Forecasting
Tournament Predictions
Every probability is derived from 8,000 Monte Carlo simulations of the remaining tournament: each run completes the group stage, resolves the best third-placed teams, seeds the knockout bracket, and plays out every tie via ELO win expectancy.
Championship Probability
Top 12 · % of simulations won
Stage-Reach Probabilities
How far each contender advances
Over- & Under-Performers
Title probability vs pre-tournament market
| Team | Pre-WC | Now | Δ |
|---|---|---|---|
| 🇪🇸Spain | 10.5% | 100.0% | +89.5% |
| 🇸🇪Sweden | 0.0% | 0.0% | +0.0% |
| 🇨🇿Czechia | 0.0% | 0.0% | +0.0% |
| 🇹🇷Türkiye | 0.0% | 0.0% | +0.0% |
| 🇧🇦Bosnia & Herzegovina | 0.0% | 0.0% | +0.0% |
| 🇩🇪Germany | 8.5% | 0.0% | -8.5% |
| 🏴England | 9.0% | 0.0% | -9.0% |
| 🇧🇷Brazil | 10.5% | 0.0% | -10.5% |
| 🇫🇷France | 11.0% | 0.0% | -11.0% |
| 🇦🇷Argentina | 13.0% | 0.0% | -13.0% |
Golden Boot ProjectionxG (expected goals) measures chance quality — how likely each shot was to score. We blend it with goals so far to project a final tally, so lucky/unlucky finishing regresses. Full explainer →
Live standings + finishing-adjusted projection · by region
| # | Player | G | xG | Proj. | Win Boot |
|---|---|---|---|---|---|
| 1 | 🇫🇷Kylian Mbappé | 10 | 0 | 12.8 | 47% |
| 2 | 🇦🇷Lionel Messi | 8 | 0 | 11.1 | 26% |
| 3 | 🇳🇴Erling Haaland | 7 | 0 | 9.2 | 10% |
| 4 | 🏴Jude Bellingham | 7 | 0 | 8.9 | 8% |
| 5 | 🏴Harry Kane | 6 | 0 | 7.8 | 4% |
| 6 | 🇫🇷Ousmane Dembélé | 6 | 0 | 7.7 | 3% |
| 7 | 🇪🇸Mikel Oyarzabal | 5 | 0 | 7 | 2% |
| 8 | 🇧🇷Vinícius Júnior | 4 | 0 | 4.9 | 0% |
| 9 | 🇲🇽Julián Quiñones | 4 | 0 | 4.9 | 0% |
| 10 | 🇸🇳Ismaïla Sarr | 4 | 0 | 4.5 | 0% |
| 11 | 🇨🇭Johan Manzambi | 3 | 0 | 4.2 | 0% |
| 12 | 🇦🇷Lautaro Martínez | 3 | 0 | 4.2 | 0% |