Tribes2/Foxox-T2-Player-Ratings
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Cleanup

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This commit is contained in:
John Drake 2025-11-10 23:50:04 -05:00
parent a5fcacafcd
commit cfaf647ab0
1 changed files with 32 additions and 41 deletions
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73
pubstatcruncher.py
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@ -11,6 +11,8 @@ from operator import itemgetter
import glicko2
from more_itertools import pairwise, distinct_combinations
print()
# load file
with open('pubresults.yaml', 'r') as file:
file_contents = yaml.full_load(file)
@ -141,12 +143,6 @@ for player,roles in players_to_roles.items():
any_roles_to_players[role] = list()
any_roles_to_players[role].append(player)
print(first_roles_to_players)
print(any_roles_to_players)
# quit()
player_to_win_count = dict()
player_to_match_count = dict()
@ -158,15 +154,15 @@ trio_to_match_count = dict()
# loop over all matches
for match in file_contents:
print()
print(match['date'], match['mission'])
# print()
# print(match['date'], match['mission'])
winning_team_score = 0
winning_team_name = None
results = match['results']
# match
merged_match_player_results = list()
for team in results:
print('team:', team)
# print('team:', team)
if results[team]['score'] > winning_team_score:
winning_team_score = results[team]['score']
winning_team_name = team
@ -320,64 +316,59 @@ for match in file_contents:
tpglickos[winning_player_tuple[0]].update_player([tpglickos[losing_player_tuple[0]].rating],[tpglickos[losing_player_tuple[0]].rd],[win])
# Sort by glicko ratings and print them out
pwglickolist = list(pwglickos.items())
pwglickolist.sort(key=lambda rating: rating[1].rating, reverse=True)
print('Point Whore Ratings, sorted:\n', [(x[0], str(round(x[1].rating))) for x in pwglickolist])
# # Sort by glicko ratings and print them out
# pwglickolist = list(pwglickos.items())
# pwglickolist.sort(key=lambda rating: rating[1].rating, reverse=True)
# print('Point Whore Ratings, sorted:\n', [(x[0], str(round(x[1].rating))) for x in pwglickolist])
# Sort by glicko ratings and print them out
stpwglickolist = list(stpwglickos.items())
stpwglickolist.sort(key=lambda rating: rating[1].rating, reverse=True)
# print('Single Team Point Whore Ratings, sorted:\n', [(x[0], str(round(x[1].rating))) for x in stpwglickolist])
print('\nSingle Team Point Whore Ratings',"\n".join([ str((x[0], str(round(x[1].rating)), str(round(x[1].rd)))) for x in stpwglickolist]))
# # Sort by glicko ratings and print them out
# stpwglickolist = list(stpwglickos.items())
# stpwglickolist.sort(key=lambda rating: rating[1].rating, reverse=True)
# # print('Single Team Point Whore Ratings, sorted:\n', [(x[0], str(round(x[1].rating))) for x in stpwglickolist])
# print('\nSingle Team Point Whore Ratings',"\n".join([ str((x[0], str(round(x[1].rating)), str(round(x[1].rd)))) for x in stpwglickolist]))
# Sort by glicko ratings and print them out
tpglickolist = list(tpglickos.items())
tpglickolist.sort(key=lambda rating: rating[1].rating, reverse=True)
print('\nTeam Player Ratings, sorted:')
print("\n".join([ str((x[0], str(round(x[1].rating)), str(round(x[1].rd)))) for x in tpglickolist]))
# # Sort by glicko ratings and print them out
# tpglickolist = list(tpglickos.items())
# tpglickolist.sort(key=lambda rating: rating[1].rating, reverse=True)
# print('\nTeam Player Ratings, sorted:')
# print("\n".join([ str((x[0], str(round(x[1].rating)), str(round(x[1].rd)))) for x in tpglickolist]))
print('\nPer role single team point whore ratings:\n')
for role, players in first_roles_to_players.items():
# print('unsorted:',role,players)
players.sort(key=lambda p: stpwglickos[p].rating if p in stpwglickos else 1400, reverse=True)
print('sorted:',role,players)
# print('\nPer role single team point whore ratings:\n')
# for role, players in first_roles_to_players.items():
# # print('unsorted:',role,players)
# players.sort(key=lambda p: stpwglickos[p].rating if p in stpwglickos else 1400, reverse=True)
# print('sorted:',role,players)
# Print conditional probabilities
player_to_win_rate = dict()
for matchkvp in player_to_match_count.items():
# Only use data with at least 10 samples (matches)
if matchkvp[1] < 30:
continue
player_to_win_rate[matchkvp[0]] = player_to_win_count[matchkvp[0]] / matchkvp[1]
player_to_win_rate_sorted = list(player_to_win_rate.items())
player_to_win_rate_sorted.sort(key=lambda p: p[1], reverse=True)
print('Best player win rates:\n','\n'.join([str(x) for x in player_to_win_rate_sorted]))
# print(player_to_match_count)
# print(player_to_win_count)
print('Best (and worst) player win rates:\n','\n'.join([str(x) for x in player_to_win_rate_sorted]))
print()
duo_to_win_rate = dict()
for matchkvp in duo_to_match_count.items():
# Only use data with at least 10 samples (matches)
if matchkvp[1] < 17:
continue
duo_to_win_rate[matchkvp[0]] = duo_to_win_count[matchkvp[0]] / matchkvp[1]
duo_to_win_rate_sorted = list(duo_to_win_rate.items())
duo_to_win_rate_sorted.sort(key=lambda p: p[1], reverse=True)
print('Best duo win rates:\n','\n'.join([str(x) for x in duo_to_win_rate_sorted]))
# print(duo_to_match_count)
# print(duo_to_win_count)
print('Best (and worst) duo win rates:\n','\n'.join([str(x) for x in duo_to_win_rate_sorted]))
print()
trio_to_win_rate = dict()
for matchkvp in trio_to_match_count.items():
# Only use data with at least 10 samples (matches)
if matchkvp[1] < 9:
continue
trio_to_win_rate[matchkvp[0]] = trio_to_win_count[matchkvp[0]] / matchkvp[1]
trio_to_win_rate_sorted = list(trio_to_win_rate.items())
trio_to_win_rate_sorted.sort(key=lambda p: p[1], reverse=True)
print('Best trio win rates:\n','\n'.join([str(x) for x in trio_to_win_rate_sorted]))
# print(trio_to_match_count)
# print(trio_to_win_count)
print('Best (and worst) trio win rates:\n','\n'.join([str(x) for x in trio_to_win_rate_sorted]))
print()