Simulate FIFA World Cup 2026 fixtures using our customized Poisson model. Select teams to load pre-calculated xG strength configurations, fine-tune properties, and find value edges against bookmakers.
Grid values indicate the joint probability of the exact scoreline. Darker/brighter background indicates higher likelihood.
| A ↓ / B → | 0 | 1 | 2 | 3 | 4 | 5 |
|---|---|---|---|---|---|---|
| 0 | 3.4% | 5.7% | 4.7% | 2.6% | 1.1% | 0.4% |
| 1 | 5.9% | 9.8% | 8.1% | 4.4% | 1.8% | 0.6% |
| 2 | 5.1% | 8.4% | 6.9% | 3.8% | 1.6% | 0.5% |
| 3 | 2.9% | 4.8% | 4.0% | 2.2% | 0.9% | 0.3% |
| 4 | 1.3% | 2.1% | 1.7% | 0.9% | 0.4% | 0.1% |
| 5 | 0.4% | 0.7% | 0.6% | 0.3% | 0.1% | 0.0% |
Sports modeling services and syndicates rely on the Poisson distribution to project football scorelines. The Poisson model expresses the probability of a given number of events (goals) occurring in a fixed interval of time (90 minutes) if these events occur with a known constant rate (Expected Goals, or xG) and independently of the time since the last event.
For example, if Argentina has an attack rating of 2.15 and France has a defense rating of 0.80, the expected goals for Argentina in a head-to-head match is λ = 2.15 × 0.80 = 1.72. The simulator calculates the probability of each goal count for both teams and multiplies them to populate the score matrix.