Match Model
A prediction model for the 2026 World Cup that earns its keep only if it can out-read the market. Every match-day, its probabilities are placed side by side with bookmaker odds — and the gap is tracked honestly, win or lose.
Decimal odds for the modelled outcome against the bookmaker line. A positive edge means the model rates the outcome more likely than the market implies.
| Stage | Fixture | Model | Book | Edge | Result |
|---|---|---|---|---|---|
| Group A | Mexico v Croatia | 2.05 | 2.20 | +0.15 | |
| Group D | USA v Wales | 1.92 | 1.85 | −0.07 | |
| Group E | Spain v Japan | 1.58 | 1.66 | +0.08 | |
| Group G | Brazil v Serbia | 1.49 | 1.55 | +0.06 | |
| Round of 16 | England v Senegal | 1.74 | 1.80 | +0.06 | |
| Quarter-final | France v Argentina | 2.38 | 2.30 | −0.08 |
Illustrative sample · full tournament ledger tracked live.
Poisson goal model
Each side's expected goals are modelled as independent Poisson processes; the outer product gives a full scoreline probability grid, from which 1X2, over/under and correct-score markets are derived.
Team-strength vectors
Rolling attack and defence strengths are encoded as decayed form vectors, weighting recent matches more heavily and adjusting for opponent quality rather than raw results.
Tournament effects
Group and knockout structure, rest days and host advantage are modelled explicitly — a neutral-venue tournament behaves differently from a league season.
Calibration
Predicted probabilities are calibrated against historical outcomes, so a stated 60% genuinely resolves true roughly 60% of the time.