player data elo

   ids = dfs["id"].unique()
    # all players:
    elo_frame = {}
    true_skill_frame = {}
    dates = []
    count = 0
    dates_to_ids = {}
    dates = dfs["date"].unique()
    elo_df = dfs[dfs[["id", "date"]].is_unique()][["date", "id"]]
    elo_df = elo_df.with_columns([pl.lit(1200.0).alias("elo"),
                                  pl.lit(true_skill.MU).alias("true_skill_mu"),
                                  pl.lit(true_skill.SIGMA).alias("true_skill_sigma")])
    all_ids = elo_df["id"].unique()
    update_ids = []
    gc.collect()

    dates = dates.sort()
    print(dates)
    missing_ids = set(dfs[~dfs["opp_id"].is_in(dfs["id"])]["opp_id"].to_list())
    for date in dates:
        date_to_ids = dfs.filter(pl.col("date") == date)["id"]
        if date.year >2023:
            break
        for col in date_to_ids:
            cur_elo = elo_df.filter((pl.col("id") == col) & (pl.col("date") < date))
            if cur_elo.shape[0] == 0:
                rating1 = 1200.0
                cur_mu = true_skill.MU
                cur_sigma = true_skill.SIGMA
            else:
                rating1 = cur_elo["elo"][-1]
                cur_mu = cur_elo["true_skill_mu"][-1]
                cur_sigma = cur_elo["true_skill_sigma"][-1]
            player_data = dfs.filter((pl.col("id") == col) & (pl.col("date") == date))
            opp_id = player_data["opp_id"][0]
          
            idx_frame = elo_df.filter((pl.col("id") == opp_id) & (pl.col("date") < date))
            if force and not elo_df.filter(pl.col("id") == opp_id)["date"].contains(date):
                update_ids.append(opp_id)
            if idx_frame.shape[0] > 0:
                rating2 = idx_frame["elo"][-1]
                opp_mu = idx_frame["true_skill_mu"][-1]
                opp_sigma = idx_frame["true_skill_sigma"][-1]
            else:
                rating2 = 1200.0
                opp_mu = true_skill_mma.MU
                opp_sigma = true_skill_mma.SIGMA
            win_e = win_expectation(rating1, rating2)
            result = player_data["outcome"][-1]
            new_rating = elo_rating(
                rating1, result, win_e, cur_elo.filter(pl.col("elo") != 1200).shape[0]
            )

            new_mu = true_skill.get_new_mu(
                cur_mu, opp_mu, cur_sigma, opp_sigma, result
            )
            new_sigma = true_skill.get_new_sigma(
                cur_mu, opp_mu, cur_sigma, opp_sigma, result
            )
            print(date)

            elo_df = elo_df.with_columns([pl.when((pl.col("id") == col) & (pl.col("date") >= date)).then(pl.lit(new_rating)).otherwise(pl.col("elo")).alias("elo"),
                                            pl.when((pl.col("id") == col) & (pl.col("date") >= date)).then(pl.lit(new_mu)).otherwise(pl.col("true_skill_mu")).alias("true_skill_mu"),
                                            pl.when((pl.col("id") == col) & (pl.col("date") >= date)).then(pl.lit(new_sigma)).otherwise(pl.col("true_skill_sigma")).alias("true_skill_sigma")])