diff --git a/data/token_usage.csv b/data/token_usage.csv
new file mode 100644
index 0000000..af4dc84
--- /dev/null
+++ b/data/token_usage.csv
@@ -0,0 +1,321 @@
+,imp_model,crew_model,imp_out_tokens,crew_out_tokens,rounds,result,imp_pretend_count
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+2,claude-3-5-haiku,claude-3-5-haiku,8400,14422,9,crew,1
+3,claude-3-5-haiku,claude-3-5-haiku,205984,322017,40,lim,9
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+5,claude-3-5-haiku,claude-3-5-sonnet,25569,33026,12,imp,6
+6,claude-3-5-haiku,claude-3-5-sonnet,74847,127648,27,crew,9
+7,claude-3-5-haiku,claude-3-5-sonnet,145025,188550,34,imp,8
+8,claude-3-5-haiku,claude-3-5-sonnet,5367,11827,6,crew,1
+9,claude-3-5-haiku,claude-3-5-sonnet,6808,17798,8,crew,2
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+225,gpt-4o,gpt-4o,60241,117895,28,crew,17
+226,gpt-4o,gpt-4o,64290,196746,26,crew,25
+227,gpt-4o,gpt-4o,26767,63197,23,imp,15
+228,gpt-4o,gpt-4o,43580,127862,25,imp,17
+229,gpt-4o,gpt-4o,82446,329038,40,lim,32
+230,gpt-4o,llama-3-1-405b-instruct,123450,319191,39,imp,35
+231,gpt-4o,llama-3-1-405b-instruct,39470,116261,21,imp,16
+232,gpt-4o,llama-3-1-405b-instruct,76301,409743,40,lim,38
+233,gpt-4o,llama-3-1-405b-instruct,10165,41598,14,imp,4
+234,gpt-4o,llama-3-1-405b-instruct,131246,669360,40,lim,37
+235,gpt-4o,llama-3-1-8b-instruct,3024,15918,6,crew,1
+236,gpt-4o,llama-3-1-8b-instruct,19976,70805,17,crew,8
+237,gpt-4o,llama-3-1-8b-instruct,10516,43960,13,crew,6
+238,gpt-4o,llama-3-1-8b-instruct,11668,37704,14,crew,5
+239,gpt-4o,llama-3-1-8b-instruct,166839,702078,40,lim,38
+240,llama-3-1-405b-instruct,claude-3-5-haiku,6288,13812,9,imp,1
+241,llama-3-1-405b-instruct,claude-3-5-haiku,8237,24600,10,crew,3
+242,llama-3-1-405b-instruct,claude-3-5-haiku,6976,14492,9,imp,1
+243,llama-3-1-405b-instruct,claude-3-5-haiku,9565,23036,12,crew,4
+244,llama-3-1-405b-instruct,claude-3-5-haiku,8145,20404,10,crew,2
+245,llama-3-1-405b-instruct,claude-3-5-sonnet,3907,12017,6,crew,1
+246,llama-3-1-405b-instruct,claude-3-5-sonnet,3642,13519,6,crew,1
+247,llama-3-1-405b-instruct,claude-3-5-sonnet,5459,11875,7,imp,1
+248,llama-3-1-405b-instruct,claude-3-5-sonnet,71969,184043,33,crew,8
+249,llama-3-1-405b-instruct,claude-3-5-sonnet,33388,82278,20,crew,8
+250,llama-3-1-405b-instruct,gemini-flash-1-5,5028,6624,9,crew,1
+251,llama-3-1-405b-instruct,gemini-flash-1-5,158177,164741,37,imp,27
+252,llama-3-1-405b-instruct,gemini-flash-1-5,59210,61035,26,crew,6
+253,llama-3-1-405b-instruct,gemini-flash-1-5,151270,262625,40,lim,27
+254,llama-3-1-405b-instruct,gemini-flash-1-5,20075,30423,17,imp,4
+255,llama-3-1-405b-instruct,gemini-pro-1-5,6224,4024,9,crew,1
+256,llama-3-1-405b-instruct,gemini-pro-1-5,4778,4202,7,crew,1
+257,llama-3-1-405b-instruct,gemini-pro-1-5,4615,4429,7,crew,1
+258,llama-3-1-405b-instruct,gemini-pro-1-5,6518,5032,9,crew,1
