n",
    "                                               'preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr','week']\n",
    "                                              ,as_index=True).size()\n",
    "PITFiledGoalsFrame2018 = pd.DataFrame(PITFiledGoalsSeries2018)\n",
    "PITFiledGoalsSeries2019 = fieldGoalsPIT2019.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo',\n",
    "                                               'yardlineSide','Result','gameClock','yardlineNumber','playResult',\n",
    "                                               'preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr','week']\n",
    "                                              ,as_index=True).size()\n",
    "PITFiledGoalsFrame2019 = pd.DataFrame(PITFiledGoalsSeries2019)\n",
    "PITFiledGoalsSeries2020 = fieldGoalsPIT2020.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo',\n",
    "                                               'yardlineSide','Result','gameClock','yardlineNumber','playResult',\n",
    "                                               'preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr','week']\n",
    "                                              ,as_index=True).size()\n",
    "PITFiledGoalsFrame2020 = pd.DataFrame(PITFiledGoalsSeries2020)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "7bc78b14-75b6-4644-8352-24795127bb77",
   "metadata": {},
   "outputs": [],
   "source": [
    "# SEA Special Plays Data Frames\n",
    "\n",
    "# Punt Frames\n",
    "SEAPuntsSeries2018 = puntsSEA2018.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo','yardlineSide','Result','gameClock',\n",
    "                                   'yardlineNumber','playResult','preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr',\n",
    "                                   'week'],as_index=True).size()\n",
    "SEAPuntsFrame2018 = pd.DataFrame(SEAPuntsSeries2018)\n",
    "\n",
    "SEAPuntsSeries2019 = puntsSEA2019.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo','yardlineSide','Result','gameClock',\n",
    "                                           'yardlineNumber','playResult','preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr',\n",
    "                                           'week'],as_index=True).size()\n",
    "SEAPuntsFrame2019 = pd.DataFrame(SEAPuntsSeries2019)\n",
    "\n",
    "SEAPuntsSeries2020 = puntsSEA2020.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo','yardlineSide','Result','gameClock',\n",
    "                                           'yardlineNumber','playResult','preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr',\n",
    "                                           'week'],as_index=True).size()\n",
    "SEAPuntsFrame2020 = pd.DataFrame(SEAPuntsSeries2020)\n",
    "\n",
    "\n",
    "# Kickoff Frames\n",
    "SEAKickoffsSeries2018 = kickoffsSEA2018.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo','yardlineSide','Result','gameClock',\n",
    "                                                 'yardlineNumber','playResult','preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr',\n",
    "                                                 'visitorTeamAbbr','week'],as_index=True).size()\n",
    "SEAKickoffsFrame2018 = pd.DataFrame(SEAKickoffsSeries2018)\n",
    "\n",
    "SEAKickoffsSeries2019 = kickoffsSEA2019.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo','yardlineSide','Result','gameClock',\n",
    "                                                 'yardlineNumber','playResult','preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr',\n",
    "                                                 'visitorTeamAbbr','week'],as_index=True).size()\n",
    "SEAKickoffsFrame2019 = pd.DataFrame(SEAKickoffsSeries2019)\n",
    "\n",
    "SEAKickoffsSeries2020 = kickoffsSEA2020.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo','yardlineSide','Result','gameClock',\n",
    "                                                 'yardlineNumber','playResult','preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr',\n",
    "                                                 'visitorTeamAbbr','week'],as_index=True).size()\n",
    "SEAKickoffsFrame2020 = pd.DataFrame(SEAKickoffsSeries2020)\n",
    "\n",
    "\n",
    "# Extra Points\n",
    "SEAExtraPointsSeries2018 = extraPointsSEA2018.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo','yardlineSide','Result','gameClock',\n",
    "                                               'yardlineNumber','playResult','preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr',\n",
    "                                               'week'],as_index=True).size()\n",
    "SEAExtraPointsFrame2018 = pd.DataFrame(SEAExtraPointsSeries2018)\n",
    "SEAExtraPointsSeries2019 = extraPointsSEA2019.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo','yardlineSide','Result','gameClock',\n",
    "                                               'yardlineNumber','playResult','preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr',\n",
    "                                               'week'],as_index=True).size()\n",
    "SEAExtraPointsFrame2019 = pd.DataFrame(SEAExtraPointsSeries2019)\n",
    "SEAExtraPointsSeries2020 = extraPointsSEA2020.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo','yardlineSide','Result','gameClock',\n",
    "                                               'yardlineNumber','playResult','preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr',\n",
    "                                               'week'],as_index=True).size()\n",
    "SEAExtraPointsFrame2020 = pd.DataFrame(SEAExtraPointsSeries2020)\n",
    "\n",
    "\n",
    "# Field Goals\n",
    "SEAFiledGoalsSeries2018 = fieldGoalsSEA2018.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo',\n",
    "                                               'yardlineSide','Result','gameClock','yardlineNumber','playResult',\n",
    "                                               'preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr','week']\n",
    "                                              ,as_index=True).size()\n",
    "SEAFiledGoalsFrame2018 = pd.DataFrame(SEAFiledGoalsSeries2018)\n",
    "SEAFiledGoalsSeries2019 = fieldGoalsSEA2019.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo',\n",
    "                                               'yardlineSide','Result','gameClock','yardlineNumber','playResult',\n",
    "                                               'preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr','week']\n",
    "                                              ,as_index=True).size()\n",
    "SEAFiledGoalsFrame2019 = pd.DataFrame(SEAFiledGoalsSeries2019)\n",
    "SEAFiledGoalsSeries2020 = fieldGoalsSEA2020.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo',\n",
    "                                               'yardlineSide','Result','gameClock','yardlineNumber','playResult',\n",
    "                                               'preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr','week']\n",
    "                                              ,as_index=True).size()\n",
    "SEAFiledGoalsFrame2020 = pd.DataFrame(SEAFiledGoalsSeries2020)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "89b81be2-22b3-40e4-96bb-681f80102812",
   "metadata": {},
   "outputs": [],
   "source": [
    "# SF Special Plays Data Frames\n",
    "\n",
    "# Punt Frames\n",
    "SFPuntsSeries2018 = puntsSF2018.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo','yardlineSide','Result','gameClock',\n",
    "                                   'yardlineNumber','playResult','preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr',\n",
    "                                   'week'],as_index=True).size()\n",
    "SFPuntsFrame2018 = pd.DataFrame(SFPuntsSeries2018)\n",
    "\n",
    "SFPuntsSeries2019 = puntsSF2019.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo','yardlineSide','Result','gameClock',\n",
    "                                           'yardlineNumber','playResult','preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr',\n",
    "                                           'week'],as_index=True).size()\n",
    "SFPuntsFrame2019 = pd.DataFrame(SFPuntsSeries2019)\n",
    "\n",
    "SFPuntsSeries2020 = puntsSF2020.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo','yardlineSide','Result','gameClock',\n",
    "                                           'yardlineNumber','playResult','preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr',\n",
    "                                           'week'],as_index=True).size()\n",
    "SFPuntsFrame2020 = pd.DataFrame(SFPuntsSeries2020)\n",
    "\n",
    "\n",
    "# Kickoff Frames\n",
    "SFKickoffsSeries2018 = kickoffsSF2018.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo','yardlineSide','Result','gameClock',\n",
    "                                                 'yardlineNumber','playResult','preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr',\n",
    "                                                 'visitorTeamAbbr','week'],as_index=True).size()\n",
    "SFKickoffsFrame2018 = pd.DataFrame(SFKickoffsSeries2018)\n",
    "\n",
    "SFKickoffsSeries2019 = kickoffsSF2019.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo','yardlineSide','Result','gameClock',\n",
    "                                                 'yardlineNumber','playResult','preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr',\n",
    "                                                 'visitorTeamAbbr','week'],as_index=True).size()\n",
    "SFKickoffsFrame2019 = pd.DataFrame(SFKickoffsSeries2019)\n",
    "\n",
    "SFKickoffsSeries2020 = kickoffsSF2020.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo','yardlineSide','Result','gameClock',\n",
    "                                                 'yardlineNumber','playResult','preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr',\n",
    "                                                 'visitorTeamAbbr','week'],as_index=True).size()\n",
    "SFKickoffsFrame2020 = pd.DataFrame(SFKickoffsSeries2020)\n",
    "\n",
    "\n",
    "# Extra Points\n",
    "SFExtraPointsSeries2018 = extraPointsSF2018.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo','yardlineSide','Result','gameClock',\n",
    "                                               'yardlineNumber','playResult','preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr',\n",
    "                                               'week'],as_index=True).size()\n",
    "SFExtraPointsFrame2018 = pd.DataFrame(SFExtraPointsSeries2018)\n",
    "SFExtraPointsSeries2019 = extraPointsSF2019.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo','yardlineSide','Result','gameClock',\n",
    "                                               'yardlineNumber','playResult','preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr',\n",
    "                                               'week'],as_index=True).size()\n",
    "SFExtraPointsFrame2019 = pd.DataFrame(SFExtraPointsSeries2019)\n",
    "SFExtraPointsSeries2020 = extraPointsSF2020.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo','yardlineSide','Result','gameClock',\n",
    "                                               'yardlineNumber','playResult','preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr',\n",
    "                                               'week'],as_index=True).size()\n",
    "SFExtraPointsFrame2020 = pd.DataFrame(SFExtraPointsSeries2020)\n",
    "\n",
    "\n",
    "# Field Goals\n",
    "SFFiledGoalsSeries2018 = fieldGoalsSF2018.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo',\n",
    "                                               'yardlineSide','Result','gameClock','yardlineNumber','playResult',\n",
    "                                               'preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr','week']\n",
    "                                              ,as_index=True).size()\n",
    "SFFiledGoalsFrame2018 = pd.DataFrame(SFFiledGoalsSeries2018)\n",
    "SFFiledGoalsSeries2019 = fieldGoalsSF2019.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo',\n",
    "                                               'yardlineSide','Result','gameClock','yardlineNumber','playResult',\n",
    "                                               'preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr','week']\n",
    "                                              ,as_index=True).size()\n",
    "SFFiledGoalsFrame2019 = pd.DataFrame(SFFiledGoalsSeries2019)\n",
    "SFFiledGoalsSeries2020 = fieldGoalsSF2020.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo',\n",
    "                                               'yardlineSide','Result','gameClock','yardlineNumber','playResult',\n",
    "                                               'preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr','week']\n",
    "                                              ,as_index=True).size()\n",
    "SFFiledGoalsFrame2020 = pd.DataFrame(SFFiledGoalsSeries2020)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "c1303f69-f5af-4971-ade0-2bbb90b73433",
   "metadata": {},
   "outputs": [],
   "source": [
    "# TB Special Plays Data Frames\n",
    "\n",
    "# Punt Frames\n",
    "TBPuntsSeries2018 = puntsTB2018.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo','yardlineSide','Result','gameClock',\n",
    "                                   'yardlineNumber','playResult','preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr',\n",
    "                                   'week'],as_index=True).size()\n",
    "TBPuntsFrame2018 = pd.DataFrame(TBPuntsSeries2018)\n",
    "\n",
    "TBPuntsSeries2019 = puntsTB2019.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo','yardlineSide','Result','gameClock',\n",
    "                                           'yardlineNumber','playResult','preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr',\n",
    "                                           'week'],as_index=True).size()\n",
    "TBPuntsFrame2019 = pd.DataFrame(TBPuntsSeries2019)\n",
    "\n",
    "TBPuntsSeries2020 = puntsTB2020.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo','yardlineSide','Result','gameClock',\n",
    "                                           'yardlineNumber','playResult','preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr',\n",
    "                                           'week'],as_index=True).size()\n",
    "TBPuntsFrame2020 = pd.DataFrame(TBPuntsSeries2020)\n",
    "\n",
    "\n",
    "# Kickoff Frames\n",
    "TBKickoffsSeries2018 = kickoffsTB2018.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo','yardlineSide','Result','gameClock',\n",
    "                                                 'yardlineNumber','playResult','preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr',\n",
    "                                                 'visitorTeamAbbr','week'],as_index=True).size()\n",
    "TBKickoffsFrame2018 = pd.DataFrame(TBKickoffsSeries2018)\n",
    "\n",
    "TBKickoffsSeries2019 = kickoffsTB2019.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo','yardlineSide','Result','gameClock',\n",
    "                                                 'yardlineNumber','playResult','preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr',\n",
    "                                                 'visitorTeamAbbr','week'],as_index=True).size()\n",
    "TBKickoffsFrame2019 = pd.DataFrame(TBKickoffsSeries2019)\n",
    "\n",
    "TBKickoffsSeries2020 = kickoffsTB2020.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo','yardlineSide','Result','gameClock',\n",
    "                                                 'yardlineNumber','playResult','preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr',\n",
    "                                                 'visitorTeamAbbr','week'],as_index=True).size()\n",
    "TBKickoffsFrame2020 = pd.DataFrame(TBKickoffsSeries2020)\n",
    "\n",
    "\n",
    "# Extra Points\n",
    "TBExtraPointsSeries2018 = extraPointsTB2018.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo','yardlineSide','Result','gameClock',\n",
    "                                               'yardlineNumber','playResult','preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr',\n",
    "                                               'week'],as_index=True).size()\n",
    "TBExtraPointsFrame2018 = pd.DataFrame(TBExtraPointsSeries2018)\n",
    "TBExtraPointsSeries2019 = extraPointsTB2019.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo','yardlineSide','Result','gameClock',\n",
    "                                               'yardlineNumber','playResult','preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr',\n",
    "                                               'week'],as_index=True).size()\n",
    "TBExtraPointsFrame2019 = pd.DataFrame(TBExtraPointsSeries2019)\n",
    "TBExtraPointsSeries2020 = extraPointsTB2020.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo','yardlineSide','Result','gameClock',\n",
    "                                               'yardlineNumber','playResult','preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr',\n",
    "                                               'week'],as_index=True).size()\n",
    "TBExtraPointsFrame2020 = pd.DataFrame(TBExtraPointsSeries2020)\n",
    "\n",
    "\n",
    "# Field Goals\n",
    "TBFiledGoalsSeries2018 = fieldGoalsTB2018.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo',\n",
    "                                               'yardlineSide','Result','gameClock','yardlineNumber','playResult',\n",
    "                                               'preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr','week']\n",
    "                                              ,as_index=True).size()\n",
    "TBFiledGoalsFrame2018 = pd.DataFrame(TBFiledGoalsSeries2018)\n",
    "TBFiledGoalsSeries2019 = fieldGoalsTB2019.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo',\n",
    "                                               'yardlineSide','Result','gameClock','yardlineNumber','playResult',\n",
    "                                               'preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr','week']\n",
    "                                              ,as_index=True).size()\n",
    "TBFiledGoalsFrame2019 = pd.DataFrame(TBFiledGoalsSeries2019)\n",
    "TBFiledGoalsSeries2020 = fieldGoalsTB2020.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo',\n",
    "                                               'yardlineSide','Result','gameClock','yardlineNumber','playResult',\n",
    "                                               'preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr','week']\n",
    "                                              ,as_index=True).size()\n",
    "TBFiledGoalsFrame2020 = pd.DataFrame(TBFiledGoalsSeries2020)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "1c0e61ef-8019-4cc4-813b-f9c70fea646f",
   "metadata": {},
   "outputs": [],
   "source": [
    "# TEN Special Plays Data Frames\n",
    "\n",
    "# Punt Frames\n",
    "TENPuntsSeries2018 = puntsTEN2018.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo','yardlineSide','Result','gameClock',\n",
    "                                   'yardlineNumber','playResult','preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr',\n",
    "                                   'week'],as_index=True).size()\n",
    "TENPuntsFrame2018 = pd.DataFrame(TENPuntsSeries2018)\n",
    "\n",
    "TENPuntsSeries2019 = puntsTEN2019.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo','yardlineSide','Result','gameClock',\n",
    "                                           'yardlineNumber','playResult','preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr',\n",
    "                                           'week'],as_index=True).size()\n",
    "TENPuntsFrame2019 = pd.DataFrame(TENPuntsSeries2019)\n",
    "\n",
    "TENPuntsSeries2020 = puntsTEN2020.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo','yardlineSide','Result','gameClock',\n",
    "                                           'yardlineNumber','playResult','preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr',\n",
    "                                           'week'],as_index=True).size()\n",
    "TENPuntsFrame2020 = pd.DataFrame(TENPuntsSeries2020)\n",
    "\n",
    "\n",
    "# Kickoff Frames\n",
    "TENKickoffsSeries2018 = kickoffsTEN2018.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo','yardlineSide','Result','gameClock',\n",
    "                                                 'yardlineNumber','playResult','preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr',\n",
    "                                                 'visitorTeamAbbr','week'],as_index=True).size()\n",
    "TENKickoffsFrame2018 = pd.DataFrame(TENKickoffsSeries2018)\n",
    "\n",
    "TENKickoffsSeries2019 = kickoffsTEN2019.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo','yardlineSide','Result','gameClock',\n",
    "                                                 'yardlineNumber','playResult','preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr',\n",
    "                                                 'visitorTeamAbbr','week'],as_index=True).size()\n",
    "TENKickoffsFrame2019 = pd.DataFrame(TENKickoffsSeries2019)\n",
    "\n",
    "TENKickoffsSeries2020 = kickoffsTEN2020.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo','yardlineSide','Result','gameClock',\n",
    "                                                 'yardlineNumber','playResult','preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr',\n",
    "                                                 'visitorTeamAbbr','week'],as_index=True).size()\n",
    "TENKickoffsFrame2020 = pd.DataFrame(TENKickoffsSeries2020)\n",
    "\n",
    "\n",
    "# Extra Points\n",
    "TENExtraPointsSeries2018 = extraPointsTEN2018.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo','yardlineSide','Result','gameClock',\n",
    "                                               'yardlineNumber','playResult','preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr',\n",
    "                                               'week'],as_index=True).size()\n",
    "TENExtraPointsFrame2018 = pd.DataFrame(TENExtraPointsSeries2018)\n",
    "TENExtraPointsSeries2019 = extraPointsTEN2019.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo','yardlineSide','Result','gameClock',\n",
    "                                               'yardlineNumber','playResult','preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr',\n",
    "                                               'week'],as_index=True).size()\n",
    "TENExtraPointsFrame2019 = pd.DataFrame(TENExtraPointsSeries2019)\n",
    "TENExtraPointsSeries2020 = extraPointsTEN2020.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo','yardlineSide','Result','gameClock',\n",
    "                                               'yardlineNumber','playResult','preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr',\n",
    "                                               'week'],as_index=True).size()\n",
    "TENExtraPointsFrame2020 = pd.DataFrame(TENExtraPointsSeries2020)\n",
    "\n",
    "\n",
    "# Field Goals\n",
    "TENFiledGoalsSeries2018 = fieldGoalsTEN2018.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo',\n",
    "                                               'yardlineSide','Result','gameClock','yardlineNumber','playResult',\n",
    "                                               'preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr','week']\n",
    "                                              ,as_index=True).size()\n",
    "TENFiledGoalsFrame2018 = pd.DataFrame(TENFiledGoalsSeries2018)\n",
    "TENFiledGoalsSeries2019 = fieldGoalsTEN2019.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo',\n",
    "                                               'yardlineSide','Result','gameClock','yardlineNumber','playResult',\n",
    "                                               'preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr','week']\n",
    "                                              ,as_index=True).size()\n",
    "TENFiledGoalsFrame2019 = pd.DataFrame(TENFiledGoalsSeries2019)\n",
    "TENFiledGoalsSeries2020 = fieldGoalsTEN2020.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo',\n",
    "                                               'yardlineSide','Result','gameClock','yardlineNumber','playResult',\n",
    "                                               'preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr','week']\n",
    "                                              ,as_index=True).size()\n",
    "TENFiledGoalsFrame2020 = pd.DataFrame(TENFiledGoalsSeries2020)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "c4adb452-bd1e-4c49-a94c-d2ea11b36c4f",
   "metadata": {},
   "outputs": [],
   "source": [
    "# WAS Special Plays Data Frames\n",
    "\n",
    "# Punt Frames\n",
    "WASPuntsSeries2018 = puntsWAS2018.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo','yardlineSide','Result','gameClock',\n",
    "                                   'yardlineNumber','playResult','preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr',\n",
    "                                   'week'],as_index=True).size()\n",
    "WASPuntsFrame2018 = pd.DataFrame(WASPuntsSeries2018)\n",
    "\n",
    "WASPuntsSeries2019 = puntsWAS2019.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo','yardlineSide','Result','gameClock',\n",
    "                                           'yardlineNumber','playResult','preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr',\n",
    "                                           'week'],as_index=True).size()\n",
    "WASPuntsFrame2019 = pd.DataFrame(WASPuntsSeries2019)\n",
    "\n",
    "WASPuntsSeries2020 = puntsWAS2020.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo','yardlineSide','Result','gameClock',\n",
    "                                           'yardlineNumber','playResult','preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr',\n",
    "                                           'week'],as_index=True).size()\n",
    "WASPuntsFrame2020 = pd.DataFrame(WASPuntsSeries2020)\n",
    "\n",
    "\n",
    "# Kickoff Frames\n",
    "WASKickoffsSeries2018 = kickoffsWAS2018.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo','yardlineSide','Result','gameClock',\n",
    "                                                 'yardlineNumber','playResult','preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr',\n",
    "                                                 'visitorTeamAbbr','week'],as_index=True).size()\n",
    "WASKickoffsFrame2018 = pd.DataFrame(WASKickoffsSeries2018)\n",
    "\n",
    "WASKickoffsSeries2019 = kickoffsWAS2019.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo','yardlineSide','Result','gameClock',\n",
    "                                                 'yardlineNumber','playResult','preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr',\n",
    "                                                 'visitorTeamAbbr','week'],as_index=True).size()\n",
    "WASKickoffsFrame2019 = pd.DataFrame(WASKickoffsSeries2019)\n",
    "\n",
    "WASKickoffsSeries2020 = kickoffsWAS2020.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo','yardlineSide','Result','gameClock',\n",
    "                                                 'yardlineNumber','playResult','preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr',\n",
    "                                                 'visitorTeamAbbr','week'],as_index=True).size()\n",
    "WASKickoffsFrame2020 = pd.DataFrame(WASKickoffsSeries2020)\n",
    "\n",
    "\n",
    "# Extra Points\n",
    "WASExtraPointsSeries2018 = extraPointsWAS2018.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo','yardlineSide','Result','gameClock',\n",
    "                                               'yardlineNumber','playResult','preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr',\n",
    "                                               'week'],as_index=True).size()\n",
    "WASExtraPointsFrame2018 = pd.DataFrame(WASExtraPointsSeries2018)\n",
    "WASExtraPointsSeries2019 = extraPointsWAS2019.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo','yardlineSide','Result','gameClock',\n",
    "                                               'yardlineNumber','playResult','preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr',\n",
    "                                               'week'],as_index=True).size()\n",
    "WASExtraPointsFrame2019 = pd.DataFrame(WASExtraPointsSeries2019)\n",
    "WASExtraPointsSeries2020 = extraPointsWAS2020.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo','yardlineSide','Result','gameClock',\n",
    "                                               'yardlineNumber','playResult','preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr',\n",
    "                                               'week'],as_index=True).size()\n",
    "WASExtraPointsFrame2020 = pd.DataFrame(WASExtraPointsSeries2020)\n",
    "\n",
    "\n",
    "# Field Goals\n",
    "WASFiledGoalsSeries2018 = fieldGoalsWAS2018.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo',\n",
    "                                               'yardlineSide','Result','gameClock','yardlineNumber','playResult',\n",
    "                                               'preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr','week']\n",
    "                                              ,as_index=True).size()\n",
    "WASFiledGoalsFrame2018 = pd.DataFrame(WASFiledGoalsSeries2018)\n",
    "WASFiledGoalsSeries2019 = fieldGoalsWAS2019.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo',\n",
    "                                               'yardlineSide','Result','gameClock','yardlineNumber','playResult',\n",
    "                                               'preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr','week']\n",
    "                                              ,as_index=True).size()\n",
    "WASFiledGoalsFrame2019 = pd.DataFrame(WASFiledGoalsSeries2019)\n",
    "WASFiledGoalsSeries2020 = fieldGoalsWAS2020.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo',\n",
    "                                               'yardlineSide','Result','gameClock','yardlineNumber','playResult',\n",
    "                                               'preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr','week']\n",
    "                                              ,as_index=True).size()\n",
    "WASFiledGoalsFrame2020 = pd.DataFrame(WASFiledGoalsSeries2020)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "05cebe5c-f710-4418-8b8d-0136037f1343",
   "metadata": {},
   "outputs": [],
   "source": [
    "# ARI Plot Data\n",
    "ARIData = [['Punt - Return', 33, 24, 17],\n",
    "            ['Punt - Fair Catch', 19, 12, 19],\n",
    "            ['Punt - Downed', 11, 7, 7],\n",
    "            ['Punt - Out of Bounds', 23, 21, 7],\n",
    "            ['Punt - Touchback', 6, 5, 5],\n",
    "            ['Punt - Muffed ', 3, 0, 1],\n",
    "            ['Punt - Non-Special Teams Result', 1, 1, 1],\n",
    "            ['Punt - Blocked Punt', 0, 1, 0],\n",
    "            ['Kickoff - Return', 27, 30, 41],\n",
    "            ['Kickoff - Touchback', 27, 45, 38],\n",
    "            ['Kickoff - Out of Bounds', 1, 2, 1],\n",
    "            ['Kickoff - Muffed', 0, 0, 1],\n",
    "            ['Extra Point - Kick Attempt Good', 23, 31, 44],\n",
    "            ['Extra Point - Kick Attempt No Good', 1, 1, 1],\n",
    "            ['Field Goal - Kick Attempt Good ', 36, 28, 19],\n",
    "            ['Field Goal - Kick Attempt No Good', 15, 2, 6],\n",
    "            ['Field Goal - Blocked Kick Attempt', 0, 1, 1]]\n",
    "\n",
    "allARIData = pd.DataFrame(ARIData, columns=['ARI Special Play', '2018', '2019', '2020'])\n",
    "\n",
    "# ATL Plot Data\n",
    "ATLData = [['Punt - Return', 20, 15, 20],\n",
    "            ['Punt - Fair Catch', 21, 15, 14],\n",
    "            ['Punt - Downed', 5, 5, 4],\n",
    "            ['Punt - Out of Bounds', 1, 4, 4],\n",
    "            ['Punt - Touchback', 2, 2, 2],\n",
    "            ['Punt - Muffed ', 3, 1, 0],\n",
    "            ['Punt - Non-Special Teams Result', 0, 0, 1],\n",
    "            ['Punt - Blocked Punt', 2, 1, 0],\n",
    "            ['Kickoff - Return', 35, 28, 36],\n",
    "            ['Kickoff - Touchback', 49, 46, 44],\n",
    "            ['Kickoff - Out of Bounds', 0, 4, 1],\n",
    "            ['Kickoff - Kickoff Team Recovery', 0, 2, 1],\n",
    "            ['Kickoff - Muffed', 0, 1, 1],\n",
    "            ['Extra Point - Kick Attempt Good', 41, 28, 27],\n",
    "            ['Extra Point - Kick Attempt No Good', 2, 2, 4],\n",
    "            ['Field Goal - Kick Attempt Good ', 23, 28, 32],\n",
    "            ['Field Goal - Kick Attempt No Good', 1, 8, 2]\n",
    "           ]\n",
    "\n",
    "allATLData = pd.DataFrame(ATLData, columns=['ATL Special Play', '2018', '2019', '2020'])\n",
    "\n",
    "# BAL Plot Data\n",
    "BALData = [['Punt - Return', 26, 11, 18],\n",
    "           ['Punt - Fair Catch', 10, 9, 15],\n",
    "           ['Punt - Out of Bounds', 6, 6, 8],\n",
    "           ['Punt - Downed', 7, 5, 4],\n",
    "           ['Punt - Touchback', 3, 4, 1],\n",
    "           ['Punt - Non-Special Teams Result', 1, 2, 0],\n",
    "           ['Punt - Muffed ', 1, 1, 0],\n",
    "           ['Punt - Blocked Punt', 1, 1, 0],\n",
    "           ['Kickoff - Return', 30, 44, 26],\n",
    "           ['Kickoff - Touchback', 56, 54, 65],\n",
    "           ['Kickoff - Muffed', 1, 0, 0],\n",
    "           ['Kickoff - Out of Bounds', 1, 0, 0],\n",
    "           ['Kickoff - Fair Catch', 0, 1, 0],\n",
    "           ['Extra Point - Kick Attempt Good', 35, 52, 44],\n",
    "           ['Extra Point - Kick Attempt No Good', 1, 2, 1],\n",
    "           ['Field Goal - Kick Attempt Good', 34, 28, 24],\n",
    "           ['Field Goal - Kick Attempt No Good', 1, 1, 3],\n",
    "           ['Field Goal - Blocked Kick Attempt', 1, 0, 0],\n",
    "           ['Field Goal - Non-Special Teams Result', 0, 1, 0]\n",
    "           ]\n",
    "\n",
    "allBALData = pd.DataFrame(BALData, columns=['BAL Special Play', '2018', '2019', '2020'])\n",
    "\n",
    "# BUF Plot Data\n",
    "BUFData = [['Punt - Return', 23, 25, 11],\n",
    "           ['Punt - Fair Catch', 16, 15, 5],\n",
    "           ['Punt - Downed', 12, 11, 4],\n",
    "           ['Punt - Out of Bounds', 7, 13, 8],\n",
    "           ['Punt - Touchback', 7, 7, 7],\n",
    "           ['Punt - Muffed', 2, 2, 1],\n",
    "           ['Punt - Non-Special Teams Result', 2, 0, 1],\n",
    "           ['Punt - Blocked Punt', 1, 1, 0],\n",
    "           ['Kickoff - Return', 28, 28, 27],\n",
    "           ['Kickoff - Touchback', 29, 42, 70],\n",
    "           ['Kickoff - Muffed', 1, 0, 0],\n",
    "           ['Extra Point - Kick Attempt Good', 22, 28, 52],\n",
    "           ['Extra Point - Non-Special Teams Result', 1, 0, 0],\n",
    "           ['Extra Point - Kick Attempt No Good', 1, 1, 2],\n",
    "           ['Extra Point - Blocked Kick Attempt', 0, 1, 0],\n",
    "           ['Field Goal - Kick Attempt Good', 20, 22, 22],\n",
    "           ['Field Goal - Kick Attempt No Good', 4, 5, 6],\n",
    "           ['Field Goal - Blocked Kick Attempt', 1, 0, 0],\n",
    "           ['Field Goal - Non-Special Teams Result', 1, 0, 0]\n",
    "           ]\n",
    "\n",
    "allBUFData = pd.DataFrame(BUFData, columns=['BUF Special Play', '2018', '2019', '2020'])\n",
    "\n",
    "# CAR Plot Data\n",
    "CARData = [['Punt - Return', 17, 28, 13],\n",
    "           ['Punt - Fair Catch', 22, 12, 12],\n",
    "           ['Punt - Downed', 6, 6, 5],\n",
    "           ['Punt - Touchback', 4, 1, 3],\n",
    "           ['Punt - Muffed', 2, 3, 3],\n",
