xG Model vs Market
The ultimate edge finder. Input your Expected Goals (xG) estimates and compare against real bookmaker odds. Find mispriced 1X2 markets using Poisson-simulated fair probabilities.
| Outcome | Model Prob | Market Prob | Edge | Fair Odds | Market Odds | Verdict |
|---|---|---|---|---|---|---|
| Home Win | 49.0% | 51.9% | -3.0% | 2.04 | 1.85 | pass |
| Draw | 24.9% | 21.4% | +3.5% | 4.02 | 3.60 | BET |
| Away Win | 26.2% | 26.7% | -0.5% | 3.82 | 4.50 | pass |
Best Value: DRAW
Edge: +3.5% vs market — Fair odds 4.02 vs offered 3.60. Modest edge. Half-Kelly recommended.
How Edge Detection Works
1. Poisson Simulation
Your xG inputs feed a Poisson model: P(h:a) = Poisson(h, λH) × Poisson(a, λA). Aggregate across all scorelines to get 1X2, Over/Under, and BTTS probabilities.
2. Strip Market Overround
Bookmaker odds include vig. We strip it proportionally: true implied prob = (1/odds) / Σ(1/odds). This gives fair market probabilities for comparison.
3. Edge = Model − Market
Positive edge = your model thinks the outcome is more likely than the market. Edge > 3% is typically actionable with proper Kelly sizing. Edge < 0% = no bet.
Ready to bet? Try these bookmakers
Use the math first, then compare regulated books in your region. A small odds difference can matter more than a bigger stake.
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