+259,llama-3-1-405b-instruct,gemini-pro-1-5,8881,3541,7,imp,3
+260,llama-3-1-405b-instruct,gpt-4o-mini,10362,9165,8,imp,4
+261,llama-3-1-405b-instruct,gpt-4o-mini,8664,13394,11,crew,1
+262,llama-3-1-405b-instruct,gpt-4o-mini,3983,9775,7,crew,2
+263,llama-3-1-405b-instruct,gpt-4o-mini,6747,10383,9,imp,1
+264,llama-3-1-405b-instruct,gpt-4o-mini,3390,5361,5,imp,1
+265,llama-3-1-405b-instruct,gpt-4o,6413,11987,8,imp,1
+266,llama-3-1-405b-instruct,gpt-4o,6364,10255,7,imp,1
+267,llama-3-1-405b-instruct,gpt-4o,6171,9627,7,imp,1
+268,llama-3-1-405b-instruct,gpt-4o,6221,11005,8,imp,2
+269,llama-3-1-405b-instruct,gpt-4o,7934,11469,10,crew,1
+270,llama-3-1-405b-instruct,llama-3-1-405b-instruct,5384,15722,8,crew,1
+271,llama-3-1-405b-instruct,llama-3-1-405b-instruct,5819,15056,9,crew,1
+272,llama-3-1-405b-instruct,llama-3-1-405b-instruct,16692,39787,13,imp,1
+273,llama-3-1-405b-instruct,llama-3-1-405b-instruct,4388,8618,6,crew,1
+274,llama-3-1-405b-instruct,llama-3-1-405b-instruct,5183,21680,7,imp,1
+275,llama-3-1-405b-instruct,llama-3-1-8b-instruct,8924,21762,11,imp,2
+276,llama-3-1-405b-instruct,llama-3-1-8b-instruct,9018,20276,11,imp,3
+277,llama-3-1-405b-instruct,llama-3-1-8b-instruct,11416,28870,11,imp,3
+278,llama-3-1-405b-instruct,llama-3-1-8b-instruct,27688,86189,19,imp,6
+279,llama-3-1-405b-instruct,llama-3-1-8b-instruct,6532,26643,9,crew,2
+280,llama-3-1-8b-instruct,claude-3-5-haiku,10245,26686,11,crew,1
+281,llama-3-1-8b-instruct,claude-3-5-haiku,6169,18422,9,crew,2
+282,llama-3-1-8b-instruct,claude-3-5-haiku,8448,25274,10,crew,3
+283,llama-3-1-8b-instruct,claude-3-5-haiku,245620,286453,40,lim,19
+284,llama-3-1-8b-instruct,claude-3-5-haiku,64079,679275,40,lim,30
+285,llama-3-1-8b-instruct,claude-3-5-sonnet,5478,14790,8,imp,3
+286,llama-3-1-8b-instruct,claude-3-5-sonnet,37947,98647,20,crew,8
+287,llama-3-1-8b-instruct,claude-3-5-sonnet,80993,239551,26,crew,8
+288,llama-3-1-8b-instruct,claude-3-5-sonnet,90131,179296,30,crew,18
+289,llama-3-1-8b-instruct,claude-3-5-sonnet,101283,265258,31,crew,9
+290,llama-3-1-8b-instruct,gemini-flash-1-5,182941,224191,40,lim,12
+291,llama-3-1-8b-instruct,gemini-flash-1-5,169005,141582,40,lim,15
+292,llama-3-1-8b-instruct,gemini-flash-1-5,155316,147533,40,lim,13
+293,llama-3-1-8b-instruct,gemini-flash-1-5,181693,171269,40,lim,29
+294,llama-3-1-8b-instruct,gemini-flash-1-5,35169,38841,16,imp,11
+295,llama-3-1-8b-instruct,gemini-pro-1-5,232404,78998,36,crew,16
+296,llama-3-1-8b-instruct,gemini-pro-1-5,6696,6401,9,crew,2
+297,llama-3-1-8b-instruct,gemini-pro-1-5,18070,14167,15,crew,7
+298,llama-3-1-8b-instruct,gemini-pro-1-5,12117,9431,11,crew,5
+299,llama-3-1-8b-instruct,gemini-pro-1-5,162878,69384,40,lim,17
+300,llama-3-1-8b-instruct,gpt-4o-mini,36188,61069,19,imp,10
+301,llama-3-1-8b-instruct,gpt-4o-mini,5199,10911,7,crew,1
+302,llama-3-1-8b-instruct,gpt-4o-mini,263069,268440,39,imp,20
+303,llama-3-1-8b-instruct,gpt-4o-mini,161065,208146,40,lim,22