    "           ['Punt - Out of Bounds', 3, 6, 1],\n",
    "           ['Punt - Non-Special Teams Result', 0, 2, 3],\n",
    "           ['Kickoff - Touchback', 59, 66, 71],\n",
    "           ['Kickoff - Return', 17, 4, 9],\n",
    "           ['Kickoff - Muffed', 0, 1, 0],\n",
    "           ['Kickoff - Kickoff Team Recovery', 0, 1, 0],\n",
    "           ['Extra Point - Kick Attempt Good', 34, 28, 30],\n",
    "           ['Extra Point - Kick Attempt No Good', 4, 3, 1],\n",
    "           ['Extra Point - Non-Special Teams Result', 1, 0, 0],\n",
    "           ['Extra Point - Blocked Kick Attempt', 0, 0, 1],\n",
    "           ['Field Goal - Kick Attempt Good', 18, 22, 19],\n",
    "           ['Field Goal - Kick Attempt No Good', 2, 5, 6],\n",
    "           ['Field Goal - Blocked Kick Attempt', 0, 1, 1]\n",
    "           ]\n",
    "\n",
    "allCARData = pd.DataFrame(CARData, columns=['CAR Special Play', '2018', '2019', '2020'])\n",
    "\n",
    "# CHI Plot Data\n",
    "CHIData = [['Punt - Return', 15, 24, 21],\n",
    "           ['Punt - Fair Catch', 18, 20, 21],\n",
    "           ['Punt - Downed', 13, 11, 9],\n",
    "           ['Punt - Touchback', 7, 1, 5],\n",
    "           ['Punt - Muffed', 2, 1, 0],\n",
    "           ['Punt - Out of Bounds', 2, 4, 1],\n",
    "           ['Punt - Blocked Punt', 1, 0, 0],\n",
    "           ['Punt - Non-Special Teams Result', 1, 0, 1],\n",
    "           ['Kickoff - Touchback', 65, 31, 42],\n",
    "           ['Kickoff - Return', 19, 25, 41],\n",
    "           ['Kickoff - Out of Bounds', 1, 3, 0],\n",
    "           ['Kickoff - Kickoff Team Recovery', 1, 1, 0],\n",
    "           ['Extra Point - Kick Attempt Good', 41, 24, 30],\n",
    "           ['Extra Point - Kick Attempt No Good', 3, 2, 1],\n",
    "           ['Field Goal - Kick Attempt Good', 23, 20, 27],\n",
    "           ['Field Goal - Kick Attempt No Good', 7, 4, 2]\n",
    "           ]\n",
    "\n",
    "allCHIData = pd.DataFrame(CHIData, columns=['CHI Special Play', '2018', '2019', '2020'])\n",
    "\n",
    "# CIN Plot Data\n",
    "CINData = [['Punt - Return', 20, 17, 22],\n",
    "           ['Punt - Fair Catch', 21, 21, 16],\n",
    "           ['Punt - Downed', 9, 5, 13],\n",
    "           ['Punt - Non-Special Teams Result', 2, 0, 2],\n",
    "           ['Punt - Touchback', 2, 4, 7],\n",
    "           ['Punt - Out of Bounds', 2, 6, 3],\n",
    "           ['Punt - Blocked Punt', 1, 0, 0],\n",
    "           ['Kickoff - Return', 27, 17, 16],\n",
    "           ['Kickoff - Touchback', 44, 46, 56],\n",
    "           ['Kickoff - Out of Bounds', 1, 0, 1],\n",
    "           ['Kickoff - Fair Catch', 1, 0, 0],\n",
    "           ['Kickoff - Kickoff Team Recover', 0, 1, 0],\n",
    "           ['Extra Point - Kick Attempt Good', 37, 21, 27],\n",
    "           ['Extra Point - Kick Attempt No Good', 2, 1, 1],\n",
    "           ['Field Goal - Kick Attempt Good', 17, 26, 26],\n",
    "           ['Field Goal - Kick Attempt No Good', 2, 4, 7]\n",
    "           ]\n",
    "\n",
    "allCINData = pd.DataFrame(CINData, columns=['CIN Special Play', '2018', '2019', '2020'])\n",
    "\n",
    "# CLE Plot Data\n",
    "CLEData = [['Punt - Return', 28, 15, 18],\n",
    "           ['Punt - Fair Catch', 20, 15, 13],\n",
    "           ['Punt - Downed', 10, 10, 4],\n",
    "           ['Punt - Touchback', 6, 3, 2],\n",
    "           ['Punt - Out of Bounds', 6, 7, 3],\n",
    "           ['Punt - Muffed', 2, 0, 0],\n",
    "           ['Punt - Blocked Punt', 2, 1, 0],\n",
    "           ['Punt - Non-Special Teams Result', 0, 0, 1],\n",
    "           ['Kickoff - Touchback', 52, 30, 43],\n",
    "           ['Kickoff - Return', 21, 41, 36],\n",
    "           ['Kickoff - Kickoff Team Recovery', 1, 0, 0],\n",
    "           ['Kickoff - Out of Bounds', 1, 2, 1],\n",
    "           ['Extra Point - Kick Attempt Good', 27, 28, 38],\n",
    "           ['Extra Point - Kick Attempt No Good', 6, 5, 5],\n",
    "           ['Field Goal - Kick Attempt Good', 15, 22, 18],\n",
    "           ['Field Goal - Kick Attempt No Good', 5, 4, 3],\n",
    "           ['Field Goal - Blocked Kick Attempt', 1, 0, 1]\n",
    "           ]\n",
    "\n",
    "allCLEData = pd.DataFrame(CLEData, columns=['CLE Special Play', '2018', '2019', '2020'])\n",
    "\n",
    "# DAL Plot Data\n",
    "DALData = [['Punt - Return', 25, 12, 11],\n",
    "           ['Punt - Fair Catch', 14, 15, 25],\n",
    "           ['Punt - Downed', 9, 8, 0],\n",
    "           ['Punt - Out of Bounds', 3, 3, 2],\n",
    "           ['Punt - Non-Special Teams Result', 1, 0, 3],\n",
    "           ['Punt - Muffed', 1, 3, 1],\n",
    "           ['Punt - Touchback', 1, 2, 3],\n",
    "           ['Punt - Blocked Punt', 0, 1, 0],\n",
    "           ['Kickoff - Touchback', 50, 49, 53],\n",
    "           ['Kickoff - Return', 23, 34, 30],\n",
    "           ['Kickoff - Muffed', 1, 0, 0],\n",
    "           ['Kickoff - Out of Bounds', 0, 3, 0],\n",
    "           ['Kickoff - Kickoff Team Recovery', 0, 0, 1],\n",
    "           ['Extra Point - Kick Attempt Good', 31, 42, 28],\n",
    "           ['Extra Point - Kick Attempt No Good', 1, 0, 1],\n",
    "           ['Extra Point - Blocked Kick Attempt', 0, 0, 1],\n",
    "           ['Field Goal - Kick Attempt Good', 28, 27, 30],\n",
    "           ['Field Goal - Kick Attempt No Good', 6, 7, 6],\n",
    "           ['Field Goal - Blocked Kick Attempt', 1, 1, 0]\n",
    "           ]\n",
    "\n",
    "allDALData = pd.DataFrame(DALData, columns=['DAL Special Play', '2018', '2019', '2020'])\n",
    "\n",
    "# DEN Plot Data\n",
    "DENData = [['Punt - Return', 24, 17, 21],\n",
    "           ['Punt - Fair Catch', 17, 13, 13],\n",
    "           ['Punt - Out of Bounds', 11, 12, 11],\n",
    "           ['Punt - Touchback', 8, 4, 4],\n",
    "           ['Punt - Downed', 6, 7, 2],\n",
    "           ['Punt - Muffed', 2, 5, 1],\n",
    "           ['Punt - Non-Special Teams Result', 1, 1, 1],\n",
    "           ['Kickoff - Return', 25, 13, 23],\n",
    "           ['Kickoff - Touchback', 37, 54, 54],\n",
    "           ['Kickoff - Out of Bounds', 1, 0, 0],\n",
    "           ['Extra Point - Kick Attempt Good', 30, 23, 22],\n",
    "           ['Extra Point - Kick Attempt No Good', 0, 1, 4],\n",
    "           ['Field Goal - Kick Attempt Good', 17, 26, 27],\n",
    "           ['Field Goal - Kick Attempt No Good', 3, 3, 5],\n",
    "           ['Field Goal - Blocked Kick Attempt', 0, 0, 2]\n",
    "           ]\n",
    "\n",
    "allDENData = pd.DataFrame(DENData, columns=['DEN Special Play', '2018', '2019', '2020'])\n",
    "\n",
    "# DET Plot Data\n",
    "DETData = [['Punt - Return', 22, 17, 19],\n",
    "           ['Punt - Fair Catch', 23, 14, 15],\n",
    "           ['Punt - Downed', 12, 11, 10],\n",
    "           ['Punt - Touchback', 4, 7, 5],\n",
    "           ['Punt - Out of Bounds', 3, 4, 4],\n",
    "           ['Punt - Muffed', 1, 1, 0],\n",
    "           ['Punt - Non-Special Teams Result', 1, 0, 1],\n",
    "           ['Kickoff - Return', 27, 46, 46],\n",
    "           ['Kickoff - Touchback', 36, 2, 26],\n",
    "           ['Kickoff - Muffed', 4, 1, 0],\n",
    "           ['Kickoff - Kickoff Team Recovery', 1, 1, 0],\n",
    "           ['Kickoff - Out of Bounds', 0, 1, 2],\n",
    "           ['Extra Point - Kick Attempt Good', 29, 33, 33],\n",
    "           ['Extra Point - Non-Special Teams Result', 1, 0, 0],\n",
    "           ['Extra Point - Kick Attempt No Good', 0, 1, 3],\n",
    "           ['Field Goal - Kick Attempt Good', 78, 21, 18],\n",
    "           ['Field Goal - Kick Attempt No Good', 12, 4, 5],\n",
    "           ['Field Goal - Non-Special Teams Result', 7, 0, 0]\n",
    "           ]\n",
    "\n",
    "allDETData = pd.DataFrame(DETData, columns=['DET Special Play', '2018', '2019', '2020'])\n",
    "\n",
    "# GB Plot Data\n",
    "GBData = [['Punt - Fair Catch', 27, 21, 10],\n",
    "          ['Punt - Return', 14, 16, 12],\n",
    "          ['Punt - Downed', 10, 10, 6],\n",
    "          ['Punt - Touchback', 7, 3, 2],\n",
    "          ['Punt - Out of Bounds', 3, 12, 9],\n",
    "          ['Punt - Blocked Punt', 1, 0, 0],\n",
    "          ['Punt - Non-Special Teams Result', 1, 0, 0],\n",
    "          ['Punt - Muffed', 1, 1, 1],\n",
    "          ['Kickoff - Return', 37, 24, 41],\n",
    "          ['Kickoff - Touchback', 40, 48, 51],\n",
    "          ['Kickoff - Muffed', 1, 1, 0],\n",
    "          ['Kickoff - Out of Bounds', 0, 1, 1],\n",
    "          ['Extra Point - Kick Attempt Good', 34, 34, 56],\n",
    "          ['Extra Point - Kick Attempt No Good', 2, 1, 3],\n",
    "          ['Field Goal - Kick Attempt Good', 28, 19, 15],\n",
    "          ['Field Goal - Kick Attempt No Good', 6, 2, 0],\n",
    "          ['Field Goal - Non-Special Teams Result', 1, 0, 0]\n",
    "          ]\n",
    "\n",
    "allGBData = pd.DataFrame(GBData, columns=['GB Special Play', '2018', '2019', '2020'])\n",
    "\n",
    "# HOU Plot Data\n",
    "HOUData = [['Punt - Return', 20, 18, 15],\n",
    "           ['Punt - Fair Catch', 20, 18, 18],\n",
    "           ['Punt - Muffed', 5, 0, 0],\n",
    "           ['Punt - Downed', 6, 9, 4],\n",
    "           ['Punt - Out of Bounds', 5, 1, 3],\n",
    "           ['Punt - Touchback', 3, 0, 6],\n",
    "           ['Punt - Non-Special Teams Result', 0, 1, 1],\n",
    "           ['Kickoff - Touchback', 56, 41, 51],\n",
    "           ['Kickoff - Return', 29, 31, 27],\n",
    "           ['Kickoff - Muffed', 3, 2, 2],\n",
    "           ['Kickoff - Kickoff Team Recovery', 0, 1, 1],\n",
    "           ['Extra Point - Kick Attempt Good', 38, 34, 33],\n",
    "           ['Extra Point - Kick Attempt No Good', 2, 3, 2],\n",
    "           ['Extra Point - Blocked Kick Attempt', 0, 1, 0],\n",
    "           ['Field Goal - Kick Attempt Good', 34, 19, 25],\n",
    "           ['Field Goal - Kick Attempt No Good', 5, 5, 3],\n",
    "           ['Field Goal - Out of Bounds', 0, 1, 0],\n",
    "           ['Field Goal - Downed', 0, 0, 1]\n",
    "           ]\n",
    "\n",
    "allHOUData = pd.DataFrame(HOUData, columns=['HOU Special Play', '2018', '2019', '2020'])\n",
    "\n",
    "# IND Plot Data\n",
    "INDData = [['Punt - Return', 14, 18, 21],\n",
    "           ['Punt - Fair Catch', 18, 12, 7],\n",
    "           ['Punt - Downed', 8, 8, 5],\n",
    "           ['Punt - Muffed', 3, 1, 0],\n",
    "           ['Punt - Touchback', 4, 1, 5],\n",
    "           ['Punt - Out of Bounds', 3, 5, 3],\n",
    "           ['Punt - Blocked Punt', 0, 0, 1],\n",
    "           ['Kickoff - Touchback', 51, 58, 46],\n",
    "           ['Kickoff - Return', 23, 18, 45],\n",
    "           ['Extra Point - Kick Attempt Good', 42, 32, 40],\n",
    "           ['Extra Point - Kick Attempt No Good', 2, 5, 2],\n",
    "           ['Extra Point - Blocked Kick Attempt', 0, 1, 0],\n",
    "           ['Field Goal - Kick Attempt Good', 22, 21, 30],\n",
    "           ['Field Goal - Kick Attempt No Good', 4, 6, 5],\n",
    "           ['Field Goal - Blocked Kick Attempt', 0, 2, 0]\n",
    "           ]\n",
    "\n",
    "allINDData = pd.DataFrame(INDData, columns=['IND Special Play', '2018', '2019', '2020'])\n",
    "\n",
    "# JAX Plot Data\n",
    "JAXData = [['Punt - Return', 25, 15, 19],\n",
    "           ['Punt - Fair Catch', 17, 23, 11],\n",
    "           ['Punt - Downed', 10, 10, 12],\n",
    "           ['Punt - Out of Bounds', 11, 9, 7],\n",
    "           ['Punt - Muffed', 5, 4, 0],\n",
    "           ['Punt - Touchback', 7, 2, 4],\n",
    "           ['Punt - Non-Special Teams Result', 1, 2, 0],\n",
    "           ['Kickoff - Touchback', 38, 39, 40],\n",
    "           ['Kickoff - Return', 17, 33, 27],\n",
    "           ['Kickoff - Kickoff Team Recovery', 1, 0, 0],\n",
    "           ['Kickoff - Muffed', 0, 0, 2],\n",
    "           ['Kickoff - Out of Bounds', 0, 0, 2],\n",
    "           ['Extra Point - Kick Attempt Good', 20, 19, 21],\n",
    "           ['Extra Point - Kick Attempt No Good', 0, 1, 3],\n",
    "           ['Field Goal - Kick Attempt Good', 22, 30, 16],\n",
    "           ['Field Goal - Kick Attempt No Good', 3, 1, 6],\n",
    "           ['Field Goal - Non-Special Teams Result', 1, 1, 0]\n",
    "           ]\n",
    "\n",
    "allJAXData = pd.DataFrame(JAXData, columns=['JAX Special Play', '2018', '2019', '2020'])\n",
    "\n",
    "# KC Plot Data\n",
    "KCData = [['Punt - Return', 11, 13, 12],\n",
    "          ['Punt - Fair Catch', 10, 9, 11],\n",
    "          ['Punt - Downed', 7, 10, 5],\n",
    "          ['Punt - Touchback', 3, 3, 4],\n",
    "          ['Punt - Muffed', 1, 3, 1],\n",
    "          ['Punt - Out of Bounds', 1, 0, 6],\n",
    "          ['Punt - Blocked Punt', 0, 1, 0],\n",
    "          ['Punt - Non-Special Teams Result', 0, 0, 1],\n",
    "          ['Kickoff - Touchback', 67, 60, 70],\n",
    "          ['Kickoff - Return', 25, 30, 19],\n",
    "          ['Kickoff - Out of Bounds', 3, 0, 2],\n",
    "          ['Extra Point - Kick Attempt Good', 58, 42, 43],\n",
    "          ['Extra Point - Kick Attempt No Good', 3, 3, 4],\n",
    "          ['Extra Point - Blocked Kick Attempt', 1, 0, 1],\n",
    "          ['Extra Point - Non-Special Teams Result', 0, 1, 0],\n",
    "          ['Field Goal - Kick Attempt Good', 23, 32, 22],\n",
    "          ['Field Goal - Kick Attempt No Good', 3, 2, 2],\n",
    "          ['Field Goal - Blocked Kick Attempt', 0, 1, 0]\n",
    "          ]\n",
    "\n",
    "allKCData = pd.DataFrame(KCData, columns=['KC Special Play', '2018', '2019', '2020'])\n",
    "\n",
    "\n",
    "# LA Plot Data\n",
    "LAData = [['Punt - Return', 11, 18, 21],\n",
    "          ['Punt - Downed', 10, 8, 9],\n",
    "          ['Punt - Out of Bounds', 9, 13, 11],\n",
    "          ['Punt - Fair Catch', 7, 13, 20],\n",
    "          ['Punt - Non-Special Teams Result', 4, 4, 0],\n",
    "          ['Punt - Touchback', 2, 3, 5],\n",
    "          ['Punt - Blocked Punt', 0, 1, 1],\n",
    "          ['Punt - Muffed', 0, 1, 1],\n",
    "          ['Kickoff - Touchback', 76, 63, 53],\n",
    "          ['Kickoff - Return', 26, 15, 23],\n",
    "          ['Kickoff - Out of Bounds', 0, 3, 1],\n",
    "          ['Kickoff - Muffed', 0, 1, 1],\n",
    "          ['Extra Point - Kick Attempt Good', 50, 41, 32],\n",
    "          ['Extra Point - Kick Attempt No Good', 2, 0, 2],\n",
    "          ['Extra Point - Blocked Kick Attempt', 0, 0, 2],\n",
    "          ['Field Goal - Kick Attempt Good', 33, 20, 18],\n",
    "          ['Field Goal - Kick Attempt No Good', 7, 6, 4],\n",
    "          ['Field Goal - Non-Special Teams Result', 1, 0, 0],\n",
    "          ['Field Goal - Blocked Kick Attempt', 0, 1, 1]\n",
    "          ]\n",
    "\n",
    "allLAData = pd.DataFrame(LAData, columns=['LA Special Play', '2018', '2019', '2020'])\n",
    "\n",
    "# LAC Plot Data\n",
    "LACData = [['Punt - Return', 17, 28, 30],\n",
    "           ['Punt - Fair Catch', 11, 6, 7],\n",
    "           ['Punt - Out of Bounds', 6, 1, 5],\n",
    "           ['Punt - Downed', 5, 2, 3],\n",
    "           ['Punt - Muffed', 3, 0, 1],\n",
    "           ['Punt - Touchback', 3, 2, 3],\n",
    "           ['Punt - Blocked Punt', 1, 0, 3],\n",
    "           ['Punt - Non-Special Teams Result', 0, 0, 1],\n",
    "           ['Kickoff - Return', 48, 33, 34],\n",
    "           ['Kickoff - Touchback', 23, 35, 48],\n",
    "           ['Extra Point - Kick Attempt Good', 36, 32, 35],\n",
    "           ['Extra Point - Kick Attempt No Good', 7, 0, 3],\n",
    "           ['Field Goal - Kick Attempt Good', 21, 24, 20],\n",
    "           ['Field Goal - Kick Attempt No Good', 4, 6, 8],\n",
    "           ['Field Goal - Blocked Kick Attempt', 0, 1, 1]\n",
    "          ]\n",
    "\n",
    "allLACData = pd.DataFrame(LACData, columns=['LAC Special Play', '2018', '2019', '2020'])\n",
    "\n",
    "# MIA Plot Data\n",
    "MIAData = [['Punt - Return', 23, 26, 17],\n",
    "           ['Punt - Fair Catch', 23, 15, 17],\n",
    "           ['Punt - Downed', 8, 12, 14],\n",
    "           ['Punt - Out of Bounds', 6, 5, 5],\n",
    "           ['Punt - Touchback', 5, 2, 1],\n",
    "           ['Punt - Muffed', 2, 0, 2],\n",
    "           ['Punt - Blocked Punt', 1, 0, 0],\n",
    "           ['Punt - Non-Special Teams Result', 1, 3, 1],\n",
    "           ['Kickoff - Touchback', 53, 46, 64],\n",
    "           ['Kickoff - Return', 8, 20, 22],\n",
    "           ['Kickoff - Out of Bounds', 1, 0, 1],\n",
    "           ['Kickoff - Muffed', 0, 1, 1],\n",
    "           ['Kickoff - Kickoff Team Recovery', 0, 1, 0],\n",
    "           ['Kickoff - Fair Catch', 0, 1, 0],\n",
    "           ['Extra Point - Kick Attempt Good', 29, 27, 29],\n",
    "           ['Extra Point - Kick Attempt No Good', 1, 1, 0],\n",
    "           ['Field Goal - Kick Attempt Good', 17, 21, 32],\n",
    "           ['Field Goal - Kick Attempt No Good', 2, 7, 3],\n",
    "           ['Field Goal - Non-Special Teams Result', 0, 2, 0]\n",
    "          ]\n",
    "\n",
    "allMIAData = pd.DataFrame(MIAData, columns=['MIA Special Play', '2018', '2019', '2020'])\n",
    "\n",
    "# MIN Plot Data\n",
    "MINData = [['Punt - Return', 17, 16, 19],\n",
    "           ['Punt - Fair Catch', 16, 16, 10],\n",
    "           ['Punt - Downed', 7, 5, 6],\n",
    "           ['Punt - Out of Bounds', 7, 6, 1],\n",
    "           ['Punt - Muffed', 4, 2, 1],\n",
    "           ['Punt - Touchback', 2, 0, 3],\n",
    "           ['Punt - Blocked Punt', 1, 0, 1],\n",
    "           ['Kickoff - Return', 29, 20, 28],\n",
    "           ['Kickoff - Touchback', 38, 64, 50],\n",
    "           ['Kickoff - Out of Bounds', 1, 0, 0],\n",
    "           ['Kickoff - Muffed', 0, 0, 1],\n",
    "           ['Extra Point - Kick Attempt Good', 31, 37, 27],\n",
    "           ['Extra Point - Kick Attempt No Good', 1, 3, 3],\n",
    "           ['Extra Point - Blocked Kick Attempt', 0, 1, 0],\n",
    "           ['Extra Point - Non-Special Teams Result', 0, 0, 1],\n",
    "           ['Field Goal - Kick Attempt Good', 21, 0, 0],\n",
    "           ['Field Goal - Kick Attempt No Good', 9, 25, 13],\n",
    "           ['Field Goal - Blocked Kick Attempt', 1, 2, 4]\n",
    "          ]\n",
    "\n",
    "allMINData = pd.DataFrame(MINData, columns=['MIN Special Play', '2018', '2019', '2020'])\n",
    "\n",
    "# NE Plot Data\n",
    "NEData = [['Punt - Return', 22, 15, 9],\n",
    "          ['Punt - Downed', 14, 10, 14],\n",
    "          ['Punt - Out of Bounds', 8, 15, 3],\n",
    "          ['Punt - Fair Catch', 6, 17, 15],\n",
    "          ['Punt - Touchback', 5, 6, 5],\n",
    "          ['Punt - Muffed', 0, 3, 1],\n",
    "          ['Kickoff - Return', 36, 25, 30],\n",
    "          ['Kickoff - Touchback', 45, 58, 42],\n",
    "          ['Kickoff - Muffed', 1, 3, 1],\n",
    "          ['Kickoff - Fair Catch', 1, 0, 0],\n",
    "          ['Kickoff - Out of Bounds', 0, 3, 0],\n",
    "          ['Extra Point - Kick Attempt Good', 43, 34, 28],\n",
    "          ['Extra Point - Kick Attempt No Good', 1, 6, 3],\n",
    "          ['Field Goal - Kick Attempt Good', 27, 26, 24],\n",
    "          ['Field Goal - Kick Attempt No Good', 4, 5, 1],\n",
    "          ['Field Goal - Blocked Kick Attempt', 0, 2, 0]\n",
    "          ]\n",
    "\n",
    "allNEData = pd.DataFrame(NEData, columns=['NE Special Play', '2018', '2019', '2020'])\n",
    "\n",
    "# NO Plot Data\n",
    "NOData = [['Punt - Return', 9, 19, 17],\n",
    "          ['Punt - Fair Catch', 13, 17, 25],\n",
    "          ['Punt - Out of Bounds', 7, 6, 6],\n",
    "          ['Punt - Downed', 3, 6, 5],\n",
    "          ['Punt - Non-Special Teams Result', 2, 2, 0],\n",
    "          ['Punt - Touchback', 2, 1, 2],\n",
    "          ['Punt - Muffed', 0, 1, 2],\n",
    "          ['Kickoff - Touchback', 63, 73, 70],\n",
    "          ['Kickoff - Return', 31, 16, 20],\n",
    "          ['Kickoff - Muffed', 0, 0, 1],\n",
    "          ['Kickoff - Out of Bounds', 0, 0, 1],\n",
    "          ['Extra Point - Kick Attempt Good', 48, 44, 49],\n",
    "          ['Extra Point - Kick Attempt No Good', 1, 0, 1],\n",
    "          ['Field Goal - Kick Attempt Good', 25, 29, 22],\n",
    "          ['Field Goal - Blocked Kick Attempt', 1, 3, 5]\n",
    "          ]\n",
    "\n",
    "allNOData = pd.DataFrame(NOData, columns=['NO Special Play', '2018', '2019', '2020'])\n",
    "\n",
    "# NYG Plot Data\n",
    "NYGData = [['Punt - Return', 19, 18, 19],\n",
    "           ['Punt - Downed', 13, 13, 13],\n",
    "           ['Punt - Fair Catch', 13, 13, 14],\n",
    "           ['Punt - Out of Bounds', 9, 8, 2],\n",
    "           ['Punt - Muffed', 3, 0, 2],\n",
    "           ['Punt - Blocked Punt', 0, 2, 1],\n",
    "           ['Punt - Touchback', 4, 2, 5],\n",
    "           ['Punt - Non-Special Teams Result', 1, 0, 0],\n",
    "           ['Kickoff - Touchback', 49, 50, 30],\n",
    "           ['Kickoff - Return', 26, 14, 39],\n",
    "           ['Kickoff - Muffed', 2, 3, 0],\n",
    "           ['Kickoff - Out of Bounds', 3, 2, 0],\n",
    "           ['Kickoff - Kickoff Team Recovery', 1, 0, 0],\n",
    "           ['Extra Point - Kick Attempt Good', 28, 30, 18],\n",
    "           ['Extra Point - Kick Attempt No Good', 1, 4, 2],\n",
    "           ['Extra Point - Non-Special Teams Result', 0, 1, 0],\n",
    "           ['Field Goal - Kick Attempt Good', 30, 8, 29],\n",
    "           ['Field Goal - Kick Attempt No Good', 1, 4, 1],\n",
    "           ['Field Goal - Non-Special Teams Result', 0, 0, 1]\n",
    "           ]\n",
    "\n",
    "allNYGData = pd.DataFrame(NYGData, columns=['NYG Special Play', '2018', '2019', '2020'])\n",
    "\n",
    "\n",
    "# NYJ Plot Data\n",
    "NYJData = [['Punt - Return', 32, 33, 29],\n",
    "           ['Punt - Fair Catch', 13, 13, 16],\n",
    "           ['Punt - Downed', 10, 16, 7],\n",
    "           ['Punt - Out of Bounds', 8, 8, 7],\n",
    "           ['Punt - Touchback', 5, 0, 3],\n",
    "           ['Punt - Muffed', 2, 5, 0],\n",
    "           ['Punt - Non-Special Teams Result', 1, 0, 0],\n",
    "           ['Kickoff - Touchback', 58, 32, 33],\n",
    "           ['Kickoff - Return', 19, 30, 22],\n",
    "           ['Kickoff - Muffed', 0, 1, 0],\n",
    "           ['Kickoff - Out of Bounds', 0, 0, 1],\n",
    "           ['Extra Point - Kick Attempt Good', 28, 21, 15],\n",
    "           ['Extra Point - Kick Attempt No Good', 3, 4, 3],\n",
    "           ['Extra Point - Blocked Kick Attempt', 0, 0, 1],\n",
    "           ['Field Goal - Kick Attempt Good', 32, 16, 21],\n",
    "           ['Field Goal - Kick Attempt No Good', 3, 6, 5],\n",
    "           ['Field Goal - Blocked Kick Attempt', 0, 0, 2]\n",
    "           ]\n",
    "\n",
    "allNYJData = pd.DataFrame(NYJData, columns=['NYJ Special Play', '2018', '2019', '2020'])\n",
    "\n",
    "\n",
    "# OAK Plot Data\n",
    "OAKData = [['Punt - Return', 19, 20, 9],\n",
    "           ['Punt - Fair Catch', 16, 16, 14],\n",
    "           ['Punt - Downed', 7, 8, 5],\n",
    "           ['Punt - Out of Bounds', 5, 3, 5],\n",
    "           ['Punt - Touchback', 4, 6, 2],\n",
    "           ['Punt - Non-Special Teams Result', 1, 1, 1],\n",
    "           ['Punt - Muffed', 0, 1, 2],\n",
    "           ['Kickoff - Return', 32, 30, 26],\n",
    "           ['Kickoff - Touchback', 28, 37, 61],\n",
    "           ['Kickoff - Muffed', 1, 0, 0],\n",
    "           ['Kickoff - Out of Bounds', 1, 0, 0],\n",
    "           ['Extra Point - Kick Attempt Good', 26, 29, 28],\n",
    "           ['Extra Point - Blocked Kick Attempt', 1, 1, 2],\n",
    "           ['Extra Point - Kick Attempt No Good', 0, 1, 0],\n",
    "           ['Field Goal - Kick Attempt Good', 25, 19, 31],\n",
    "           ['Field Goal - Kick Attempt No Good', 4, 7, 2],\n",
    "           ['Field Goal - Non-Special Teams Result', 0, 0, 1]\n",
    "           ]\n",
    "\n",
    "allOAKData = pd.DataFrame(OAKData, columns=['OAK Special Play', '2018', '2019', '2020'])\n",
    "\n",
    "# PHI Plot Data\n",
    "PHIData = [['Punt - Return', 22, 21, 34],\n",
    "           ['Punt - Fair Catch', 15, 17, 9],\n",
    "           ['Punt - Touchback', 6, 4, 5],\n",
    "           ['Punt - Downed', 4, 7, 4],\n",
    "           ['Punt - Muffed', 1, 0, 2],\n",
    "           ['Punt - Out of Bounds', 2, 6, 6],\n",
    "           ['Punt - Blocked Punt', 0, 0, 1],\n",
    "           ['Kickoff - Touchback', 55, 49, 42],\n",
    "           ['Kickoff - Return', 23, 28, 27],\n",
    "           ['Kickoff - Muffed', 0, 1, 0],\n",
    "           ['Extra Point - Kick Attempt Good', 28, 31, 21],\n",
    "           ['Extra Point - Kick Attempt No Good', 2, 1, 2],\n",
    "           ['Extra Point - Non-Special Teams Result', 0, 0, 1],\n",
    "           ['Field Goal - Kick Attempt Good', 26, 19, 8],\n",
    "           ['Field Goal - Kick Attempt No Good', 5, 4, 3],\n",
    "           ['Field Goal - Non-Special Teams Result', 0, 1, 0]\n",
    "           ]\n",
    "\n",
    "allPHIData = pd.DataFrame(PHIData, columns=['PHI Special Play', '2018', '2019', '2020'])\n",
    "\n",
    "# PIT Plot Data\n",
    "PITData = [['Punt - Fair Catch', 18, 22, 24],\n",
    "           ['Punt - Return', 11, 25, 21],\n",
    "           ['Punt - Downed', 11, 10, 5],\n",
    "           ['Punt - Out of Bounds', 6, 5, 5],\n",
    "           ['Punt - Touchback', 4, 4, 5],\n",
    "           ['Punt - Non-Special Teams Result', 1, 2, 0],\n",
    "           ['Punt - Muffed', 0, 0, 1],\n",
    "           ['Kickoff - Touchback', 48, 36, 43],\n",
    "           ['Kickoff - Return', 25, 31, 38],\n",
    "           ['Kickoff - Muffed', 0, 2, 1],\n",
    "           ['Kickoff - Out of Bounds', 0, 0, 1],\n",
    "           ['Extra Point - Kick Attempt Good', 42, 27, 37],\n",
    "           ['Extra Point - Kick Attempt No Good', 4, 0, 3],\n",
    "           ['Extra Point - Blocked Kick Attempt', 0, 0, 1],\n",
    "           ['Field Goal - Kick Attempt Good', 15, 26, 21],\n",
    "           ['Field Goal - Kick Attempt No Good', 5, 2, 0],\n",
    "           ['Field Goal - Blocked Kick Attempt', 1, 0, 0]\n",
    "           ]\n",
    "\n",
    "allPITData = pd.DataFrame(PITData, columns=['PIT Special Play', '2018', '2019', '2020'])\n",
    "\n",
    "# SEA Plot Data\n",
    "SEAData = [['Punt - Return', 25, 25, 21],\n",
    "           ['Punt - Downed', 10, 8, 7],\n",
    "           ['Punt - Out of Bounds', 11, 8, 3],\n",
    "           ['Punt - Fair Catch', 9, 15, 12],\n",
    "           ['Punt - Touchback', 5, 2, 6],\n",
    "           ['Punt - Muffed', 2, 0, 1],\n",
    "           ['Punt - Non-Special Teams Result', 1, 1, 0],\n",
    "           ['Punt - Blocked Punt', 1, 0, 0],\n",
    "           ['Kickoff - Return', 32, 21, 37],\n",
    "           ['Kickoff - Touchback', 36, 59, 50],\n",
    "           ['Kickoff - Muffed', 1, 2, 1],\n",
    "           ['Kickoff - Out of Bounds', 1, 0, 0],\n",
    "           ['Kickoff - Fair Catch', 0, 1, 0],\n",
    "           ['Extra Point - Kick Attempt Good', 43, 36, 40],\n",
    "           ['Extra Point - Kick Attempt No Good', 3, 4, 4],\n",
    "           ['Field Goal - Kick Attempt Good', 20, 20, 19],\n",
    "           ['Field Goal - Kick Attempt No Good', 4, 4, 0]\n",
    "           ]\n",
    "\n",
    "allSEAData = pd.DataFrame(SEAData, columns=['SEA Special Play', '2018', '2019', '2020'])\n",
    "\n",
    "# SF Plot Data\n",
    "SFData = [['Punt - Fair Catch', 24, 10, 24],\n",
    "          ['Punt - Return', 14, 16, 19],\n",
    "          ['Punt - Out of Bounds', 7, 5, 4],\n",
    "          ['Punt - Touchback', 4, 2, 5],\n",
    "          ['Punt - Muffed', 1, 2, 2],\n",
    "          ['Punt - Downed', 2, 7, 4],\n",
    "          ['Punt - Blocked Punt', 1, 0, 0],\n",
    "          ['Kickoff - Touchback', 45, 47, 43],\n",
    "          ['Kickoff - Return', 23, 36, 34],\n",
    "          ['Kickoff - Muffed', 1, 1, 0],\n",
    "          ['Kickoff - Out of Bounds', 0, 1, 0],\n",
    "          ['Extra Point - Kick Attempt Good', 24, 36, 33],\n",
    "          ['Extra Point - Kick Attempt No Good', 2, 1, 1],\n",
    "          ['Extra Point - Non-Special Teams Result', 1, 1, 1],\n",
    "          ['Extra Point - Blocked Kick Attempt', 0, 0, 1],\n",
    "          ['Field Goal - Kick Attempt Good', 30, 23, 18],\n",
    "          ['Field Goal - Kick Attempt No Good', 1, 6, 4],\n",
    "          ['Field Goal - Blocked Kick Attempt', 0, 2, 0]\n",
    "          ]\n",
    "\n",
    "allSFData = pd.DataFrame(SFData, columns=['SF Special Play', '2018', '2019', '2020'])\n",
    "\n",
    "# TB Plot Data\n",
    "TBData = [['Punt - Return', 19, 16, 20],\n",
    "          ['Punt - Fair Catch', 15, 12, 13],\n",
    "          ['Punt - Downed', 7, 8, 6],\n",
    "          ['Punt - Touchback', 3, 3, 2],\n",
    "          ['Punt - Out of Bounds', 3, 1, 7],\n",
    "          ['Punt - Muffed', 2, 4, 1],\n",
    "          ['Punt - Non-Special Teams Result', 1, 0, 0],\n",
    "          ['Punt - Blocked Punt', 1, 0, 0],\n",
    "          ['Kickoff - Return', 38, 4, 13],\n",
    "          ['Kickoff - Touchback', 48, 85, 85],\n",
    "          ['Kickoff - Muffed', 2, 1, 1],\n",
    "          ['Kickoff - Out of Bounds', 0, 1, 1],\n",
    "          ['Extra Point - Kick Attempt Good', 36, 41, 43],\n",
    "          ['Extra Point - Kick Attempt No Good', 4, 3, 3],\n",
    "          ['Extra Point - Non-Special Teams Result', 1, 0, 0],\n",
    "          ['Extra Point - Blocked Kick Attempt', 0, 2, 2],\n",
    "          ['Field Goal - Kick Attempt Good', 18, 25, 25],\n",
    "          ['Field Goal - Kick Attempt No Good', 6, 6, 2],\n",
    "          ['Field Goal - Blocked Kick Attempt', 0, 1, 1]\n",
    "          ]\n",
    "\n",
    "allTBData = pd.DataFrame(TBData, columns=['TB Special Play', '2018', '2019', '2020'])\n",
    "\n",
    "# TEN Plot Data\n",
    "TENData = [['Punt - Return', 24, 23, 16],\n",
    "           ['Punt - Out of Bounds', 12, 16, 6],\n",
    "           ['Punt - Fair Catch', 12, 18, 11],\n",
    "           ['Punt - Downed', 6, 9, 5],\n",
    "           ['Punt - Touchback', 2, 2, 4],\n",
    "           ['Punt - Blocked Punt', 1, 0, 1],\n",
    "           ['Punt - Non-Special Teams Result', 0, 2, 1],\n",
    "           ['Punt - Muffed', 0, 1, 0],\n",
    "           ['Kickoff - Touchback', 44, 38, 51],\n",
    "           ['Kickoff - Return', 25, 32, 35],\n",
    "           ['Kickoff - Muffed', 0, 1, 1],\n",
    "           ['Kickoff - Out of Bounds', 0, 0, 2],\n",
    "           ['Extra Point - Kick Attempt Good', 26, 46, 44],\n",
    "           ['Extra Point - Blocked Kick Attempt', 1, 0, 0],\n",
    "           ['Extra Point - Kick Attempt No Good', 2, 2, 0],\n",
    "           ['Extra Point - Non-Special Teams Result', 0, 0, 1],\n",
    "           ['Field Goal - Kick Attempt Good', 24, 5, 20],\n",
    "           ['Field Goal - Kick Attempt No Good', 3, 7, 6],\n",
    "           ['Field Goal - Blocked Kick Attempt', 0, 2, 2],\n",
    "           ['Field Goal - Non-Special Teams Result', 0, 1, 0]\n",
    "          ]\n",
    "\n",
    "allTENData = pd.DataFrame(TENData, columns=['TEN Special Play', '2018', '2019', '2020'])\n",
    "\n",
    "# WAS Plot Data\n",
    "WASData = [['Punt - Return', 25, 31, 28],\n",
    "           ['Punt - Downed', 16, 11, 7],\n",
    "           ['Punt - Fair Catch', 19, 15, 23],\n",
    "           ['Punt - Out of Bounds', 3, 5, 0],\n",
    "           ['Punt - Non-Special Teams Result', 1, 0, 0],\n",
    "           ['Punt - Touchback', 0, 4, 3],\n",
    "           ['Punt - Muffed', 0, 2, 1],\n",
    "           ['Kickoff - Touchback', 51, 46, 62],\n",
    "           ['Kickoff - Return', 13, 17, 10],\n",
    "           ['Kickoff - Muffed', 0, 0, 1],\n",
    "           ['Extra Point - Kick Attempt Good', 22, 19, 22],\n",
    "           ['Extra Point - Kick Attempt No Good', 1, 1, 1],\n",
    "           ['Field Goal - Kick Attempt Good', 25, 24, 21],\n",
    "           ['Field Goal - Kick Attempt No Good', 3, 3, 6],\n",
    "           ['Field Goal - Blocked Kick Attempt', 0, 1, 0]\n",
    "           ]\n",
    "\n",
    "allWASData = pd.DataFrame(WASData, columns=['WAS Special Play', '2018', '2019', '2020'])\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "b6786d16-54e7-41da-a521-73022e660551",
   "metadata": {},
   "outputs": [],
   "source": [
    "# For Bar Plot\n",
    "sumARIData = allARIData[\"2018\"] + allARIData[\"2019\"] + allARIData['2020']\n",
    "allARIData[\"Total\"] = sumARIData\n",
    "allARIData = allARIData.sort_values(by=['Total'],ascending=False)\n",
    "\n",
    "sumATLData = allATLData[\"2018\"] + allATLData[\"2019\"] + allATLData['2020']\n",
    "allATLData[\"Total\"] = sumATLData\n",
    "allATLData = allATLData.sort_values(by=['Total'],ascending=False)\n",
    "\n",
    "sumBALData = allBALData[\"2018\"] + allBALData[\"2019\"] + allBALData['2020']\n",
    "allBALData[\"Total\"] = sumBALData\n",
    "allBALData = allBALData.sort_values(by=['Total'],ascending=False)\n",
    "\n",
    "sumBUFData = allBUFData[\"2018\"] + allBUFData[\"2019\"] + allBUFData['2020']\n",
    "allBUFData[\"Total\"] = sumBUFData\n",
    "allBUFData = allBUFData.sort_values(by=['Total'],ascending=False)\n",
    "\n",
    "sumCARData = allCARData[\"2018\"] + allCARData[\"2019\"] + allCARData['2020']\n",
    "allCARData[\"Total\"] = sumCARData\n",
    "allCARData = allCARData.sort_values(by=['Total'],ascending=False)\n",
    "\n",
    "sumCHIData = allCHIData[\"2018\"] + allCHIData[\"2019\"] + allCHIData['2020']\n",
    "allCHIData[\"Total\"] = sumCHIData\n",
    "allCHIData = allCHIData.sort_values(by=['Total'],ascending=False)\n",
    "\n",
    "sumCINData = allCINData[\"2018\"] + allCINData[\"2019\"] + allCINData['2020']\n",
    "allCINData[\"Total\"] = sumCINData\n",
    "allCINData = allCINData.sort_values(by=['Total'],ascending=False)\n",
    "\n",
    "sumCLEData = allCLEData[\"2018\"] + allCLEData[\"2019\"] + allCLEData['2020']\n",
    "allCLEData[\"Total\"] = sumCLEData\n",
    "allCLEData = allCLEData.sort_values(by=['Total'],ascending=False)\n",
    "\n",
    "sumDALData = allDALData[\"2018\"] + allDALData[\"2019\"] + allDALData['2020']\n",
    "allDALData[\"Total\"] = sumDALData\n",
    "allDALData = allDALData.sort_values(by=['Total'],ascending=False)\n",
    "\n",
    "sumDENData = allDENData[\"2018\"] + allDENData[\"2019\"] + allDENData['2020']\n",
    "allDENData[\"Total\"] = sumDENData\n",
    "allDENData = allDENData.sort_values(by=['Total'],ascending=False)\n",
    "\n",
    "sumDETData = allDETData[\"2018\"] + allDETData[\"2019\"] + allDETData['2020']\n",
    "allDETData[\"Total\"] = sumDETData\n",
    "allDETData = allDETData.sort_values(by=['Total'],ascending=False)\n",
    "\n",
    "sumGBData = allGBData[\"2018\"] + allGBData[\"2019\"] + allGBData['2020']\n",
    "allGBData[\"Total\"] = sumGBData\n",
    "allGBData = allGBData.sort_values(by=['Total'],ascending=False)\n",
    "\n",
    "sumHOUData = allHOUData[\"2018\"] + allHOUData[\"2019\"] + allHOUData['2020']\n",
    "allHOUData[\"Total\"] = sumHOUData\n",
    "allHOUData = allHOUData.sort_values(by=['Total'],ascending=False)\n",
    "\n",
    "sumINDData = allINDData[\"2018\"] + allINDData[\"2019\"] + allINDData['2020']\n",
    "allINDData[\"Total\"] = sumINDData\n",
    "allINDData = allINDData.sort_values(by=['Total'],ascending=False)\n",
    "\n",
    "sumJAXData = allJAXData[\"2018\"] + allJAXData[\"2019\"] + allJAXData['2020']\n",
    "allJAXData[\"Total\"] = sumJAXData\n",
    "allJAXData = allJAXData.sort_values(by=['Total'],ascending=False)\n",
    "\n",
    "sumKCData = allKCData[\"2018\"] + allKCData[\"2019\"] + allKCData['2020']\n",
    "allKCData[\"Total\"] = sumKCData\n",
