NBA sports betting using machine learning
Visualization and analysis of NBA player tracking data
🏀 An application to build an NBA database backed by MariaDB/MySQL, Postgres compatible databases, or SQLite.
Labelling NBA action using deep learning 🏀
Predicts Daily NBA Games Using a Logistic Regression Model
Tools to help developers and data scientists in sports
Using AI to predict the outcomes of NBA games.
NBA game prediction model
Being able to perform gameplay analysis of NBA players, NBA Predictive Analytics is a basketball coach's new best friend.
Interactive exploration of NBA roster turnover
Analysis of NBA player stats and salaries of the 2016-17 for the 17-18 season
🔮 Predicting NBA games using statistics (65% accuracy so far)
The NBA Statistics Dashboard is an innovative and user-focused project that harnesses daily data scraping to create a dynamic platform for sports bettors, NBA enthusiasts, and fantasy league participants.
A NBA player data explorer web app in Python using the Streamlit library
WebScraping NBA's Asian Handicaps and Over/Unders from OddsPortal, to evaluate the accuracy of NBA odds market
Machine Learning Technion Course Final Project - NBA Teams Playoffs Qualification
Uses SportsVU Optical Tracking Data to check if screens occur in a play
Developed models used NBA play-by-play data to determine the value and effectiveness of late game timeouts.
An analysis of the accuracy of Sportsbooks' Totals (Over/Under) Lines against actual final game score for historical NBA games.
Provides overview of in-game stats from parsed play-by-play stats from SportRadar
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