Simulate Bets

get_ml_bet_winnings.py

def get_ml_bet_winnings(ml_odds, bet_amount):
    if ml_odds < 0:
        returns = (-100.0 / ml_odds) * bet_amount
    else:
        returns = (bet_amount / 100.0) * ml_odds
    return returns

simulate_bets.py

# Function that simulates a betting strategy

def simulate_bets(dataset_df=df_pin, bet_amount=100, win_prob_threshold=0.5):
    total_profit = 0
    all_winnings = []
    running_profits = []

    df_generator = dataset_df.iterrows()
    for (i, row1), (j, row2) in zip(df_generator, df_generator):
        ### 1. Determine who to bet on for this game
        t1_ml = row1['ml_PIN']
        t2_ml = row2['ml_PIN']
        t1_score = row1['score']
        t2_score = row2['score']
        t1_win_prob = row1['win_prob_norm_PIN']
        t2_win_prob = row2['win_prob_norm_PIN']

        # If any odds are missing, just skip the game
        if pd.isnull(t1_ml) or pd.isnull(t2_ml):
            continue

        if t1_win_prob < win_prob_threshold:
            placed_bet_on = 1
            bet_ml = t1_ml
        elif t2_win_prob <= win_prob_threshold:
            placed_bet_on = 2
            bet_ml = t2_ml
        else:
            # Not a favorable bet. Skip to next game
            continue

        ### 2. Deterimine if we won or lost this bet
        if t1_score > t2_score:
            game_winner = 1
        elif t2_score > t1_score:
            game_winner = 2
        else:
            # Throw out any games missing scores (shouldn't be any)
            continue
        
        is_win = game_winner == placed_bet_on

        ### 3. Calculate winnings from this bet

        # If favorite lost, then deduct bet from net profits
        if is_win is False:
            winnings = -bet_amount

        # If favorite won, then add winnings to net profits
        if is_win is True:
            winnings = get_ml_bet_winnings(bet_ml, bet_amount)

        ### 4. Record winnings and update total profits
        total_profit += winnings
        all_winnings.append(winnings)
        running_profits.append(total_profit)

    return total_profit, all_winnings, running_profits