    "allKCData = allKCData.sort_values(by=['Total'],ascending=False)\n",
    "\n",
    "sumLAData = allLAData[\"2018\"] + allLAData[\"2019\"] + allLAData['2020']\n",
    "allLAData[\"Total\"] = sumLAData\n",
    "allLAData = allLAData.sort_values(by=['Total'],ascending=False)\n",
    "\n",
    "sumLACData = allLACData[\"2018\"] + allLACData[\"2019\"] + allLACData['2020']\n",
    "allLACData[\"Total\"] = sumLACData\n",
    "allLACData = allLACData.sort_values(by=['Total'],ascending=False)\n",
    "\n",
    "sumMIAData = allMIAData[\"2018\"] + allMIAData[\"2019\"] + allMIAData['2020']\n",
    "allMIAData[\"Total\"] = sumMIAData\n",
    "allMIAData = allMIAData.sort_values(by=['Total'],ascending=False)\n",
    "\n",
    "sumMINData = allMINData[\"2018\"] + allMINData[\"2019\"] + allMINData['2020']\n",
    "allMINData[\"Total\"] = sumMINData\n",
    "allMINData = allMINData.sort_values(by=['Total'],ascending=False)\n",
    "\n",
    "sumNEData = allNEData[\"2018\"] + allNEData[\"2019\"] + allNEData['2020']\n",
    "allNEData[\"Total\"] = sumNEData\n",
    "allNEData = allNEData.sort_values(by=['Total'],ascending=False)\n",
    "\n",
    "sumNOData = allNOData[\"2018\"] + allNOData[\"2019\"] + allNOData['2020']\n",
    "allNOData[\"Total\"] = sumNOData\n",
    "allNOData = allNOData.sort_values(by=['Total'],ascending=False)\n",
    "\n",
    "sumNYGData = allNYGData[\"2018\"] + allNYGData[\"2019\"] + allNYGData['2020']\n",
    "allNYGData[\"Total\"] = sumNYGData\n",
    "allNYGData = allNYGData.sort_values(by=['Total'],ascending=False)\n",
    "\n",
    "sumNYJData = allNYJData[\"2018\"] + allNYJData[\"2019\"] + allNYJData['2020']\n",
    "allNYJData[\"Total\"] = sumNYJData\n",
    "allNYJData = allNYJData.sort_values(by=['Total'],ascending=False)\n",
    "\n",
    "sumOAKData = allOAKData[\"2018\"] + allOAKData[\"2019\"] + allOAKData['2020']\n",
    "allOAKData[\"Total\"] = sumOAKData\n",
    "allOAKData = allOAKData.sort_values(by=['Total'],ascending=False)\n",
    "\n",
    "sumPHIData = allPHIData[\"2018\"] + allPHIData[\"2019\"] + allPHIData['2020']\n",
    "allPHIData[\"Total\"] = sumPHIData\n",
    "allPHIData = allPHIData.sort_values(by=['Total'],ascending=False)\n",
    "\n",
    "sumPITData = allPITData[\"2018\"] + allPITData[\"2019\"] + allPITData['2020']\n",
    "allPITData[\"Total\"] = sumPITData\n",
    "allPITData = allPITData.sort_values(by=['Total'],ascending=False)\n",
    "\n",
    "sumSEAData = allSEAData[\"2018\"] + allSEAData[\"2019\"] + allSEAData['2020']\n",
    "allSEAData[\"Total\"] = sumSEAData\n",
    "allSEAData = allSEAData.sort_values(by=['Total'],ascending=False)\n",
    "\n",
    "sumSFData = allSFData[\"2018\"] + allSFData[\"2019\"] + allSFData['2020']\n",
    "allSFData[\"Total\"] = sumSFData\n",
    "allSFData = allSFData.sort_values(by=['Total'],ascending=False)\n",
    "\n",
    "sumTBData = allTBData[\"2018\"] + allTBData[\"2019\"] + allTBData['2020']\n",
    "allTBData[\"Total\"] = sumTBData\n",
    "allTBData = allTBData.sort_values(by=['Total'],ascending=False)\n",
    "\n",
    "sumTENData = allTENData[\"2018\"] + allTENData[\"2019\"] + allTENData['2020']\n",
    "allTENData[\"Total\"] = sumTENData\n",
    "allTENData = allTENData.sort_values(by=['Total'],ascending=False)\n",
    "\n",
    "sumWASData = allWASData[\"2018\"] + allWASData[\"2019\"] + allWASData['2020']\n",
    "allWASData[\"Total\"] = sumWASData\n",
    "allWASData = allWASData.sort_values(by=['Total'],ascending=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "cdc90db9-3b8d-4eb8-bad0-2c741115dc38",
   "metadata": {},
   "outputs": [],
   "source": [
    "ARI2018SpecialTeamPlayCountsSeries = allARIData.groupby('ARI Special Play')['2018'].sum().sort_values(ascending=False)\n",
    "ARI2019SpecialTeamPlayCountsSeries = allARIData.groupby('ARI Special Play')['2019'].sum().sort_values(ascending=False)\n",
    "ARI2020SpecialTeamPlayCountsSeries = allARIData.groupby('ARI Special Play')['2020'].sum().sort_values(ascending=False)\n",
    "\n",
    "\n",
    "ATL2018SpecialTeamPlayCountsSeries = allATLData.groupby('ATL Special Play')['2018'].sum().sort_values(ascending=False)\n",
    "ATL2019SpecialTeamPlayCountsSeries = allATLData.groupby('ATL Special Play')['2019'].sum().sort_values(ascending=False)\n",
    "ATL2020SpecialTeamPlayCountsSeries = allATLData.groupby('ATL Special Play')['2020'].sum().sort_values(ascending=False)\n",
    "\n",
    "\n",
    "BAL2018SpecialTeamPlayCountsSeries = allBALData.groupby('BAL Special Play')['2018'].sum().sort_values(ascending=False)\n",
    "BAL2019SpecialTeamPlayCountsSeries = allBALData.groupby('BAL Special Play')['2019'].sum().sort_values(ascending=False)\n",
    "BAL2020SpecialTeamPlayCountsSeries = allBALData.groupby('BAL Special Play')['2020'].sum().sort_values(ascending=False)\n",
    "\n",
    "\n",
    "BUF2018SpecialTeamPlayCountsSeries = allBUFData.groupby('BUF Special Play')['2018'].sum().sort_values(ascending=False)\n",
    "BUF2019SpecialTeamPlayCountsSeries = allBUFData.groupby('BUF Special Play')['2019'].sum().sort_values(ascending=False)\n",
    "BUF2020SpecialTeamPlayCountsSeries = allBUFData.groupby('BUF Special Play')['2020'].sum().sort_values(ascending=False)\n",
    "\n",
    "\n",
    "CAR2018SpecialTeamPlayCountsSeries = allCARData.groupby('CAR Special Play')['2018'].sum().sort_values(ascending=False)\n",
    "CAR2019SpecialTeamPlayCountsSeries = allCARData.groupby('CAR Special Play')['2019'].sum().sort_values(ascending=False)\n",
    "CAR2020SpecialTeamPlayCountsSeries = allCARData.groupby('CAR Special Play')['2020'].sum().sort_values(ascending=False)\n",
    "\n",
    "\n",
    "CHI2018SpecialTeamPlayCountsSeries = allCHIData.groupby('CHI Special Play')['2018'].sum().sort_values(ascending=False)\n",
    "CHI2019SpecialTeamPlayCountsSeries = allCHIData.groupby('CHI Special Play')['2019'].sum().sort_values(ascending=False)\n",
    "CHI2020SpecialTeamPlayCountsSeries = allCHIData.groupby('CHI Special Play')['2020'].sum().sort_values(ascending=False)\n",
    "\n",
    "\n",
    "CIN2018SpecialTeamPlayCountsSeries = allCINData.groupby('CIN Special Play')['2018'].sum().sort_values(ascending=False)\n",
    "CIN2019SpecialTeamPlayCountsSeries = allCINData.groupby('CIN Special Play')['2019'].sum().sort_values(ascending=False)\n",
    "CIN2020SpecialTeamPlayCountsSeries = allCINData.groupby('CIN Special Play')['2020'].sum().sort_values(ascending=False)\n",
    "\n",
    "\n",
    "CLE2018SpecialTeamPlayCountsSeries = allCLEData.groupby('CLE Special Play')['2018'].sum().sort_values(ascending=False)\n",
    "CLE2019SpecialTeamPlayCountsSeries = allCLEData.groupby('CLE Special Play')['2019'].sum().sort_values(ascending=False)\n",
    "CLE2020SpecialTeamPlayCountsSeries = allCLEData.groupby('CLE Special Play')['2020'].sum().sort_values(ascending=False)\n",
    "\n",
    "\n",
    "DAL2018SpecialTeamPlayCountsSeries = allDALData.groupby('DAL Special Play')['2018'].sum().sort_values(ascending=False)\n",
    "DAL2019SpecialTeamPlayCountsSeries = allDALData.groupby('DAL Special Play')['2019'].sum().sort_values(ascending=False)\n",
    "DAL2020SpecialTeamPlayCountsSeries = allDALData.groupby('DAL Special Play')['2020'].sum().sort_values(ascending=False)\n",
    "\n",
    "\n",
    "DEN2018SpecialTeamPlayCountsSeries = allDENData.groupby('DEN Special Play')['2018'].sum().sort_values(ascending=False)\n",
    "DEN2019SpecialTeamPlayCountsSeries = allDENData.groupby('DEN Special Play')['2019'].sum().sort_values(ascending=False)\n",
    "DEN2020SpecialTeamPlayCountsSeries = allDENData.groupby('DEN Special Play')['2020'].sum().sort_values(ascending=False)\n",
    "\n",
    "\n",
    "DET2018SpecialTeamPlayCountsSeries = allDETData.groupby('DET Special Play')['2018'].sum().sort_values(ascending=False)\n",
    "DET2019SpecialTeamPlayCountsSeries = allDETData.groupby('DET Special Play')['2019'].sum().sort_values(ascending=False)\n",
    "DET2020SpecialTeamPlayCountsSeries = allDETData.groupby('DET Special Play')['2020'].sum().sort_values(ascending=False)\n",
    "\n",
    "\n",
    "GB2018SpecialTeamPlayCountsSeries = allGBData.groupby('GB Special Play')['2018'].sum().sort_values(ascending=False)\n",
    "GB2019SpecialTeamPlayCountsSeries = allGBData.groupby('GB Special Play')['2019'].sum().sort_values(ascending=False)\n",
    "GB2020SpecialTeamPlayCountsSeries = allGBData.groupby('GB Special Play')['2020'].sum().sort_values(ascending=False)\n",
    "\n",
    "\n",
    "HOU2018SpecialTeamPlayCountsSeries = allHOUData.groupby('HOU Special Play')['2018'].sum().sort_values(ascending=False)\n",
    "HOU2019SpecialTeamPlayCountsSeries = allHOUData.groupby('HOU Special Play')['2019'].sum().sort_values(ascending=False)\n",
    "HOU2020SpecialTeamPlayCountsSeries = allHOUData.groupby('HOU Special Play')['2020'].sum().sort_values(ascending=False)\n",
    "\n",
    "\n",
    "IND2018SpecialTeamPlayCountsSeries = allINDData.groupby('IND Special Play')['2018'].sum().sort_values(ascending=False)\n",
    "IND2019SpecialTeamPlayCountsSeries = allINDData.groupby('IND Special Play')['2019'].sum().sort_values(ascending=False)\n",
    "IND2020SpecialTeamPlayCountsSeries = allINDData.groupby('IND Special Play')['2020'].sum().sort_values(ascending=False)\n",
    "\n",
    "\n",
    "JAX2018SpecialTeamPlayCountsSeries = allJAXData.groupby('JAX Special Play')['2018'].sum().sort_values(ascending=False)\n",
    "JAX2019SpecialTeamPlayCountsSeries = allJAXData.groupby('JAX Special Play')['2019'].sum().sort_values(ascending=False)\n",
    "JAX2020SpecialTeamPlayCountsSeries = allJAXData.groupby('JAX Special Play')['2020'].sum().sort_values(ascending=False)\n",
    "\n",
    "\n",
    "KC2018SpecialTeamPlayCountsSeries = allKCData.groupby('KC Special Play')['2018'].sum().sort_values(ascending=False)\n",
    "KC2019SpecialTeamPlayCountsSeries = allKCData.groupby('KC Special Play')['2019'].sum().sort_values(ascending=False)\n",
    "KC2020SpecialTeamPlayCountsSeries = allKCData.groupby('KC Special Play')['2020'].sum().sort_values(ascending=False)\n",
    "\n",
    "\n",
    "LA2018SpecialTeamPlayCountsSeries = allLAData.groupby('LA Special Play')['2018'].sum().sort_values(ascending=False)\n",
    "LA2019SpecialTeamPlayCountsSeries = allLAData.groupby('LA Special Play')['2019'].sum().sort_values(ascending=False)\n",
    "LA2020SpecialTeamPlayCountsSeries = allLAData.groupby('LA Special Play')['2020'].sum().sort_values(ascending=False)\n",
    "\n",
    "\n",
    "LAC2018SpecialTeamPlayCountsSeries = allLACData.groupby('LAC Special Play')['2018'].sum().sort_values(ascending=False)\n",
    "LAC2019SpecialTeamPlayCountsSeries = allLACData.groupby('LAC Special Play')['2019'].sum().sort_values(ascending=False)\n",
    "LAC2020SpecialTeamPlayCountsSeries = allLACData.groupby('LAC Special Play')['2020'].sum().sort_values(ascending=False)\n",
    "\n",
    "\n",
    "MIA2018SpecialTeamPlayCountsSeries = allMIAData.groupby('MIA Special Play')['2018'].sum().sort_values(ascending=False)\n",
    "MIA2019SpecialTeamPlayCountsSeries = allMIAData.groupby('MIA Special Play')['2019'].sum().sort_values(ascending=False)\n",
    "MIA2020SpecialTeamPlayCountsSeries = allMIAData.groupby('MIA Special Play')['2020'].sum().sort_values(ascending=False)\n",
    "\n",
    "\n",
    "MIN2018SpecialTeamPlayCountsSeries = allMINData.groupby('MIN Special Play')['2018'].sum().sort_values(ascending=False)\n",
    "MIN2019SpecialTeamPlayCountsSeries = allMINData.groupby('MIN Special Play')['2019'].sum().sort_values(ascending=False)\n",
    "MIN2020SpecialTeamPlayCountsSeries = allMINData.groupby('MIN Special Play')['2020'].sum().sort_values(ascending=False)\n",
    "\n",
    "\n",
    "NE2018SpecialTeamPlayCountsSeries = allNEData.groupby('NE Special Play')['2018'].sum().sort_values(ascending=False)\n",
    "NE2019SpecialTeamPlayCountsSeries = allNEData.groupby('NE Special Play')['2019'].sum().sort_values(ascending=False)\n",
    "NE2020SpecialTeamPlayCountsSeries = allNEData.groupby('NE Special Play')['2020'].sum().sort_values(ascending=False)\n",
    "\n",
    "\n",
    "NO2018SpecialTeamPlayCountsSeries = allNOData.groupby('NO Special Play')['2018'].sum().sort_values(ascending=False)\n",
    "NO2019SpecialTeamPlayCountsSeries = allNOData.groupby('NO Special Play')['2019'].sum().sort_values(ascending=False)\n",
    "NO2020SpecialTeamPlayCountsSeries = allNOData.groupby('NO Special Play')['2020'].sum().sort_values(ascending=False)\n",
    "\n",
    "\n",
    "NYG2018SpecialTeamPlayCountsSeries = allNYGData.groupby('NYG Special Play')['2018'].sum().sort_values(ascending=False)\n",
    "NYG2019SpecialTeamPlayCountsSeries = allNYGData.groupby('NYG Special Play')['2019'].sum().sort_values(ascending=False)\n",
    "NYG2020SpecialTeamPlayCountsSeries = allNYGData.groupby('NYG Special Play')['2020'].sum().sort_values(ascending=False)\n",
    "\n",
    "\n",
    "NYJ2018SpecialTeamPlayCountsSeries = allNYJData.groupby('NYJ Special Play')['2018'].sum().sort_values(ascending=False)\n",
    "NYJ2019SpecialTeamPlayCountsSeries = allNYJData.groupby('NYJ Special Play')['2019'].sum().sort_values(ascending=False)\n",
    "NYJ2020SpecialTeamPlayCountsSeries = allNYJData.groupby('NYJ Special Play')['2020'].sum().sort_values(ascending=False)\n",
    "\n",
    "OAK2018SpecialTeamPlayCountsSeries = allOAKData.groupby('OAK Special Play')['2018'].sum().sort_values(ascending=False)\n",
    "OAK2019SpecialTeamPlayCountsSeries = allOAKData.groupby('OAK Special Play')['2019'].sum().sort_values(ascending=False)\n",
    "OAK2020SpecialTeamPlayCountsSeries = allOAKData.groupby('OAK Special Play')['2020'].sum().sort_values(ascending=False)\n",
    "\n",
    "\n",
    "PHI2018SpecialTeamPlayCountsSeries = allPHIData.groupby('PHI Special Play')['2018'].sum().sort_values(ascending=False)\n",
    "PHI2019SpecialTeamPlayCountsSeries = allPHIData.groupby('PHI Special Play')['2019'].sum().sort_values(ascending=False)\n",
    "PHI2020SpecialTeamPlayCountsSeries = allPHIData.groupby('PHI Special Play')['2020'].sum().sort_values(ascending=False)\n",
    "\n",
    "\n",
    "PIT2018SpecialTeamPlayCountsSeries = allPITData.groupby('PIT Special Play')['2018'].sum().sort_values(ascending=False)\n",
    "PIT2019SpecialTeamPlayCountsSeries = allPITData.groupby('PIT Special Play')['2019'].sum().sort_values(ascending=False)\n",
    "PIT2020SpecialTeamPlayCountsSeries = allPITData.groupby('PIT Special Play')['2020'].sum().sort_values(ascending=False)\n",
    "\n",
    "\n",
    "SEA2018SpecialTeamPlayCountsSeries = allSEAData.groupby('SEA Special Play')['2018'].sum().sort_values(ascending=False)\n",
    "SEA2019SpecialTeamPlayCountsSeries = allSEAData.groupby('SEA Special Play')['2019'].sum().sort_values(ascending=False)\n",
    "SEA2020SpecialTeamPlayCountsSeries = allSEAData.groupby('SEA Special Play')['2020'].sum().sort_values(ascending=False)\n",
    "\n",
    "\n",
    "SF2018SpecialTeamPlayCountsSeries = allSFData.groupby('SF Special Play')['2018'].sum().sort_values(ascending=False)\n",
    "SF2019SpecialTeamPlayCountsSeries = allSFData.groupby('SF Special Play')['2019'].sum().sort_values(ascending=False)\n",
    "SF2020SpecialTeamPlayCountsSeries = allSFData.groupby('SF Special Play')['2020'].sum().sort_values(ascending=False)\n",
    "\n",
    "\n",
    "TB2018SpecialTeamPlayCountsSeries = allTBData.groupby('TB Special Play')['2018'].sum().sort_values(ascending=False)\n",
    "TB2019SpecialTeamPlayCountsSeries = allTBData.groupby('TB Special Play')['2019'].sum().sort_values(ascending=False)\n",
    "TB2020SpecialTeamPlayCountsSeries = allTBData.groupby('TB Special Play')['2020'].sum().sort_values(ascending=False)\n",
    "\n",
    "\n",
    "TEN2018SpecialTeamPlayCountsSeries = allTENData.groupby('TEN Special Play')['2018'].sum().sort_values(ascending=False)\n",
    "TEN2019SpecialTeamPlayCountsSeries = allTENData.groupby('TEN Special Play')['2019'].sum().sort_values(ascending=False)\n",
    "TEN2020SpecialTeamPlayCountsSeries = allTENData.groupby('TEN Special Play')['2020'].sum().sort_values(ascending=False)\n",
    "\n",
    "\n",
    "WAS2018SpecialTeamPlayCountsSeries = allWASData.groupby('WAS Special Play')['2018'].sum().sort_values(ascending=False)\n",
    "WAS2019SpecialTeamPlayCountsSeries = allWASData.groupby('WAS Special Play')['2019'].sum().sort_values(ascending=False)\n",
    "WAS2020SpecialTeamPlayCountsSeries = allWASData.groupby('WAS Special Play')['2020'].sum().sort_values(ascending=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "74307056-9f0f-4860-afc9-a5604f048dc7",
   "metadata": {},
   "outputs": [],
   "source": [
    "ARI2018Labels = []\n",
    "ARI2018Values = []\n",
    "ARI2018Counts = 6\n",
    "otherARI2018Count = 0\n",
    "for c in ARI2018SpecialTeamPlayCountsSeries.index:\n",
    "    if ARI2018Counts > 0:\n",
    "        ARI2018Labels.append(c)\n",
    "        ARI2018Values.append(ARI2018SpecialTeamPlayCountsSeries[c])\n",
    "        ARI2018Counts -= 1\n",
    "    else:\n",
    "        otherARI2018Count += ARI2018SpecialTeamPlayCountsSeries[c]\n",
    "ARI2018Labels.append(\"Other\")\n",
    "ARI2018Values.append(otherARI2018Count)\n",
    "\n",
    "\n",
    "ARI2019Labels = []\n",
    "ARI2019Values = []\n",
    "ARI2019Counts = 6\n",
    "otherARI2019Count = 0\n",
    "for c in ARI2019SpecialTeamPlayCountsSeries.index:\n",
    "    if ARI2019Counts > 0:\n",
    "        ARI2019Labels.append(c)\n",
    "        ARI2019Values.append(ARI2019SpecialTeamPlayCountsSeries[c])\n",
    "        ARI2019Counts -= 1\n",
    "    else:\n",
    "        otherARI2019Count += ARI2019SpecialTeamPlayCountsSeries[c]\n",
    "ARI2019Labels.append(\"Other\")\n",
    "ARI2019Values.append(otherARI2019Count)\n",
    "\n",
    "\n",
    "ARI2020Labels = []\n",
    "ARI2020Values = []\n",
    "ARI2020Counts = 6\n",
    "otherARI2020Count = 0\n",
    "for c in ARI2020SpecialTeamPlayCountsSeries.index:\n",
    "    if ARI2020Counts > 0:\n",
    "        ARI2020Labels.append(c)\n",
    "        ARI2020Values.append(ARI2020SpecialTeamPlayCountsSeries[c])\n",
    "        ARI2020Counts -= 1\n",
    "    else:\n",
    "        otherARI2020Count += ARI2020SpecialTeamPlayCountsSeries[c]\n",
    "ARI2020Labels.append(\"Other\")\n",
    "ARI2020Values.append(otherARI2020Count)\n",
    "\n",
    "\n",
    "ATL2018Labels = []\n",
    "ATL2018Values = []\n",
    "ATL2018Counts = 6\n",
    "otherATL2018Count = 0\n",
    "for c in ATL2018SpecialTeamPlayCountsSeries.index:\n",
    "    if ATL2018Counts > 0:\n",
    "        ATL2018Labels.append(c)\n",
    "        ATL2018Values.append(ATL2018SpecialTeamPlayCountsSeries[c])\n",
    "        ATL2018Counts -= 1\n",
    "    else:\n",
    "        otherATL2018Count += ATL2018SpecialTeamPlayCountsSeries[c]\n",
    "ATL2018Labels.append(\"Other\")\n",
    "ATL2018Values.append(otherATL2018Count)\n",
    "\n",
    "\n",
    "ATL2019Labels = []\n",
    "ATL2019Values = []\n",
    "ATL2019Counts = 6\n",
    "otherATL2019Count = 0\n",
    "for c in ATL2019SpecialTeamPlayCountsSeries.index:\n",
    "    if ATL2019Counts > 0:\n",
    "        ATL2019Labels.append(c)\n",
    "        ATL2019Values.append(ATL2019SpecialTeamPlayCountsSeries[c])\n",
    "        ATL2019Counts -= 1\n",
    "    else:\n",
    "        otherATL2019Count += ATL2019SpecialTeamPlayCountsSeries[c]\n",
    "ATL2019Labels.append(\"Other\")\n",
    "ATL2019Values.append(otherATL2019Count)\n",
    "\n",
    "\n",
    "ATL2020Labels = []\n",
    "ATL2020Values = []\n",
    "ATL2020Counts = 6\n",
    "otherATL2020Count = 0\n",
    "for c in ATL2020SpecialTeamPlayCountsSeries.index:\n",
    "    if ATL2020Counts > 0:\n",
    "        ATL2020Labels.append(c)\n",
    "        ATL2020Values.append(ATL2020SpecialTeamPlayCountsSeries[c])\n",
    "        ATL2020Counts -= 1\n",
    "    else:\n",
    "        otherATL2020Count += ATL2020SpecialTeamPlayCountsSeries[c]\n",
    "ATL2020Labels.append(\"Other\")\n",
    "ATL2020Values.append(otherATL2020Count)\n",
    "\n",
    "\n",
    "BAL2018Labels = []\n",
    "BAL2018Values = []\n",
    "BAL2018Counts = 6\n",
    "otherBAL2018Count = 0\n",
    "for c in BAL2018SpecialTeamPlayCountsSeries.index:\n",
    "    if BAL2018Counts > 0:\n",
    "        BAL2018Labels.append(c)\n",
    "        BAL2018Values.append(BAL2018SpecialTeamPlayCountsSeries[c])\n",
    "        BAL2018Counts -= 1\n",
    "    else:\n",
    "        otherBAL2018Count += BAL2018SpecialTeamPlayCountsSeries[c]\n",
    "BAL2018Labels.append(\"Other\")\n",
    "BAL2018Values.append(otherBAL2018Count)\n",
    "\n",
    "\n",
    "BAL2019Labels = []\n",
    "BAL2019Values = []\n",
    "BAL2019Counts = 6\n",
    "otherBAL2019Count = 0\n",
    "for c in BAL2019SpecialTeamPlayCountsSeries.index:\n",
    "    if BAL2019Counts > 0:\n",
    "        BAL2019Labels.append(c)\n",
    "        BAL2019Values.append(BAL2019SpecialTeamPlayCountsSeries[c])\n",
    "        BAL2019Counts -= 1\n",
    "    else:\n",
    "        otherBAL2019Count += BAL2019SpecialTeamPlayCountsSeries[c]\n",
    "BAL2019Labels.append(\"Other\")\n",
    "BAL2019Values.append(otherBAL2019Count)\n",
    "\n",
    "\n",
    "BAL2020Labels = []\n",
    "BAL2020Values = []\n",
    "BAL2020Counts = 6\n",
    "otherBAL2020Count = 0\n",
    "for c in BAL2020SpecialTeamPlayCountsSeries.index:\n",
    "    if BAL2020Counts > 0:\n",
    "        BAL2020Labels.append(c)\n",
    "        BAL2020Values.append(BAL2020SpecialTeamPlayCountsSeries[c])\n",
    "        BAL2020Counts -= 1\n",
    "    else:\n",
    "        otherBAL2020Count += BAL2020SpecialTeamPlayCountsSeries[c]\n",
    "BAL2020Labels.append(\"Other\")\n",
    "BAL2020Values.append(otherBAL2020Count)\n",
    "\n",
    "\n",
    "BUF2018Labels = []\n",
    "BUF2018Values = []\n",
    "BUF2018Counts = 6\n",
    "otherBUF2018Count = 0\n",
    "for c in BUF2018SpecialTeamPlayCountsSeries.index:\n",
    "    if BUF2018Counts > 0:\n",
    "        BUF2018Labels.append(c)\n",
    "        BUF2018Values.append(BUF2018SpecialTeamPlayCountsSeries[c])\n",
    "        BUF2018Counts -= 1\n",
    "    else:\n",
    "        otherBUF2018Count += BUF2018SpecialTeamPlayCountsSeries[c]\n",
    "BUF2018Labels.append(\"Other\")\n",
    "BUF2018Values.append(otherBUF2018Count)\n",
    "\n",
    "\n",
    "BUF2019Labels = []\n",
    "BUF2019Values = []\n",
    "BUF2019Counts = 6\n",
    "otherBUF2019Count = 0\n",
    "for c in BUF2019SpecialTeamPlayCountsSeries.index:\n",
    "    if BUF2019Counts > 0:\n",
    "        BUF2019Labels.append(c)\n",
    "        BUF2019Values.append(BUF2019SpecialTeamPlayCountsSeries[c])\n",
    "        BUF2019Counts -= 1\n",
    "    else:\n",
    "        otherBUF2019Count += BUF2019SpecialTeamPlayCountsSeries[c]\n",
    "BUF2019Labels.append(\"Other\")\n",
    "BUF2019Values.append(otherBUF2019Count)\n",
    "\n",
    "\n",
    "BUF2020Labels = []\n",
    "BUF2020Values = []\n",
    "BUF2020Counts = 6\n",
    "otherBUF2020Count = 0\n",
    "for c in BUF2020SpecialTeamPlayCountsSeries.index:\n",
    "    if BUF2020Counts > 0:\n",
    "        BUF2020Labels.append(c)\n",
    "        BUF2020Values.append(BUF2020SpecialTeamPlayCountsSeries[c])\n",
    "        BUF2020Counts -= 1\n",
    "    else:\n",
    "        otherBUF2020Count += BUF2020SpecialTeamPlayCountsSeries[c]\n",
    "BUF2020Labels.append(\"Other\")\n",
    "BUF2020Values.append(otherBUF2020Count)\n",
    "\n",
    "\n",
    "CAR2018Labels = []\n",
    "CAR2018Values = []\n",
    "CAR2018Counts = 6\n",
    "otherCAR2018Count = 0\n",
    "for c in CAR2018SpecialTeamPlayCountsSeries.index:\n",
    "    if CAR2018Counts > 0:\n",
    "        CAR2018Labels.append(c)\n",
    "        CAR2018Values.append(CAR2018SpecialTeamPlayCountsSeries[c])\n",
    "        CAR2018Counts -= 1\n",
    "    else:\n",
    "        otherCAR2018Count += CAR2018SpecialTeamPlayCountsSeries[c]\n",
    "CAR2018Labels.append(\"Other\")\n",
    "CAR2018Values.append(otherCAR2018Count)\n",
    "\n",
    "\n",
    "CAR2019Labels = []\n",
    "CAR2019Values = []\n",
    "CAR2019Counts = 6\n",
    "otherCAR2019Count = 0\n",
    "for c in CAR2019SpecialTeamPlayCountsSeries.index:\n",
    "    if CAR2019Counts > 0:\n",
    "        CAR2019Labels.append(c)\n",
    "        CAR2019Values.append(CAR2019SpecialTeamPlayCountsSeries[c])\n",
    "        CAR2019Counts -= 1\n",
    "    else:\n",
    "        otherCAR2019Count += CAR2019SpecialTeamPlayCountsSeries[c]\n",
    "CAR2019Labels.append(\"Other\")\n",
    "CAR2019Values.append(otherCAR2019Count)\n",
    "\n",
    "\n",
    "CAR2020Labels = []\n",
    "CAR2020Values = []\n",
    "CAR2020Counts = 6\n",
    "otherCAR2020Count = 0\n",
    "for c in CAR2020SpecialTeamPlayCountsSeries.index:\n",
    "    if CAR2020Counts > 0:\n",
    "        CAR2020Labels.append(c)\n",
    "        CAR2020Values.append(CAR2020SpecialTeamPlayCountsSeries[c])\n",
    "        CAR2020Counts -= 1\n",
    "    else:\n",
    "        otherCAR2020Count += CAR2020SpecialTeamPlayCountsSeries[c]\n",
    "CAR2020Labels.append(\"Other\")\n",
    "CAR2020Values.append(otherCAR2020Count)\n",
    "\n",
    "\n",
    "CHI2018Labels = []\n",
    "CHI2018Values = []\n",
    "CHI2018Counts = 6\n",
    "otherCHI2018Count = 0\n",
    "for c in CHI2018SpecialTeamPlayCountsSeries.index:\n",
    "    if CHI2018Counts > 0:\n",
    "        CHI2018Labels.append(c)\n",
    "        CHI2018Values.append(CHI2018SpecialTeamPlayCountsSeries[c])\n",
    "        CHI2018Counts -= 1\n",
    "    else:\n",
    "        otherCHI2018Count += CHI2018SpecialTeamPlayCountsSeries[c]\n",
    "CHI2018Labels.append(\"Other\")\n",
    "CHI2018Values.append(otherCHI2018Count)\n",
    "\n",
    "\n",
    "CHI2019Labels = []\n",
    "CHI2019Values = []\n",
    "CHI2019Counts = 6\n",
    "otherCHI2019Count = 0\n",
    "for c in CHI2019SpecialTeamPlayCountsSeries.index:\n",
    "    if CHI2019Counts > 0:\n",
    "        CHI2019Labels.append(c)\n",
    "        CHI2019Values.append(CHI2019SpecialTeamPlayCountsSeries[c])\n",
    "        CHI2019Counts -= 1\n",
    "    else:\n",
    "        otherCHI2019Count += CHI2019SpecialTeamPlayCountsSeries[c]\n",
    "CHI2019Labels.append(\"Other\")\n",
    "CHI2019Values.append(otherCHI2019Count)\n",
    "\n",
    "\n",
    "CHI2020Labels = []\n",
    "CHI2020Values = []\n",
    "CHI2020Counts = 6\n",
    "otherCHI2020Count = 0\n",
    "for c in CHI2020SpecialTeamPlayCountsSeries.index:\n",
    "    if CHI2020Counts > 0:\n",
    "        CHI2020Labels.append(c)\n",
    "        CHI2020Values.append(CHI2020SpecialTeamPlayCountsSeries[c])\n",
    "        CHI2020Counts -= 1\n",
    "    else:\n",
    "        otherCHI2020Count += CHI2020SpecialTeamPlayCountsSeries[c]\n",
    "CHI2020Labels.append(\"Other\")\n",
    "CHI2020Values.append(otherCHI2020Count)\n",
    "\n",
    "\n",
    "CIN2018Labels = []\n",
    "CIN2018Values = []\n",
    "CIN2018Counts = 6\n",
    "otherCIN2018Count = 0\n",
    "for c in CIN2018SpecialTeamPlayCountsSeries.index:\n",
    "    if CIN2018Counts > 0:\n",
    "        CIN2018Labels.append(c)\n",
    "        CIN2018Values.append(CIN2018SpecialTeamPlayCountsSeries[c])\n",
    "        CIN2018Counts -= 1\n",
    "    else:\n",
    "        otherCIN2018Count += CIN2018SpecialTeamPlayCountsSeries[c]\n",
    "CIN2018Labels.append(\"Other\")\n",
    "CIN2018Values.append(otherCIN2018Count)\n",
    "\n",
    "\n",
    "CIN2019Labels = []\n",
    "CIN2019Values = []\n",
    "CIN2019Counts = 6\n",
    "otherCIN2019Count = 0\n",
    "for c in CIN2019SpecialTeamPlayCountsSeries.index:\n",
    "    if CIN2019Counts > 0:\n",
    "        CIN2019Labels.append(c)\n",
    "        CIN2019Values.append(CIN2019SpecialTeamPlayCountsSeries[c])\n",
    "        CIN2019Counts -= 1\n",
    "    else:\n",
    "        otherCIN2019Count += CIN2019SpecialTeamPlayCountsSeries[c]\n",
    "CIN2019Labels.append(\"Other\")\n",
    "CIN2019Values.append(otherCIN2019Count)\n",
    "\n",
    "\n",
    "CIN2020Labels = []\n",
    "CIN2020Values = []\n",
    "CIN2020Counts = 6\n",
    "otherCIN2020Count = 0\n",
    "for c in CIN2020SpecialTeamPlayCountsSeries.index:\n",
    "    if CIN2020Counts > 0:\n",
    "        CIN2020Labels.append(c)\n",
    "        CIN2020Values.append(CIN2020SpecialTeamPlayCountsSeries[c])\n",
    "        CIN2020Counts -= 1\n",
    "    else:\n",
    "        otherCIN2020Count += CIN2020SpecialTeamPlayCountsSeries[c]\n",
    "CIN2020Labels.append(\"Other\")\n",
    "CIN2020Values.append(otherCIN2020Count)\n",
    "\n",
    "\n",
    "CLE2018Labels = []\n",
    "CLE2018Values = []\n",
    "CLE2018Counts = 6\n",
    "otherCLE2018Count = 0\n",
    "for c in CLE2018SpecialTeamPlayCountsSeries.index:\n",
    "    if CLE2018Counts > 0:\n",
    "        CLE2018Labels.append(c)\n",
    "        CLE2018Values.append(CLE2018SpecialTeamPlayCountsSeries[c])\n",
    "        CLE2018Counts -= 1\n",
    "    else:\n",
    "        otherCLE2018Count += CLE2018SpecialTeamPlayCountsSeries[c]\n",
    "CLE2018Labels.append(\"Other\")\n",
    "CLE2018Values.append(otherCLE2018Count)\n",
    "\n",
    "\n",
    "CLE2019Labels = []\n",
    "CLE2019Values = []\n",
    "CLE2019Counts = 6\n",
    "otherCLE2019Count = 0\n",
    "for c in CLE2019SpecialTeamPlayCountsSeries.index:\n",
    "    if CLE2019Counts > 0:\n",
    "        CLE2019Labels.append(c)\n",
    "        CLE2019Values.append(CLE2019SpecialTeamPlayCountsSeries[c])\n",
    "        CLE2019Counts -= 1\n",
    "    else:\n",
    "        otherCLE2019Count += CLE2019SpecialTeamPlayCountsSeries[c]\n",
    "CLE2019Labels.append(\"Other\")\n",
    "CLE2019Values.append(otherCLE2019Count)\n",
    "\n",
    "\n",
    "CLE2020Labels = []\n",
    "CLE2020Values = []\n",
    "CLE2020Counts = 6\n",
    "otherCLE2020Count = 0\n",
    "for c in CLE2020SpecialTeamPlayCountsSeries.index:\n",
    "    if CLE2020Counts > 0:\n",
    "        CLE2020Labels.append(c)\n",
    "        CLE2020Values.append(CLE2020SpecialTeamPlayCountsSeries[c])\n",
    "        CLE2020Counts -= 1\n",
    "    else:\n",
    "        otherCLE2020Count += CLE2020SpecialTeamPlayCountsSeries[c]\n",
    "CLE2020Labels.append(\"Other\")\n",
    "CLE2020Values.append(otherCLE2020Count)\n",
    "\n",
    "\n",
    "DAL2018Labels = []\n",
    "DAL2018Values = []\n",
    "DAL2018Counts = 6\n",
    "otherDAL2018Count = 0\n",
    "for c in DAL2018SpecialTeamPlayCountsSeries.index:\n",
    "    if DAL2018Counts > 0:\n",
    "        DAL2018Labels.append(c)\n",
    "        DAL2018Values.append(DAL2018SpecialTeamPlayCountsSeries[c])\n",
    "        DAL2018Counts -= 1\n",
    "    else:\n",
    "        otherDAL2018Count += DAL2018SpecialTeamPlayCountsSeries[c]\n",
    "DAL2018Labels.append(\"Other\")\n",
    "DAL2018Values.append(otherDAL2018Count)\n",
    "\n",
    "\n",
    "DAL2019Labels = []\n",
    "DAL2019Values = []\n",
    "DAL2019Counts = 6\n",
    "otherDAL2019Count = 0\n",
    "for c in DAL2019SpecialTeamPlayCountsSeries.index:\n",
    "    if DAL2019Counts > 0:\n",
    "        DAL2019Labels.append(c)\n",
    "        DAL2019Values.append(DAL2019SpecialTeamPlayCountsSeries[c])\n",
    "        DAL2019Counts -= 1\n",
    "    else:\n",
    "        otherDAL2019Count += DAL2019SpecialTeamPlayCountsSeries[c]\n",
    "DAL2019Labels.append(\"Other\")\n",
    "DAL2019Values.append(otherDAL2019Count)\n",
    "\n",
    "\n",
    "DAL2020Labels = []\n",
    "DAL2020Values = []\n",
    "DAL2020Counts = 6\n",
    "otherDAL2020Count = 0\n",
    "for c in DAL2020SpecialTeamPlayCountsSeries.index:\n",
    "    if DAL2020Counts > 0:\n",
    "        DAL2020Labels.append(c)\n",
    "        DAL2020Values.append(DAL2020SpecialTeamPlayCountsSeries[c])\n",
    "        DAL2020Counts -= 1\n",
    "    else:\n",
    "        otherATL2020Count += DAL2020SpecialTeamPlayCountsSeries[c]\n",
    "DAL2020Labels.append(\"Other\")\n",
    "DAL2020Values.append(otherDAL2020Count)\n",
    "\n",
    "\n",
    "DEN2018Labels = []\n",
    "DEN2018Values = []\n",
    "DEN2018Counts = 6\n",
    "otherDEN2018Count = 0\n",
    "for c in DEN2018SpecialTeamPlayCountsSeries.index:\n",
    "    if DEN2018Counts > 0:\n",
    "        DEN2018Labels.append(c)\n",
    "        DEN2018Values.append(DEN2018SpecialTeamPlayCountsSeries[c])\n",
    "        DEN2018Counts -= 1\n",
    "    else:\n",
    "        otherDEN2018Count += DEN2018SpecialTeamPlayCountsSeries[c]\n",
    "DEN2018Labels.append(\"Other\")\n",
    "DEN2018Values.append(otherDEN2018Count)\n",
    "\n",
    "\n",
    "DEN2019Labels = []\n",
    "DEN2019Values = []\n",
    "DEN2019Counts = 6\n",
    "otherDEN2019Count = 0\n",
    "for c in DEN2019SpecialTeamPlayCountsSeries.index:\n",
    "    if DEN2019Counts > 0:\n",
    "        DEN2019Labels.append(c)\n",
    "        DEN2019Values.append(DEN2019SpecialTeamPlayCountsSeries[c])\n",
    "        DEN2019Counts -= 1\n",
    "    else:\n",
    "        otherDEN2019Count += DEN2019SpecialTeamPlayCountsSeries[c]\n",
    "DEN2019Labels.append(\"Other\")\n",
    "DEN2019Values.append(otherDEN2019Count)\n",
    "\n",
    "\n",
    "DEN2020Labels = []\n",
    "DEN2020Values = []\n",
    "DEN2020Counts = 6\n",
    "otherDEN2020Count = 0\n",
    "for c in DEN2020SpecialTeamPlayCountsSeries.index:\n",
    "    if DEN2020Counts > 0:\n",
    "        DEN2020Labels.append(c)\n",
    "        DEN2020Values.append(DEN2020SpecialTeamPlayCountsSeries[c])\n",
    "        DEN2020Counts -= 1\n",
    "    else:\n",
    "        otherDEN2020Count += DEN2020SpecialTeamPlayCountsSeries[c]\n",
    "DEN2020Labels.append(\"Other\")\n",
    "DEN2020Values.append(otherDEN2020Count)\n",
    "\n",
    "\n",
    "DET2018Labels = []\n",
    "DET2018Values = []\n",
    "DET2018Counts = 6\n",
    "otherDET2018Count = 0\n",
    "for c in DET2018SpecialTeamPlayCountsSeries.index:\n",
    "    if DET2018Counts > 0:\n",
    "        DET2018Labels.append(c)\n",
    "        DET2018Values.append(DET2018SpecialTeamPlayCountsSeries[c])\n",
    "        DET2018Counts -= 1\n",
    "    else:\n",
    "        otherDET2018Count += DET2018SpecialTeamPlayCountsSeries[c]\n",
    "DET2018Labels.append(\"Other\")\n",
    "DET2018Values.append(otherDET2018Count)\n",
    "\n",
    "\n",
    "DET2019Labels = []\n",
    "DET2019Values = []\n",
    "DET2019Counts = 6\n",
    "otherDET2019Count = 0\n",
    "for c in DET2019SpecialTeamPlayCountsSeries.index:\n",
    "    if DET2019Counts > 0:\n",
    "        DET2019Labels.append(c)\n",
    "        DET2019Values.append(DET2019SpecialTeamPlayCountsSeries[c])\n",
    "        DET2019Counts -= 1\n",
    "    else:\n",
    "        otherDET2019Count += DET2019SpecialTeamPlayCountsSeries[c]\n",
    "DET2019Labels.append(\"Other\")\n",
    "DET2019Values.append(otherDET2019Count)\n",
    "\n",
    "\n",
    "DET2020Labels = []\n",
    "DET2020Values = []\n",
    "DET2020Counts = 6\n",
    "otherDET2020Count = 0\n",
    "for c in DET2020SpecialTeamPlayCountsSeries.index:\n",
    "    if DET2020Counts > 0:\n",
    "        DET2020Labels.append(c)\n",
    "        DET2020Values.append(DET2020SpecialTeamPlayCountsSeries[c])\n",
    "        DET2020Counts -= 1\n",
    "    else:\n",
    "        otherATL2020Count += DET2020SpecialTeamPlayCountsSeries[c]\n",
    "DET2020Labels.append(\"Other\")\n",
    "DET2020Values.append(otherDET2020Count)\n",
    "\n",
    "\n",
    "GB2018Labels = []\n",
    "GB2018Values = []\n",
    "GB2018Counts = 6\n",
    "otherGB2018Count = 0\n",
    "for c in GB2018SpecialTeamPlayCountsSeries.index:\n",
    "    if GB2018Counts > 0:\n",
    "        GB2018Labels.append(c)\n",
    "        GB2018Values.append(GB2018SpecialTeamPlayCountsSeries[c])\n",
    "        GB2018Counts -= 1\n",
    "    else:\n",
    "        otherGB2018Count += GB2018SpecialTeamPlayCountsSeries[c]\n",
    "GB2018Labels.append(\"Other\")\n",
    "GB2018Values.append(otherGB2018Count)\n",
    "\n",
    "\n",
    "GB2019Labels = []\n",
    "GB2019Values = []\n",
    "GB2019Counts = 6\n",
    "otherGB2019Count = 0\n",
    "for c in GB2019SpecialTeamPlayCountsSeries.index:\n",
    "    if GB2019Counts > 0:\n",
    "        GB2019Labels.append(c)\n",
