Identifying Arbitrage Opportunities#

An arbitrage bet (or “arb”) is a risk-free opportunity. It exists when you can bet on all outcomes of a single event across different bookmakers and guarantee a profit, because their odds are misaligned. These are rare but highly valuable.

The find_arbitrage_opportunities Function#

This function scans lists of odds from multiple bookmakers for the same event to find these risk-free opportunities.

penaltyblog.betting.find_arbitrage_opportunities(
    bookmaker_odds_list: List[List[float]],
    outcome_labels: List[str] = None
) -> ArbitrageResult

Parameters#

  • bookmaker_odds_list: A list of lists. Each inner list represents one bookmaker’s odds for all outcomes of an event.

  • outcome_labels: Optional names for the outcomes (e.g., [“Home”, “Away”]).

Returns (ArbitrageResult)#

  • has_arbitrage (bool): True if a risk-free opportunity exists.

  • guaranteed_return (float): The guaranteed profit as a percentage of your total stake.

  • best_odds (List[float]): The best odds found for each outcome across all bookmakers.

  • best_bookmakers (List[int]): The index of the bookmaker offering the best odds for each outcome.

  • stake_percentages (List[float]): The percentage of your total stake to place on each outcome to guarantee the profit.

Usage Example#

import penaltyblog as pb

# Odds for a soccer match (Home Win, Draw, Away Win) from three different bookmakers
# Each inner list represents one bookmaker's odds for [Home, Draw, Away]
odds_data = [
    [2.80, 3.50, 3.10],  # Bookmaker 1
    [3.10, 3.40, 2.90],  # Bookmaker 2
    [3.00, 3.20, 3.00],  # Bookmaker 3
]

# Define the labels for the outcomes
outcome_labels = ["Home Win", "Draw", "Away Win"]

arb_result = pb.betting.find_arbitrage_opportunities(odds_data, outcome_labels)

if arb_result.has_arbitrage:
    print("Arbitrage opportunity found!")
    print(f"Guaranteed Return on Investment: {arb_result.guaranteed_return:.2%}")
    print("-" * 20)

    # The function tells you exactly where to bet and how much to stake
    for i, label in enumerate(arb_result.outcome_labels):
        stake_pct = arb_result.stake_percentages[i]
        best_odd = arb_result.best_odds[i]
        # Adding 1 to the index to make it human-readable (Bookmaker 1, 2, 3)
        bookie_idx = arb_result.best_bookmakers[i] + 1

        print(f"Bet {stake_pct:.2%} on {label} at odds {best_odd} with Bookmaker {bookie_idx}")
else:
    print("No arbitrage opportunity found.")

Arbitrage opportunity found!
Guaranteed Return on Investment: 7.43%
--------------------
Bet 34.65% on Home Win at odds 3.1 with Bookmaker 2
Bet 30.69% on Draw at odds 3.5 with Bookmaker 1
Bet 34.65% on Away Win at odds 3.1 with Bookmaker 1

Simple Expected Value Calculation#

If you don’t need the full analysis from identify_value_bet and just want a quick Expected Value (EV) calculation, you can use this lightweight utility function.

penaltyblog.betting.calculate_bet_value(
    bookmaker_odds: float,
    estimated_probability: float
) -> float

import penaltyblog as pb

# 60% chance at odds of 2.0
ev = pb.betting.calculate_bet_value(2.0, 0.6)
print(f"Expected Value (per £1 staked): £{ev:.2f}")

Expected Value (per £1 staked): £0.20