calc_elo.py

import json, csv

K = 32  # ELO constant (adjust as needed)

def expected_win_probability(rating1, rating2):
    return 1 / (1 + 10 ** ((rating2 - rating1) / 400))

with open("league_starting_elo_map_v1.csv", "r") as f:
    starting_elos = list(csv.reader(f))[1:]

with open("league_team_map.json") as f:
    league_team_map = json.load(f)

# Initialize elo based on league
elo_ratings = {} 
for leagueIdName, teams in league_team_map.items():
    starting_elo = int(next(elo[1] for elo in starting_elos if elo[0].split("|")[0] == leagueIdName.split("|")[0]))
    for team in teams:
        if team in elo_ratings:
            if elo_ratings[team] > starting_elo: continue
        elo_ratings[team] = starting_elo


# Read the CSV file and update ELO ratings
with open("game_results_v1.csv", mode='r') as file:
    reader = csv.reader(file)
    next(reader)  # Skip the header row
    for row in reader:
        team1_id = row[1]
        team2_id = row[2]
        winner_id = row[3]
        if (team1_id not in elo_ratings or team2_id not in elo_ratings): continue

        # Calculate expected win probabilities
        expected_win1 = expected_win_probability(elo_ratings[team1_id], elo_ratings[team2_id])
        expected_win2 = expected_win_probability(elo_ratings[team2_id], elo_ratings[team1_id])

        # Update ELO ratings based on the winner
        if winner_id == team1_id:
            elo_ratings[team1_id] += K * (1 - expected_win1)
            elo_ratings[team2_id] += K * (0 - expected_win2)
        elif winner_id == team2_id:
            elo_ratings[team1_id] += K * (0 - expected_win1)
            elo_ratings[team2_id] += K * (1 - expected_win2)

# Create elo rating rows and sort
elo_list = [[team_id, elo] for team_id, elo in elo_ratings.items()]
elo_list.sort(key=lambda x: x[1], reverse=True)

with open("esports-data/teams.json", encoding="utf-8") as f:
    team_data = json.load(f)
    for row in elo_list:
        team_id = row[0]

        # Add league column
        highest_starting_elo = -1
        highest_starting_league = None
        for league_id_name, team_ids in league_team_map.items():
            if team_id in team_ids:
                starting_elo = int(next(elo[1] for elo in starting_elos if elo[0].split("|")[0] == league_id_name.split("|")[0]))
                if starting_elo > highest_starting_elo:
                    highest_starting_elo = starting_elo
                    highest_starting_league = league_id_name
        row.append(highest_starting_league)

        # Add name column
        for team in team_data:
            if team["team_id"] == team_id:
                row.append(team["name"])
                break


with open("elo_ratings.csv", "w", newline="", encoding="utf-8") as f:
    writer = csv.writer(f)
    writer.writerow(["team_id", "elo", "league", "name"])
    writer.writerows(elo_list)

print(f'ELO ratings saved to elo_rating.csv')

league_starting_elo_map_v1.csv