    "        GB2019Values.append(GB2019SpecialTeamPlayCountsSeries[c])\n",
    "        GB2019Counts -= 1\n",
    "    else:\n",
    "        otherGB2019Count += GB2019SpecialTeamPlayCountsSeries[c]\n",
    "GB2019Labels.append(\"Other\")\n",
    "GB2019Values.append(otherGB2019Count)\n",
    "\n",
    "\n",
    "GB2020Labels = []\n",
    "GB2020Values = []\n",
    "GB2020Counts = 6\n",
    "otherGB2020Count = 0\n",
    "for c in GB2020SpecialTeamPlayCountsSeries.index:\n",
    "    if GB2020Counts > 0:\n",
    "        GB2020Labels.append(c)\n",
    "        GB2020Values.append(GB2020SpecialTeamPlayCountsSeries[c])\n",
    "        GB2020Counts -= 1\n",
    "    else:\n",
    "        otherGB2020Count += GB2020SpecialTeamPlayCountsSeries[c]\n",
    "GB2020Labels.append(\"Other\")\n",
    "GB2020Values.append(otherGB2020Count)\n",
    "\n",
    "HOU2018Labels = []\n",
    "HOU2018Values = []\n",
    "HOU2018Counts = 6\n",
    "otherHOU2018Count = 0\n",
    "for c in HOU2018SpecialTeamPlayCountsSeries.index:\n",
    "    if HOU2018Counts > 0:\n",
    "        HOU2018Labels.append(c)\n",
    "        HOU2018Values.append(HOU2018SpecialTeamPlayCountsSeries[c])\n",
    "        HOU2018Counts -= 1\n",
    "    else:\n",
    "        otherHOU2018Count += HOU2018SpecialTeamPlayCountsSeries[c]\n",
    "HOU2018Labels.append(\"Other\")\n",
    "HOU2018Values.append(otherHOU2018Count)\n",
    "\n",
    "\n",
    "HOU2019Labels = []\n",
    "HOU2019Values = []\n",
    "HOU2019Counts = 6\n",
    "otherHOU2019Count = 0\n",
    "for c in HOU2019SpecialTeamPlayCountsSeries.index:\n",
    "    if HOU2019Counts > 0:\n",
    "        HOU2019Labels.append(c)\n",
    "        HOU2019Values.append(HOU2019SpecialTeamPlayCountsSeries[c])\n",
    "        HOU2019Counts -= 1\n",
    "    else:\n",
    "        otherHOU2019Count += HOU2019SpecialTeamPlayCountsSeries[c]\n",
    "HOU2019Labels.append(\"Other\")\n",
    "HOU2019Values.append(otherHOU2019Count)\n",
    "\n",
    "\n",
    "HOU2020Labels = []\n",
    "HOU2020Values = []\n",
    "HOU2020Counts = 6\n",
    "otherHOU2020Count = 0\n",
    "for c in HOU2020SpecialTeamPlayCountsSeries.index:\n",
    "    if HOU2020Counts > 0:\n",
    "        HOU2020Labels.append(c)\n",
    "        HOU2020Values.append(HOU2020SpecialTeamPlayCountsSeries[c])\n",
    "        HOU2020Counts -= 1\n",
    "    else:\n",
    "        otherHOU2020Count += HOU2020SpecialTeamPlayCountsSeries[c]\n",
    "HOU2020Labels.append(\"Other\")\n",
    "HOU2020Values.append(otherHOU2020Count)\n",
    "\n",
    "\n",
    "IND2018Labels = []\n",
    "IND2018Values = []\n",
    "IND2018Counts = 6\n",
    "otherIND2018Count = 0\n",
    "for c in IND2018SpecialTeamPlayCountsSeries.index:\n",
    "    if IND2018Counts > 0:\n",
    "        IND2018Labels.append(c)\n",
    "        IND2018Values.append(IND2018SpecialTeamPlayCountsSeries[c])\n",
    "        IND2018Counts -= 1\n",
    "    else:\n",
    "        otherIND2018Count += IND2018SpecialTeamPlayCountsSeries[c]\n",
    "IND2018Labels.append(\"Other\")\n",
    "IND2018Values.append(otherIND2018Count)\n",
    "\n",
    "\n",
    "IND2019Labels = []\n",
    "IND2019Values = []\n",
    "IND2019Counts = 6\n",
    "otherIND2019Count = 0\n",
    "for c in IND2019SpecialTeamPlayCountsSeries.index:\n",
    "    if IND2019Counts > 0:\n",
    "        IND2019Labels.append(c)\n",
    "        IND2019Values.append(IND2019SpecialTeamPlayCountsSeries[c])\n",
    "        IND2019Counts -= 1\n",
    "    else:\n",
    "        otherIND2019Count += IND2019SpecialTeamPlayCountsSeries[c]\n",
    "IND2019Labels.append(\"Other\")\n",
    "IND2019Values.append(otherIND2019Count)\n",
    "\n",
    "\n",
    "IND2020Labels = []\n",
    "IND2020Values = []\n",
    "IND2020Counts = 6\n",
    "otherIND2020Count = 0\n",
    "for c in IND2020SpecialTeamPlayCountsSeries.index:\n",
    "    if IND2020Counts > 0:\n",
    "        IND2020Labels.append(c)\n",
    "        IND2020Values.append(IND2020SpecialTeamPlayCountsSeries[c])\n",
    "        IND2020Counts -= 1\n",
    "    else:\n",
    "        otherIND2020Count += IND2020SpecialTeamPlayCountsSeries[c]\n",
    "IND2020Labels.append(\"Other\")\n",
    "IND2020Values.append(otherIND2020Count)\n",
    "\n",
    "\n",
    "JAX2018Labels = []\n",
    "JAX2018Values = []\n",
    "JAX2018Counts = 6\n",
    "otherJAX2018Count = 0\n",
    "for c in JAX2018SpecialTeamPlayCountsSeries.index:\n",
    "    if JAX2018Counts > 0:\n",
    "        JAX2018Labels.append(c)\n",
    "        JAX2018Values.append(JAX2018SpecialTeamPlayCountsSeries[c])\n",
    "        JAX2018Counts -= 1\n",
    "    else:\n",
    "        otherJAX2018Count += JAX2018SpecialTeamPlayCountsSeries[c]\n",
    "JAX2018Labels.append(\"Other\")\n",
    "JAX2018Values.append(otherJAX2018Count)\n",
    "\n",
    "\n",
    "JAX2019Labels = []\n",
    "JAX2019Values = []\n",
    "JAX2019Counts = 6\n",
    "otherJAX2019Count = 0\n",
    "for c in JAX2019SpecialTeamPlayCountsSeries.index:\n",
    "    if JAX2019Counts > 0:\n",
    "        JAX2019Labels.append(c)\n",
    "        JAX2019Values.append(JAX2019SpecialTeamPlayCountsSeries[c])\n",
    "        JAX2019Counts -= 1\n",
    "    else:\n",
    "        otherJAX2019Count += JAX2019SpecialTeamPlayCountsSeries[c]\n",
    "JAX2019Labels.append(\"Other\")\n",
    "JAX2019Values.append(otherJAX2019Count)\n",
    "\n",
    "\n",
    "JAX2020Labels = []\n",
    "JAX2020Values = []\n",
    "JAX2020Counts = 6\n",
    "otherJAX2020Count = 0\n",
    "for c in JAX2020SpecialTeamPlayCountsSeries.index:\n",
    "    if JAX2020Counts > 0:\n",
    "        JAX2020Labels.append(c)\n",
    "        JAX2020Values.append(JAX2020SpecialTeamPlayCountsSeries[c])\n",
    "        JAX2020Counts -= 1\n",
    "    else:\n",
    "        otherJAX2020Count += JAX2020SpecialTeamPlayCountsSeries[c]\n",
    "JAX2020Labels.append(\"Other\")\n",
    "JAX2020Values.append(otherJAX2020Count)\n",
    "\n",
    "\n",
    "KC2018Labels = []\n",
    "KC2018Values = []\n",
    "KC2018Counts = 6\n",
    "otherKC2018Count = 0\n",
    "for c in KC2018SpecialTeamPlayCountsSeries.index:\n",
    "    if KC2018Counts > 0:\n",
    "        KC2018Labels.append(c)\n",
    "        KC2018Values.append(KC2018SpecialTeamPlayCountsSeries[c])\n",
    "        KC2018Counts -= 1\n",
    "    else:\n",
    "        otherKC2018Count += KC2018SpecialTeamPlayCountsSeries[c]\n",
    "KC2018Labels.append(\"Other\")\n",
    "KC2018Values.append(otherKC2018Count)\n",
    "\n",
    "\n",
    "KC2019Labels = []\n",
    "KC2019Values = []\n",
    "KC2019Counts = 6\n",
    "otherKC2019Count = 0\n",
    "for c in KC2019SpecialTeamPlayCountsSeries.index:\n",
    "    if KC2019Counts > 0:\n",
    "        KC2019Labels.append(c)\n",
    "        KC2019Values.append(KC2019SpecialTeamPlayCountsSeries[c])\n",
    "        KC2019Counts -= 1\n",
    "    else:\n",
    "        otherKC2019Count += KC2019SpecialTeamPlayCountsSeries[c]\n",
    "KC2019Labels.append(\"Other\")\n",
    "KC2019Values.append(otherKC2019Count)\n",
    "\n",
    "\n",
    "KC2020Labels = []\n",
    "KC2020Values = []\n",
    "KC2020Counts = 6\n",
    "otherKC2020Count = 0\n",
    "for c in KC2020SpecialTeamPlayCountsSeries.index:\n",
    "    if KC2020Counts > 0:\n",
    "        KC2020Labels.append(c)\n",
    "        KC2020Values.append(KC2020SpecialTeamPlayCountsSeries[c])\n",
    "        KC2020Counts -= 1\n",
    "    else:\n",
    "        otherKC2020Count += KC2020SpecialTeamPlayCountsSeries[c]\n",
    "KC2020Labels.append(\"Other\")\n",
    "KC2020Values.append(otherKC2020Count)\n",
    "\n",
    "\n",
    "LA2018Labels = []\n",
    "LA2018Values = []\n",
    "LA2018Counts = 6\n",
    "otherLA2018Count = 0\n",
    "for c in LA2018SpecialTeamPlayCountsSeries.index:\n",
    "    if LA2018Counts > 0:\n",
    "        LA2018Labels.append(c)\n",
    "        LA2018Values.append(LA2018SpecialTeamPlayCountsSeries[c])\n",
    "        LA2018Counts -= 1\n",
    "    else:\n",
    "        otherLA2018Count += LA2018SpecialTeamPlayCountsSeries[c]\n",
    "LA2018Labels.append(\"Other\")\n",
    "LA2018Values.append(otherLA2018Count)\n",
    "\n",
    "\n",
    "LA2019Labels = []\n",
    "LA2019Values = []\n",
    "LA2019Counts = 6\n",
    "otherLA2019Count = 0\n",
    "for c in LA2019SpecialTeamPlayCountsSeries.index:\n",
    "    if LA2019Counts > 0:\n",
    "        LA2019Labels.append(c)\n",
    "        LA2019Values.append(LA2019SpecialTeamPlayCountsSeries[c])\n",
    "        LA2019Counts -= 1\n",
    "    else:\n",
    "        otherLA2019Count += LA2019SpecialTeamPlayCountsSeries[c]\n",
    "LA2019Labels.append(\"Other\")\n",
    "LA2019Values.append(otherLA2019Count)\n",
    "\n",
    "\n",
    "LA2020Labels = []\n",
    "LA2020Values = []\n",
    "LA2020Counts = 6\n",
    "otherLA2020Count = 0\n",
    "for c in LA2020SpecialTeamPlayCountsSeries.index:\n",
    "    if LA2020Counts > 0:\n",
    "        LA2020Labels.append(c)\n",
    "        LA2020Values.append(LA2020SpecialTeamPlayCountsSeries[c])\n",
    "        LA2020Counts -= 1\n",
    "    else:\n",
    "        otherLA2020Count += LA2020SpecialTeamPlayCountsSeries[c]\n",
    "LA2020Labels.append(\"Other\")\n",
    "LA2020Values.append(otherLA2020Count)\n",
    "\n",
    "\n",
    "LAC2018Labels = []\n",
    "LAC2018Values = []\n",
    "LAC2018Counts = 6\n",
    "otherLAC2018Count = 0\n",
    "for c in LAC2018SpecialTeamPlayCountsSeries.index:\n",
    "    if LAC2018Counts > 0:\n",
    "        LAC2018Labels.append(c)\n",
    "        LAC2018Values.append(LAC2018SpecialTeamPlayCountsSeries[c])\n",
    "        LAC2018Counts -= 1\n",
    "    else:\n",
    "        otherLAC2018Count += LAC2018SpecialTeamPlayCountsSeries[c]\n",
    "LAC2018Labels.append(\"Other\")\n",
    "LAC2018Values.append(otherLAC2018Count)\n",
    "\n",
    "\n",
    "LAC2019Labels = []\n",
    "LAC2019Values = []\n",
    "LAC2019Counts = 6\n",
    "otherLAC2019Count = 0\n",
    "for c in LAC2019SpecialTeamPlayCountsSeries.index:\n",
    "    if LAC2019Counts > 0:\n",
    "        LAC2019Labels.append(c)\n",
    "        LAC2019Values.append(LAC2019SpecialTeamPlayCountsSeries[c])\n",
    "        LAC2019Counts -= 1\n",
    "    else:\n",
    "        otherLAC2019Count += LAC2019SpecialTeamPlayCountsSeries[c]\n",
    "LAC2019Labels.append(\"Other\")\n",
    "LAC2019Values.append(otherLAC2019Count)\n",
    "\n",
    "\n",
    "LAC2020Labels = []\n",
    "LAC2020Values = []\n",
    "LAC2020Counts = 6\n",
    "otherLAC2020Count = 0\n",
    "for c in LAC2020SpecialTeamPlayCountsSeries.index:\n",
    "    if LAC2020Counts > 0:\n",
    "        LAC2020Labels.append(c)\n",
    "        LAC2020Values.append(LAC2020SpecialTeamPlayCountsSeries[c])\n",
    "        LAC2020Counts -= 1\n",
    "    else:\n",
    "        otherLAC2020Count += LAC2020SpecialTeamPlayCountsSeries[c]\n",
    "LAC2020Labels.append(\"Other\")\n",
    "LAC2020Values.append(otherLAC2020Count)\n",
    "\n",
    "\n",
    "MIA2018Labels = []\n",
    "MIA2018Values = []\n",
    "MIA2018Counts = 6\n",
    "otherMIA2018Count = 0\n",
    "for c in MIA2018SpecialTeamPlayCountsSeries.index:\n",
    "    if MIA2018Counts > 0:\n",
    "        MIA2018Labels.append(c)\n",
    "        MIA2018Values.append(MIA2018SpecialTeamPlayCountsSeries[c])\n",
    "        MIA2018Counts -= 1\n",
    "    else:\n",
    "        otherMIA2018Count += MIA2018SpecialTeamPlayCountsSeries[c]\n",
    "MIA2018Labels.append(\"Other\")\n",
    "MIA2018Values.append(otherMIA2018Count)\n",
    "\n",
    "\n",
    "MIA2019Labels = []\n",
    "MIA2019Values = []\n",
    "MIA2019Counts = 6\n",
    "otherMIA2019Count = 0\n",
    "for c in MIA2019SpecialTeamPlayCountsSeries.index:\n",
    "    if MIA2019Counts > 0:\n",
    "        MIA2019Labels.append(c)\n",
    "        MIA2019Values.append(MIA2019SpecialTeamPlayCountsSeries[c])\n",
    "        MIA2019Counts -= 1\n",
    "    else:\n",
    "        otherMIA2019Count += MIA2019SpecialTeamPlayCountsSeries[c]\n",
    "MIA2019Labels.append(\"Other\")\n",
    "MIA2019Values.append(otherMIA2019Count)\n",
    "\n",
    "\n",
    "MIA2020Labels = []\n",
    "MIA2020Values = []\n",
    "MIA2020Counts = 6\n",
    "otherMIA2020Count = 0\n",
    "for c in MIA2020SpecialTeamPlayCountsSeries.index:\n",
    "    if MIA2020Counts > 0:\n",
    "        MIA2020Labels.append(c)\n",
    "        MIA2020Values.append(MIA2020SpecialTeamPlayCountsSeries[c])\n",
    "        MIA2020Counts -= 1\n",
    "    else:\n",
    "        otherMIA2020Count += MIA2020SpecialTeamPlayCountsSeries[c]\n",
    "MIA2020Labels.append(\"Other\")\n",
    "MIA2020Values.append(otherMIA2020Count)\n",
    "\n",
    "\n",
    "MIN2018Labels = []\n",
    "MIN2018Values = []\n",
    "MIN2018Counts = 6\n",
    "otherMIN2018Count = 0\n",
    "for c in MIN2018SpecialTeamPlayCountsSeries.index:\n",
    "    if MIN2018Counts > 0:\n",
    "        MIN2018Labels.append(c)\n",
    "        MIN2018Values.append(MIN2018SpecialTeamPlayCountsSeries[c])\n",
    "        MIN2018Counts -= 1\n",
    "    else:\n",
    "        otherMIN2018Count += MIN2018SpecialTeamPlayCountsSeries[c]\n",
    "MIN2018Labels.append(\"Other\")\n",
    "MIN2018Values.append(otherMIN2018Count)\n",
    "\n",
    "\n",
    "MIN2019Labels = []\n",
    "MIN2019Values = []\n",
    "MIN2019Counts = 6\n",
    "otherMIN2019Count = 0\n",
    "for c in MIN2019SpecialTeamPlayCountsSeries.index:\n",
    "    if MIN2019Counts > 0:\n",
    "        MIN2019Labels.append(c)\n",
    "        MIN2019Values.append(MIN2019SpecialTeamPlayCountsSeries[c])\n",
    "        MIN2019Counts -= 1\n",
    "    else:\n",
    "        otherMIN2019Count += MIN2019SpecialTeamPlayCountsSeries[c]\n",
    "MIN2019Labels.append(\"Other\")\n",
    "MIN2019Values.append(otherMIN2019Count)\n",
    "\n",
    "\n",
    "MIN2020Labels = []\n",
    "MIN2020Values = []\n",
    "MIN2020Counts = 6\n",
    "otherMIN2020Count = 0\n",
    "for c in MIN2020SpecialTeamPlayCountsSeries.index:\n",
    "    if MIN2020Counts > 0:\n",
    "        MIN2020Labels.append(c)\n",
    "        MIN2020Values.append(MIN2020SpecialTeamPlayCountsSeries[c])\n",
    "        MIN2020Counts -= 1\n",
    "    else:\n",
    "        otherMIN2020Count += MIN2020SpecialTeamPlayCountsSeries[c]\n",
    "MIN2020Labels.append(\"Other\")\n",
    "MIN2020Values.append(otherMIN2020Count)\n",
    "\n",
    "\n",
    "NE2018Labels = []\n",
    "NE2018Values = []\n",
    "NE2018Counts = 6\n",
    "otherNE2018Count = 0\n",
    "for c in NE2018SpecialTeamPlayCountsSeries.index:\n",
    "    if NE2018Counts > 0:\n",
    "        NE2018Labels.append(c)\n",
    "        NE2018Values.append(NE2018SpecialTeamPlayCountsSeries[c])\n",
    "        NE2018Counts -= 1\n",
    "    else:\n",
    "        otherNE2018Count += NE2018SpecialTeamPlayCountsSeries[c]\n",
    "NE2018Labels.append(\"Other\")\n",
    "NE2018Values.append(otherNE2018Count)\n",
    "\n",
    "\n",
    "NE2019Labels = []\n",
    "NE2019Values = []\n",
    "NE2019Counts = 6\n",
    "otherNE2019Count = 0\n",
    "for c in NE2019SpecialTeamPlayCountsSeries.index:\n",
    "    if NE2019Counts > 0:\n",
    "        NE2019Labels.append(c)\n",
    "        NE2019Values.append(NE2019SpecialTeamPlayCountsSeries[c])\n",
    "        NE2019Counts -= 1\n",
    "    else:\n",
    "        otherNE2019Count += NE2019SpecialTeamPlayCountsSeries[c]\n",
    "NE2019Labels.append(\"Other\")\n",
    "NE2019Values.append(otherNE2019Count)\n",
    "\n",
    "\n",
    "NE2020Labels = []\n",
    "NE2020Values = []\n",
    "NE2020Counts = 6\n",
    "otherNE2020Count = 0\n",
    "for c in NE2020SpecialTeamPlayCountsSeries.index:\n",
    "    if NE2020Counts > 0:\n",
    "        NE2020Labels.append(c)\n",
    "        NE2020Values.append(NE2020SpecialTeamPlayCountsSeries[c])\n",
    "        NE2020Counts -= 1\n",
    "    else:\n",
    "        otherNE2020Count += NE2020SpecialTeamPlayCountsSeries[c]\n",
    "NE2020Labels.append(\"Other\")\n",
    "NE2020Values.append(otherNE2020Count)\n",
    "\n",
    "\n",
    "NO2018Labels = []\n",
    "NO2018Values = []\n",
    "NO2018Counts = 6\n",
    "otherNO2018Count = 0\n",
    "for c in NO2018SpecialTeamPlayCountsSeries.index:\n",
    "    if NO2018Counts > 0:\n",
    "        NO2018Labels.append(c)\n",
    "        NO2018Values.append(NO2018SpecialTeamPlayCountsSeries[c])\n",
    "        NO2018Counts -= 1\n",
    "    else:\n",
    "        otherNO2018Count += NO2018SpecialTeamPlayCountsSeries[c]\n",
    "NO2018Labels.append(\"Other\")\n",
    "NO2018Values.append(otherNO2018Count)\n",
    "\n",
    "\n",
    "NO2019Labels = []\n",
    "NO2019Values = []\n",
    "NO2019Counts = 6\n",
    "otherNO2019Count = 0\n",
    "for c in NO2019SpecialTeamPlayCountsSeries.index:\n",
    "    if NO2019Counts > 0:\n",
    "        NO2019Labels.append(c)\n",
    "        NO2019Values.append(NO2019SpecialTeamPlayCountsSeries[c])\n",
    "        NO2019Counts -= 1\n",
    "    else:\n",
    "        otherNO2019Count += NO2019SpecialTeamPlayCountsSeries[c]\n",
    "NO2019Labels.append(\"Other\")\n",
    "NO2019Values.append(otherNO2019Count)\n",
    "\n",
    "\n",
    "NO2020Labels = []\n",
    "NO2020Values = []\n",
    "NO2020Counts = 6\n",
    "otherNO2020Count = 0\n",
    "for c in NO2020SpecialTeamPlayCountsSeries.index:\n",
    "    if NO2020Counts > 0:\n",
    "        NO2020Labels.append(c)\n",
    "        NO2020Values.append(NO2020SpecialTeamPlayCountsSeries[c])\n",
    "        NO2020Counts -= 1\n",
    "    else:\n",
    "        otherNO2020Count += NO2020SpecialTeamPlayCountsSeries[c]\n",
    "NO2020Labels.append(\"Other\")\n",
    "NO2020Values.append(otherNO2020Count)\n",
    "\n",
    "\n",
    "NYG2018Labels = []\n",
    "NYG2018Values = []\n",
    "NYG2018Counts = 6\n",
    "otherNYG2018Count = 0\n",
    "for c in NYG2018SpecialTeamPlayCountsSeries.index:\n",
    "    if NYG2018Counts > 0:\n",
    "        NYG2018Labels.append(c)\n",
    "        NYG2018Values.append(NYG2018SpecialTeamPlayCountsSeries[c])\n",
    "        NYG2018Counts -= 1\n",
    "    else:\n",
    "        otherNYG2018Count += NYG2018SpecialTeamPlayCountsSeries[c]\n",
    "NYG2018Labels.append(\"Other\")\n",
    "NYG2018Values.append(otherNYG2018Count)\n",
    "\n",
    "\n",
    "NYG2019Labels = []\n",
    "NYG2019Values = []\n",
    "NYG2019Counts = 6\n",
    "otherNYG2019Count = 0\n",
    "for c in NYG2019SpecialTeamPlayCountsSeries.index:\n",
    "    if NYG2019Counts > 0:\n",
    "        NYG2019Labels.append(c)\n",
    "        NYG2019Values.append(NYG2019SpecialTeamPlayCountsSeries[c])\n",
    "        NYG2019Counts -= 1\n",
    "    else:\n",
    "        otherNYG2019Count += NYG2019SpecialTeamPlayCountsSeries[c]\n",
    "NYG2019Labels.append(\"Other\")\n",
    "NYG2019Values.append(otherNYG2019Count)\n",
    "\n",
    "\n",
    "NYG2020Labels = []\n",
    "NYG2020Values = []\n",
    "NYG2020Counts = 6\n",
    "otherNYG2020Count = 0\n",
    "for c in NYG2020SpecialTeamPlayCountsSeries.index:\n",
    "    if NYG2020Counts > 0:\n",
    "        NYG2020Labels.append(c)\n",
    "        NYG2020Values.append(NYG2020SpecialTeamPlayCountsSeries[c])\n",
    "        NYG2020Counts -= 1\n",
    "    else:\n",
    "        otherNYG2020Count += NYG2020SpecialTeamPlayCountsSeries[c]\n",
    "NYG2020Labels.append(\"Other\")\n",
    "NYG2020Values.append(otherNYG2020Count)\n",
    "\n",
    "\n",
    "NYJ2018Labels = []\n",
    "NYJ2018Values = []\n",
    "NYJ2018Counts = 6\n",
    "otherNYJ2018Count = 0\n",
    "for c in NYJ2018SpecialTeamPlayCountsSeries.index:\n",
    "    if NYJ2018Counts > 0:\n",
    "        NYJ2018Labels.append(c)\n",
    "        NYJ2018Values.append(NYJ2018SpecialTeamPlayCountsSeries[c])\n",
    "        NYJ2018Counts -= 1\n",
    "    else:\n",
    "        otherNYJ2018Count += NYJ2018SpecialTeamPlayCountsSeries[c]\n",
    "NYJ2018Labels.append(\"Other\")\n",
    "NYJ2018Values.append(otherNYJ2018Count)\n",
    "\n",
    "\n",
    "NYJ2019Labels = []\n",
    "NYJ2019Values = []\n",
    "NYJ2019Counts = 6\n",
    "otherNYJ2019Count = 0\n",
    "for c in NYJ2019SpecialTeamPlayCountsSeries.index:\n",
    "    if NYJ2019Counts > 0:\n",
    "        NYJ2019Labels.append(c)\n",
    "        NYJ2019Values.append(NYJ2019SpecialTeamPlayCountsSeries[c])\n",
    "        NYJ2019Counts -= 1\n",
    "    else:\n",
    "        otherNYJ2019Count += NYJ2019SpecialTeamPlayCountsSeries[c]\n",
    "NYJ2019Labels.append(\"Other\")\n",
    "NYJ2019Values.append(otherNYJ2019Count)\n",
    "\n",
    "\n",
    "NYJ2020Labels = []\n",
    "NYJ2020Values = []\n",
    "NYJ2020Counts = 6\n",
    "otherNYJ2020Count = 0\n",
    "for c in NYJ2020SpecialTeamPlayCountsSeries.index:\n",
    "    if NYJ2020Counts > 0:\n",
    "        NYJ2020Labels.append(c)\n",
    "        NYJ2020Values.append(NYJ2020SpecialTeamPlayCountsSeries[c])\n",
    "        NYJ2020Counts -= 1\n",
    "    else:\n",
    "        otherNYJ2020Count += NYJ2020SpecialTeamPlayCountsSeries[c]\n",
    "NYJ2020Labels.append(\"Other\")\n",
    "NYJ2020Values.append(otherNYJ2020Count)\n",
    "\n",
    "OAK2018Labels = []\n",
    "OAK2018Values = []\n",
    "OAK2018Counts = 6\n",
    "otherOAK2018Count = 0\n",
    "for c in OAK2018SpecialTeamPlayCountsSeries.index:\n",
    "    if OAK2018Counts > 0:\n",
    "        OAK2018Labels.append(c)\n",
    "        OAK2018Values.append(OAK2018SpecialTeamPlayCountsSeries[c])\n",
    "        OAK2018Counts -= 1\n",
    "    else:\n",
    "        otherOAK2018Count += OAK2018SpecialTeamPlayCountsSeries[c]\n",
    "OAK2018Labels.append(\"Other\")\n",
    "OAK2018Values.append(otherOAK2018Count)\n",
    "\n",
    "\n",
    "OAK2019Labels = []\n",
    "OAK2019Values = []\n",
    "OAK2019Counts = 6\n",
    "otherOAK2019Count = 0\n",
    "for c in OAK2019SpecialTeamPlayCountsSeries.index:\n",
    "    if OAK2019Counts > 0:\n",
    "        OAK2019Labels.append(c)\n",
    "        OAK2019Values.append(OAK2019SpecialTeamPlayCountsSeries[c])\n",
    "        OAK2019Counts -= 1\n",
    "    else:\n",
    "        otherOAK2019Count += OAK2019SpecialTeamPlayCountsSeries[c]\n",
    "OAK2019Labels.append(\"Other\")\n",
    "OAK2019Values.append(otherOAK2019Count)\n",
    "\n",
    "\n",
    "OAK2020Labels = []\n",
    "OAK2020Values = []\n",
    "OAK2020Counts = 6\n",
    "otherOAK2020Count = 0\n",
    "for c in OAK2020SpecialTeamPlayCountsSeries.index:\n",
    "    if OAK2020Counts > 0:\n",
    "        OAK2020Labels.append(c)\n",
    "        OAK2020Values.append(OAK2020SpecialTeamPlayCountsSeries[c])\n",
    "        OAK2020Counts -= 1\n",
    "    else:\n",
    "        otherOAK2020Count += OAK2020SpecialTeamPlayCountsSeries[c]\n",
    "OAK2020Labels.append(\"Other\")\n",
    "OAK2020Values.append(otherOAK2020Count)\n",
    "\n",
    "\n",
    "PHI2018Labels = []\n",
    "PHI2018Values = []\n",
    "PHI2018Counts = 6\n",
    "otherPHI2018Count = 0\n",
    "for c in PHI2018SpecialTeamPlayCountsSeries.index:\n",
    "    if PHI2018Counts > 0:\n",
    "        PHI2018Labels.append(c)\n",
    "        PHI2018Values.append(PHI2018SpecialTeamPlayCountsSeries[c])\n",
    "        PHI2018Counts -= 1\n",
    "    else:\n",
    "        otherPHI2018Count += PHI2018SpecialTeamPlayCountsSeries[c]\n",
    "PHI2018Labels.append(\"Other\")\n",
    "PHI2018Values.append(otherPHI2018Count)\n",
    "\n",
    "\n",
    "PHI2019Labels = []\n",
    "PHI2019Values = []\n",
    "PHI2019Counts = 6\n",
    "otherPHI2019Count = 0\n",
    "for c in PHI2019SpecialTeamPlayCountsSeries.index:\n",
    "    if PHI2019Counts > 0:\n",
    "        PHI2019Labels.append(c)\n",
    "        PHI2019Values.append(PHI2019SpecialTeamPlayCountsSeries[c])\n",
    "        PHI2019Counts -= 1\n",
    "    else:\n",
    "        otherPHI2019Count += PHI2019SpecialTeamPlayCountsSeries[c]\n",
    "PHI2019Labels.append(\"Other\")\n",
    "PHI2019Values.append(otherPHI2019Count)\n",
    "\n",
    "\n",
    "PHI2020Labels = []\n",
    "PHI2020Values = []\n",
    "PHI2020Counts = 6\n",
    "otherPHI2020Count = 0\n",
    "for c in PHI2020SpecialTeamPlayCountsSeries.index:\n",
    "    if PHI2020Counts > 0:\n",
    "        PHI2020Labels.append(c)\n",
    "        PHI2020Values.append(PHI2020SpecialTeamPlayCountsSeries[c])\n",
    "        PHI2020Counts -= 1\n",
    "    else:\n",
    "        otherPHI2020Count += PHI2020SpecialTeamPlayCountsSeries[c]\n",
    "PHI2020Labels.append(\"Other\")\n",
    "PHI2020Values.append(otherPHI2020Count)\n",
    "\n",
    "\n",
    "PIT2018Labels = []\n",
    "PIT2018Values = []\n",
    "PIT2018Counts = 6\n",
    "otherPIT2018Count = 0\n",
    "for c in PIT2018SpecialTeamPlayCountsSeries.index:\n",
    "    if PIT2018Counts > 0:\n",
    "        PIT2018Labels.append(c)\n",
    "        PIT2018Values.append(PIT2018SpecialTeamPlayCountsSeries[c])\n",
    "        PIT2018Counts -= 1\n",
    "    else:\n",
    "        otherPIT2018Count += PIT2018SpecialTeamPlayCountsSeries[c]\n",
    "PIT2018Labels.append(\"Other\")\n",
    "PIT2018Values.append(otherPIT2018Count)\n",
    "\n",
    "\n",
    "PIT2019Labels = []\n",
    "PIT2019Values = []\n",
    "PIT2019Counts = 6\n",
    "otherPIT2019Count = 0\n",
    "for c in PIT2019SpecialTeamPlayCountsSeries.index:\n",
    "    if PIT2019Counts > 0:\n",
    "        PIT2019Labels.append(c)\n",
    "        PIT2019Values.append(PIT2019SpecialTeamPlayCountsSeries[c])\n",
    "        PIT2019Counts -= 1\n",
    "    else:\n",
    "        otherPIT2019Count += PIT2019SpecialTeamPlayCountsSeries[c]\n",
    "PIT2019Labels.append(\"Other\")\n",
    "PIT2019Values.append(otherPIT2019Count)\n",
    "\n",
    "\n",
    "PIT2020Labels = []\n",
    "PIT2020Values = []\n",
    "PIT2020Counts = 6\n",
    "otherPIT2020Count = 0\n",
    "for c in PIT2020SpecialTeamPlayCountsSeries.index:\n",
    "    if PIT2020Counts > 0:\n",
    "        PIT2020Labels.append(c)\n",
    "        PIT2020Values.append(PIT2020SpecialTeamPlayCountsSeries[c])\n",
    "        PIT2020Counts -= 1\n",
    "    else:\n",
    "        otherPIT2020Count += PIT2020SpecialTeamPlayCountsSeries[c]\n",
    "PIT2020Labels.append(\"Other\")\n",
    "PIT2020Values.append(otherPIT2020Count)\n",
    "\n",
    "\n",
    "SEA2018Labels = []\n",
    "SEA2018Values = []\n",
    "SEA2018Counts = 6\n",
    "otherSEA2018Count = 0\n",
    "for c in SEA2018SpecialTeamPlayCountsSeries.index:\n",
    "    if SEA2018Counts > 0:\n",
    "        SEA2018Labels.append(c)\n",
    "        SEA2018Values.append(SEA2018SpecialTeamPlayCountsSeries[c])\n",
    "        SEA2018Counts -= 1\n",
    "    else:\n",
    "        otherSEA2018Count += SEA2018SpecialTeamPlayCountsSeries[c]\n",
    "SEA2018Labels.append(\"Other\")\n",
    "SEA2018Values.append(otherSEA2018Count)\n",
    "\n",
    "\n",
    "SEA2019Labels = []\n",
    "SEA2019Values = []\n",
    "SEA2019Counts = 6\n",
    "otherSEA2019Count = 0\n",
    "for c in SEA2019SpecialTeamPlayCountsSeries.index:\n",
    "    if SEA2019Counts > 0:\n",
    "        SEA2019Labels.append(c)\n",
    "        SEA2019Values.append(SEA2019SpecialTeamPlayCountsSeries[c])\n",
    "        SEA2019Counts -= 1\n",
    "    else:\n",
    "        otherSEA2019Count += SEA2019SpecialTeamPlayCountsSeries[c]\n",
    "SEA2019Labels.append(\"Other\")\n",
    "SEA2019Values.append(otherSEA2019Count)\n",
    "\n",
    "\n",
    "SEA2020Labels = []\n",
    "SEA2020Values = []\n",
    "SEA2020Counts = 6\n",
    "otherSEA2020Count = 0\n",
    "for c in SEA2020SpecialTeamPlayCountsSeries.index:\n",
    "    if SEA2020Counts > 0:\n",
    "        SEA2020Labels.append(c)\n",
    "        SEA2020Values.append(SEA2020SpecialTeamPlayCountsSeries[c])\n",
    "        SEA2020Counts -= 1\n",
    "    else:\n",
    "        otherSEA2020Count += SEA2020SpecialTeamPlayCountsSeries[c]\n",
    "SEA2020Labels.append(\"Other\")\n",
    "SEA2020Values.append(otherSEA2020Count)\n",
    "\n",
    "\n",
    "SF2018Labels = []\n",
    "SF2018Values = []\n",
    "SF2018Counts = 6\n",
    "otherSF2018Count = 0\n",
    "for c in SF2018SpecialTeamPlayCountsSeries.index:\n",
    "    if SF2018Counts > 0:\n",
    "        SF2018Labels.append(c)\n",
    "        SF2018Values.append(SF2018SpecialTeamPlayCountsSeries[c])\n",
    "        SF2018Counts -= 1\n",
    "    else:\n",
    "        otherSF2018Count += SF2018SpecialTeamPlayCountsSeries[c]\n",
    "SF2018Labels.append(\"Other\")\n",
    "SF2018Values.append(otherSF2018Count)\n",
    "\n",
    "\n",
    "SF2019Labels = []\n",
    "SF2019Values = []\n",
    "SF2019Counts = 6\n",
    "otherSF2019Count = 0\n",
    "for c in SF2019SpecialTeamPlayCountsSeries.index:\n",
    "    if SF2019Counts > 0:\n",
    "        SF2019Labels.append(c)\n",
    "        SF2019Values.append(SF2019SpecialTeamPlayCountsSeries[c])\n",
    "        SF2019Counts -= 1\n",
    "    else:\n",
    "        otherSF2019Count += SF2019SpecialTeamPlayCountsSeries[c]\n",
    "SF2019Labels.append(\"Other\")\n",
    "SF2019Values.append(otherSF2019Count)\n",
    "\n",
    "\n",
    "SF2020Labels = []\n",
    "SF2020Values = []\n",
    "SF2020Counts = 6\n",
    "otherSF2020Count = 0\n",
    "for c in SF2020SpecialTeamPlayCountsSeries.index:\n",
    "    if SF2020Counts > 0:\n",
    "        SF2020Labels.append(c)\n",
    "        SF2020Values.append(SF2020SpecialTeamPlayCountsSeries[c])\n",
    "        SF2020Counts -= 1\n",
    "    else:\n",
    "        otherSF2020Count += SF2020SpecialTeamPlayCountsSeries[c]\n",
    "SF2020Labels.append(\"Other\")\n",
    "SF2020Values.append(otherSF2020Count)\n",
    "\n",
    "\n",
    "TB2018Labels = []\n",
    "TB2018Values = []\n",
    "TB2018Counts = 6\n",
    "otherTB2018Count = 0\n",
    "for c in TB2018SpecialTeamPlayCountsSeries.index:\n",
    "    if TB2018Counts > 0:\n",
    "        TB2018Labels.append(c)\n",
    "        TB2018Values.append(TB2018SpecialTeamPlayCountsSeries[c])\n",
    "        TB2018Counts -= 1\n",
    "    else:\n",
    "        otherTB2018Count += TB2018SpecialTeamPlayCountsSeries[c]\n",
    "TB2018Labels.append(\"Other\")\n",
    "TB2018Values.append(otherTB2018Count)\n",
    "\n",
    "\n",
    "TB2019Labels = []\n",
    "TB2019Values = []\n",
    "TB2019Counts = 6\n",
    "otherTB2019Count = 0\n",
    "for c in TB2019SpecialTeamPlayCountsSeries.index:\n",
    "    if TB2019Counts > 0:\n",
    "        TB2019Labels.append(c)\n",
    "        TB2019Values.append(TB2019SpecialTeamPlayCountsSeries[c])\n",
    "        TB2019Counts -= 1\n",
    "    else:\n",
    "        otherTB2019Count += TB2019SpecialTeamPlayCountsSeries[c]\n",
    "TB2019Labels.append(\"Other\")\n",
    "TB2019Values.append(otherTB2019Count)\n",
    "\n",
    "\n",
    "TB2020Labels = []\n",
    "TB2020Values = []\n",
    "TB2020Counts = 6\n",
    "otherTB2020Count = 0\n",
    "for c in TB2020SpecialTeamPlayCountsSeries.index:\n",
    "    if TB2020Counts > 0:\n",
    "        TB2020Labels.append(c)\n",
    "        TB2020Values.append(TB2020SpecialTeamPlayCountsSeries[c])\n",
    "        TB2020Counts -= 1\n",
    "    else:\n",
    "        otherTB2020Count += TB2020SpecialTeamPlayCountsSeries[c]\n",
    "TB2020Labels.append(\"Other\")\n",
    "TB2020Values.append(otherTB2020Count)\n",
    "\n",
    "\n",
    "TEN2018Labels = []\n",
    "TEN2018Values = []\n",
    "TEN2018Counts = 6\n",
    "otherTEN2018Count = 0\n",
    "for c in TEN2018SpecialTeamPlayCountsSeries.index:\n",
    "    if TEN2018Counts > 0:\n",
    "        TEN2018Labels.append(c)\n",
    "        TEN2018Values.append(TEN2018SpecialTeamPlayCountsSeries[c])\n",
    "        TEN2018Counts -= 1\n",
    "    else:\n",
    "        otherTEN2018Count += TEN2018SpecialTeamPlayCountsSeries[c]\n",
    "TEN2018Labels.append(\"Other\")\n",
    "TEN2018Values.append(otherTEN2018Count)\n",
    "\n",
    "\n",
    "TEN2019Labels = []\n",
    "TEN2019Values = []\n",
    "TEN2019Counts = 6\n",
    "otherTEN2019Count = 0\n",
    "for c in TEN2019SpecialTeamPlayCountsSeries.index:\n",
    "    if TEN2019Counts > 0:\n",
    "        TEN2019Labels.append(c)\n",
    "        TEN2019Values.append(TEN2019SpecialTeamPlayCountsSeries[c])\n",
    "        TEN2019Counts -= 1\n",
    "    else:\n",
    "        otherTEN2019Count += TEN2019SpecialTeamPlayCountsSeries[c]\n",
    "TEN2019Labels.append(\"Other\")\n",
    "TEN2019Values.append(otherTEN2019Count)\n",
    "\n",
    "\n",
    "TEN2020Labels = []\n",
    "TEN2020Values = []\n",
    "TEN2020Counts = 6\n",
    "otherTEN2020Count = 0\n",
    "for c in TEN2020SpecialTeamPlayCountsSeries.index:\n",
    "    if TEN2020Counts > 0:\n",
    "        TEN2020Labels.append(c)\n",
    "        TEN2020Values.append(TEN2020SpecialTeamPlayCountsSeries[c])\n",
    "        TEN2020Counts -= 1\n",
    "    else:\n",
    "        otherTEN2020Count += TEN2020SpecialTeamPlayCountsSeries[c]\n",
    "TEN2020Labels.append(\"Other\")\n",
    "TEN2020Values.append(otherTEN2020Count)\n",
    "\n",
    "\n",
    "WAS2018Labels = []\n",
    "WAS2018Values = []\n",
    "WAS2018Counts = 6\n",
    "otherWAS2018Count = 0\n",
    "for c in WAS2018SpecialTeamPlayCountsSeries.index:\n",
    "    if WAS2018Counts > 0:\n",
    "        WAS2018Labels.append(c)\n",
    "        WAS2018Values.append(WAS2018SpecialTeamPlayCountsSeries[c])\n",
    "        WAS2018Counts -= 1\n",
    "    else:\n",
    "        otherWAS2018Count += WAS2018SpecialTeamPlayCountsSeries[c]\n",
    "WAS2018Labels.append(\"Other\")\n",
    "WAS2018Values.append(otherWAS2018Count)\n",
    "\n",
    "\n",
    "WAS2019Labels = []\n",
    "WAS2019Values = []\n",
    "WAS2019Counts = 6\n",
    "otherWAS2019Count = 0\n",
    "for c in WAS2019SpecialTeamPlayCountsSeries.index:\n",
    "    if WAS2019Counts > 0:\n",
    "        WAS2019Labels.append(c)\n",
    "        WAS2019Values.append(WAS2019SpecialTeamPlayCountsSeries[c])\n",
    "        WAS2019Counts -= 1\n",
    "    else:\n",
    "        otherWAS2019Count += WAS2019SpecialTeamPlayCountsSeries[c]\n",
    "WAS2019Labels.append(\"Other\")\n",
    "WAS2019Values.append(otherWAS2019Count)\n",
    "\n",
    "\n",
    "WAS2020Labels = []\n",
    "WAS2020Values = []\n",
    "WAS2020Counts = 6\n",
    "otherWAS2020Count = 0\n",
    "for c in WAS2020SpecialTeamPlayCountsSeries.index:\n",
    "    if WAS2020Counts > 0:\n",
    "        WAS2020Labels.append(c)\n",
    "        WAS2020Values.append(WAS2020SpecialTeamPlayCountsSeries[c])\n",
    "        WAS2020Counts -= 1\n",
    "    else:\n",
    "        otherWAS2020Count += WAS2020SpecialTeamPlayCountsSeries[c]\n",
    "WAS2020Labels.append(\"Other\")\n",
    "WAS2020Values.append(otherWAS2020Count)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "991b20bc-251b-4f6b-9b11-63a5e8c047f6",
   "metadata": {},
   "outputs": [],
   "source": [
    "x = 0\n",
    "y = 0\n",
    "sns.set_style('dark')\n",
    "colors2018 = sns.color_palette('pastel')\n",
    "colors2019 = sns.color_palette('Set2')\n",
    "colors2020 = sns.color_palette('Set3')\n",
    "fig, axes = plt.subplots(8, 3, figsize=(180, 380))\n",
    "axes[0,0].pie(ARI2018Values, labels=ARI2018Labels, colors=colors2018, autopct='%.0f%%',\n",
    "            explode=[0.05 for i in ARI2018Labels], shadow=True, startangle=120,\n",
    "            textprops={'fontweight': 'semibold', 'fontsize': 90}, wedgeprops={'linewidth': 12, 'edgecolor': 'k'},\n",
    "            labeldistance=1.1)\n",
    "axes[0,0].add_artist(plt.Circle((0, 0), 0.35, fc='#E4E6EB', ec='black', lw=12))\n",
    "axes[0,0].set_title(\"ARI Special Team Plays 2018\", fontweight=\"bold\", fontsize=110, pad=21)\n",
    "axes[0,0].annotate(\"Season\\n2018\", xy=(x, y), fontweight=\"bold\", fontsize=110,va=\"center\", ha=\"center\")\n",
    "axes[0,1].pie(ARI2019Values, labels=ARI2019Labels, colors=colors2019, autopct='%.0f%%',\n",
    "            explode=[0.05 for i in ARI2019Labels], shadow=True, startangle=120,\n",
    "            textprops={'fontweight': 'semibold', 'fontsize': 90}, wedgeprops={'linewidth': 12, 'edgecolor': 'k'},\n",
    "            labeldistance=1.1)\n",
    "axes[0,1].add_artist(plt.Circle((0, 0), 0.35, fc='#E4E6EB', ec='black', lw=12))\n",