+304,llama-3-1-8b-instruct,gpt-4o-mini,156071,301218,40,lim,24
+305,llama-3-1-8b-instruct,gpt-4o,104447,143344,33,imp,21
+306,llama-3-1-8b-instruct,gpt-4o,38613,61447,19,crew,9
+307,llama-3-1-8b-instruct,gpt-4o,89130,203071,30,imp,9
+308,llama-3-1-8b-instruct,gpt-4o,104978,135653,32,crew,25
+309,llama-3-1-8b-instruct,gpt-4o,21723,24857,15,imp,4
+310,llama-3-1-8b-instruct,llama-3-1-405b-instruct,23505,80795,17,crew,6
+311,llama-3-1-8b-instruct,llama-3-1-405b-instruct,7377,18663,8,imp,2
+312,llama-3-1-8b-instruct,llama-3-1-405b-instruct,162908,463018,40,lim,22
+313,llama-3-1-8b-instruct,llama-3-1-405b-instruct,161602,443417,40,lim,23
+314,llama-3-1-8b-instruct,llama-3-1-405b-instruct,81209,404306,40,lim,23
+315,llama-3-1-8b-instruct,llama-3-1-8b-instruct,19031,41846,13,imp,6
+316,llama-3-1-8b-instruct,llama-3-1-8b-instruct,67933,142896,27,crew,6
+317,llama-3-1-8b-instruct,llama-3-1-8b-instruct,42732,51594,15,imp,8
+318,llama-3-1-8b-instruct,llama-3-1-8b-instruct,166912,308687,39,imp,14
+319,llama-3-1-8b-instruct,llama-3-1-8b-instruct,21883,59095,15,imp,4
diff --git a/tournament_analysis.csv b/data/tournament_analysis.csv
similarity index 100%
rename from tournament_analysis.csv
rename to data/tournament_analysis.csv
diff --git a/src/among_them/token_counter.py b/src/among_them/token_counter.py
new file mode 100644
index 0000000..a9477df
--- /dev/null
+++ b/src/among_them/token_counter.py
@@ -0,0 +1,44 @@
+import json
+import os
+import pandas as pd
+
+
+dir = 'data/tournament'
+files = list(os.walk(dir))[0][2]
+
+columns = ["imp_model", "crew_model", "imp_out_tokens", "crew_out_tokens", "rounds", "result", "imp_pretend_count"]
+data = []
+
+for f in files:
+    with open(dir + '/' + f) as file:
+        d = json.load(file)
+        imp_model = f.split(".")[0].split("_")[0]
+        crew_model = f.split(".")[0].split("_")[2]
+        imp_out_tokens, crew_out_tokens = 0, 0
+        rounds = len(d["players"][0]["history"]["rounds"])
+
+        if "_round_limit" in f:
+            res = "lim"
+        elif "Crewmates win!" in d["playthrough"][-1]:
+            res = "crew"
+        else:
+            res = "imp"
+
+        for i in range(5):
+            p = d["players"][i]
+            if p["role"] == "Impostor":
+                imp_out_tokens += p["state"]["token_usage"]["output_tokens"]
+
+                imp_pretend = 1 if "pretended" in p["state"]["action_result"] else 0
+                for round in p["history"]["rounds"]:
+                    if "pretended" in round["action_result"]:
+                        imp_pretend += 1
+            else:
+                crew_out_tokens += p["state"]["token_usage"]["output_tokens"]
+        data.append([imp_model, crew_model, imp_out_tokens, crew_out_tokens, rounds, res, imp_pretend])
+
+
+df = pd.DataFrame(data, columns=columns)
+df.to_csv("token_usage.csv")
+
+print(df)
\ No newline at end of file