    "axes[0,1].set_title(\"ARI Special Team Plays 2019\", fontweight=\"bold\", fontsize=110, pad=21)\n",
    "axes[0,1].annotate(\"Season\\n2019\", xy=(x, y), fontweight=\"bold\", fontsize=110,va=\"center\",  ha=\"center\")\n",
    "axes[0,2].pie(ARI2020Values, labels=ARI2020Labels, colors=colors2020, autopct='%.0f%%',\n",
    "            explode=[0.05 for i in ARI2020Labels], shadow=True, startangle=120,\n",
    "            textprops={'fontweight': 'semibold', 'fontsize': 90}, wedgeprops={'linewidth': 12, 'edgecolor': 'k'},\n",
    "            labeldistance=1.1)\n",
    "axes[0,2].add_artist(plt.Circle((0, 0), 0.35, fc='#E4E6EB', ec='black', lw=12))\n",
    "axes[0,2].set_title(\"ARI Special Team Plays 2020\", fontweight=\"bold\", fontsize=110, pad=21)\n",
    "axes[0,2].annotate(\"Season\\n2020\", xy=(x, y), fontweight=\"bold\", fontsize=110,va=\"center\",  ha=\"center\")\n",
    "\n",
    "axes[1,0].pie(ATL2018Values, labels=ATL2018Labels, colors=colors2018, autopct='%.0f%%',\n",
    "            explode=[0.05 for i in ATL2018Labels], shadow=True, startangle=120,\n",
    "            textprops={'fontweight': 'semibold', 'fontsize': 90}, wedgeprops={'linewidth': 12, 'edgecolor': 'k'},\n",
    "            labeldistance=1.1)\n",
    "axes[1,0].add_artist(plt.Circle((0, 0), 0.35, fc='#E4E6EB', ec='black', lw=12))\n",
    "axes[1,0].set_title(\"ATL Special Team Plays 2018\", fontweight=\"bold\", fontsize=110, pad=21)\n",
    "axes[1,0].annotate(\"Season\\n2018\", xy=(x, y), fontweight=\"bold\", fontsize=110,va=\"center\",  ha=\"center\")\n",
    "axes[1,1].pie(ATL2019Values, labels=ATL2019Labels, colors=colors2019, autopct='%.0f%%',\n",
    "            explode=[0.05 for i in ATL2019Labels], shadow=True, startangle=120,\n",
    "            textprops={'fontweight': 'semibold', 'fontsize': 90}, wedgeprops={'linewidth': 12, 'edgecolor': 'k'},\n",
    "            labeldistance=1.1)\n",
    "axes[1,1].add_artist(plt.Circle((0, 0), 0.35, fc='#E4E6EB', ec='black', lw=12))\n",
    "axes[1,1].set_title(\"ATL Special Team Plays 2019\", fontweight=\"bold\", fontsize=110, pad=21)\n",
    "axes[1,1].annotate(\"Season\\n2019\", xy=(x, y), fontweight=\"bold\", fontsize=110,va=\"center\",  ha=\"center\")\n",
    "axes[1,2].pie(ATL2020Values, labels=ATL2020Labels, colors=colors2020, autopct='%.0f%%',\n",
    "            explode=[0.05 for i in ATL2020Labels], shadow=True, startangle=120,\n",
    "            textprops={'fontweight': 'semibold', 'fontsize': 90}, wedgeprops={'linewidth': 12, 'edgecolor': 'k'},\n",
    "            labeldistance=1.1)\n",
    "axes[1,2].add_artist(plt.Circle((0, 0), 0.35, fc='#E4E6EB', ec='black', lw=12))\n",
    "axes[1,2].set_title(\"ATL Special Team Plays 2020\", fontweight=\"bold\", fontsize=110, pad=21)\n",
    "axes[1,2].annotate(\"Season\\n2020\", xy=(x, y), fontweight=\"bold\", fontsize=110,va=\"center\",  ha=\"center\")\n",
    "\n",
    "axes[2,0].pie(BAL2018Values, labels=BAL2018Labels, colors=colors2018, autopct='%.0f%%',\n",
    "            explode=[0.05 for i in BAL2018Labels], shadow=True, startangle=120,\n",
    "            textprops={'fontweight': 'semibold', 'fontsize': 90}, wedgeprops={'linewidth': 12, 'edgecolor': 'k'},\n",
    "            labeldistance=1.1)\n",
    "axes[2,0].add_artist(plt.Circle((0, 0), 0.35, fc='#E4E6EB', ec='black', lw=12))\n",
    "axes[2,0].set_title(\"BAL Special Team Plays 2018\", fontweight=\"bold\", fontsize=110, pad=21)\n",
    "axes[2,0].annotate(\"Season\\n2018\", xy=(x, y), fontweight=\"bold\", fontsize=110,va=\"center\",  ha=\"center\")\n",
    "axes[2,1].pie(BAL2019Values, labels=BAL2019Labels, colors=colors2019, autopct='%.0f%%',\n",
    "            explode=[0.05 for i in BAL2019Labels], shadow=True, startangle=120,\n",
    "            textprops={'fontweight': 'semibold', 'fontsize': 90}, wedgeprops={'linewidth': 12, 'edgecolor': 'k'},\n",
    "            labeldistance=1.1)\n",
    "axes[2,1].add_artist(plt.Circle((0, 0), 0.35, fc='#E4E6EB', ec='black', lw=12))\n",
    "axes[2,1].set_title(\"BAL Special Team Plays 2019\", fontweight=\"bold\", fontsize=110, pad=21)\n",
    "axes[2,1].annotate(\"Season\\n2019\", xy=(x, y), fontweight=\"bold\", fontsize=110,va=\"center\",  ha=\"center\")\n",
    "axes[2,2].pie(BAL2020Values, labels=BAL2020Labels, colors=colors2020, autopct='%.0f%%',\n",
    "            explode=[0.05 for i in BAL2020Labels], shadow=True, startangle=120,\n",
    "            textprops={'fontweight': 'semibold', 'fontsize': 90}, wedgeprops={'linewidth': 12, 'edgecolor': 'k'},\n",
    "            labeldistance=1.1)\n",
    "axes[2,2].add_artist(plt.Circle((0, 0), 0.35, fc='#E4E6EB', ec='black', lw=12))\n",
    "axes[2,2].set_title(\"BAL Special Team Plays 2020\", fontweight=\"bold\", fontsize=110, pad=21)\n",
    "axes[2,2].annotate(\"Season\\n2020\", xy=(x, y), fontweight=\"bold\", fontsize=110,va=\"center\",  ha=\"center\")\n",
    "\n",
    "axes[3,0].pie(BUF2018Values, labels=BUF2018Labels, colors=colors2018, autopct='%.0f%%',\n",
    "            explode=[0.05 for i in BUF2018Labels], shadow=True, startangle=110,\n",
    "            textprops={'fontweight': 'semibold', 'fontsize': 90}, wedgeprops={'linewidth': 12, 'edgecolor': 'k'},\n",
    "            labeldistance=1.1)\n",
    "axes[3,0].add_artist(plt.Circle((0, 0), 0.35, fc='#E4E6EB', ec='black', lw=12))\n",
    "axes[3,0].set_title(\"BUF Special Team Plays 2018\", fontweight=\"bold\", fontsize=110, pad=21)\n",
    "axes[3,0].annotate(\"Season\\n2018\", xy=(x, y), fontweight=\"bold\", fontsize=110,va=\"center\",  ha=\"center\")\n",
    "axes[3,1].pie(BUF2019Values, labels=BUF2019Labels, colors=colors2019, autopct='%.0f%%',\n",
    "            explode=[0.05 for i in BUF2019Labels], shadow=True, startangle=130,\n",
    "            textprops={'fontweight': 'semibold', 'fontsize': 90}, wedgeprops={'linewidth': 12, 'edgecolor': 'k'},\n",
    "            labeldistance=1.1)\n",
    "axes[3,1].add_artist(plt.Circle((0, 0), 0.35, fc='#E4E6EB', ec='black', lw=12))\n",
    "axes[3,1].set_title(\"BUF Special Team Plays 2019\", fontweight=\"bold\", fontsize=110, pad=21)\n",
    "axes[3,1].annotate(\"Season\\n2019\", xy=(x, y), fontweight=\"bold\", fontsize=110,va=\"center\",  ha=\"center\")\n",
    "axes[3,2].pie(BUF2020Values, labels=BUF2020Labels, colors=colors2020, autopct='%.0f%%',\n",
    "            explode=[0.05 for i in BUF2020Labels], shadow=True, startangle=120,\n",
    "            textprops={'fontweight': 'semibold', 'fontsize': 90}, wedgeprops={'linewidth': 12, 'edgecolor': 'k'},\n",
    "            labeldistance=1.1)\n",
    "axes[3,2].add_artist(plt.Circle((0, 0), 0.35, fc='#E4E6EB', ec='black', lw=12))\n",
    "axes[3,2].set_title(\"BUF Special Team Plays 2020\", fontweight=\"bold\", fontsize=110, pad=21)\n",
    "axes[3,2].annotate(\"Season\\n2020\", xy=(x, y), fontweight=\"bold\", fontsize=110,va=\"center\",  ha=\"center\")\n",
    "\n",
    "axes[4,0].pie(CAR2018Values, labels=CAR2018Labels, colors=colors2018, autopct='%.0f%%',\n",
    "            explode=[0.05 for i in CAR2018Labels], shadow=True, startangle=120,\n",
    "            textprops={'fontweight': 'semibold', 'fontsize': 90}, wedgeprops={'linewidth': 12, 'edgecolor': 'k'},\n",
    "            labeldistance=1.1)\n",
    "axes[4,0].add_artist(plt.Circle((0, 0), 0.35, fc='#E4E6EB', ec='black', lw=12))\n",
    "axes[4,0].set_title(\"CAR Special Team Plays 2018\", fontweight=\"bold\", fontsize=110, pad=21)\n",
    "axes[4,0].annotate(\"Season\\n2018\", xy=(x, y), fontweight=\"bold\", fontsize=110,va=\"center\",  ha=\"center\")\n",
    "axes[4,1].pie(CAR2019Values, labels=CAR2019Labels, colors=colors2019, autopct='%.0f%%',\n",
    "            explode=[0.05 for i in CAR2019Labels], shadow=True, startangle=120,\n",
    "            textprops={'fontweight': 'semibold', 'fontsize': 90}, wedgeprops={'linewidth': 12, 'edgecolor': 'k'},\n",
    "            labeldistance=1.1)\n",
    "axes[4,1].add_artist(plt.Circle((0, 0), 0.35, fc='#E4E6EB', ec='black', lw=12))\n",
    "axes[4,1].set_title(\"CAR Special Team Plays 2019\", fontweight=\"bold\", fontsize=110, pad=21)\n",
    "axes[4,1].annotate(\"Season\\n2019\", xy=(x, y), fontweight=\"bold\", fontsize=110,va=\"center\",  ha=\"center\")\n",
    "axes[4,2].pie(CAR2020Values, labels=CAR2020Labels, colors=colors2020, autopct='%.0f%%',\n",
    "            explode=[0.05 for i in CAR2020Labels], shadow=True, startangle=120,\n",
    "            textprops={'fontweight': 'semibold', 'fontsize': 90}, wedgeprops={'linewidth': 12, 'edgecolor': 'k'},\n",
    "            labeldistance=1.1)\n",
    "axes[4,2].add_artist(plt.Circle((0, 0), 0.35, fc='#E4E6EB', ec='black', lw=12))\n",
    "axes[4,2].set_title(\"CAR Special Team Plays 2020\", fontweight=\"bold\", fontsize=110, pad=21)\n",
    "axes[4,2].annotate(\"Season\\n2020\", xy=(x, y), fontweight=\"bold\", fontsize=110,va=\"center\", ha=\"center\")\n",
    "\n",
    "axes[5,0].pie(CHI2018Values, labels=CHI2018Labels, colors=colors2018, autopct='%.0f%%',\n",
    "            explode=[0.05 for i in CHI2018Labels], shadow=True, startangle=120,\n",
    "            textprops={'fontweight': 'semibold', 'fontsize': 90}, wedgeprops={'linewidth': 12, 'edgecolor': 'k'},\n",
    "            labeldistance=1.1)\n",
    "axes[5,0].add_artist(plt.Circle((0, 0), 0.35, fc='#E4E6EB', ec='black', lw=12))\n",
    "axes[5,0].set_title(\"CHI Special Team Plays 2018\", fontweight=\"bold\", fontsize=110, pad=21)\n",
    "axes[5,0].annotate(\"Season\\n2018\", xy=(x, y), fontweight=\"bold\", fontsize=110,va=\"center\",  ha=\"center\")\n",
    "axes[5,1].pie(CHI2019Values, labels=CHI2019Labels, colors=colors2019, autopct='%.0f%%',\n",
    "            explode=[0.05 for i in CHI2019Labels], shadow=True, startangle=120,\n",
    "            textprops={'fontweight': 'semibold', 'fontsize': 90}, wedgeprops={'linewidth': 12, 'edgecolor': 'k'},\n",
    "            labeldistance=1.1)\n",
    "axes[5,1].add_artist(plt.Circle((0, 0), 0.35, fc='#E4E6EB', ec='black', lw=12))\n",
    "axes[5,1].set_title(\"CHI Special Team Plays 2019\", fontweight=\"bold\", fontsize=110, pad=21)\n",
    "axes[5,1].annotate(\"Season\\n2019\", xy=(x, y), fontweight=\"bold\", fontsize=110,va=\"center\",  ha=\"center\")\n",
    "axes[5,2].pie(CHI2020Values, labels=CHI2020Labels, colors=colors2020, autopct='%.0f%%',\n",
    "            explode=[0.05 for i in CHI2020Labels], shadow=True, startangle=120,\n",
    "            textprops={'fontweight': 'semibold', 'fontsize': 90}, wedgeprops={'linewidth': 12, 'edgecolor': 'k'},\n",
    "            labeldistance=1.1)\n",
    "axes[5,2].add_artist(plt.Circle((0, 0), 0.35, fc='#E4E6EB', ec='black', lw=12))\n",
    "axes[5,2].set_title(\"CHI Special Team Plays 2020\", fontweight=\"bold\", fontsize=110, pad=21)\n",
    "axes[5,2].annotate(\"Season\\n2020\", xy=(x, y), fontweight=\"bold\", fontsize=110,va=\"center\",  ha=\"center\")\n",
    "\n",
    "axes[6,0].pie(CIN2018Values, labels=CIN2018Labels, colors=colors2018, autopct='%.0f%%',\n",
    "            explode=[0.05 for i in CIN2018Labels], shadow=True, startangle=120,\n",
    "            textprops={'fontweight': 'semibold', 'fontsize': 90}, wedgeprops={'linewidth': 12, 'edgecolor': 'k'},\n",
    "            labeldistance=1.1)\n",
    "axes[6,0].add_artist(plt.Circle((0, 0), 0.35, fc='#E4E6EB', ec='black', lw=12))\n",
    "axes[6,0].set_title(\"CIN Special Team Plays 2018\", fontweight=\"bold\", fontsize=110, pad=21)\n",
    "axes[6,0].annotate(\"Season\\n2018\", xy=(x, y), fontweight=\"bold\", fontsize=110,va=\"center\",  ha=\"center\")\n",
    "axes[6,1].pie(CIN2019Values, labels=CIN2019Labels, colors=colors2019, autopct='%.0f%%',\n",
    "            explode=[0.05 for i in CIN2019Labels], shadow=True, startangle=120,\n",
    "            textprops={'fontweight': 'semibold', 'fontsize': 90}, wedgeprops={'linewidth': 12, 'edgecolor': 'k'},\n",
    "            labeldistance=1.1)\n",
    "axes[6,1].add_artist(plt.Circle((0, 0), 0.35, fc='#E4E6EB', ec='black', lw=12))\n",
    "axes[6,1].set_title(\"CIN Special Team Plays 2019\", fontweight=\"bold\", fontsize=110, pad=21)\n",
    "axes[6,1].annotate(\"Season\\n2019\", xy=(x, y), fontweight=\"bold\", fontsize=110,va=\"center\",  ha=\"center\")\n",
    "axes[6,2].pie(CIN2020Values, labels=CIN2020Labels, colors=colors2020, autopct='%.0f%%',\n",
    "            explode=[0.05 for i in CIN2020Labels], shadow=True, startangle=120,\n",
    "            textprops={'fontweight': 'semibold', 'fontsize': 90}, wedgeprops={'linewidth': 12, 'edgecolor': 'k'},\n",
    "            labeldistance=1.1)\n",
    "axes[6,2].add_artist(plt.Circle((0, 0), 0.35, fc='#E4E6EB', ec='black', lw=12))\n",
    "axes[6,2].set_title(\"CIN Special Team Plays 2020\", fontweight=\"bold\", fontsize=110, pad=21)\n",
    "axes[6,2].annotate(\"Season\\n2020\", xy=(x, y), fontweight=\"bold\", fontsize=110,va=\"center\",  ha=\"center\")\n",
    "\n",
    "axes[7,0].pie(CLE2018Values, labels=CLE2018Labels, colors=colors2018, autopct='%.0f%%',\n",
    "            explode=[0.05 for i in CLE2018Labels], shadow=True, startangle=120,\n",
    "            textprops={'fontweight': 'semibold', 'fontsize': 90}, wedgeprops={'linewidth': 12, 'edgecolor': 'k'},\n",
    "            labeldistance=1.1)\n",
    "axes[7,0].add_artist(plt.Circle((0, 0), 0.35, fc='#E4E6EB', ec='black', lw=12))\n",
    "axes[7,0].set_title(\"CLE Special Team Plays 2018\", fontweight=\"bold\", fontsize=110, pad=21)\n",
    "axes[7,0].annotate(\"Season\\n2018\", xy=(x, y), fontweight=\"bold\", fontsize=110,va=\"center\",  ha=\"center\")\n",
    "axes[7,1].pie(CLE2019Values, labels=CLE2019Labels, colors=colors2019, autopct='%.0f%%',\n",
    "            explode=[0.05 for i in CLE2019Labels], shadow=True, startangle=120,\n",
    "            textprops={'fontweight': 'semibold', 'fontsize': 90}, wedgeprops={'linewidth': 12, 'edgecolor': 'k'},\n",
    "            labeldistance=1.1)\n",
    "axes[7,1].add_artist(plt.Circle((0, 0), 0.35, fc='#E4E6EB', ec='black', lw=12))\n",
    "axes[7,1].set_title(\"CLE Special Team Plays 2019\", fontweight=\"bold\", fontsize=110, pad=21)\n",
    "axes[7,1].annotate(\"Season\\n2019\", xy=(x, y), fontweight=\"bold\", fontsize=110,va=\"center\",  ha=\"center\")\n",
    "axes[7,2].pie(CLE2020Values, labels=CLE2020Labels, colors=colors2020, autopct='%.0f%%',\n",
    "            explode=[0.05 for i in CLE2020Labels], shadow=True, startangle=120,\n",
    "            textprops={'fontweight': 'semibold', 'fontsize': 90}, wedgeprops={'linewidth': 12, 'edgecolor': 'k'},\n",
    "            labeldistance=1.1)\n",
    "axes[7,2].add_artist(plt.Circle((0, 0), 0.35, fc='#E4E6EB', ec='black', lw=12))\n",
    "axes[7,2].set_title(\"CLE Special Team Plays 2020\", fontweight=\"bold\", fontsize=110, pad=21)\n",
    "axes[7,2].annotate(\"Season\\n2020\", xy=(x, y), fontweight=\"bold\", fontsize=110, va=\"center\", ha=\"center\")\n",
    "fig.suptitle(\"NFL Special Teams Play Analysis (2018-20) Part-I\", y=1, fontweight=\"bold\", fontsize=200)\n",
    "plt.tight_layout(pad=1, w_pad=1, h_pad=1)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "2aba3010-9cfe-4796-bf7f-5102607419e0",
   "metadata": {},
   "outputs": [],
   "source": [
    "sns.set_style(\"dark\")\n",
    "plt.figure(figsize=(20, 12))\n",
    "p1 = plt.bar(allARIData['ARI Special Play'],allARIData['2020'], color='#191970',edgecolor='black',linewidth=2)\n",
    "p2 = plt.bar(allARIData['ARI Special Play'],allARIData['2019'], bottom = allARIData['2020'], color='#FFD700',edgecolor='black',linewidth=2)\n",
    "p3 = plt.bar(allARIData['ARI Special Play'],allARIData['2018'], bottom = allARIData['2020'] + allARIData['2019'] , color='#97233f',edgecolor='black',linewidth=2)\n",
    "\n",
    "for r1,r2,r3 in zip(p1,p2,p3):\n",
    "    h1 = r1.get_height()\n",
    "    h2 = r2.get_height()\n",
    "    h3 = r3.get_height()\n",
    "    plt.text(r1.get_x()+r1.get_width()/2., h1+h2+h3, '%s'% (h1+h2+h3), ha = 'center', va='bottom',color='black', size=15)\n",
    "plt.legend([\"2020\", \"2019\", \"2018\"],prop={'size': 15})\n",
    "plt.title(\"ARI Special Team Plays\", fontweight=\"bold\", fontsize=25, pad=21)\n",
    "plt.xticks(fontsize=14,fontweight=\"bold\",rotation=90)\n",
    "plt.yticks(fontsize=14,fontweight=\"bold\")\n",
    "plt.tight_layout(pad=1, w_pad=1, h_pad=1)\n",
    "plt.show()\n",
    "\n",
    "plt.figure(figsize=(20, 12))\n",
    "p1 = plt.bar(allATLData['ATL Special Play'],allATLData['2020'], color='#a5acaf',edgecolor='black',linewidth=2)\n",
    "p2 = plt.bar(allATLData['ATL Special Play'],allATLData['2019'], bottom = allATLData['2020'], color='black',edgecolor='black',linewidth=2)\n",
    "p3 = plt.bar(allATLData['ATL Special Play'],allATLData['2018'], bottom = allATLData['2020'] + allATLData['2019'] , color='#a71930',edgecolor='black',linewidth=2)\n",
    "\n",
    "for r1,r2,r3 in zip(p1,p2,p3):\n",
    "    h1 = r1.get_height()\n",
    "    h2 = r2.get_height()\n",
    "    h3 = r3.get_height()\n",
    "    plt.text(r1.get_x()+r1.get_width()/2., h1+h2+h3, '%s'% (h1+h2+h3), ha = 'center', va='bottom',color='black', size=15)\n",
    "plt.legend([\"2020\", \"2019\", \"2018\"],prop={'size': 15})\n",
    "plt.title(\"ATL Special Team Plays\", fontweight=\"bold\", fontsize=25, pad=21)\n",
    "plt.xticks(fontsize=14,fontweight=\"bold\",rotation=90)\n",
    "plt.yticks(fontsize=14,fontweight=\"bold\")\n",
    "plt.tight_layout(pad=1, w_pad=1, h_pad=1)\n",
    "plt.show()\n",
    "\n",
    "plt.figure(figsize=(20, 12))\n",
    "p1 = plt.bar(allBALData['BAL Special Play'],allBALData['2020'], color='#241773',edgecolor='black',linewidth=2)\n",
    "p2 = plt.bar(allBALData['BAL Special Play'],allBALData['2019'], bottom = allBALData['2020'], color='white',edgecolor='black',linewidth=2)\n",
    "p3 = plt.bar(allBALData['BAL Special Play'],allBALData['2018'], bottom = allBALData['2020'] + allBALData['2019'] , color='#9e7c0c',edgecolor='black',linewidth=2)\n",
    "\n",
    "for r1,r2,r3 in zip(p1,p2,p3):\n",
    "    h1 = r1.get_height()\n",
    "    h2 = r2.get_height()\n",
    "    h3 = r3.get_height()\n",
    "    plt.text(r1.get_x()+r1.get_width()/2., h1+h2+h3, '%s'% (h1+h2+h3), ha = 'center', va='bottom',color='black', size=15)\n",
    "plt.legend([\"2020\", \"2019\", \"2018\"],prop={'size': 15})\n",
    "plt.title(\"BAL Special Team Plays\", fontweight=\"bold\", fontsize=25, pad=21)\n",
    "plt.xticks(fontsize=14,fontweight=\"bold\",rotation=90)\n",
    "plt.yticks(fontsize=14,fontweight=\"bold\")\n",
    "plt.tight_layout(pad=1, w_pad=1, h_pad=1)\n",
    "plt.show()\n",
    "\n",
    "plt.figure(figsize=(20, 12))\n",
    "p1 = plt.bar(allBUFData['BUF Special Play'],allBUFData['2020'], color='#00338d',edgecolor='black',linewidth=2)\n",
    "p2 = plt.bar(allBUFData['BUF Special Play'],allBUFData['2019'], bottom = allBUFData['2020'], color='#c60c30',edgecolor='black',linewidth=2)\n",
    "p3 = plt.bar(allBUFData['BUF Special Play'],allBUFData['2018'], bottom = allBUFData['2020'] + allBUFData['2019'] , color='#00274d',edgecolor='black',linewidth=2)\n",
    "\n",
    "for r1,r2,r3 in zip(p1,p2,p3):\n",
    "    h1 = r1.get_height()\n",
    "    h2 = r2.get_height()\n",
    "    h3 = r3.get_height()\n",
    "    plt.text(r1.get_x()+r1.get_width()/2., h1+h2+h3, '%s'% (h1+h2+h3), ha = 'center', va='bottom',color='black', size=15)\n",
    "plt.legend([\"2020\", \"2019\", \"2018\"],prop={'size': 15})\n",
    "plt.title(\"BUF Special Team Plays\", fontweight=\"bold\", fontsize=25, pad=21)\n",
    "plt.xticks(fontsize=14,fontweight=\"bold\",rotation=90)\n",
    "plt.yticks(fontsize=14,fontweight=\"bold\")\n",
    "plt.tight_layout(pad=1, w_pad=1, h_pad=1)\n",
    "plt.show()\n",
    "\n",
    "plt.figure(figsize=(20, 12))\n",
    "p1 = plt.bar(allCARData['CAR Special Play'],allCARData['2020'], color='#0085ca',edgecolor='black',linewidth=2)\n",
    "p2 = plt.bar(allCARData['CAR Special Play'],allCARData['2019'], bottom = allCARData['2020'], color='black',edgecolor='black',linewidth=2)\n",
    "p3 = plt.bar(allCARData['CAR Special Play'],allCARData['2018'], bottom = allCARData['2020'] + allCARData['2019'] , color='#bfc0bf',edgecolor='black',linewidth=2)\n",
    "\n",
    "for r1,r2,r3 in zip(p1,p2,p3):\n",
    "    h1 = r1.get_height()\n",
    "    h2 = r2.get_height()\n",
    "    h3 = r3.get_height()\n",
    "    plt.text(r1.get_x()+r1.get_width()/2., h1+h2+h3, '%s'% (h1+h2+h3), ha = 'center', va='bottom',color='black', size=15)\n",
    "plt.legend([\"2020\", \"2019\", \"2018\"],prop={'size': 15})\n",
    "plt.title(\"CAR Special Team Plays\", fontweight=\"bold\", fontsize=25, pad=21)\n",
    "plt.xticks(fontsize=14,fontweight=\"bold\",rotation=90)\n",
    "plt.yticks(fontsize=14,fontweight=\"bold\")\n",
    "plt.tight_layout(pad=1, w_pad=1, h_pad=1)\n",
    "plt.show()\n",
    "\n",
    "plt.figure(figsize=(20, 12))\n",
    "p1 = plt.bar(allCHIData['CHI Special Play'],allCHIData['2020'], color='#c83803',edgecolor='black',linewidth=2)\n",
    "p2 = plt.bar(allCHIData['CHI Special Play'],allCHIData['2019'], bottom = allCHIData['2020'], color='#191970',edgecolor='black',linewidth=2)\n",
    "p3 = plt.bar(allCHIData['CHI Special Play'],allCHIData['2018'], bottom = allCHIData['2020'] + allCHIData['2019'] , color='#a71930',edgecolor='black',linewidth=2)\n",
    "\n",
    "for r1,r2,r3 in zip(p1,p2,p3):\n",
    "    h1 = r1.get_height()\n",
    "    h2 = r2.get_height()\n",
    "    h3 = r3.get_height()\n",
    "    plt.text(r1.get_x()+r1.get_width()/2., h1+h2+h3, '%s'% (h1+h2+h3), ha = 'center', va='bottom',color='black', size=15)\n",
    "plt.legend([\"2020\", \"2019\", \"2018\"],prop={'size': 15})\n",
    "plt.title(\"CHI Special Team Plays\", fontweight=\"bold\", fontsize=25, pad=21)\n",
    "plt.xticks(fontsize=14,fontweight=\"bold\",rotation=90)\n",
    "plt.yticks(fontsize=14,fontweight=\"bold\")\n",
    "plt.tight_layout(pad=1, w_pad=1, h_pad=1)\n",
    "plt.show()\n",
    "\n",
    "plt.figure(figsize=(20, 12))\n",
    "p1 = plt.bar(allCINData['CIN Special Play'],allCINData['2020'], color='#fb4f14',edgecolor='black',linewidth=2)\n",
    "p2 = plt.bar(allCINData['CIN Special Play'],allCINData['2019'], bottom = allCINData['2020'], color='white',edgecolor='black',linewidth=2)\n",
    "p3 = plt.bar(allCINData['CIN Special Play'],allCINData['2018'], bottom = allCINData['2020'] + allCINData['2019'] , color='#97233f',edgecolor='black',linewidth=2)\n",
    "\n",
    "for r1,r2,r3 in zip(p1,p2,p3):\n",
    "    h1 = r1.get_height()\n",
    "    h2 = r2.get_height()\n",
    "    h3 = r3.get_height()\n",
    "    plt.text(r1.get_x()+r1.get_width()/2., h1+h2+h3, '%s'% (h1+h2+h3), ha = 'center', va='bottom',color='black', size=15)\n",
    "plt.legend([\"2020\", \"2019\", \"2018\"],prop={'size': 15})\n",
    "plt.title(\"CIN Special Team Plays\", fontweight=\"bold\", fontsize=25, pad=21)\n",
    "plt.xticks(fontsize=14,fontweight=\"bold\",rotation=90)\n",
    "plt.yticks(fontsize=14,fontweight=\"bold\")\n",
    "plt.tight_layout(pad=1, w_pad=1, h_pad=1)\n",
    "plt.show()\n",
    "\n",
    "plt.figure(figsize=(20, 12))\n",
    "p1 = plt.bar(allCLEData['CLE Special Play'],allCLEData['2020'], color='#311d00',edgecolor='black',linewidth=2)\n",
    "p2 = plt.bar(allCLEData['CLE Special Play'],allCLEData['2019'], bottom = allCLEData['2020'], color='white',edgecolor='black',linewidth=2)\n",
    "p3 = plt.bar(allCLEData['CLE Special Play'],allCLEData['2018'], bottom = allCLEData['2020'] + allCLEData['2019'] , color='#ff3c00',edgecolor='black',linewidth=2)\n",
    "\n",
    "for r1,r2,r3 in zip(p1,p2,p3):\n",
    "    h1 = r1.get_height()\n",
    "    h2 = r2.get_height()\n",
    "    h3 = r3.get_height()\n",
    "    plt.text(r1.get_x()+r1.get_width()/2., h1+h2+h3, '%s'% (h1+h2+h3), ha = 'center', va='bottom',color='black', size=15)\n",
    "plt.legend([\"2020\", \"2019\", \"2018\"],prop={'size': 15})\n",
    "plt.title(\"CLE Special Team Plays\", fontweight=\"bold\", fontsize=25, pad=21)\n",
    "plt.xticks(fontsize=14,fontweight=\"bold\",rotation=90)\n",
    "plt.yticks(fontsize=14,fontweight=\"bold\")\n",
    "plt.tight_layout(pad=1, w_pad=1, h_pad=1)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "91172c76-5bfa-4547-8001-be7c085eb385",
   "metadata": {},
   "outputs": [],
   "source": [
    "x = 0\n",
    "y = 0\n",
    "sns.set_style('dark')\n",
    "colors2018 = sns.color_palette('pastel')\n",
    "colors2019 = sns.color_palette('Set2')\n",
    "colors2020 = sns.color_palette('Set3')\n",
    "fig, axes = plt.subplots(8, 3, figsize=(180, 380))\n",
    "axes[0,0].pie(DAL2018Values, labels=DAL2018Labels, colors=colors2018, autopct='%.0f%%',\n",
    "            explode=[0.05 for i in DAL2018Labels], shadow=True, startangle=120,\n",
    "            textprops={'fontweight': 'semibold', 'fontsize': 90}, wedgeprops={'linewidth': 12, 'edgecolor': 'k'},\n",
    "            labeldistance=1.1)\n",
    "axes[0,0].add_artist(plt.Circle((0, 0), 0.35, fc='#E4E6EB', ec='black', lw=12))\n",
    "axes[0,0].set_title(\"DAL Special Team Plays 2018\", fontweight=\"bold\", fontsize=110, pad=21)\n",
    "axes[0,0].annotate(\"Season\\n2018\", xy=(x, y), fontweight=\"bold\", fontsize=110,va=\"center\", ha=\"center\")\n",
    "axes[0,1].pie(DAL2019Values, labels=DAL2019Labels, colors=colors2019, autopct='%.0f%%',\n",
    "            explode=[0.05 for i in DAL2019Labels], shadow=True, startangle=130,\n",
    "            textprops={'fontweight': 'semibold', 'fontsize': 90}, wedgeprops={'linewidth': 12, 'edgecolor': 'k'},\n",
    "            labeldistance=1.1)\n",
    "axes[0,1].add_artist(plt.Circle((0, 0), 0.35, fc='#E4E6EB', ec='black', lw=12))\n",
    "axes[0,1].set_title(\"DAL Special Team Plays 2019\", fontweight=\"bold\", fontsize=110, pad=21)\n",
    "axes[0,1].annotate(\"Season\\n2019\", xy=(x, y), fontweight=\"bold\", fontsize=110,va=\"center\",  ha=\"center\")\n",
    "axes[0,2].pie(DAL2020Values, labels=DAL2020Labels, colors=colors2020, autopct='%.0f%%',\n",
    "            explode=[0.05 for i in DAL2020Labels], shadow=True, startangle=120,\n",
    "            textprops={'fontweight': 'semibold', 'fontsize': 90}, wedgeprops={'linewidth': 12, 'edgecolor': 'k'},\n",
    "            labeldistance=1.1)\n",
    "axes[0,2].add_artist(plt.Circle((0, 0), 0.35, fc='#E4E6EB', ec='black', lw=12))\n",
    "axes[0,2].set_title(\"DAL Special Team Plays 2020\", fontweight=\"bold\", fontsize=110, pad=21)\n",
    "axes[0,2].annotate(\"Season\\n2020\", xy=(x, y), fontweight=\"bold\", fontsize=110,va=\"center\",  ha=\"center\")\n",
    "\n",
    "axes[1,0].pie(DEN2018Values, labels=DEN2018Labels, colors=colors2018, autopct='%.0f%%',\n",
    "            explode=[0.05 for i in DEN2018Labels], shadow=True, startangle=120,\n",
    "            textprops={'fontweight': 'semibold', 'fontsize': 90}, wedgeprops={'linewidth': 12, 'edgecolor': 'k'},\n",
    "            labeldistance=1.1)\n",
    "axes[1,0].add_artist(plt.Circle((0, 0), 0.35, fc='#E4E6EB', ec='black', lw=12))\n",
    "axes[1,0].set_title(\"DEN Special Team Plays 2018\", fontweight=\"bold\", fontsize=110, pad=21)\n",
    "axes[1,0].annotate(\"Season\\n2018\", xy=(x, y), fontweight=\"bold\", fontsize=110,va=\"center\",  ha=\"center\")\n",
    "axes[1,1].pie(DEN2019Values, labels=DEN2019Labels, colors=colors2019, autopct='%.0f%%',\n",
    "            explode=[0.05 for i in DEN2019Labels], shadow=True, startangle=120,\n",
    "            textprops={'fontweight': 'semibold', 'fontsize': 90}, wedgeprops={'linewidth': 12, 'edgecolor': 'k'},\n",
    "            labeldistance=1.1)\n",
    "axes[1,1].add_artist(plt.Circle((0, 0), 0.35, fc='#E4E6EB', ec='black', lw=12))\n",
    "axes[1,1].set_title(\"DEN Special Team Plays 2019\", fontweight=\"bold\", fontsize=110, pad=21)\n",
    "axes[1,1].annotate(\"Season\\n2019\", xy=(x, y), fontweight=\"bold\", fontsize=110,va=\"center\",  ha=\"center\")\n",
    "axes[1,2].pie(DEN2020Values, labels=DEN2020Labels, colors=colors2020, autopct='%.0f%%',\n",
    "            explode=[0.05 for i in DEN2020Labels], shadow=True, startangle=120,\n",
    "            textprops={'fontweight': 'semibold', 'fontsize': 90}, wedgeprops={'linewidth': 12, 'edgecolor': 'k'},\n",
    "            labeldistance=1.1)\n",
    "axes[1,2].add_artist(plt.Circle((0, 0), 0.35, fc='#E4E6EB', ec='black', lw=12))\n",
    "axes[1,2].set_title(\"DEN Special Team Plays 2020\", fontweight=\"bold\", fontsize=110, pad=21)\n",
    "axes[1,2].annotate(\"Season\\n2020\", xy=(x, y), fontweight=\"bold\", fontsize=110,va=\"center\",  ha=\"center\")\n",
    "\n",
    "axes[2,0].pie(DET2018Values, labels=DET2018Labels, colors=colors2018, autopct='%.0f%%',\n",
    "            explode=[0.05 for i in DET2018Labels], shadow=True, startangle=120,\n",
    "            textprops={'fontweight': 'semibold', 'fontsize': 90}, wedgeprops={'linewidth': 12, 'edgecolor': 'k'},\n",
    "            labeldistance=1.1)\n",
    "axes[2,0].add_artist(plt.Circle((0, 0), 0.35, fc='#E4E6EB', ec='black', lw=12))\n",
    "axes[2,0].set_title(\"DET Special Team Plays 2018\", fontweight=\"bold\", fontsize=110, pad=21)\n",
    "axes[2,0].annotate(\"Season\\n2018\", xy=(x, y), fontweight=\"bold\", fontsize=110,va=\"center\",  ha=\"center\")\n",
    "axes[2,1].pie(DET2019Values, labels=DET2019Labels, colors=colors2019, autopct='%.0f%%',\n",
    "            explode=[0.05 for i in DET2019Labels], shadow=True, startangle=120,\n",
    "            textprops={'fontweight': 'semibold', 'fontsize': 90}, wedgeprops={'linewidth': 12, 'edgecolor': 'k'},\n",
    "            labeldistance=1.1)\n",
    "axes[2,1].add_artist(plt.Circle((0, 0), 0.35, fc='#E4E6EB', ec='black', lw=12))\n",
    "axes[2,1].set_title(\"DET Special Team Plays 2019\", fontweight=\"bold\", fontsize=110, pad=21)\n",
    "axes[2,1].annotate(\"Season\\n2019\", xy=(x, y), fontweight=\"bold\", fontsize=110,va=\"center\",  ha=\"center\")\n",
    "axes[2,2].pie(DET2020Values, labels=DET2020Labels, colors=colors2020, autopct='%.0f%%',\n",
    "            explode=[0.05 for i in DET2020Labels], shadow=True, startangle=120,\n",
    "            textprops={'fontweight': 'semibold', 'fontsize': 90}, wedgeprops={'linewidth': 12, 'edgecolor': 'k'},\n",
    "            labeldistance=1.1)\n",
    "axes[2,2].add_artist(plt.Circle((0, 0), 0.35, fc='#E4E6EB', ec='black', lw=12))\n",
    "axes[2,2].set_title(\"DET Special Team Plays 2020\", fontweight=\"bold\", fontsize=110, pad=21)\n",
    "axes[2,2].annotate(\"Season\\n2020\", xy=(x, y), fontweight=\"bold\", fontsize=110,va=\"center\",  ha=\"center\")\n",
    "\n",
    "axes[3,0].pie(GB2018Values, labels=GB2018Labels, colors=colors2018, autopct='%.0f%%',\n",
    "            explode=[0.05 for i in GB2018Labels], shadow=True, startangle=120,\n",
    "            textprops={'fontweight': 'semibold', 'fontsize': 90}, wedgeprops={'linewidth': 12, 'edgecolor': 'k'},\n",
    "            labeldistance=1.1)\n",
    "axes[3,0].add_artist(plt.Circle((0, 0), 0.35, fc='#E4E6EB', ec='black', lw=12))\n",
    "axes[3,0].set_title(\"GB Special Team Plays 2018\", fontweight=\"bold\", fontsize=110, pad=21)\n",
    "axes[3,0].annotate(\"Season\\n2018\", xy=(x, y), fontweight=\"bold\", fontsize=110,va=\"center\",  ha=\"center\")\n",
    "axes[3,1].pie(GB2019Values, labels=GB2019Labels, colors=colors2019, autopct='%.0f%%',\n",
    "            explode=[0.05 for i in GB2019Labels], shadow=True, startangle=130,\n",
    "            textprops={'fontweight': 'semibold', 'fontsize': 90}, wedgeprops={'linewidth': 12, 'edgecolor': 'k'},\n",
    "            labeldistance=1.1)\n",
    "axes[3,1].add_artist(plt.Circle((0, 0), 0.35, fc='#E4E6EB', ec='black', lw=12))\n",
    "axes[3,1].set_title(\"GB Special Team Plays 2019\", fontweight=\"bold\", fontsize=110, pad=21)\n",
    "axes[3,1].annotate(\"Season\\n2019\", xy=(x, y), fontweight=\"bold\", fontsize=110,va=\"center\",  ha=\"center\")\n",
    "axes[3,2].pie(GB2020Values, labels=GB2020Labels, colors=colors2020, autopct='%.0f%%',\n",
    "            explode=[0.05 for i in GB2020Labels], shadow=True, startangle=120,\n",
    "            textprops={'fontweight': 'semibold', 'fontsize': 90}, wedgeprops={'linewidth': 12, 'edgecolor': 'k'},\n",
    "            labeldistance=1.1)\n",
    "axes[3,2].add_artist(plt.Circle((0, 0), 0.35, fc='#E4E6EB', ec='black', lw=12))\n",
    "axes[3,2].set_title(\"GB Special Team Plays 2020\", fontweight=\"bold\", fontsize=110, pad=21)\n",
    "axes[3,2].annotate(\"Season\\n2020\", xy=(x, y), fontweight=\"bold\", fontsize=110,va=\"center\",  ha=\"center\")\n",
    "\n",
    "axes[4,0].pie(HOU2018Values, labels=HOU2018Labels, colors=colors2018, autopct='%.0f%%',\n",
    "            explode=[0.05 for i in HOU2018Labels], shadow=True, startangle=120,\n",
    "            textprops={'fontweight': 'semibold', 'fontsize': 90}, wedgeprops={'linewidth': 12, 'edgecolor': 'k'},\n",
    "            labeldistance=1.1)\n",
    "axes[4,0].add_artist(plt.Circle((0, 0), 0.35, fc='#E4E6EB', ec='black', lw=12))\n",
    "axes[4,0].set_title(\"HOU Special Team Plays 2018\", fontweight=\"bold\", fontsize=110, pad=21)\n",
    "axes[4,0].annotate(\"Season\\n2018\", xy=(x, y), fontweight=\"bold\", fontsize=110,va=\"center\",  ha=\"center\")\n",
    "axes[4,1].pie(HOU2019Values, labels=HOU2019Labels, colors=colors2019, autopct='%.0f%%',\n",
    "            explode=[0.05 for i in HOU2019Labels], shadow=True, startangle=130,\n",
    "            textprops={'fontweight': 'semibold', 'fontsize': 90}, wedgeprops={'linewidth': 12, 'edgecolor': 'k'},\n",
    "            labeldistance=1.1)\n",
    "axes[4,1].add_artist(plt.Circle((0, 0), 0.35, fc='#E4E6EB', ec='black', lw=12))\n",
    "axes[4,1].set_title(\"HOU Special Team Plays 2019\", fontweight=\"bold\", fontsize=110, pad=21)\n",
    "axes[4,1].annotate(\"Season\\n2019\", xy=(x, y), fontweight=\"bold\", fontsize=110,va=\"center\",  ha=\"center\")\n",
    "axes[4,2].pie(HOU2020Values, labels=HOU2020Labels, colors=colors2020, autopct='%.0f%%',\n",
    "            explode=[0.05 for i in HOU2020Labels], shadow=True, startangle=120,\n",
    "            textprops={'fontweight': 'semibold', 'fontsize': 90}, wedgeprops={'linewidth': 12, 'edgecolor': 'k'},\n",
    "            labeldistance=1.1)\n",
    "axes[4,2].add_artist(plt.Circle((0, 0), 0.35, fc='#E4E6EB', ec='black', lw=12))\n",
    "axes[4,2].set_title(\"HOU Special Team Plays 2020\", fontweight=\"bold\", fontsize=110, pad=21)\n",
    "axes[4,2].annotate(\"Season\\n2020\", xy=(x, y), fontweight=\"bold\", fontsize=110,va=\"center\", ha=\"center\")\n",
    "\n",
    "axes[5,0].pie(IND2018Values, labels=IND2018Labels, colors=colors2018, autopct='%.0f%%',\n",
    "            explode=[0.05 for i in IND2018Labels], shadow=True, startangle=120,\n",
    "            textprops={'fontweight': 'semibold', 'fontsize': 90}, wedgeprops={'linewidth': 12, 'edgecolor': 'k'},\n",
    "            labeldistance=1.1)\n",
    "axes[5,0].add_artist(plt.Circle((0, 0), 0.35, fc='#E4E6EB', ec='black', lw=12))\n",
    "axes[5,0].set_title(\"IND Special Team Plays 2018\", fontweight=\"bold\", fontsize=110, pad=21)\n",
    "axes[5,0].annotate(\"Season\\n2018\", xy=(x, y), fontweight=\"bold\", fontsize=110,va=\"center\",  ha=\"center\")\n",
    "axes[5,1].pie(IND2019Values, labels=IND2019Labels, colors=colors2019, autopct='%.0f%%',\n",
    "            explode=[0.05 for i in IND2019Labels], shadow=True, startangle=120,\n",
    "            textprops={'fontweight': 'semibold', 'fontsize': 90}, wedgeprops={'linewidth': 12, 'edgecolor': 'k'},\n",
    "            labeldistance=1.1)\n",
    "axes[5,1].add_artist(plt.Circle((0, 0), 0.35, fc='#E4E6EB', ec='black', lw=12))\n",
    "axes[5,1].set_title(\"IND Special Team Plays 2019\", fontweight=\"bold\", fontsize=110, pad=21)\n",
    "axes[5,1].annotate(\"Season\\n2019\", xy=(x, y), fontweight=\"bold\", fontsize=110,va=\"center\",  ha=\"center\")\n",
    "axes[5,2].pie(IND2020Values, labels=IND2020Labels, colors=colors2020, autopct='%.0f%%',\n",
    "            explode=[0.05 for i in IND2020Labels], shadow=True, startangle=120,\n",
    "            textprops={'fontweight': 'semibold', 'fontsize': 90}, wedgeprops={'linewidth': 12, 'edgecolor': 'k'},\n",
    "            labeldistance=1.1)\n",
    "axes[5,2].add_artist(plt.Circle((0, 0), 0.35, fc='#E4E6EB', ec='black', lw=12))\n",
    "axes[5,2].set_title(\"IND Special Team Plays 2020\", fontweight=\"bold\", fontsize=110, pad=21)\n",
    "axes[5,2].annotate(\"Season\\n2020\", xy=(x, y), fontweight=\"bold\", fontsize=110,va=\"center\",  ha=\"center\")\n",
    "\n",
    "axes[6,0].pie(JAX2018Values, labels=JAX2018Labels, colors=colors2018, autopct='%.0f%%',\n",
    "            explode=[0.05 for i in JAX2018Labels], shadow=True, startangle=120,\n",
    "            textprops={'fontweight': 'semibold', 'fontsize': 90}, wedgeprops={'linewidth': 12, 'edgecolor': 'k'},\n",
    "            labeldistance=1.1)\n",
    "axes[6,0].add_artist(plt.Circle((0, 0), 0.35, fc='#E4E6EB', ec='black', lw=12))\n",
    "axes[6,0].set_title(\"JAX Special Team Plays 2018\", fontweight=\"bold\", fontsize=110, pad=21)\n",
    "axes[6,0].annotate(\"Season\\n2018\", xy=(x, y), fontweight=\"bold\", fontsize=110,va=\"center\",  ha=\"center\")\n",
    "axes[6,1].pie(JAX2019Values, labels=JAX2019Labels, colors=colors2019, autopct='%.0f%%',\n",
    "            explode=[0.05 for i in JAX2019Labels], shadow=True, startangle=120,\n",
    "            textprops={'fontweight': 'semibold', 'fontsize': 90}, wedgeprops={'linewidth': 12, 'edgecolor': 'k'},\n",
    "            labeldistance=1.1)\n",
    "axes[6,1].add_artist(plt.Circle((0, 0), 0.35, fc='#E4E6EB', ec='black', lw=12))\n",
    "axes[6,1].set_title(\"JAX Special Team Plays 2019\", fontweight=\"bold\", fontsize=110, pad=21)\n",
    "axes[6,1].annotate(\"Season\\n2019\", xy=(x, y), fontweight=\"bold\", fontsize=110,va=\"center\",  ha=\"center\")\n",
    "axes[6,2].pie(JAX2020Values, labels=JAX2020Labels, colors=colors2020, autopct='%.0f%%',\n",
    "            explode=[0.05 for i in JAX2020Labels], shadow=True, startangle=120,\n",
    "            textprops={'fontweight': 'semibold', 'fontsize': 90}, wedgeprops={'linewidth': 12, 'edgecolor': 'k'},\n",
    "            labeldistance=1.1)\n",
    "axes[6,2].add_artist(plt.Circle((0, 0), 0.35, fc='#E4E6EB', ec='black', lw=12))\n",
    "axes[6,2].set_title(\"JAX Special Team Plays 2020\", fontweight=\"bold\", fontsize=110, pad=21)\n",
    "axes[6,2].annotate(\"Season\\n2020\", xy=(x, y), fontweight=\"bold\", fontsize=110,va=\"center\",  ha=\"center\")\n",
    "\n",
    "axes[7,0].pie(KC2018Values, labels=KC2018Labels, colors=colors2018, autopct='%.0f%%',\n",
    "            explode=[0.05 for i in KC2018Labels], shadow=True, startangle=120,\n",
    "            textprops={'fontweight': 'semibold', 'fontsize': 90}, wedgeprops={'linewidth': 12, 'edgecolor': 'k'},\n",
    "            labeldistance=1.1)\n",
    "axes[7,0].add_artist(plt.Circle((0, 0), 0.35, fc='#E4E6EB', ec='black', lw=12))\n",
    "axes[7,0].set_title(\"KC Special Team Plays 2018\", fontweight=\"bold\", fontsize=110, pad=21)\n",
    "axes[7,0].annotate(\"Season\\n2018\", xy=(x, y), fontweight=\"bold\", fontsize=110,va=\"center\",  ha=\"center\")\n",
    "axes[7,1].pie(KC2019Values, labels=KC2019Labels, colors=colors2019, autopct='%.0f%%',\n",
    "            explode=[0.05 for i in KC2019Labels], shadow=True, startangle=120,\n",
    "            textprops={'fontweight': 'semibold', 'fontsize': 90}, wedgeprops={'linewidth': 12, 'edgecolor': 'k'},\n",
    "            labeldistance=1.1)\n",
    "axes[7,1].add_artist(plt.Circle((0, 0), 0.35, fc='#E4E6EB', ec='black', lw=12))\n",
    "axes[7,1].set_title(\"KC Special Team Plays 2019\", fontweight=\"bold\", fontsize=110, pad=21)\n",
    "axes[7,1].annotate(\"Season\\n2019\", xy=(x, y), fontweight=\"bold\", fontsize=120,va=\"center\",  ha=\"center\")\n",
    "axes[7,2].pie(KC2020Values, labels=KC2020Labels, colors=colors2020, autopct='%.0f%%',\n",
    "            explode=[0.05 for i in KC2020Labels], shadow=True, startangle=120,\n",
    "            textprops={'fontweight': 'semibold', 'fontsize': 90}, wedgeprops={'linewidth': 12, 'edgecolor': 'k'},\n",
    "            labeldistance=1.1)\n",
    "axes[7,2].add_artist(plt.Circle((0, 0), 0.35, fc='#E4E6EB', ec='black', lw=12))\n",
    "axes[7,2].set_title(\"KC Special Team Plays 2020\", fontweight=\"bold\", fontsize=110, pad=21)\n",
    "axes[7,2].annotate(\"Season\\n2020\", xy=(x, y), fontweight=\"bold\", fontsize=110, va=\"center\", ha=\"center\")\n",
    "fig.suptitle(\"NFL Special Teams Play Analysis (2018-20) Part-II\", y=1, fontweight=\"bold\", fontsize=200)\n",
    "plt.tight_layout(pad=1, w_pad=1, h_pad=1)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "ee7e21a1-fe9d-4712-af55-27bcfb2948e2",
   "metadata": {},
   "outputs": [],
   "source": [
    "sns.set_style(\"dark\")\n",
    "plt.figure(figsize=(20, 12))\n",
    "p1 = plt.bar(allDALData['DAL Special Play'],allDALData['2020'], color='#869397',edgecolor='black',linewidth=2)\n",
    "p2 = plt.bar(allDALData['DAL Special Play'],allDALData['2019'], bottom = allDALData['2020'], color='white',edgecolor='black',linewidth=2)\n",
    "p3 = plt.bar(allDALData['DAL Special Play'],allDALData['2018'], bottom = allDALData['2020'] + allDALData['2019'] , color='#00338d',edgecolor='black',linewidth=2)\n",
    "\n",
    "for r1,r2,r3 in zip(p1,p2,p3):\n",
    "    h1 = r1.get_height()\n",
    "    h2 = r2.get_height()\n",
    "    h3 = r3.get_height()\n",
    "    plt.text(r1.get_x()+r1.get_width()/2., h1+h2+h3, '%s'% (h1+h2+h3), ha = 'center', va='bottom',color='black', size=15)\n",
    "plt.legend([\"2020\", \"2019\", \"2018\"],prop={'size': 15})\n",
    "plt.title(\"DAL Special Team Plays\", fontweight=\"bold\", fontsize=25, pad=21)\n",
    "plt.xticks(fontsize=14,fontweight=\"bold\",rotation=90)\n",
    "plt.yticks(fontsize=14,fontweight=\"bold\")\n",
    "plt.tight_layout(pad=1, w_pad=1, h_pad=1)\n",
    "plt.show()\n",
    "\n",
    "plt.figure(figsize=(20, 12))\n",
    "p1 = plt.bar(allDENData['DEN Special Play'],allDENData['2020'], color='#fb4f14',edgecolor='black',linewidth=2)\n",
    "p2 = plt.bar(allDENData['DEN Special Play'],allDENData['2019'], bottom = allDENData['2020'], color='white',edgecolor='black',linewidth=2)\n",
    "p3 = plt.bar(allDENData['DEN Special Play'],allDENData['2018'], bottom = allDENData['2020'] + allDENData['2019'] , color='#002244',edgecolor='black',linewidth=2)\n",
    "\n",
    "for r1,r2,r3 in zip(p1,p2,p3):\n",
    "    h1 = r1.get_height()\n",
    "    h2 = r2.get_height()\n",
    "    h3 = r3.get_height()\n",
    "    plt.text(r1.get_x()+r1.get_width()/2., h1+h2+h3, '%s'% (h1+h2+h3), ha = 'center', va='bottom',color='black', size=15)\n",
    "plt.legend([\"2020\", \"2019\", \"2018\"],prop={'size': 15})\n",
    "plt.title(\"DEN Special Team Plays\", fontweight=\"bold\", fontsize=25, pad=21)\n",
    "plt.xticks(fontsize=14,fontweight=\"bold\",rotation=90)\n",
    "plt.yticks(fontsize=14,fontweight=\"bold\")\n",
    "plt.tight_layout(pad=1, w_pad=1, h_pad=1)\n",
    "plt.show()\n",
    "\n",
    "plt.figure(figsize=(20, 12))\n",
    "p1 = plt.bar(allDETData['DET Special Play'],allDETData['2020'], color='#0076b6',edgecolor='black',linewidth=2)\n",
    "p2 = plt.bar(allDETData['DET Special Play'],allDETData['2019'], bottom = allDETData['2020'], color='white',edgecolor='black',linewidth=2)\n",
    "p3 = plt.bar(allDETData['DET Special Play'],allDETData['2018'], bottom = allDETData['2020'] + allDETData['2019'] , color='#b0b7bc',edgecolor='black',linewidth=2)\n",
    "\n",
    "for r1,r2,r3 in zip(p1,p2,p3):\n",
    "    h1 = r1.get_height()\n",
    "    h2 = r2.get_height()\n",
    "    h3 = r3.get_height()\n",
    "    plt.text(r1.get_x()+r1.get_width()/2., h1+h2+h3, '%s'% (h1+h2+h3), ha = 'center', va='bottom',color='black', size=15)\n",
    "plt.legend([\"2020\", \"2019\", \"2018\"],prop={'size': 15})\n",
    "plt.title(\"DET Special Team Plays\", fontweight=\"bold\", fontsize=25, pad=21)\n",
    "plt.xticks(fontsize=14,fontweight=\"bold\",rotation=90)\n",
    "plt.yticks(fontsize=14,fontweight=\"bold\")\n",
    "plt.tight_layout(pad=1, w_pad=1, h_pad=1)\n",
    "plt.show()\n",
    "\n",
    "plt.figure(figsize=(20, 12))\n",
    "p1 = plt.bar(allGBData['GB Special Play'],allGBData['2020'], color='#203731',edgecolor='black',linewidth=2)\n",
    "p2 = plt.bar(allGBData['GB Special Play'],allGBData['2019'], bottom = allGBData['2020'], color='#ffb612',edgecolor='black',linewidth=2)\n",
    "p3 = plt.bar(allGBData['GB Special Play'],allGBData['2018'], bottom = allGBData['2020'] + allGBData['2019'] , color='white',edgecolor='black',linewidth=2)\n",
    "\n",
    "for r1,r2,r3 in zip(p1,p2,p3):\n",
    "    h1 = r1.get_height()\n",
    "    h2 = r2.get_height()\n",
    "    h3 = r3.get_height()\n",
    "    plt.text(r1.get_x()+r1.get_width()/2., h1+h2+h3, '%s'% (h1+h2+h3), ha = 'center', va='bottom',color='black', size=15)\n",
    "plt.legend([\"2020\", \"2019\", \"2018\"],prop={'size': 15})\n",
    "plt.title(\"GB Special Team Plays\", fontweight=\"bold\", fontsize=25, pad=21)\n",
    "plt.xticks(fontsize=14,fontweight=\"bold\",rotation=90)\n",
    "plt.yticks(fontsize=14,fontweight=\"bold\")\n",
    "plt.tight_layout(pad=1, w_pad=1, h_pad=1)\n",
    "plt.show()\n",
    "\n",
    "plt.figure(figsize=(20, 12))\n",
    "p1 = plt.bar(allHOUData['HOU Special Play'],allHOUData['2020'], color='#03202f',edgecolor='black',linewidth=2)\n",
    "p2 = plt.bar(allHOUData['HOU Special Play'],allHOUData['2019'], bottom = allHOUData['2020'], color='white',edgecolor='black',linewidth=2)\n",
    "p3 = plt.bar(allHOUData['HOU Special Play'],allHOUData['2018'], bottom = allHOUData['2020'] + allHOUData['2019'] , color='#a71930',edgecolor='black',linewidth=2)\n",
    "\n",
    "for r1,r2,r3 in zip(p1,p2,p3):\n",
    "    h1 = r1.get_height()\n",
    "    h2 = r2.get_height()\n",
    "    h3 = r3.get_height()\n",
    "    plt.text(r1.get_x()+r1.get_width()/2., h1+h2+h3, '%s'% (h1+h2+h3), ha = 'center', va='bottom',color='black', size=15)\n",
    "plt.legend([\"2020\", \"2019\", \"2018\"],prop={'size': 15})\n",
    "plt.title(\"HOU Special Team Plays\", fontweight=\"bold\", fontsize=25, pad=21)\n",
    "plt.xticks(fontsize=14,fontweight=\"bold\",rotation=90)\n",
    "plt.yticks(fontsize=14,fontweight=\"bold\")\n",
    "plt.tight_layout(pad=1, w_pad=1, h_pad=1)\n",
    "plt.show()\n",
    "\n",
    "plt.figure(figsize=(20, 12))\n",
    "p1 = plt.bar(allINDData['IND Special Play'],allINDData['2020'], color='white',edgecolor='black',linewidth=2)\n",
    "p2 = plt.bar(allINDData['IND Special Play'],allINDData['2019'], bottom = allINDData['2020'], color='#002c5f',edgecolor='black',linewidth=2)\n",
    "p3 = plt.bar(allINDData['IND Special Play'],allINDData['2018'], bottom = allINDData['2020'] + allINDData['2019'] , color='#a5acaf',edgecolor='black',linewidth=2)\n",
    "\n",
    "for r1,r2,r3 in zip(p1,p2,p3):\n",
    "    h1 = r1.get_height()\n",
    "    h2 = r2.get_height()\n",
    "    h3 = r3.get_height()\n",
    "    plt.text(r1.get_x()+r1.get_width()/2., h1+h2+h3, '%s'% (h1+h2+h3), ha = 'center', va='bottom',color='black', size=15)\n",
    "plt.legend([\"2020\", \"2019\", \"2018\"],prop={'size': 15})\n",
    "plt.title(\"IND Special Team Plays\", fontweight=\"bold\", fontsize=25, pad=21)\n",
    "plt.xticks(fontsize=14,fontweight=\"bold\",rotation=90)\n",
    "plt.yticks(fontsize=14,fontweight=\"bold\")\n",
    "plt.tight_layout(pad=1, w_pad=1, h_pad=1)\n",
    "plt.show()\n",
    "\n",
    "plt.figure(figsize=(20, 12))\n",
    "p1 = plt.bar(allJAXData['JAX Special Play'],allJAXData['2020'], color='#006778',edgecolor='black',linewidth=2)\n",
    "p2 = plt.bar(allJAXData['JAX Special Play'],allJAXData['2019'], bottom = allJAXData['2020'], color='#9f792c',edgecolor='black',linewidth=2)\n",
    "p3 = plt.bar(allJAXData['JAX Special Play'],allJAXData['2018'], bottom = allJAXData['2020'] + allJAXData['2019'] , color='white',edgecolor='black',linewidth=2)\n",
    "\n",
    "for r1,r2,r3 in zip(p1,p2,p3):\n",
    "    h1 = r1.get_height()\n",
    "    h2 = r2.get_height()\n",
    "    h3 = r3.get_height()\n",
    "    plt.text(r1.get_x()+r1.get_width()/2., h1+h2+h3, '%s'% (h1+h2+h3), ha = 'center', va='bottom',color='black', size=15)\n",
    "plt.legend([\"2020\", \"2019\", \"2018\"],prop={'size': 15})\n",
    "plt.title(\"JAX Special Team Plays\", fontweight=\"bold\", fontsize=25, pad=21)\n",
    "plt.xticks(fontsize=14,fontweight=\"bold\",rotation=90)\n",
    "plt.yticks(fontsize=14,fontweight=\"bold\")\n",
    "plt.tight_layout(pad=1, w_pad=1, h_pad=1)\n",
    "plt.show()\n",
    "\n",
    "plt.figure(figsize=(20, 12))\n",
    "p1 = plt.bar(allKCData['KC Special Play'],allKCData['2020'], color='#e31837',edgecolor='black',linewidth=2)\n",
    "p2 = plt.bar(allKCData['KC Special Play'],allKCData['2019'], bottom = allKCData['2020'], color='white',edgecolor='black',linewidth=2)\n",
    "p3 = plt.bar(allKCData['KC Special Play'],allKCData['2018'], bottom = allKCData['2020'] + allKCData['2019'] , color='#ffb612',edgecolor='black',linewidth=2)\n",
    "\n",
    "for r1,r2,r3 in zip(p1,p2,p3):\n",
    "    h1 = r1.get_height()\n",
    "    h2 = r2.get_height()\n",
    "    h3 = r3.get_height()\n",
    "    plt.text(r1.get_x()+r1.get_width()/2., h1+h2+h3, '%s'% (h1+h2+h3), ha = 'center', va='bottom',color='black', size=15)\n",
    "plt.legend([\"2020\", \"2019\", \"2018\"],prop={'size': 15})\n",
    "plt.title(\"KC Special Team Plays\", fontweight=\"bold\", fontsize=25, pad=21)\n",
    "plt.xticks(fontsize=14,fontweight=\"bold\", rotation=90)\n",
    "plt.yticks(fontsize=14,fontweight=\"bold\")\n",
    "plt.tight_layout(pad=1, w_pad=1, h_pad=1)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "e4a02abc-2499-423d-9127-a861b5ee331b",
   "metadata": {},
   "outputs": [],
   "source": [
    "x = 0\n",
    "y = 0\n",
    "sns.set_style('dark')\n",
    "colors2018 = sns.color_palette('pastel')\n",
    "colors2019 = sns.color_palette('Set2')\n",
    "colors2020 = sns.color_palette('Set3')\n",
    "fig, axes = plt.subplots(8, 3, figsize=(180, 380))\n",
    "axes[0,0].pie(LA2018Values, labels=LA2018Labels, colors=colors2018, autopct='%.0f%%',\n",
    "            explode=[0.05 for i in LA2018Labels], shadow=True, startangle=120,\n",
    "            textprops={'fontweight': 'semibold', 'fontsize': 90}, wedgeprops={'linewidth': 12, 'edgecolor': 'k'},\n",
    "            labeldistance=1.1)\n",
    "axes[0,0].add_artist(plt.Circle((0, 0), 0.35, fc='#E4E6EB', ec='black', lw=12))\n",
    "axes[0,0].set_title(\"LA Special Team Plays 2018\", fontweight=\"bold\", fontsize=110, pad=21)\n",
    "axes[0,0].annotate(\"Season\\n2018\", xy=(x, y), fontweight=\"bold\", fontsize=110,va=\"center\", ha=\"center\")\n",
    "axes[0,1].pie(LA2019Values, labels=LA2019Labels, colors=colors2019, autopct='%.0f%%',\n",
    "            explode=[0.05 for i in LA2019Labels], shadow=True, startangle=130,\n",
    "            textprops={'fontweight': 'semibold', 'fontsize': 90}, wedgeprops={'linewidth': 12, 'edgecolor': 'k'},\n",
    "            labeldistance=1.1)\n",
    "axes[0,1].add_artist(plt.Circle((0, 0), 0.35, fc='#E4E6EB', ec='black', lw=12))\n",
    "axes[0,1].set_title(\"LA Special Team Plays 2019\", fontweight=\"bold\", fontsize=110, pad=21)\n",
    "axes[0,1].annotate(\"Season\\n2019\", xy=(x, y), fontweight=\"bold\", fontsize=110,va=\"center\",  ha=\"center\")\n",
    "axes[0,2].pie(LA2020Values, labels=LA2020Labels, colors=colors2020, autopct='%.0f%%',\n",
    "            explode=[0.05 for i in LA2020Labels], shadow=True, startangle=120,\n",
    "            textprops={'fontweight': 'semibold', 'fontsize': 90}, wedgeprops={'linewidth': 12, 'edgecolor': 'k'},\n",
    "            labeldistance=1.1)\n",
    "axes[0,2].add_artist(plt.Circle((0, 0), 0.35, fc='#E4E6EB', ec='black', lw=12))\n",
    "axes[0,2].set_title(\"LA Special Team Plays 2020\", fontweight=\"bold\", fontsize=110, pad=21)\n",
    "axes[0,2].annotate(\"Season\\n2020\", xy=(x, y), fontweight=\"bold\", fontsize=110,va=\"center\",  ha=\"center\")\n",
    "\n",
    "axes[1,0].pie(LAC2018Values, labels=LAC2018Labels, colors=colors2018, autopct='%.0f%%',\n",
    "            explode=[0.05 for i in LAC2018Labels], shadow=True, startangle=120,\n",
    "            textprops={'fontweight': 'semibold', 'fontsize': 90}, wedgeprops={'linewidth': 12, 'edgecolor': 'k'},\n",
    "            labeldistance=1.1)\n",
    "axes[1,0].add_artist(plt.Circle((0, 0), 0.35, fc='#E4E6EB', ec='black', lw=12))\n",
    "axes[1,0].set_title(\"LAC Special Team Plays 2018\", fontweight=\"bold\", fontsize=110, pad=21)\n",
    "axes[1,0].annotate(\"Season\\n2018\", xy=(x, y), fontweight=\"bold\", fontsize=110,va=\"center\",  ha=\"center\")\n",
    "axes[1,1].pie(LAC2019Values, labels=LAC2019Labels, colors=colors2019, autopct='%.0f%%',\n",
    "            explode=[0.05 for i in LAC2019Labels], shadow=True, startangle=110,\n",
    "            textprops={'fontweight': 'semibold', 'fontsize': 90}, wedgeprops={'linewidth': 12, 'edgecolor': 'k'},\n",
    "            labeldistance=1.1)\n",
    "axes[1,1].add_artist(plt.Circle((0, 0), 0.35, fc='#E4E6EB', ec='black', lw=12))\n",
    "axes[1,1].set_title(\"LAC Special Team Plays 2019\", fontweight=\"bold\", fontsize=110, pad=21)\n",
    "axes[1,1].annotate(\"Season\\n2019\", xy=(x, y), fontweight=\"bold\", fontsize=110,va=\"center\",  ha=\"center\")\n",
    "axes[1,2].pie(LAC2020Values, labels=LAC2020Labels, colors=colors2020, autopct='%.0f%%',\n",
    "            explode=[0.05 for i in LAC2020Labels], shadow=True, startangle=120,\n",
    "            textprops={'fontweight': 'semibold', 'fontsize': 90}, wedgeprops={'linewidth': 12, 'edgecolor': 'k'},\n",
    "            labeldistance=1.1)\n",
    "axes[1,2].add_artist(plt.Circle((0, 0), 0.35, fc='#E4E6EB', ec='black', lw=12))\n",
    "axes[1,2].set_title(\"LAC Special Team Plays 2020\", fontweight=\"bold\", fontsize=110, pad=21)\n",
    "axes[1,2].annotate(\"Season\\n2020\", xy=(x, y), fontweight=\"bold\", fontsize=110,va=\"center\",  ha=\"center\")\n",
    "\n",
    "axes[2,0].pie(MIA2018Values, labels=MIA2018Labels, colors=colors2018, autopct='%.0f%%',\n",
    "            explode=[0.05 for i in MIA2018Labels], shadow=True, startangle=120,\n",
    "            textprops={'fontweight': 'semibold', 'fontsize': 90}, wedgeprops={'linewidth': 12, 'edgecolor': 'k'},\n",
    "            labeldistance=1.1)\n",
    "axes[2,0].add_artist(plt.Circle((0, 0), 0.35, fc='#E4E6EB', ec='black', lw=12))\n",
    "axes[2,0].set_title(\"MIA Special Team Plays 2018\", fontweight=\"bold\", fontsize=110, pad=21)\n",
    "axes[2,0].annotate(\"Season\\n2018\", xy=(x, y), fontweight=\"bold\", fontsize=110,va=\"center\",  ha=\"center\")\n",
    "axes[2,1].pie(MIA2019Values, labels=MIA2019Labels, colors=colors2019, autopct='%.0f%%',\n",
    "            explode=[0.05 for i in MIA2019Labels], shadow=True, startangle=120,\n",
    "            textprops={'fontweight': 'semibold', 'fontsize': 90}, wedgeprops={'linewidth': 12, 'edgecolor': 'k'},\n",
    "            labeldistance=1.1)\n",
    "axes[2,1].add_artist(plt.Circle((0, 0), 0.35, fc='#E4E6EB', ec='black', lw=12))\n",
    "axes[2,1].set_title(\"MIA Special Team Plays 2019\", fontweight=\"bold\", fontsize=110, pad=21)\n",
    "axes[2,1].annotate(\"Season\\n2019\", xy=(x, y), fontweight=\"bold\", fontsize=110,va=\"center\",  ha=\"center\")\n",
    "axes[2,2].pie(MIA2020Values, labels=MIA2020Labels, colors=colors2020, autopct='%.0f%%',\n",
    "            explode=[0.05 for i in MIA2020Labels], shadow=True, startangle=120,\n",
    "            textprops={'fontweight': 'semibold', 'fontsize': 90}, wedgeprops={'linewidth': 12, 'edgecolor': 'k'},\n",
    "            labeldistance=1.1)\n",
    "axes[2,2].add_artist(plt.Circle((0, 0), 0.35, fc='#E4E6EB', ec='black', lw=12))\n",
    "axes[2,2].set_title(\"MIA Special Team Plays 2020\", fontweight=\"bold\", fontsize=110, pad=21)\n",
    "axes[2,2].annotate(\"Season\\n2020\", xy=(x, y), fontweight=\"bold\", fontsize=110,va=\"center\",  ha=\"center\")\n",
    "\n",
    "axes[3,0].pie(MIN2018Values, labels=MIN2018Labels, colors=colors2018, autopct='%.0f%%',\n",
    "            explode=[0.05 for i in MIN2018Labels], shadow=True, startangle=120,\n",
    "            textprops={'fontweight': 'semibold', 'fontsize': 90}, wedgeprops={'linewidth': 12, 'edgecolor': 'k'},\n",
    "            labeldistance=1.1)\n",
    "axes[3,0].add_artist(plt.Circle((0, 0), 0.35, fc='#E4E6EB', ec='black', lw=12))\n",
    "axes[3,0].set_title(\"MIN Special Team Plays 2018\", fontweight=\"bold\", fontsize=110, pad=21)\n",
    "axes[3,0].annotate(\"Season\\n2018\", xy=(x, y), fontweight=\"bold\", fontsize=110,va=\"center\",  ha=\"center\")\n",
    "axes[3,1].pie(MIN2019Values, labels=MIN2019Labels, colors=colors2019, autopct='%.0f%%',\n",
    "            explode=[0.05 for i in MIN2019Labels], shadow=True, startangle=130,\n",
    "            textprops={'fontweight': 'semibold', 'fontsize': 90}, wedgeprops={'linewidth': 12, 'edgecolor': 'k'},\n",
    "            labeldistance=1.1)\n",
    "axes[3,1].add_artist(plt.Circle((0, 0), 0.35, fc='#E4E6EB', ec='black', lw=12))\n",
    "axes[3,1].set_title(\"MIN Special Team Plays 2019\", fontweight=\"bold\", fontsize=110, pad=21)\n",
    "axes[3,1].annotate(\"Season\\n2019\", xy=(x, y), fontweight=\"bold\", fontsize=110,va=\"center\",  ha=\"center\")\n",
    "axes[3,2].pie(MIN2020Values, labels=MIN2020Labels, colors=colors2020, autopct='%.0f%%',\n",
    "            explode=[0.05 for i in MIN2020Labels], shadow=True, startangle=120,\n",
    "            textprops={'fontweight': 'semibold', 'fontsize': 90}, wedgeprops={'linewidth': 12, 'edgecolor': 'k'},\n",
    "            labeldistance=1.1)\n",
    "axes[3,2].add_artist(plt.Circle((0, 0), 0.35, fc='#E4E6EB', ec='black', lw=12))\n",
    "axes[3,2].set_title(\"MIN Special Team Plays 2020\", fontweight=\"bold\", fontsize=110, pad=21)\n",
    "axes[3,2].annotate(\"Season\\n2020\", xy=(x, y), fontweight=\"bold\", fontsize=110,va=\"center\",  ha=\"center\")\n",
    "\n",
    "axes[4,0].pie(NE2018Values, labels=NE2018Labels, colors=colors2018, autopct='%.0f%%',\n",
    "            explode=[0.05 for i in NE2018Labels], shadow=True, startangle=120,\n",
    "            textprops={'fontweight': 'semibold', 'fontsize': 90}, wedgeprops={'linewidth': 12, 'edgecolor': 'k'},\n",
    "            labeldistance=1.1)\n",
    "axes[4,0].add_artist(plt.Circle((0, 0), 0.35, fc='#E4E6EB', ec='black', lw=12))\n",
    "axes[4,0].set_title(\"NE Special Team Plays 2018\", fontweight=\"bold\", fontsize=110, pad=21)\n",
    "axes[4,0].annotate(\"Season\\n2018\", xy=(x, y), fontweight=\"bold\", fontsize=110,va=\"center\",  ha=\"center\")\n",
    "axes[4,1].pie(NE2019Values, labels=NE2019Labels, colors=colors2019, autopct='%.0f%%',\n",
    "            explode=[0.05 for i in NE2019Labels], shadow=True, startangle=120,\n",
    "            textprops={'fontweight': 'semibold', 'fontsize': 90}, wedgeprops={'linewidth': 12, 'edgecolor': 'k'},\n",
    "            labeldistance=1.1)\n",
    "axes[4,1].add_artist(plt.Circle((0, 0), 0.35, fc='#E4E6EB', ec='black', lw=12))\n",
    "axes[4,1].set_title(\"NE Special Team Plays 2019\", fontweight=\"bold\", fontsize=110, pad=21)\n",
    "axes[4,1].annotate(\"Season\\n2019\", xy=(x, y), fontweight=\"bold\", fontsize=110,va=\"center\",  ha=\"center\")\n",
    "axes[4,2].pie(NE2020Values, labels=NE2020Labels, colors=colors2020, autopct='%.0f%%',\n",
    "            explode=[0.05 for i in NE2020Labels], shadow=True, startangle=120,\n",
    "            textprops={'fontweight': 'semibold', 'fontsize': 90}, wedgeprops={'linewidth': 12, 'edgecolor': 'k'},\n",
    "            labeldistance=1.1)\n",
    "axes[4,2].add_artist(plt.Circle((0, 0), 0.35, fc='#E4E6EB', ec='black', lw=12))\n",
    "axes[4,2].set_title(\"NE Special Team Plays 2020\", fontweight=\"bold\", fontsize=110, pad=21)\n",
    "axes[4,2].annotate(\"Season\\n2020\", xy=(x, y), fontweight=\"bold\", fontsize=110,va=\"center\", ha=\"center\")\n",
    "\n",
    "axes[5,0].pie(NO2018Values, labels=NO2018Labels, colors=colors2018, autopct='%.0f%%',\n",
    "            explode=[0.05 for i in NO2018Labels], shadow=True, startangle=120,\n",
    "            textprops={'fontweight': 'semibold', 'fontsize': 90}, wedgeprops={'linewidth': 12, 'edgecolor': 'k'},\n",
    "            labeldistance=1.1)\n",
    "axes[5,0].add_artist(plt.Circle((0, 0), 0.35, fc='#E4E6EB', ec='black', lw=12))\n",
    "axes[5,0].set_title(\"NO Special Team Plays 2018\", fontweight=\"bold\", fontsize=110, pad=21)\n",
    "axes[5,0].annotate(\"Season\\n2018\", xy=(x, y), fontweight=\"bold\", fontsize=110,va=\"center\",  ha=\"center\")\n",
    "axes[5,1].pie(NO2019Values, labels=NO2019Labels, colors=colors2019, autopct='%.0f%%',\n",
    "            explode=[0.05 for i in NO2019Labels], shadow=True, startangle=110,\n",
    "            textprops={'fontweight': 'semibold', 'fontsize': 90}, wedgeprops={'linewidth': 12, 'edgecolor': 'k'},\n",
    "            labeldistance=1.1)\n",
    "axes[5,1].add_artist(plt.Circle((0, 0), 0.35, fc='#E4E6EB', ec='black', lw=12))\n",
    "axes[5,1].set_title(\"NO Special Team Plays 2019\", fontweight=\"bold\", fontsize=110, pad=21)\n",
    "axes[5,1].annotate(\"Season\\n2019\", xy=(x, y), fontweight=\"bold\", fontsize=110,va=\"center\",  ha=\"center\")\n",
    "axes[5,2].pie(NO2020Values, labels=NO2020Labels, colors=colors2020, autopct='%.0f%%',\n",
    "            explode=[0.05 for i in NO2020Labels], shadow=True, startangle=120,\n",
    "            textprops={'fontweight': 'semibold', 'fontsize': 90}, wedgeprops={'linewidth': 12, 'edgecolor': 'k'},\n",
    "            labeldistance=1.1)\n",
    "axes[5,2].add_artist(plt.Circle((0, 0), 0.35, fc='#E4E6EB', ec='black', lw=12))\n",
    "axes[5,2].set_title(\"NO Special Team Plays 2020\", fontweight=\"bold\", fontsize=110, pad=21)\n",
    "axes[5,2].annotate(\"Season\\n2020\", xy=(x, y), fontweight=\"bold\", fontsize=110,va=\"center\",  ha=\"center\")\n",
    "\n",
    "axes[6,0].pie(NYG2018Values, labels=NYG2018Labels, colors=colors2018, autopct='%.0f%%',\n",
    "            explode=[0.05 for i in NYG2018Labels], shadow=True, startangle=120,\n",
    "            textprops={'fontweight': 'semibold', 'fontsize': 90}, wedgeprops={'linewidth': 12, 'edgecolor': 'k'},\n",
    "            labeldistance=1.1)\n",
    "axes[6,0].add_artist(plt.Circle((0, 0), 0.35, fc='#E4E6EB', ec='black', lw=12))\n",
    "axes[6,0].set_title(\"NYG Special Team Plays 2018\", fontweight=\"bold\", fontsize=110, pad=21)\n",
    "axes[6,0].annotate(\"Season\\n2018\", xy=(x, y), fontweight=\"bold\", fontsize=110,va=\"center\",  ha=\"center\")\n",
    "axes[6,1].pie(NYG2019Values, labels=NYG2019Labels, colors=colors2019, autopct='%.0f%%',\n",
    "            explode=[0.05 for i in NYG2019Labels], shadow=True, startangle=120,\n",
    "            textprops={'fontweight': 'semibold', 'fontsize': 90}, wedgeprops={'linewidth': 12, 'edgecolor': 'k'},\n",
    "            labeldistance=1.1)\n",
    "axes[6,1].add_artist(plt.Circle((0, 0), 0.35, fc='#E4E6EB', ec='black', lw=12))\n",
    "axes[6,1].set_title(\"NYG Special Team Plays 2019\", fontweight=\"bold\", fontsize=110, pad=21)\n",
    "axes[6,1].annotate(\"Season\\n2019\", xy=(x, y), fontweight=\"bold\", fontsize=110,va=\"center\",  ha=\"center\")\n",
    "axes[6,2].pie(NYG2020Values, labels=NYG2020Labels, colors=colors2020, autopct='%.0f%%',\n",
    "            explode=[0.05 for i in NYG2020Labels], shadow=True, startangle=120,\n",
    "            textprops={'fontweight': 'semibold', 'fontsize': 90}, wedgeprops={'linewidth': 12, 'edgecolor': 'k'},\n",
    "            labeldistance=1.1)\n",
    "axes[6,2].add_artist(plt.Circle((0, 0), 0.35, fc='#E4E6EB', ec='black', lw=12))\n",
    "axes[6,2].set_title(\"NYG Special Team Plays 2020\", fontweight=\"bold\", fontsize=110, pad=21)\n",
    "axes[6,2].annotate(\"Season\\n2020\", xy=(x, y), fontweight=\"bold\", fontsize=110,va=\"center\",  ha=\"center\")\n",
    "\n",
    "axes[7,0].pie(NYJ2018Values, labels=NYJ2018Labels, colors=colors2018, autopct='%.0f%%',\n",
    "            explode=[0.05 for i in NYJ2018Labels], shadow=True, startangle=120,\n",
    "            textprops={'fontweight': 'semibold', 'fontsize': 90}, wedgeprops={'linewidth': 12, 'edgecolor': 'k'},\n",
    "            labeldistance=1.1)\n",
    "axes[7,0].add_artist(plt.Circle((0, 0), 0.35, fc='#E4E6EB', ec='black', lw=12))\n",
    "axes[7,0].set_title(\"NYJ Special Team Plays 2018\", fontweight=\"bold\", fontsize=110, pad=21)\n",
    "axes[7,0].annotate(\"Season\\n2018\", xy=(x, y), fontweight=\"bold\", fontsize=110,va=\"center\",  ha=\"center\")\n",
    "axes[7,1].pie(NYJ2019Values, labels=NYJ2019Labels, colors=colors2019, autopct='%.0f%%',\n",
    "            explode=[0.05 for i in NYJ2019Labels], shadow=True, startangle=120,\n",
    "            textprops={'fontweight': 'semibold', 'fontsize': 90}, wedgeprops={'linewidth': 12, 'edgecolor': 'k'},\n",
    "            labeldistance=1.1)\n",
    "axes[7,1].add_artist(plt.Circle((0, 0), 0.35, fc='#E4E6EB', ec='black', lw=12))\n",
    "axes[7,1].set_title(\"NYJ Special Team Plays 2019\", fontweight=\"bold\", fontsize=110, pad=21)\n",
    "axes[7,1].annotate(\"Season\\n2019\", xy=(x, y), fontweight=\"bold\", fontsize=110,va=\"center\",  ha=\"center\")\n",
    "axes[7,2].pie(NYJ2020Values, labels=NYJ2020Labels, colors=colors2020, autopct='%.0f%%',\n",
    "            explode=[0.05 for i in NYJ2020Labels], shadow=True, startangle=120,\n",
    "            textprops={'fontweight': 'semibold', 'fontsize': 90}, wedgeprops={'linewidth': 12, 'edgecolor': 'k'},\n",
    "            labeldistance=1.1)\n",
    "axes[7,2].add_artist(plt.Circle((0, 0), 0.35, fc='#E4E6EB', ec='black', lw=12))\n",
    "axes[7,2].set_title(\"NYJ Special Team Plays 2020\", fontweight=\"bold\", fontsize=110, pad=21)\n",
    "axes[7,2].annotate(\"Season\\n2020\", xy=(x, y), fontweight=\"bold\", fontsize=110, va=\"center\", ha=\"center\")\n",
    "fig.suptitle(\"NFL Special Teams Play Analysis (2018-20) Part-III\", y=1, fontweight=\"bold\", fontsize=200)\n",
    "plt.tight_layout(pad=1, w_pad=1, h_pad=1)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "39bcf1d0-ec57-460a-abd8-00ff342cb74e",
   "metadata": {},
   "outputs": [],
   "source": [
    "sns.set_style(\"dark\")\n",
    "plt.figure(figsize=(20, 12))\n",
    "p1 = plt.bar(allLAData['LA Special Play'],allLAData['2020'], color='#b3995d',edgecolor='black',linewidth=2)\n",
    "p2 = plt.bar(allLAData['LA Special Play'],allLAData['2019'], bottom = allLAData['2020'], color='#002244',edgecolor='black',linewidth=2)\n",
    "p3 = plt.bar(allLAData['LA Special Play'],allLAData['2018'], bottom = allLAData['2020'] + allLAData['2019'] , color='white',edgecolor='black',linewidth=2)\n",
    "\n",
    "for r1,r2,r3 in zip(p1,p2,p3):\n",
    "    h1 = r1.get_height()\n",
    "    h2 = r2.get_height()\n",
    "    h3 = r3.get_height()\n",
    "    plt.text(r1.get_x()+r1.get_width()/2., h1+h2+h3, '%s'% (h1+h2+h3), ha = 'center', va='bottom',color='black', size=15)\n",
    "plt.legend([\"2020\", \"2019\", \"2018\"],prop={'size': 15})\n",
    "plt.title(\"LA Special Team Plays\", fontweight=\"bold\", fontsize=25, pad=21)\n",
    "plt.xticks(fontsize=14,fontweight=\"bold\",rotation=90)\n",
    "plt.yticks(fontsize=14,fontweight=\"bold\")\n",
    "plt.tight_layout(pad=1, w_pad=1, h_pad=1)\n",
    "plt.show()\n",
    "\n",
    "plt.figure(figsize=(20, 12))\n",
    "p1 = plt.bar(allLACData['LAC Special Play'],allLACData['2020'], color='#0073cf',edgecolor='black',linewidth=2)\n",
    "p2 = plt.bar(allLACData['LAC Special Play'],allLACData['2019'], bottom = allLACData['2020'], color='#ffb612',edgecolor='black',linewidth=2)\n",
    "p3 = plt.bar(allLACData['LAC Special Play'],allLACData['2018'], bottom = allLACData['2020'] + allLACData['2019'] , color='#002244',edgecolor='black',linewidth=2)\n",
    "\n",
    "for r1,r2,r3 in zip(p1,p2,p3):\n",
    "    h1 = r1.get_height()\n",
    "    h2 = r2.get_height()\n",
    "    h3 = r3.get_height()\n",
    "    plt.text(r1.get_x()+r1.get_width()/2., h1+h2+h3, '%s'% (h1+h2+h3), ha = 'center', va='bottom',color='black', size=15)\n",
    "plt.legend([\"2020\", \"2019\", \"2018\"],prop={'size': 15})\n",
    "plt.title(\"LAC Special Team Plays\", fontweight=\"bold\", fontsize=25, pad=21)\n",
    "plt.xticks(fontsize=14,fontweight=\"bold\",rotation=90)\n",
    "plt.yticks(fontsize=14,fontweight=\"bold\")\n",
    "plt.tight_layout(pad=1, w_pad=1, h_pad=1)\n",
    "plt.show()\n",
    "\n",
    "plt.figure(figsize=(20, 12))\n",
    "p1 = plt.bar(allMIAData['MIA Special Play'],allMIAData['2020'], color='#008e97',edgecolor='black',linewidth=2)\n",
    "p2 = plt.bar(allMIAData['MIA Special Play'],allMIAData['2019'], bottom = allMIAData['2020'], color='#f26a24',edgecolor='black',linewidth=2)\n",
    "p3 = plt.bar(allMIAData['MIA Special Play'],allMIAData['2018'], bottom = allMIAData['2020'] + allMIAData['2019'] , color='#005778',edgecolor='black',linewidth=2)\n",
    "\n",
    "for r1,r2,r3 in zip(p1,p2,p3):\n",
    "    h1 = r1.get_height()\n",
    "    h2 = r2.get_height()\n",
    "    h3 = r3.get_height()\n",
    "    plt.text(r1.get_x()+r1.get_width()/2., h1+h2+h3, '%s'% (h1+h2+h3), ha = 'center', va='bottom',color='black', size=15)\n",
    "plt.legend([\"2020\", \"2019\", \"2018\"],prop={'size': 15})\n",
    "plt.title(\"MIA Special Team Plays\", fontweight=\"bold\", fontsize=25, pad=21)\n",
    "plt.xticks(fontsize=14,fontweight=\"bold\",rotation=90)\n",
    "plt.yticks(fontsize=14,fontweight=\"bold\")\n",
    "plt.tight_layout(pad=1, w_pad=1, h_pad=1)\n",
    "plt.show()\n",
    "\n",
    "plt.figure(figsize=(20, 12))\n",
    "p1 = plt.bar(allMINData['MIN Special Play'],allMINData['2020'], color='#4f2683',edgecolor='black',linewidth=2)\n",
    "p2 = plt.bar(allMINData['MIN Special Play'],allMINData['2019'], bottom = allMINData['2020'], color='white',edgecolor='black',linewidth=2)\n",
    "p3 = plt.bar(allMINData['MIN Special Play'],allMINData['2018'], bottom = allMINData['2020'] + allMINData['2019'] , color='#ffc62f',edgecolor='black',linewidth=2)\n",
    "\n",
    "for r1,r2,r3 in zip(p1,p2,p3):\n",
    "    h1 = r1.get_height()\n",
    "    h2 = r2.get_height()\n",
    "    h3 = r3.get_height()\n",
    "    plt.text(r1.get_x()+r1.get_width()/2., h1+h2+h3, '%s'% (h1+h2+h3), ha = 'center', va='bottom',color='black', size=15)\n",
    "plt.legend([\"2020\", \"2019\", \"2018\"],prop={'size': 15})\n",
    "plt.title(\"MIN Special Team Plays\", fontweight=\"bold\", fontsize=25, pad=21)\n",
    "plt.xticks(fontsize=14,fontweight=\"bold\",rotation=90)\n",
    "plt.yticks(fontsize=14,fontweight=\"bold\")\n",
    "plt.tight_layout(pad=1, w_pad=1, h_pad=1)\n",
    "plt.show()\n",
    "\n",
    "plt.figure(figsize=(20, 12))\n",
    "p1 = plt.bar(allNEData['NE Special Play'],allNEData['2020'], color='#002244',edgecolor='black',linewidth=2)\n",
    "p2 = plt.bar(allNEData['NE Special Play'],allNEData['2019'], bottom = allNEData['2020'], color='#c60c30',edgecolor='black',linewidth=2)\n",
    "p3 = plt.bar(allNEData['NE Special Play'],allNEData['2018'], bottom = allNEData['2020'] + allNEData['2019'] , color='#b0b7bc',edgecolor='black',linewidth=2)\n",
    "\n",
    "for r1,r2,r3 in zip(p1,p2,p3):\n",
    "    h1 = r1.get_height()\n",
    "    h2 = r2.get_height()\n",
    "    h3 = r3.get_height()\n",
    "    plt.text(r1.get_x()+r1.get_width()/2., h1+h2+h3, '%s'% (h1+h2+h3), ha = 'center', va='bottom',color='black', size=15)\n",
    "plt.legend([\"2020\", \"2019\", \"2018\"],prop={'size': 15})\n",
    "plt.title(\"NE Special Team Plays\", fontweight=\"bold\", fontsize=25, pad=21)\n",
    "plt.xticks(fontsize=14,fontweight=\"bold\",rotation=90)\n",
    "plt.yticks(fontsize=14,fontweight=\"bold\")\n",
    "plt.tight_layout(pad=1, w_pad=1, h_pad=1)\n",
    "plt.show()\n",
    "\n",
    "plt.figure(figsize=(20, 12))\n",
    "p1 = plt.bar(allNOData['NO Special Play'],allNOData['2020'], color='#000000',edgecolor='black',linewidth=2)\n",
    "p2 = plt.bar(allNOData['NO Special Play'],allNOData['2019'], bottom = allNOData['2020'], color='#d3bc8d',edgecolor='black',linewidth=2)\n",
    "p3 = plt.bar(allNOData['NO Special Play'],allNOData['2018'], bottom = allNOData['2020'] + allNOData['2019'] , color='white',edgecolor='black',linewidth=2)\n",
    "\n",
    "for r1,r2,r3 in zip(p1,p2,p3):\n",
    "    h1 = r1.get_height()\n",
    "    h2 = r2.get_height()\n",
    "    h3 = r3.get_height()\n",
    "    plt.text(r1.get_x()+r1.get_width()/2., h1+h2+h3, '%s'% (h1+h2+h3), ha = 'center', va='bottom',color='black', size=15)\n",
    "plt.legend([\"2020\", \"2019\", \"2018\"],prop={'size': 15})\n",
    "plt.title(\"NO Special Team Plays\", fontweight=\"bold\", fontsize=25, pad=21)\n",
    "plt.xticks(fontsize=14,fontweight=\"bold\",rotation=90)\n",
    "plt.yticks(fontsize=14,fontweight=\"bold\")\n",
    "plt.tight_layout(pad=1, w_pad=1, h_pad=1)\n",
    "plt.show()\n",
    "\n",
    "plt.figure(figsize=(20, 12))\n",
    "p1 = plt.bar(allNYGData['NYG Special Play'],allNYGData['2020'], color='#a5acaf',edgecolor='black',linewidth=2)\n",
    "p2 = plt.bar(allNYGData['NYG Special Play'],allNYGData['2019'], bottom = allNYGData['2020'], color='#a71930',edgecolor='black',linewidth=2)\n",
    "p3 = plt.bar(allNYGData['NYG Special Play'],allNYGData['2018'], bottom = allNYGData['2020'] + allNYGData['2019'] , color='#0b2265',edgecolor='black',linewidth=2)\n",
    "\n",
    "for r1,r2,r3 in zip(p1,p2,p3):\n",
    "    h1 = r1.get_height()\n",
    "    h2 = r2.get_height()\n",
    "    h3 = r3.get_height()\n",
    "    plt.text(r1.get_x()+r1.get_width()/2., h1+h2+h3, '%s'% (h1+h2+h3), ha = 'center', va='bottom',color='black', size=15)\n",
    "plt.legend([\"2020\", \"2019\", \"2018\"],prop={'size': 15})\n",
    "plt.title(\"NYG Special Team Plays\", fontweight=\"bold\", fontsize=25, pad=21)\n",
    "plt.xticks(fontsize=14,fontweight=\"bold\",rotation=90)\n",
    "plt.yticks(fontsize=14,fontweight=\"bold\")\n",
    "plt.tight_layout(pad=1, w_pad=1, h_pad=1)\n",
    "plt.show()\n",
    "\n",
    "plt.figure(figsize=(20, 12))\n",
    "p1 = plt.bar(allNYJData['NYJ Special Play'],allNYJData['2020'], color='white',edgecolor='black',linewidth=2)\n",
    "p2 = plt.bar(allNYJData['NYJ Special Play'],allNYJData['2019'], bottom = allNYJData['2020'], color='#003f2d',edgecolor='black',linewidth=2)\n",
    "p3 = plt.bar(allNYJData['NYJ Special Play'],allNYJData['2018'], bottom = allNYJData['2020'] + allNYJData['2019'] , color='green',edgecolor='black',linewidth=2)\n",
    "\n",
    "for r1,r2,r3 in zip(p1,p2,p3):\n",
    "    h1 = r1.get_height()\n",
    "    h2 = r2.get_height()\n",
    "    h3 = r3.get_height()\n",
    "    plt.text(r1.get_x()+r1.get_width()/2., h1+h2+h3, '%s'% (h1+h2+h3), ha = 'center', va='bottom',color='black', size=15)\n",
    "plt.legend([\"2020\", \"2019\", \"2018\"],prop={'size': 15})\n",
    "plt.title(\"NYJ Special Team Plays\", fontweight=\"bold\", fontsize=25, pad=21)\n",
    "plt.xticks(fontsize=14,fontweight=\"bold\",rotation=90)\n",
    "plt.yticks(fontsize=14,fontweight=\"bold\")\n",
    "plt.tight_layout(pad=1, w_pad=1, h_pad=1)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "92abc7a1-197e-48b2-8664-789c80b583dc",
   "metadata": {},
   "outputs": [],
   "source": [
    "x = 0\n",
    "y = 0\n",
    "sns.set_style('dark')\n",
    "colors2018 = sns.color_palette('pastel')\n",
    "colors2019 = sns.color_palette('Set2')\n",
    "colors2020 = sns.color_palette('Set3')\n",
    "fig, axes = plt.subplots(8, 3, figsize=(180, 380))\n",
    "axes[0,0].pie(OAK2018Values, labels=OAK2018Labels, colors=colors2018, autopct='%.0f%%',\n",
    "            explode=[0.05 for i in OAK2018Labels], shadow=True, startangle=120,\n",
    "            textprops={'fontweight': 'semibold', 'fontsize': 90}, wedgeprops={'linewidth': 12, 'edgecolor': 'k'},\n",
    "            labeldistance=1.1)\n",
    "axes[0,0].add_artist(plt.Circle((0, 0), 0.35, fc='#E4E6EB', ec='black', lw=12))\n",
    "axes[0,0].set_title(\"OAK Special Team Plays 2018\", fontweight=\"bold\", fontsize=110, pad=21)\n",
    "axes[0,0].annotate(\"Season\\n2018\", xy=(x, y), fontweight=\"bold\", fontsize=110,va=\"center\", ha=\"center\")\n",
    "axes[0,1].pie(OAK2019Values, labels=OAK2019Labels, colors=colors2019, autopct='%.0f%%',\n",
    "            explode=[0.05 for i in OAK2019Labels], shadow=True, startangle=120,\n",
    "            textprops={'fontweight': 'semibold', 'fontsize': 90}, wedgeprops={'linewidth': 12, 'edgecolor': 'k'},\n",
    "            labeldistance=1.1)\n",
    "axes[0,1].add_artist(plt.Circle((0, 0), 0.35, fc='#E4E6EB', ec='black', lw=12))\n",
    "axes[0,1].set_title(\"OAK Special Team Plays 2019\", fontweight=\"bold\", fontsize=110, pad=21)\n",
    "axes[0,1].annotate(\"Season\\n2019\", xy=(x, y), fontweight=\"bold\", fontsize=110,va=\"center\",  ha=\"center\")\n",
    "axes[0,2].pie(OAK2020Values, labels=OAK2020Labels, colors=colors2020, autopct='%.0f%%',\n",
    "            explode=[0.05 for i in OAK2020Labels], shadow=True, startangle=120,\n",
    "            textprops={'fontweight': 'semibold', 'fontsize': 90}, wedgeprops={'linewidth': 12, 'edgecolor': 'k'},\n",
    "            labeldistance=1.1)\n",
    "axes[0,2].add_artist(plt.Circle((0, 0), 0.35, fc='#E4E6EB', ec='black', lw=12))\n",
    "axes[0,2].set_title(\"OAK/LV: Special Team Plays 2020\", fontweight=\"bold\", fontsize=110, pad=21)\n",
    "axes[0,2].annotate(\"Season\\n2020\", xy=(x, y), fontweight=\"bold\", fontsize=110,va=\"center\",  ha=\"center\")\n",
    "\n",
    "axes[1,0].pie(PHI2018Values, labels=PHI2018Labels, colors=colors2018, autopct='%.0f%%',\n",
    "            explode=[0.05 for i in PHI2018Labels], shadow=True, startangle=120,\n",
    "            textprops={'fontweight': 'semibold', 'fontsize': 90}, wedgeprops={'linewidth': 12, 'edgecolor': 'k'},\n",
    "            labeldistance=1.1)\n",
    "axes[1,0].add_artist(plt.Circle((0, 0), 0.35, fc='#E4E6EB', ec='black', lw=12))\n",
    "axes[1,0].set_title(\"PHI Special Team Plays 2018\", fontweight=\"bold\", fontsize=110, pad=21)\n",
    "axes[1,0].annotate(\"Season\\n2018\", xy=(x, y), fontweight=\"bold\", fontsize=110,va=\"center\",  ha=\"center\")\n",
    "axes[1,1].pie(PHI2019Values, labels=PHI2019Labels, colors=colors2019, autopct='%.0f%%',\n",
    "            explode=[0.05 for i in PHI2019Labels], shadow=True, startangle=120,\n",
    "            textprops={'fontweight': 'semibold', 'fontsize': 90}, wedgeprops={'linewidth': 12, 'edgecolor': 'k'},\n",
    "            labeldistance=1.1)\n",
    "axes[1,1].add_artist(plt.Circle((0, 0), 0.35, fc='#E4E6EB', ec='black', lw=12))\n",
    "axes[1,1].set_title(\"PHI Special Team Plays 2019\", fontweight=\"bold\", fontsize=110, pad=21)\n",
    "axes[1,1].annotate(\"Season\\n2019\", xy=(x, y), fontweight=\"bold\", fontsize=110,va=\"center\",  ha=\"center\")\n",
    "axes[1,2].pie(PHI2020Values, labels=PHI2020Labels, colors=colors2020, autopct='%.0f%%',\n",
    "            explode=[0.05 for i in PHI2020Labels], shadow=True, startangle=120,\n",
    "            textprops={'fontweight': 'semibold', 'fontsize': 90}, wedgeprops={'linewidth': 12, 'edgecolor': 'k'},\n",
    "            labeldistance=1.1)\n",
    "axes[1,2].add_artist(plt.Circle((0, 0), 0.35, fc='#E4E6EB', ec='black', lw=12))\n",
    "axes[1,2].set_title(\"PHI Special Team Plays 2020\", fontweight=\"bold\", fontsize=110, pad=21)\n",
    "axes[1,2].annotate(\"Season\\n2020\", xy=(x, y), fontweight=\"bold\", fontsize=110,va=\"center\",  ha=\"center\")\n",
    "\n",
    "axes[2,0].pie(PIT2018Values, labels=PIT2018Labels, colors=colors2018, autopct='%.0f%%',\n",
    "            explode=[0.05 for i in PIT2018Labels], shadow=True, startangle=120,\n",
    "            textprops={'fontweight': 'semibold', 'fontsize': 90}, wedgeprops={'linewidth': 12, 'edgecolor': 'k'},\n",
    "            labeldistance=1.1)\n",
    "axes[2,0].add_artist(plt.Circle((0, 0), 0.35, fc='#E4E6EB', ec='black', lw=12))\n",
    "axes[2,0].set_title(\"PIT Special Team Plays 2018\", fontweight=\"bold\", fontsize=110, pad=21)\n",
    "axes[2,0].annotate(\"Season\\n2018\", xy=(x, y), fontweight=\"bold\", fontsize=110,va=\"center\",  ha=\"center\")\n",
    "axes[2,1].pie(PIT2019Values, labels=PIT2019Labels, colors=colors2019, autopct='%.0f%%',\n",
    "            explode=[0.05 for i in PIT2019Labels], shadow=True, startangle=120,\n",
    "            textprops={'fontweight': 'semibold', 'fontsize': 90}, wedgeprops={'linewidth': 12, 'edgecolor': 'k'},\n",
    "            labeldistance=1.1)\n",
    "axes[2,1].add_artist(plt.Circle((0, 0), 0.35, fc='#E4E6EB', ec='black', lw=12))\n",
    "axes[2,1].set_title(\"PIT Special Team Plays 2019\", fontweight=\"bold\", fontsize=110, pad=21)\n",
    "axes[2,1].annotate(\"Season\\n2019\", xy=(x, y), fontweight=\"bold\", fontsize=110,va=\"center\",  ha=\"center\")\n",
    "axes[2,2].pie(PIT2020Values, labels=PIT2020Labels, colors=colors2020, autopct='%.0f%%',\n",
    "            explode=[0.05 for i in PIT2020Labels], shadow=True, startangle=120,\n",
    "            textprops={'fontweight': 'semibold', 'fontsize': 90}, wedgeprops={'linewidth': 12, 'edgecolor': 'k'},\n",
    "            labeldistance=1.1)\n",
    "axes[2,2].add_artist(plt.Circle((0, 0), 0.35, fc='#E4E6EB', ec='black', lw=12))\n",
    "axes[2,2].set_title(\"PIT Special Team Plays 2020\", fontweight=\"bold\", fontsize=110, pad=21)\n",
    "axes[2,2].annotate(\"Season\\n2020\", xy=(x, y), fontweight=\"bold\", fontsize=110,va=\"center\",  ha=\"center\")\n",
    "\n",
    "axes[3,0].pie(SEA2018Values, labels=SEA2018Labels, colors=colors2018, autopct='%.0f%%',\n",
    "            explode=[0.05 for i in SEA2018Labels], shadow=True, startangle=120,\n",
    "            textprops={'fontweight': 'semibold', 'fontsize': 90}, wedgeprops={'linewidth': 12, 'edgecolor': 'k'},\n",
    "            labeldistance=1.1)\n",
    "axes[3,0].add_artist(plt.Circle((0, 0), 0.35, fc='#E4E6EB', ec='black', lw=12))\n",
    "axes[3,0].set_title(\"SEA Special Team Plays 2018\", fontweight=\"bold\", fontsize=110, pad=21)\n",
    "axes[3,0].annotate(\"Season\\n2018\", xy=(x, y), fontweight=\"bold\", fontsize=110,va=\"center\",  ha=\"center\")\n",
    "axes[3,1].pie(SEA2019Values, labels=SEA2019Labels, colors=colors2019, autopct='%.0f%%',\n",
    "            explode=[0.05 for i in SEA2019Labels], shadow=True, startangle=110,\n",
    "            textprops={'fontweight': 'semibold', 'fontsize': 90}, wedgeprops={'linewidth': 12, 'edgecolor': 'k'},\n",
    "            labeldistance=1.1)\n",
    "axes[3,1].add_artist(plt.Circle((0, 0), 0.35, fc='#E4E6EB', ec='black', lw=12))\n",
    "axes[3,1].set_title(\"SEA Special Team Plays 2019\", fontweight=\"bold\", fontsize=110, pad=21)\n",
    "axes[3,1].annotate(\"Season\\n2019\", xy=(x, y), fontweight=\"bold\", fontsize=110,va=\"center\",  ha=\"center\")\n",
    "axes[3,2].pie(SEA2020Values, labels=SEA2020Labels, colors=colors2020, autopct='%.0f%%',\n",
    "            explode=[0.05 for i in SEA2020Labels], shadow=True, startangle=120,\n",
    "            textprops={'fontweight': 'semibold', 'fontsize': 90}, wedgeprops={'linewidth': 12, 'edgecolor': 'k'},\n",
    "            labeldistance=1.1)\n",
    "axes[3,2].add_artist(plt.Circle((0, 0), 0.35, fc='#E4E6EB', ec='black', lw=12))\n",
    "axes[3,2].set_title(\"SEA Special Team Plays 2020\", fontweight=\"bold\", fontsize=110, pad=21)\n",
    "axes[3,2].annotate(\"Season\\n2020\", xy=(x, y), fontweight=\"bold\", fontsize=110,va=\"center\",  ha=\"center\")\n",
    "\n",
    "axes[4,0].pie(SF2018Values, labels=SF2018Labels, colors=colors2018, autopct='%.0f%%',\n",
    "            explode=[0.05 for i in SF2018Labels], shadow=True, startangle=120,\n",
    "            textprops={'fontweight': 'semibold', 'fontsize': 90}, wedgeprops={'linewidth': 12, 'edgecolor': 'k'},\n",
    "            labeldistance=1.1)\n",
    "axes[4,0].add_artist(plt.Circle((0, 0), 0.35, fc='#E4E6EB', ec='black', lw=12))\n",
    "axes[4,0].set_title(\"SF Special Team Plays 2018\", fontweight=\"bold\", fontsize=110, pad=21)\n",
    "axes[4,0].annotate(\"Season\\n2018\", xy=(x, y), fontweight=\"bold\", fontsize=110,va=\"center\",  ha=\"center\")\n",
    "axes[4,1].pie(SF2019Values, labels=SF2019Labels, colors=colors2019, autopct='%.0f%%',\n",
    "            explode=[0.05 for i in SF2019Labels], shadow=True, startangle=130,\n",
    "            textprops={'fontweight': 'semibold', 'fontsize': 90}, wedgeprops={'linewidth': 12, 'edgecolor': 'k'},\n",
    "            labeldistance=1.1)\n",
    "axes[4,1].add_artist(plt.Circle((0, 0), 0.35, fc='#E4E6EB', ec='black', lw=12))\n",
    "axes[4,1].set_title(\"SF Special Team Plays 2019\", fontweight=\"bold\", fontsize=110, pad=21)\n",
    "axes[4,1].annotate(\"Season\\n2019\", xy=(x, y), fontweight=\"bold\", fontsize=110,va=\"center\",  ha=\"center\")\n",
    "axes[4,2].pie(SF2020Values, labels=SF2020Labels, colors=colors2020, autopct='%.0f%%',\n",
    "            explode=[0.05 for i in SF2020Labels], shadow=True, startangle=120,\n",
    "            textprops={'fontweight': 'semibold', 'fontsize': 90}, wedgeprops={'linewidth': 12, 'edgecolor': 'k'},\n",
    "            labeldistance=1.1)\n",
    "axes[4,2].add_artist(plt.Circle((0, 0), 0.35, fc='#E4E6EB', ec='black', lw=12))\n",
    "axes[4,2].set_title(\"SF Special Team Plays 2020\", fontweight=\"bold\", fontsize=110, pad=21)\n",
    "axes[4,2].annotate(\"Season\\n2020\", xy=(x, y), fontweight=\"bold\", fontsize=110,va=\"center\", ha=\"center\")\n",
    "\n",
    "axes[5,0].pie(TB2018Values, labels=TB2018Labels, colors=colors2018, autopct='%.0f%%',\n",
    "            explode=[0.05 for i in TB2018Labels], shadow=True, startangle=120,\n",
    "            textprops={'fontweight': 'semibold', 'fontsize': 90}, wedgeprops={'linewidth': 12, 'edgecolor': 'k'},\n",
    "            labeldistance=1.1)\n",
    "axes[5,0].add_artist(plt.Circle((0, 0), 0.35, fc='#E4E6EB', ec='black', lw=12))\n",
    "axes[5,0].set_title(\"TB Special Team Plays 2018\", fontweight=\"bold\", fontsize=110, pad=21)\n",
    "axes[5,0].annotate(\"Season\\n2018\", xy=(x, y), fontweight=\"bold\", fontsize=110,va=\"center\",  ha=\"center\")\n",
    "axes[5,1].pie(TB2019Values, labels=TB2019Labels, colors=colors2019, autopct='%.0f%%',\n",
    "            explode=[0.05 for i in TB2019Labels], shadow=True, startangle=130,\n",
    "            textprops={'fontweight': 'semibold', 'fontsize': 90}, wedgeprops={'linewidth': 12, 'edgecolor': 'k'},\n",
    "            labeldistance=1.1)\n",
    "axes[5,1].add_artist(plt.Circle((0, 0), 0.35, fc='#E4E6EB', ec='black', lw=12))\n",
    "axes[5,1].set_title(\"TB Special Team Plays 2019\", fontweight=\"bold\", fontsize=110, pad=21)\n",
    "axes[5,1].annotate(\"Season\\n2019\", xy=(x, y), fontweight=\"bold\", fontsize=110,va=\"center\",  ha=\"center\")\n",
    "axes[5,2].pie(TB2020Values, labels=TB2020Labels, colors=colors2020, autopct='%.0f%%',\n",
    "            explode=[0.05 for i in TB2020Labels], shadow=True, startangle=130,\n",
    "            textprops={'fontweight': 'semibold', 'fontsize': 90}, wedgeprops={'linewidth': 12, 'edgecolor': 'k'},\n",
    "            labeldistance=1.1)\n",
    "axes[5,2].add_artist(plt.Circle((0, 0), 0.35, fc='#E4E6EB', ec='black', lw=12))\n",
    "axes[5,2].set_title(\"TB Special Team Plays 2020\", fontweight=\"bold\", fontsize=110, pad=21)\n",
    "axes[5,2].annotate(\"Season\\n2020\", xy=(x, y), fontweight=\"bold\", fontsize=110,va=\"center\",  ha=\"center\")\n",
    "\n",
    "axes[6,0].pie(TEN2018Values, labels=TEN2018Labels, colors=colors2018, autopct='%.0f%%',\n",
    "            explode=[0.05 for i in TEN2018Labels], shadow=True, startangle=120,\n",
    "            textprops={'fontweight': 'semibold', 'fontsize': 90}, wedgeprops={'linewidth': 12, 'edgecolor': 'k'},\n",
    "            labeldistance=1.1)\n",
    "axes[6,0].add_artist(plt.Circle((0, 0), 0.35, fc='#E4E6EB', ec='black', lw=12))\n",
    "axes[6,0].set_title(\"TEN Special Team Plays 2018\", fontweight=\"bold\", fontsize=110, pad=21)\n",
    "axes[6,0].annotate(\"Season\\n2018\", xy=(x, y), fontweight=\"bold\", fontsize=110,va=\"center\",  ha=\"center\")\n",
    "axes[6,1].pie(TEN2019Values, labels=TEN2019Labels, colors=colors2019, autopct='%.0f%%',\n",
    "            explode=[0.05 for i in TEN2019Labels], shadow=True, startangle=120,\n",
    "            textprops={'fontweight': 'semibold', 'fontsize': 90}, wedgeprops={'linewidth': 12, 'edgecolor': 'k'},\n",
    "            labeldistance=1.1)\n",
    "axes[6,1].add_artist(plt.Circle((0, 0), 0.35, fc='#E4E6EB', ec='black', lw=12))\n",
    "axes[6,1].set_title(\"TEN Special Team Plays 2019\", fontweight=\"bold\", fontsize=110, pad=21)\n",
    "axes[6,1].annotate(\"Season\\n2019\", xy=(x, y), fontweight=\"bold\", fontsize=110,va=\"center\",  ha=\"center\")\n",
    "axes[6,2].pie(TEN2020Values, labels=TEN2020Labels, colors=colors2020, autopct='%.0f%%',\n",
    "            explode=[0.05 for i in TEN2020Labels], shadow=True, startangle=120,\n",
    "            textprops={'fontweight': 'semibold', 'fontsize': 90}, wedgeprops={'linewidth': 12, 'edgecolor': 'k'},\n",
    "            labeldistance=1.1)\n",
    "axes[6,2].add_artist(plt.Circle((0, 0), 0.35, fc='#E4E6EB', ec='black', lw=12))\n",
    "axes[6,2].set_title(\"TEN Special Team Plays 2020\", fontweight=\"bold\", fontsize=110, pad=21)\n",
    "axes[6,2].annotate(\"Season\\n2020\", xy=(x, y), fontweight=\"bold\", fontsize=110,va=\"center\",  ha=\"center\")\n",
    "\n",
    "axes[7,0].pie(WAS2018Values, labels=WAS2018Labels, colors=colors2018, autopct='%.0f%%',\n",
    "            explode=[0.05 for i in WAS2018Labels], shadow=True, startangle=120,\n",
    "            textprops={'fontweight': 'semibold', 'fontsize': 90}, wedgeprops={'linewidth': 12, 'edgecolor': 'k'},\n",
    "            labeldistance=1.1)\n",
    "axes[7,0].add_artist(plt.Circle((0, 0), 0.35, fc='#E4E6EB', ec='black', lw=12))\n",
    "axes[7,0].set_title(\"WAS Special Team Plays 2018\", fontweight=\"bold\", fontsize=110, pad=21)\n",
    "axes[7,0].annotate(\"Season\\n2018\", xy=(x, y), fontweight=\"bold\", fontsize=110,va=\"center\",  ha=\"center\")\n",
    "axes[7,1].pie(WAS2019Values, labels=WAS2019Labels, colors=colors2019, autopct='%.0f%%',\n",
    "            explode=[0.05 for i in WAS2019Labels], shadow=True, startangle=120,\n",
    "            textprops={'fontweight': 'semibold', 'fontsize': 90}, wedgeprops={'linewidth': 12, 'edgecolor': 'k'},\n",
    "            labeldistance=1.1)\n",
    "axes[7,1].add_artist(plt.Circle((0, 0), 0.35, fc='#E4E6EB', ec='black', lw=12))\n",
    "axes[7,1].set_title(\"WAS Special Team Plays 2019\", fontweight=\"bold\", fontsize=110, pad=21)\n",
    "axes[7,1].annotate(\"Season\\n2019\", xy=(x, y), fontweight=\"bold\", fontsize=120,va=\"center\",  ha=\"center\")\n",
    "axes[7,2].pie(WAS2020Values, labels=WAS2020Labels, colors=colors2020, autopct='%.0f%%',\n",
    "            explode=[0.05 for i in WAS2020Labels], shadow=True, startangle=130,\n",
    "            textprops={'fontweight': 'semibold', 'fontsize': 90}, wedgeprops={'linewidth': 12, 'edgecolor': 'k'},\n",
    "            labeldistance=1.1)\n",
    "axes[7,2].add_artist(plt.Circle((0, 0), 0.35, fc='#E4E6EB', ec='black', lw=12))\n",
    "axes[7,2].set_title(\"WAS Special Team Plays 2020\", fontweight=\"bold\", fontsize=110, pad=21)\n",
    "axes[7,2].annotate(\"Season\\n2020\", xy=(x, y), fontweight=\"bold\", fontsize=110, va=\"center\", ha=\"center\")\n",
    "fig.suptitle(\"NFL Special Teams Play Analysis (2018-20) Part-IV\", y=1, fontweight=\"bold\", fontsize=200)\n",
    "plt.tight_layout(pad=1, w_pad=1, h_pad=1)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "b3cfee46-5171-4127-aea2-b35c213013a7",
   "metadata": {},
   "outputs": [],
   "source": [
    "sns.set_style(\"dark\")\n",
    "plt.figure(figsize=(20, 12))\n",
    "p1 = plt.bar(allOAKData['OAK Special Play'],allOAKData['2020'], color='#a5acaf',edgecolor='black',linewidth=2)\n",
    "p2 = plt.bar(allOAKData['OAK Special Play'],allOAKData['2019'], bottom = allOAKData['2020'], color='black',edgecolor='black',linewidth=2)\n",
    "p3 = plt.bar(allOAKData['OAK Special Play'],allOAKData['2018'], bottom = allOAKData['2020'] + allOAKData['2019'] , color='white',edgecolor='black',linewidth=2)\n",
    "\n",
    "for r1,r2,r3 in zip(p1,p2,p3):\n",
    "    h1 = r1.get_height()\n",
    "    h2 = r2.get_height()\n",
    "    h3 = r3.get_height()\n",
    "    plt.text(r1.get_x()+r1.get_width()/2., h1+h2+h3, '%s'% (h1+h2+h3), ha = 'center', va='bottom',color='black', size=15)\n",
    "plt.legend([\"2020\", \"2019\", \"2018\"],prop={'size': 15})\n",
    "plt.title(\"OAK / LV Special Team Plays\", fontweight=\"bold\", fontsize=25, pad=21)\n",
    "plt.xticks(fontsize=14,fontweight=\"bold\",rotation=90)\n",
    "plt.yticks(fontsize=14,fontweight=\"bold\")\n",
    "plt.tight_layout(pad=1, w_pad=1, h_pad=1)\n",
    "plt.show()\n",
    "\n",
    "plt.figure(figsize=(20, 12))\n",
    "p1 = plt.bar(allPHIData['PHI Special Play'],allPHIData['2020'], color='#a5acaf',edgecolor='black',linewidth=2)\n",
    "p2 = plt.bar(allPHIData['PHI Special Play'],allPHIData['2019'], bottom = allPHIData['2020'], color='white',edgecolor='black',linewidth=2)\n",
    "p3 = plt.bar(allPHIData['PHI Special Play'],allPHIData['2018'], bottom = allPHIData['2020'] + allPHIData['2019'] , color='#004c54',edgecolor='black',linewidth=2)\n",
    "\n",
    "for r1,r2,r3 in zip(p1,p2,p3):\n",
    "    h1 = r1.get_height()\n",
    "    h2 = r2.get_height()\n",
    "    h3 = r3.get_height()\n",
    "    plt.text(r1.get_x()+r1.get_width()/2., h1+h2+h3, '%s'% (h1+h2+h3), ha = 'center', va='bottom',color='black', size=15)\n",
    "plt.legend([\"2020\", \"2019\", \"2018\"],prop={'size': 15})\n",
    "plt.title(\"PHI Special Team Plays\", fontweight=\"bold\", fontsize=25, pad=21)\n",
    "plt.xticks(fontsize=14,fontweight=\"bold\",rotation=90)\n",
    "plt.yticks(fontsize=14,fontweight=\"bold\")\n",
    "plt.tight_layout(pad=1, w_pad=1, h_pad=1)\n",
    "plt.show()\n",
    "\n",
    "plt.figure(figsize=(20, 12))\n",
    "p1 = plt.bar(allPITData['PIT Special Play'],allPITData['2020'], color='#c60c30',edgecolor='black',linewidth=2)\n",
    "p2 = plt.bar(allPITData['PIT Special Play'],allPITData['2019'], bottom = allPITData['2020'], color='#ffb612',edgecolor='black',linewidth=2)\n",
    "p3 = plt.bar(allPITData['PIT Special Play'],allPITData['2018'], bottom = allPITData['2020'] + allPITData['2019'] , color='#00539b',edgecolor='black',linewidth=2)\n",
    "\n",
    "for r1,r2,r3 in zip(p1,p2,p3):\n",
    "    h1 = r1.get_height()\n",
    "    h2 = r2.get_height()\n",
    "    h3 = r3.get_height()\n",
    "    plt.text(r1.get_x()+r1.get_width()/2., h1+h2+h3, '%s'% (h1+h2+h3), ha = 'center', va='bottom',color='black', size=15)\n",
    "plt.legend([\"2020\", \"2019\", \"2018\"],prop={'size': 15})\n",
    "plt.title(\"PIT Special Team Plays\", fontweight=\"bold\", fontsize=25, pad=21)\n",
    "plt.xticks(fontsize=14,fontweight=\"bold\",rotation=90)\n",
    "plt.yticks(fontsize=14,fontweight=\"bold\")\n",
    "plt.tight_layout(pad=1, w_pad=1, h_pad=1)\n",
    "plt.show()\n",
    "\n",
    "plt.figure(figsize=(20, 12))\n",
    "p1 = plt.bar(allSEAData['SEA Special Play'],allSEAData['2020'], color='#69be28',edgecolor='black',linewidth=2)\n",
    "p2 = plt.bar(allSEAData['SEA Special Play'],allSEAData['2019'], bottom = allSEAData['2020'], color='#a5acaf',edgecolor='black',linewidth=2)\n",
    "p3 = plt.bar(allSEAData['SEA Special Play'],allSEAData['2018'], bottom = allSEAData['2020'] + allSEAData['2019'] , color='#002244',edgecolor='black',linewidth=2)\n",
    "\n",
    "for r1,r2,r3 in zip(p1,p2,p3):\n",
    "    h1 = r1.get_height()\n",
    "    h2 = r2.get_height()\n",
    "    h3 = r3.get_height()\n",
    "    plt.text(r1.get_x()+r1.get_width()/2., h1+h2+h3, '%s'% (h1+h2+h3), ha = 'center', va='bottom',color='black', size=15)\n",
    "plt.legend([\"2020\", \"2019\", \"2018\"],prop={'size': 15})\n",
    "plt.title(\"SEA Special Team Plays\", fontweight=\"bold\", fontsize=25, pad=21)\n",
    "plt.xticks(fontsize=14,fontweight=\"bold\",rotation=90)\n",
    "plt.yticks(fontsize=14,fontweight=\"bold\")\n",
    "plt.tight_layout(pad=1, w_pad=1, h_pad=1)\n",
    "plt.show()\n",
    "\n",
    "plt.figure(figsize=(20, 12))\n",
    "p1 = plt.bar(allSFData['SF Special Play'],allSFData['2020'], color='#b3995d',edgecolor='black',linewidth=2)\n",
    "p2 = plt.bar(allSFData['SF Special Play'],allSFData['2019'], bottom = allSFData['2020'], color='white',edgecolor='black',linewidth=2)\n",
    "p3 = plt.bar(allSFData['SF Special Play'],allSFData['2018'], bottom = allSFData['2020'] + allSFData['2019'] , color='#aa0000',edgecolor='black',linewidth=2)\n",
    "\n",
    "for r1,r2,r3 in zip(p1,p2,p3):\n",
    "    h1 = r1.get_height()\n",
    "    h2 = r2.get_height()\n",
    "    h3 = r3.get_height()\n",
    "    plt.text(r1.get_x()+r1.get_width()/2., h1+h2+h3, '%s'% (h1+h2+h3), ha = 'center', va='bottom',color='black', size=15)\n",
    "plt.legend([\"2020\", \"2019\", \"2018\"],prop={'size': 15})\n",
    "plt.title(\"SF Special Team Plays\", fontweight=\"bold\", fontsize=25, pad=21)\n",
    "plt.xticks(fontsize=14,fontweight=\"bold\",rotation=90)\n",
    "plt.yticks(fontsize=14,fontweight=\"bold\")\n",
    "plt.tight_layout(pad=1, w_pad=1, h_pad=1)\n",
    "plt.show()\n",
    "\n",
    "plt.figure(figsize=(20, 12))\n",
    "p1 = plt.bar(allTBData['TB Special Play'],allTBData['2020'], color='#ff7900',edgecolor='black',linewidth=2)\n",
    "p2 = plt.bar(allTBData['TB Special Play'],allTBData['2019'], bottom = allTBData['2020'], color='#34302b',edgecolor='black',linewidth=2)\n",
    "p3 = plt.bar(allTBData['TB Special Play'],allTBData['2018'], bottom = allTBData['2020'] + allTBData['2019'] , color='#d50a0a',edgecolor='black',linewidth=2)\n",
    "\n",
    "for r1,r2,r3 in zip(p1,p2,p3):\n",
    "    h1 = r1.get_height()\n",
    "    h2 = r2.get_height()\n",
    "    h3 = r3.get_height()\n",
    "    plt.text(r1.get_x()+r1.get_width()/2., h1+h2+h3, '%s'% (h1+h2+h3), ha = 'center', va='bottom',color='black', size=15)\n",
    "plt.legend([\"2020\", \"2019\", \"2018\"],prop={'size': 15})\n",
    "plt.title(\"TB Special Team Plays\", fontweight=\"bold\", fontsize=25, pad=21)\n",
    "plt.xticks(fontsize=14,fontweight=\"bold\",rotation=90)\n",
    "plt.yticks(fontsize=14,fontweight=\"bold\")\n",
    "plt.tight_layout(pad=1, w_pad=1, h_pad=1)\n",
    "plt.show()\n",
    "\n",
    "plt.figure(figsize=(20, 12))\n",
    "p1 = plt.bar(allTENData['TEN Special Play'],allTENData['2020'], color='#c60c30',edgecolor='black',linewidth=2)\n",
    "p2 = plt.bar(allTENData['TEN Special Play'],allTENData['2019'], bottom = allTENData['2020'], color='#4b92db',edgecolor='black',linewidth=2)\n",
    "p3 = plt.bar(allTENData['TEN Special Play'],allTENData['2018'], bottom = allTENData['2020'] + allTENData['2019'] , color='#a5acaf',edgecolor='black',linewidth=2)\n",
    "\n",
    "for r1,r2,r3 in zip(p1,p2,p3):\n",
    "    h1 = r1.get_height()\n",
    "    h2 = r2.get_height()\n",
    "    h3 = r3.get_height()\n",
    "    plt.text(r1.get_x()+r1.get_width()/2., h1+h2+h3, '%s'% (h1+h2+h3), ha = 'center', va='bottom',color='black', size=15)\n",
    "plt.legend([\"2020\", \"2019\", \"2018\"],prop={'size': 15})\n",
    "plt.title(\"TEN Special Team Plays\", fontweight=\"bold\", fontsize=25, pad=21)\n",
    "plt.xticks(fontsize=14,fontweight=\"bold\",rotation=90)\n",
    "plt.yticks(fontsize=14,fontweight=\"bold\")\n",
    "plt.tight_layout(pad=1, w_pad=1, h_pad=1)\n",
    "plt.show()\n",
    "\n",
    "plt.figure(figsize=(20, 12))\n",
    "p1 = plt.bar(allWASData['WAS Special Play'],allWASData['2020'], color='#773141',edgecolor='black',linewidth=2)\n",
    "p2 = plt.bar(allWASData['WAS Special Play'],allWASData['2019'], bottom = allWASData['2020'], color='white',edgecolor='black',linewidth=2)\n",
    "p3 = plt.bar(allWASData['WAS Special Play'],allWASData['2018'], bottom = allWASData['2020'] + allWASData['2019'] , color='#ffb612',edgecolor='black',linewidth=2)\n",
    "\n",
    "for r1,r2,r3 in zip(p1,p2,p3):\n",
    "    h1 = r1.get_height()\n",
    "    h2 = r2.get_height()\n",
    "    h3 = r3.get_height()\n",
    "    plt.text(r1.get_x()+r1.get_width()/2., h1+h2+h3, '%s'% (h1+h2+h3), ha = 'center', va='bottom',color='black', size=15)\n",
    "plt.legend([\"2020\", \"2019\", \"2018\"],prop={'size': 15})\n",
    "plt.title(\"WAS Special Team Plays\", fontweight=\"bold\", fontsize=25, pad=21)\n",
    "plt.xticks(fontsize=14,fontweight=\"bold\",rotation=90)\n",
    "plt.yticks(fontsize=14,fontweight=\"bold\")\n",
    "plt.tight_layout(pad=1, w_pad=1, h_pad=1)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "d4a4ae3c-ea08-4ab6-9d53-39029a4afc9d",
   "metadata": {},
   "outputs": [],
   "source": [
    "games_ids = {}\n",
    "games = mergedGamePlaysAndTrackingFullData.groupby(by=[\"gameId\"])\n",
    "for game, data in games:\n",
    "    games_ids[game] = list(set(data.playId.tolist()))\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "eea69ea9-2da2-40e2-9d73-3a628712cc1b",
   "metadata": {},
   "outputs": [],
   "source": [
    "plt.rcParams['figure.figsize'] = [20, 16]\n",
    "def drawPitch(width, height, color=\"w\"):\n",
    "    fig = plt.figure()\n",
    "    ax = plt.axes(xlim=(-10, width + 30), ylim=(-15, height + 5))\n",
    "    plt.axis('off')\n",
    "\n",
    "    rect = patches.Rectangle((-10, -5), width + 40, height + 10, linewidth=1, facecolor='#00994c', capstyle='round')\n",
    "    ax.add_patch(rect)\n",
    "\n",
    "    rect = plt.Rectangle((0, 0), width + 20, height, ec=color, fc=\"None\", lw=2)\n",
    "    ax.add_patch(rect)\n",
    "\n",
    "    for i in range(21):\n",
    "        plt.plot([10 + 5 * i, 10 + 5 * i], [0, height], c=\"w\", lw=2)\n",
    "\n",
    "    for yards in range(10, width, 10):\n",
    "        yards_text = yards if yards <= width / 2 else width - yards\n",
    "        # top markers\n",
    "        plt.text(10 + yards - 2, height - 7.5, yards_text, size=20, c=\"w\", weight=\"bold\")\n",
    "        # botoom markers\n",
    "        plt.text(10 + yards - 2, 7.5, yards_text, size=20, c=\"w\", weight=\"bold\", rotation=180)\n",
    "\n",
    "    for x in range(20):\n",
    "        for j in range(1, 5):\n",
    "            plt.plot([10 + x * 5 + j, 10 + x * 5 + j], [1, 3], color=\"w\", lw=3)\n",
    "\n",
    "    for x in range(20):\n",
    "        for j in range(1, 5):\n",
    "            plt.plot([10 + x * 5 + j, 10 + x * 5 + j], [height - 1, height - 3], color=\"w\", lw=3)\n",
    "\n",
    "    y = (height - 18.5) / 2\n",
    "    for x in range(20):\n",
    "        for j in range(1, 5):\n",
    "            plt.plot([10 + x * 5 + j, 10 + x * 5 + j], [y, y + 2], color=\"w\", lw=3)\n",
    "\n",
    "    for x in range(20):\n",
    "        for j in range(1, 5):\n",
    "            plt.plot([10 + x * 5 + j, 10 + x * 5 + j], [height - y, height - y - 2], color=\"w\", lw=3)\n",
    "\n",
    "    plt.text(2.5, (height - 10) / 3.5, \"Carolina Panthers\", size=40, c=\"w\", weight=\"bold\", rotation=90)\n",
    "    rect = plt.Rectangle((0, 0), 10, height, ec=color, fc=\"#0085ca\", lw=2)\n",
    "    ax.add_patch(rect)\n",
    "  \n",
    "    plt.text(112.5, (height - 10) / 5, \"Tampa Bay Buccaneers\", size=40, c=\"w\", weight=\"bold\", rotation=-90)\n",
    "    rect = plt.Rectangle((width + 10, 0), 10, height, ec=color, fc=\"#d50a0a\", lw=2)\n",
    "    ax.add_patch(rect)\n",
    "    \n",
    "    y = (height - 3) / 2\n",
    "    plt.plot([10 + 2, 10 + 2], [y, y + 3], c=\"w\", lw=2)\n",
    "\n",
    "    plt.plot([width + 10 - 2, width + 10 - 2], [y, y + 3], c=\"w\", lw=2)\n",
    "\n",
    "    goal_width = 6 # yards\n",
    "    y = (height - goal_width) / 2\n",
    "    plt.plot([0, 0], [y, y + goal_width], \"-\", c=\"#F4C430\", lw=10, ms=20)\n",
    "    plt.plot([width + 20, width + 20], [y, y + goal_width], \"-\", c=\"#F4C430\", lw=10, ms=20)\n",
    "    \n",
    "    return fig, ax\n",
    "\n",
    "fig, ax = drawPitch(100, 53.3)\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "64a13f50-efd9-43df-81bf-d3b297cb011a",
   "metadata": {},
   "outputs": [],
   "source": [
    "def extract_one_game(game_id, play_id):\n",
    "    game = mergedGamePlaysAndTrackingFullData[\n",
    "        (mergedGamePlaysAndTrackingFullData.gameId == game_id) & (mergedGamePlaysAndTrackingFullData.playId == play_id)]\n",
    "    home = {}\n",
    "    away = {}\n",
    "    balls = []\n",
    "\n",
    "    players = game.sort_values(['frameId'], ascending=True).groupby('nflId')\n",
    "\n",
    "    for id, dx in players:\n",
    "        jerseyNumber = int(dx.jerseyNumber.iloc[0])\n",
    "        if dx.team.iloc[0] == \"home\":\n",
    "            home[jerseyNumber] = list(zip(dx.x.tolist(), dx.y.tolist()))\n",
    "        elif dx.team.iloc[0] == \"away\":\n",
    "            away[jerseyNumber] = list(zip(dx.x.tolist(), dx.y.tolist()))\n",
    "\n",
    "    ball_df = game.sort_values(['frameId'], ascending=True)\n",
    "    ball_df = ball_df[ball_df.team == \"football\"]\n",
    "    balls = list(zip(ball_df.x.tolist(), ball_df.y.tolist()))\n",
    "    return home, away, balls\n",
    "\n",
    "\n",
    "def animate_one_play(game_id, play_id):\n",
    "    fig, ax = drawPitch(100, 53.3)\n",
    "\n",
    "    home, away, balls = extract_one_game(game_id, play_id)\n",
    "\n",
    "    team_left, = ax.plot([], [], 'o', markersize=18, markerfacecolor=\"#0085ca\", markeredgewidth=2,\n",
    "                         markeredgecolor=\"black\", zorder=7)\n",
    "    team_right, = ax.plot([], [], 'o', markersize=18, markerfacecolor=\"#d50a0a\", markeredgewidth=2,\n",
    "                          markeredgecolor=\"black\", zorder=7)\n",
    "    ball, = ax.plot([], [], 'o', markersize=10, markerfacecolor=\"#654321\", markeredgewidth=2, markeredgecolor=\"white\",\n",
    "                    zorder=7)\n",
    "    drawings = [team_left, team_right, ball]\n",
    "\n",
    "    def init():\n",
    "        team_left.set_data([], [])\n",
    "        team_right.set_data([], [])\n",
    "        ball.set_data([], [])\n",
    "        return drawings\n",
    "\n",
    "    def draw_teams(i):\n",
    "        X = []\n",
    "        Y = []\n",
    "        for k, v in home.items():\n",
    "            x, y = v[i]\n",
    "            X.append(x)\n",
    "            Y.append(y)\n",
    "        team_left.set_data(X, Y)\n",
    "\n",
    "        X = []\n",
    "        Y = []\n",
    "        for k, v in away.items():\n",
    "            x, y = v[i]\n",
    "            X.append(x)\n",
    "            Y.append(y)\n",
    "        team_right.set_data(X, Y)\n",
    "\n",
    "    def animate(i):\n",
    "        draw_teams(i)\n",
    "\n",
    "        x, y = balls[i]\n",
    "        ball.set_data([x, y])\n",
    "        return drawings\n",
    "\n",
    "    anim = animation.FuncAnimation(fig, animate, init_func=init,\n",
    "                                   frames=len(balls), interval=150, blit=True)\n",
    "#     ax.text(.5, 1.05,\n",
    "#             \"TB's Kickoff Return Yards lossed by possession Team in 2020\\n\\nTampa Bay Buccaneers vs Carolina Panthers\\n\\n GameId:- 2020111500, PlayId:- 3154, Week: 10\\nDescription:- B.Pinion kicks 67 yards from TB 35 to CAR -2. T.Cannon to TB 4 for 98 yards (S.Murphy-Bunting).\\n\", \n",
    "#             transform=ax.transAxes, ha='center', va='center', fontsize='xx-large', fontweight='extra bold')\n",
    "\n",
    "#     anim.save('/Users/kushtrivedi/Desktop/NFL/TampaBay/Video/TB-Kickoff-Return-Yards-Loss-2020.mp4')\n",
    "\n",
    "    return HTML(anim.to_html5_video())\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "d3d32b0d-ed09-4df7-86a1-4078de5c67f4",
   "metadata": {},
   "outputs": [],
   "source": [
    "animate_one_play(2018122302\t, 1858)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "5eaad65f-d31a-4de0-a3ab-d4b33d49a47c",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Kickoff Types:- Data Preparation\n",
    "\n",
    "# Data Preparation for Kickoff by all aspects\n",
    "\n",
    "# Kickoff Return\n",
    "allKickoffReturn = task1DataFrameKickoffs[(task1DataFrameKickoffs.Result == 'Kickoff - Return') \n",
    "                                          & (task1DataFrameKickoffs.penaltyCodes == 0) \n",
    "                                          & (task1DataFrameKickoffs.event != 'None') & (task1DataFrameKickoffs.kickReturnYardage > 25)]\n",
    "# Kickoff Touchback\n",
    "allKickoffTouchback = task1DataFrameKickoffs[(task1DataFrameKickoffs.Result == 'Kickoff - Touchback') \n",
    "                                          & (task1DataFrameKickoffs.penaltyCodes == 0) \n",
    "                                          & (task1DataFrameKickoffs.event != 'None')]\n",
    "\n",
    "# Kickoff - Muffed\n",
    "allKickoffMuffed = task1DataFrameKickoffs[(task1DataFrameKickoffs.Result == 'Kickoff - Muffed') \n",
    "                                          & (task1DataFrameKickoffs.penaltyCodes == 0) \n",
    "                                          & (task1DataFrameKickoffs.event != 'None')]\n",
    "\n",
    "# Kickoff - Kickoff Team Recovery\n",
    "allKickoffTeamRecovery = task1DataFrameKickoffs[(task1DataFrameKickoffs.Result == 'Kickoff - Kickoff Team Recovery') \n",
    "                                          & (task1DataFrameKickoffs.penaltyCodes == 0) \n",
    "                                          & (task1DataFrameKickoffs.event != 'None')]\n",
    "\n",
    "# Kickoff - Out of Bounds\n",
    "allKickoffOutOfBounds = task1DataFrameKickoffs[(task1DataFrameKickoffs.Result == 'Kickoff - Out of Bounds') \n",
    "                                          & (task1DataFrameKickoffs.penaltyCodes == 0) \n",
    "                                          & (task1DataFrameKickoffs.event != 'None')]\n",
    "\n",
    "# Kickoff - Fair Catch\n",
    "allKickoffFairCatch = task1DataFrameKickoffs[(task1DataFrameKickoffs.Result == 'Kickoff - Fair Catch') \n",
    "                                          & (task1DataFrameKickoffs.penaltyCodes == 0) \n",
    "                                          & (task1DataFrameKickoffs.event != 'None')]\n",
    "\n",
    "# Kickoff - Downed\n",
    "allKickoffDowned = task1DataFrameKickoffs[(task1DataFrameKickoffs.Result == 'Kickoff - Downed') & (task1DataFrameKickoffs.event != 'None')]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "e052b43d-d4de-4823-a92d-855a2300aca9",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Punt Types:- Data Preparation\n",
    "\n",
    "# Data Preparation for Punt by all aspects\n",
    "\n",
    "# Punt Return\n",
    "allPuntReturn = task1DataFramePunts[(task1DataFramePunts.Result == 'Punt - Return') \n",
    "                                          & (task1DataFramePunts.penaltyCodes == 0) \n",
    "                                          & (task1DataFramePunts.event != 'None')]\n",
    "# Punt Touchback\n",
    "allPuntTouchback = task1DataFramePunts[(task1DataFramePunts.Result == 'Punt - Touchback') \n",
    "                                          & (task1DataFramePunts.penaltyCodes == 0) \n",
    "                                          & (task1DataFramePunts.event != 'None')]\n",
    "\n",
    "# Punt - Fair Catch\n",
    "allPuntFairCatch = task1DataFramePunts[(task1DataFramePunts.Result == 'Punt - Fair Catch') \n",
    "                                          & (task1DataFramePunts.penaltyCodes == 0) \n",
    "                                          & (task1DataFramePunts.event != 'None')]\n",
    "\n",
    "# Punt - Out of Bounds\n",
    "allPuntOutOfBounds = task1DataFramePunts[(task1DataFramePunts.Result == 'Punt - Out of Bounds') \n",
    "                                          & (task1DataFramePunts.penaltyCodes == 0) \n",
    "                                          & (task1DataFramePunts.event != 'None')]\n",
    "\n",
    "# Punt - Muffed\n",
    "allPuntMuffed = task1DataFramePunts[(task1DataFramePunts.Result == 'Punt - Muffed') \n",
    "                                          & (task1DataFramePunts.penaltyCodes == 0) \n",
    "                                          & (task1DataFramePunts.event != 'None')]\n",
    "\n",
    "# Punt - Downed\n",
    "allPuntDowned = task1DataFramePunts[(task1DataFramePunts.Result == 'Punt - Downed') & (task1DataFramePunts.event != 'None')]\n",
    "\n",
    "# Punt - Non-Special Teams Result\n",
    "allPuntNonSpecialTeamsResult = task1DataFramePunts[(task1DataFramePunts.Result == 'Punt - Non-Special Teams Result') \n",
    "                                          & (task1DataFramePunts.penaltyCodes == 0) \n",
    "                                          & (task1DataFramePunts.event != 'None')]\n",
    "\n",
    "# Punt - Blocked Punt\n",
    "allPuntBlockedPunt = task1DataFramePunts[(task1DataFramePunts.Result == 'Punt - Blocked Punt') \n",
    "                                          & (task1DataFramePunts.penaltyCodes == 0) \n",
    "                                          & (task1DataFramePunts.event != 'None')]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "bcdd5c38-12dc-4ca9-9734-4e95e37e1ae9",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Kickoff Types:- DataFrames\n",
    "\n",
    "# Kickoff Return\n",
    "allKickoffReturnSeries = allKickoffReturn.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo','yardlineSide','Result','gameClock',\n",
    "                                   'yardlineNumber','kickReturnYardage','playResult','preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr',\n",
    "                                   'week'],as_index=True).size()\n",
    "allKickoffReturnFrame = pd.DataFrame(allKickoffReturnSeries)\n",
    "\n",
    "# Kickoff Touchback\n",
    "allKickoffTouchbackSeries = allKickoffTouchback.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo','yardlineSide','Result','gameClock',\n",
    "                                   'yardlineNumber','playResult','preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr',\n",
    "                                   'week'],as_index=True).size()\n",
    "allKickoffTouchbackFrame = pd.DataFrame(allKickoffTouchbackSeries)\n",
    "\n",
    "# Kickoff - Muffed\n",
    "allKickoffMuffedSeries = allKickoffMuffed.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo','yardlineSide','Result','gameClock',\n",
    "                                   'yardlineNumber','playResult','preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr',\n",
    "                                   'week'],as_index=True).size()\n",
    "allKickoffMuffedFrame = pd.DataFrame(allKickoffMuffedSeries)\n",
    "\n",
    "# Kickoff - Kickoff Team Recovery\n",
    "allKickoffTeamRecoverySeries = allKickoffTeamRecovery.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo','yardlineSide','Result','gameClock',\n",
    "                                   'yardlineNumber','playResult','preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr',\n",
    "                                   'week'],as_index=True).size()\n",
    "allKickoffTeamRecoveryFrame = pd.DataFrame(allKickoffTeamRecoverySeries)\n",
    "\n",
    "# Kickoff - Out of Bounds\n",
    "allKickoffOutOfBoundsSeries = allKickoffOutOfBounds.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo','yardlineSide','Result','gameClock',\n",
    "                                   'yardlineNumber','playResult','preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr',\n",
    "                                   'week'],as_index=True).size()\n",
    "allKickoffOutOfBoundsFrame = pd.DataFrame(allKickoffOutOfBoundsSeries)\n",
    "\n",
    "# Kickoff - Fair Catch\n",
    "allKickoffFairCatchSeries = allKickoffFairCatch.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo','yardlineSide','Result','gameClock',\n",
    "                                   'yardlineNumber','playResult','preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr',\n",
    "                                   'week'],as_index=True).size()\n",
    "allKickoffFairCatchFrame = pd.DataFrame(allKickoffFairCatchSeries)\n",
    "\n",
    "# Kickoff - Downed\n",
    "allKickoffDownedSeries = allKickoffDowned.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo','yardlineSide','Result','gameClock',\n",
    "                                   'yardlineNumber','playResult','preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr',\n",
    "                                   'week'],as_index=True).size()\n",
    "allKickoffDownedFrame = pd.DataFrame(allKickoffDownedSeries)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "7cf6e148-4ff7-4c6a-895f-ab0f53d26a37",
   "metadata": {},
   "outputs": [],
   "source": [
    "allPuntReturnSeries = allPuntReturn.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo','yardlineSide','Result','gameClock',\n",
    "                                   'yardlineNumber','kickReturnYardage','playResult','preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr',\n",
    "                                   'week'],as_index=True).size()\n",
    "allPuntReturnFrame = pd.DataFrame(allPuntReturnSeries)\n",
    "\n",
    "\n",
    "allPuntTouchbackSeries = allPuntTouchback.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo','yardlineSide','Result','gameClock',\n",
    "                                   'yardlineNumber','playResult','preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr',\n",
    "                                   'week'],as_index=True).size()\n",
    "allPuntTouchbackFrame = pd.DataFrame(allPuntTouchbackSeries)\n",
    "\n",
    "\n",
    "\n",
    "allPuntFairCatchSeries = allPuntFairCatch.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo','yardlineSide','Result','gameClock',\n",
    "                                   'yardlineNumber','playResult','preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr',\n",
    "                                   'week'],as_index=True).size()\n",
    "allPuntFairCatchFrame = pd.DataFrame(allPuntFairCatchSeries)\n",
    "\n",
    "\n",
    "\n",
    "allPuntOutOfBoundsSeries = allPuntOutOfBounds.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo','yardlineSide','Result','gameClock',\n",
    "                                   'yardlineNumber','playResult','preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr',\n",
    "                                   'week'],as_index=True).size()\n",
    "allPuntOutOfBoundsFrame = pd.DataFrame(allPuntOutOfBoundsSeries)\n",
    "\n",
    "\n",
    "\n",
    "allPuntMuffedSeries = allPuntMuffed.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo','yardlineSide','Result','gameClock',\n",
    "                                   'yardlineNumber','playResult','preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr',\n",
    "                                   'week'],as_index=True).size()\n",
    "allPuntMuffedFrame = pd.DataFrame(allPuntMuffedSeries)\n",
    "\n",
    "\n",
    "\n",
    "allPuntDownedSeries = allPuntDowned.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo','yardlineSide','Result','gameClock',\n",
    "                                   'yardlineNumber','playResult','preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr',\n",
    "                                   'week'],as_index=True).size()\n",
    "allPuntDownedFrame = pd.DataFrame(allPuntDownedSeries)\n",
    "\n",
    "\n",
    "\n",
    "allPuntNonSpecialTeamsResultSeries = allPuntNonSpecialTeamsResult.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo','yardlineSide','Result','gameClock',\n",
    "                                   'yardlineNumber','playResult','preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr',\n",
    "                                   'week'],as_index=True).size()\n",
    "allPuntNonSpecialTeamsResultFrame = pd.DataFrame(allPuntNonSpecialTeamsResultSeries)\n",
    "\n",
    "\n",
    "\n",
    "allPuntBlockedPuntSeries = allPuntBlockedPunt.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo','yardlineSide','Result','gameClock',\n",
    "                                   'yardlineNumber','playResult','preSnapHomeScore','preSnapVisitorScore','homeTeamAbbr','visitorTeamAbbr',\n",
    "                                   'week'],as_index=False).size()\n",
    "allPuntBlockedPuntFrame = pd.DataFrame(allPuntBlockedPuntSeries)\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "e4186757-eb3a-4935-8ffc-30a474931a50",
   "metadata": {},
   "outputs": [],
   "source": [
    "allKickoffReturnFrame.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "e3333023-8b44-44d8-9965-e0b9e679dbcc",
   "metadata": {},
   "outputs": [],
   "source": [
    "# task2DataFrameARI = task2DataFrame[(task2DataFrame.possessionTeam == 'ARI') & (task2DataFrame.down != 0) & (task2DataFrame.penaltyCodes == 0) & (task2DataFrame.event != 'None')]\n",
    "# task2DataFrameATL = task2DataFrame[(task2DataFrame.possessionTeam == 'ATL') & (task2DataFrame.down != 0) & (task2DataFrame.penaltyCodes == 0) & (task2DataFrame.event != 'None')]\n",
    "# task2DataFrameBAL = task2DataFrame[(task2DataFrame.possessionTeam == 'BAL') & (task2DataFrame.down != 0) & (task2DataFrame.penaltyCodes == 0) & (task2DataFrame.event != 'None')]\n",
    "# task2DataFrameBUF = task2DataFrame[(task2DataFrame.possessionTeam == 'BUF') & (task2DataFrame.down != 0) & (task2DataFrame.penaltyCodes == 0) & (task2DataFrame.event != 'None')]\n",
    "\n",
    "# task2DataFrameCAR = task2DataFrame[(task2DataFrame.possessionTeam == 'CAR') & (task2DataFrame.down != 0) & (task2DataFrame.penaltyCodes == 0) & (task2DataFrame.event != 'None')]\n",
    "# task2DataFrameCHI = task2DataFrame[(task2DataFrame.possessionTeam == 'CHI') & (task2DataFrame.down != 0) & (task2DataFrame.penaltyCodes == 0) & (task2DataFrame.event != 'None')]\n",
    "# task2DataFrameCIN = task2DataFrame[(task2DataFrame.possessionTeam == 'CIN') & (task2DataFrame.down != 0) & (task2DataFrame.penaltyCodes == 0) & (task2DataFrame.event != 'None')]\n",
    "# task2DataFrameCLE = task2DataFrame[(task2DataFrame.possessionTeam == 'CLE') & (task2DataFrame.down != 0) & (task2DataFrame.penaltyCodes == 0) & (task2DataFrame.event != 'None')]\n",
    "\n",
    "# task2DataFrameDAL = task2DataFrame[(task2DataFrame.possessionTeam == 'DAL') & (task2DataFrame.down != 0) & (task2DataFrame.penaltyCodes == 0) & (task2DataFrame.event != 'None')]\n",
    "# task2DataFrameDEN = task2DataFrame[(task2DataFrame.possessionTeam == 'DEN') & (task2DataFrame.down != 0) & (task2DataFrame.penaltyCodes == 0) & (task2DataFrame.event != 'None')]\n",
    "# task2DataFrameDET = task2DataFrame[(task2DataFrame.possessionTeam == 'DET') & (task2DataFrame.down != 0) & (task2DataFrame.penaltyCodes == 0) & (task2DataFrame.event != 'None')]\n",
    "# task2DataFrameGB = task2DataFrame[(task2DataFrame.possessionTeam == 'GB') & (task2DataFrame.down != 0) & (task2DataFrame.penaltyCodes == 0) & (task2DataFrame.event != 'None')]\n",
    "\n",
    "# task2DataFrameHOU = task2DataFrame[(task2DataFrame.possessionTeam == 'HOU') & (task2DataFrame.down != 0) & (task2DataFrame.penaltyCodes == 0) & (task2DataFrame.event != 'None')]\n",
    "# task2DataFrameIND = task2DataFrame[(task2DataFrame.possessionTeam == 'IND') & (task2DataFrame.down != 0) & (task2DataFrame.penaltyCodes == 0) & (task2DataFrame.event != 'None')]\n",
    "# task2DataFrameJAX = task2DataFrame[(task2DataFrame.possessionTeam == 'JAX') & (task2DataFrame.down != 0) & (task2DataFrame.penaltyCodes == 0) & (task2DataFrame.event != 'None')]\n",
    "# task2DataFrameKC = task2DataFrame[(task2DataFrame.possessionTeam == 'KC') & (task2DataFrame.down != 0) & (task2DataFrame.penaltyCodes == 0)]\n",
    "\n",
    "# task2DataFrameLA = task2DataFrame[(task2DataFrame.possessionTeam == 'LA') & (task2DataFrame.down != 0) & (task2DataFrame.penaltyCodes == 0) & (task2DataFrame.event != 'None')]\n",
    "# task2DataFrameLAC = task2DataFrame[(task2DataFrame.possessionTeam == 'LAC') & (task2DataFrame.down != 0) & (task2DataFrame.penaltyCodes == 0) & (task2DataFrame.event != 'None')]\n",
    "# task2DataFrameMIA = task2DataFrame[(task2DataFrame.possessionTeam == 'MIA') & (task2DataFrame.down != 0) & (task2DataFrame.penaltyCodes == 0) & (task2DataFrame.event != 'None')]\n",
    "# task2DataFrameMIN = task2DataFrame[(task2DataFrame.possessionTeam == 'MIN') & (task2DataFrame.down != 0) & (task2DataFrame.penaltyCodes == 0) & (task2DataFrame.event != 'None')]\n",
    "\n",
    "# task2DataFrameNE = task2DataFrame[(task2DataFrame.possessionTeam == 'NE') & (task2DataFrame.down != 0) & (task2DataFrame.penaltyCodes == 0) & (task2DataFrame.event != 'None')]\n",
    "# task2DataFrameNO = task2DataFrame[(task2DataFrame.possessionTeam == 'NO') & (task2DataFrame.down != 0) & (task2DataFrame.penaltyCodes == 0) & (task2DataFrame.event != 'None')]\n",
    "# task2DataFrameNYG = task2DataFrame[(task2DataFrame.possessionTeam == 'NYG') & (task2DataFrame.down != 0) & (task2DataFrame.penaltyCodes == 0) & (task2DataFrame.event != 'None')]\n",
    "# task2DataFrameNYJ = task2DataFrame[(task2DataFrame.possessionTeam == 'NYJ') & (task2DataFrame.down != 0) & (task2DataFrame.penaltyCodes == 0) & (task2DataFrame.event != 'None')]\n",
    "\n",
    "# task2DataFrameOAK = task2DataFrame[(task2DataFrame.possessionTeam == 'OAK') & (task2DataFrame.down != 0) & (task2DataFrame.penaltyCodes == 0) & (task2DataFrame.event != 'None')]\n",
    "# task2DataFramePHI = task2DataFrame[(task2DataFrame.possessionTeam == 'PHI') & (task2DataFrame.down != 0) & (task2DataFrame.penaltyCodes == 0) & (task2DataFrame.event != 'None')]\n",
    "# task2DataFramePIT = task2DataFrame[(task2DataFrame.possessionTeam == 'PIT') & (task2DataFrame.down != 0) & (task2DataFrame.penaltyCodes == 0) & (task2DataFrame.event != 'None')]\n",
    "# task2DataFrameSEA = task2DataFrame[(task2DataFrame.possessionTeam == 'SEA') & (task2DataFrame.down != 0) & (task2DataFrame.penaltyCodes == 0) & (task2DataFrame.event != 'None')]\n",
    "\n",
    "# task2DataFrameSF = task2DataFrame[(task2DataFrame.possessionTeam == 'SF') & (task2DataFrame.down != 0) & (task2DataFrame.penaltyCodes == 0) & (task2DataFrame.event != 'None')]\n",
    "# task2DataFrameTB = task2DataFrame[(task2DataFrame.possessionTeam == 'TB') & (task2DataFrame.down != 0) & (task2DataFrame.penaltyCodes == 0) & (task2DataFrame.event != 'None')]\n",
    "# task2DataFrameTEN = task2DataFrame[(task2DataFrame.possessionTeam == 'TEN') & (task2DataFrame.down != 0) & (task2DataFrame.penaltyCodes == 0) & (task2DataFrame.event != 'None')]\n",
    "# task2DataFrameWAS = task2DataFrame[(task2DataFrame.possessionTeam == 'WAS') & (task2DataFrame.down != 0) & (task2DataFrame.penaltyCodes == 0) & (task2DataFrame.event != 'None')]\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "a36826f7-9161-462d-9185-4b76a81bc26c",
   "metadata": {},
   "outputs": [],
   "source": [
    "# task2DataFrameARISeries = task2DataFrameARI.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo',\n",
    "#                                                'yardlineSide','Result','gameClock','yardlineNumber','playResult',\n",
    "#                                                'preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr','week']\n",
    "#                                               ,as_index=False).size()\n",
    "# task2DataFrameARIFinal = pd.DataFrame(task2DataFrameARISeries)\n",
    "\n",
    "# task2DataFrameATLSeries = task2DataFrameATL.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo',\n",
    "#                                                'yardlineSide','Result','gameClock','yardlineNumber','playResult',\n",
    "#                                                'preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr','week']\n",
    "#                                               ,as_index=False).size()\n",
    "# task2DataFrameATLFinal = pd.DataFrame(task2DataFrameATLSeries)\n",
    "\n",
    "# task2DataFrameBALSeries = task2DataFrameBAL.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo',\n",
    "#                                                'yardlineSide','Result','gameClock','yardlineNumber','playResult',\n",
    "#                                                'preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr','week']\n",
    "#                                               ,as_index=False).size()\n",
    "# task2DataFrameBALFinal = pd.DataFrame(task2DataFrameBALSeries)\n",
    "\n",
    "# task2DataFrameBUFSeries = task2DataFrameBUF.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo',\n",
    "#                                                'yardlineSide','Result','gameClock','yardlineNumber','playResult',\n",
    "#                                                'preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr','week']\n",
    "#                                               ,as_index=False).size()\n",
    "# task2DataFrameBUFFinal = pd.DataFrame(task2DataFrameBUFSeries)\n",
    "\n",
    "\n",
    "# task2DataFrameCARSeries = task2DataFrameCAR.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo',\n",
    "#                                                'yardlineSide','Result','gameClock','yardlineNumber','playResult',\n",
    "#                                                'preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr','week']\n",
    "#                                               ,as_index=False).size()\n",
    "# task2DataFrameCARFinal = pd.DataFrame(task2DataFrameCARSeries)\n",
    "\n",
    "# task2DataFrameCHISeries = task2DataFrameCHI.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo',\n",
    "#                                                'yardlineSide','Result','gameClock','yardlineNumber','playResult',\n",
    "#                                                'preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr','week']\n",
    "#                                               ,as_index=False).size()\n",
    "# task2DataFrameCHIFinal = pd.DataFrame(task2DataFrameCHISeries)\n",
    "\n",
    "# task2DataFrameCINSeries = task2DataFrameCIN.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo',\n",
    "#                                                'yardlineSide','Result','gameClock','yardlineNumber','playResult',\n",
    "#                                                'preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr','week']\n",
    "#                                               ,as_index=False).size()\n",
    "# task2DataFrameCINFinal = pd.DataFrame(task2DataFrameCINSeries)\n",
    "\n",
    "# task2DataFrameCLESeries = task2DataFrameCLE.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo',\n",
    "#                                                'yardlineSide','Result','gameClock','yardlineNumber','playResult',\n",
    "#                                                'preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr','week']\n",
    "#                                               ,as_index=False).size()\n",
    "# task2DataFrameCLEFinal = pd.DataFrame(task2DataFrameCLESeries)\n",
    "\n",
    "\n",
    "# task2DataFrameDALSeries = task2DataFrameDAL.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo',\n",
    "#                                                'yardlineSide','Result','gameClock','yardlineNumber','playResult',\n",
    "#                                                'preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr','week']\n",
    "#                                               ,as_index=False).size()\n",
    "# task2DataFrameDALFinal = pd.DataFrame(task2DataFrameDALSeries)\n",
    "\n",
    "# task2DataFrameDENSeries = task2DataFrameDEN.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo',\n",
    "#                                                'yardlineSide','Result','gameClock','yardlineNumber','playResult',\n",
    "#                                                'preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr','week']\n",
    "#                                               ,as_index=False).size()\n",
    "# task2DataFrameDENFinal = pd.DataFrame(task2DataFrameDENSeries)\n",
    "\n",
    "# task2DataFrameDETSeries = task2DataFrameDET.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo',\n",
    "#                                                'yardlineSide','Result','gameClock','yardlineNumber','playResult',\n",
    "#                                                'preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr','week']\n",
    "#                                               ,as_index=False).size()\n",
    "# task2DataFrameDETFinal = pd.DataFrame(task2DataFrameDETSeries)\n",
    "\n",
    "# task2DataFrameGBSeries = task2DataFrameGB.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo',\n",
    "#                                                'yardlineSide','Result','gameClock','yardlineNumber','playResult',\n",
    "#                                                'preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr','week']\n",
    "#                                               ,as_index=False).size()\n",
    "# task2DataFrameGBFinal = pd.DataFrame(task2DataFrameGBSeries)\n",
    "\n",
    "# task2DataFrameHOUSeries = task2DataFrameHOU.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo',\n",
    "#                                                'yardlineSide','Result','gameClock','yardlineNumber','playResult',\n",
    "#                                                'preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr','week']\n",
    "#                                               ,as_index=False).size()\n",
    "# task2DataFrameHOUFinal = pd.DataFrame(task2DataFrameHOUSeries)\n",
    "\n",
    "# task2DataFrameINDSeries = task2DataFrameIND.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo',\n",
    "#                                                'yardlineSide','Result','gameClock','yardlineNumber','playResult',\n",
    "#                                                'preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr','week']\n",
    "#                                               ,as_index=False).size()\n",
    "# task2DataFrameINDFinal = pd.DataFrame(task2DataFrameINDSeries)\n",
    "\n",
    "# task2DataFrameJAXSeries = task2DataFrameJAX.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo',\n",
    "#                                                'yardlineSide','Result','gameClock','yardlineNumber','playResult',\n",
    "#                                                'preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr','week']\n",
    "#                                               ,as_index=False).size()\n",
    "# task2DataFrameJAXFinal = pd.DataFrame(task2DataFrameJAXSeries)\n",
    "\n",
    "# task2DataFrameKCSeries = task2DataFrameKC.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo',\n",
    "#                                                'yardlineSide','Result','gameClock','yardlineNumber','playResult',\n",
    "#                                                'preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr','week']\n",
    "#                                               ,as_index=False).size()\n",
    "# task2DataFrameKCFinal = pd.DataFrame(task2DataFrameKCSeries)\n",
    "\n",
    "\n",
    "# task2DataFrameLASeries = task2DataFrameLA.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo',\n",
    "#                                                'yardlineSide','Result','gameClock','yardlineNumber','playResult',\n",
    "#                                                'preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr','week']\n",
    "#                                               ,as_index=False).size()\n",
    "# task2DataFrameLAFinal = pd.DataFrame(task2DataFrameLASeries)\n",
    "\n",
    "# task2DataFrameLACSeries = task2DataFrameLAC.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo',\n",
    "#                                                'yardlineSide','Result','gameClock','yardlineNumber','playResult',\n",
    "#                                                'preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr','week']\n",
    "#                                               ,as_index=False).size()\n",
    "# task2DataFrameLACFinal = pd.DataFrame(task2DataFrameLACSeries)\n",
    "\n",
    "# task2DataFrameMIASeries = task2DataFrameMIA.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo',\n",
    "#                                                'yardlineSide','Result','gameClock','yardlineNumber','playResult',\n",
    "#                                                'preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr','week']\n",
    "#                                               ,as_index=False).size()\n",
    "# task2DataFrameMIAFinal = pd.DataFrame(task2DataFrameMIASeries)\n",
    "\n",
    "# task2DataFrameMINSeries = task2DataFrameMIN.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo',\n",
    "#                                                'yardlineSide','Result','gameClock','yardlineNumber','playResult',\n",
    "#                                                'preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr','week']\n",
    "#                                               ,as_index=False).size()\n",
    "# task2DataFrameMINFinal = pd.DataFrame(task2DataFrameMINSeries)\n",
    "\n",
    "\n",
    "\n",
    "# task2DataFrameNESeries = task2DataFrameNE.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo',\n",
    "#                                                'yardlineSide','Result','gameClock','yardlineNumber','playResult',\n",
    "#                                                'preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr','week']\n",
    "#                                               ,as_index=False).size()\n",
    "# task2DataFrameNEFinal = pd.DataFrame(task2DataFrameNESeries)\n",
    "\n",
    "# task2DataFrameNOSeries = task2DataFrameNO.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo',\n",
    "#                                                'yardlineSide','Result','gameClock','yardlineNumber','playResult',\n",
    "#                                                'preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr','week']\n",
    "#                                               ,as_index=False).size()\n",
    "# task2DataFrameNOFinal = pd.DataFrame(task2DataFrameNOSeries)\n",
    "\n",
    "# task2DataFrameNYGSeries = task2DataFrameNYG.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo',\n",
    "#                                                'yardlineSide','Result','gameClock','yardlineNumber','playResult',\n",
    "#                                                'preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr','week']\n",
    "#                                               ,as_index=False).size()\n",
    "# task2DataFrameNYGFinal = pd.DataFrame(task2DataFrameNYGSeries)\n",
    "\n",
    "# task2DataFrameNYJSeries = task2DataFrameNYJ.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo',\n",
    "#                                                'yardlineSide','Result','gameClock','yardlineNumber','playResult',\n",
    "#                                                'preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr','week']\n",
    "#                                               ,as_index=False).size()\n",
    "# task2DataFrameNYJFinal = pd.DataFrame(task2DataFrameNYJSeries)\n",
    "\n",
    "\n",
    "\n",
    "# task2DataFrameOAKSeries = task2DataFrameOAK.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo',\n",
    "#                                                'yardlineSide','Result','gameClock','yardlineNumber','playResult',\n",
    "#                                                'preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr','week']\n",
    "#                                               ,as_index=False).size()\n",
    "# task2DataFrameOAKFinal = pd.DataFrame(task2DataFrameOAKSeries)\n",
    "\n",
    "# task2DataFramePHISeries = task2DataFramePHI.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo',\n",
    "#                                                'yardlineSide','Result','gameClock','yardlineNumber','playResult',\n",
    "#                                                'preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr','week']\n",
    "#                                               ,as_index=False).size()\n",
    "# task2DataFramePHIFinal = pd.DataFrame(task2DataFramePHISeries)\n",
    "\n",
    "# task2DataFramePITSeries = task2DataFramePIT.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo',\n",
    "#                                                'yardlineSide','Result','gameClock','yardlineNumber','playResult',\n",
    "#                                                'preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr','week']\n",
    "#                                               ,as_index=False).size()\n",
    "# task2DataFramePITFinal = pd.DataFrame(task2DataFramePITSeries)\n",
    "\n",
    "# task2DataFrameSEASeries = task2DataFrameSEA.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo',\n",
    "#                                                'yardlineSide','Result','gameClock','yardlineNumber','playResult',\n",
    "#                                                'preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr','week']\n",
    "#                                               ,as_index=False).size()\n",
    "# task2DataFrameSEAFinal = pd.DataFrame(task2DataFrameSEASeries)\n",
    "\n",
    "\n",
    "\n",
    "# task2DataFrameSFSeries = task2DataFrameSF.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo',\n",
    "#                                                'yardlineSide','Result','gameClock','yardlineNumber','playResult',\n",
    "#                                                'preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr','week']\n",
    "#                                               ,as_index=False).size()\n",
    "# task2DataFrameSFFinal = pd.DataFrame(task2DataFrameSFSeries)\n",
    "\n",
    "# task2DataFrameTBSeries = task2DataFrameTB.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo',\n",
    "#                                                'yardlineSide','Result','gameClock','yardlineNumber','playResult',\n",
    "#                                                'preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr','week']\n",
    "#                                               ,as_index=False).size()\n",
    "# task2DataFrameTBFinal = pd.DataFrame(task2DataFrameTBSeries)\n",
    "\n",
    "# task2DataFrameTENSeries = task2DataFrameTEN.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo',\n",
    "#                                                'yardlineSide','Result','gameClock','yardlineNumber','playResult',\n",
    "#                                                'preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr','week']\n",
    "#                                               ,as_index=False).size()\n",
    "# task2DataFrameTENFinal = pd.DataFrame(task2DataFrameTENSeries)\n",
    "\n",
    "# task2DataFrameWASSeries = task2DataFrameWAS.groupby(['season','possessionTeam','gameId','playId','quarter','down','yardsToGo',\n",
    "#                                                'yardlineSide','Result','gameClock','yardlineNumber','playResult',\n",
    "#                                                'preSnapHomeScore','preSnapVisitorScore','event','homeTeamAbbr','visitorTeamAbbr','week']\n",
    "#                                               ,as_index=False).size()\n",
    "# task2DataFrameWASFinal = pd.DataFrame(task2DataFrameWASSeries)\n"
   ]
  },
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