🏆 FIFA World Cup 2026
Live version (matches already played are fixed) · Poisson (Dixon-Coles) + Elo · 1,000,000 Monte Carlo simulations · click a team or try the Match Lab
Validated on ~4500 unseen matches: 60% accuracy · RPS 0.172 (naive 0.228) — bookmaker level.
21.0%
17.3% 📅 Today's matches kickoffs in WEST (UTC+1)
📊 Odds over time since kickoff
Biggest movers:
| Team | Before | Now | Δ |
|---|---|---|---|
| Spain | 13.4% | 17.3% | +3.9 |
| Argentina | 21.6% | 21.0% | -0.6 |
| Belgium | 1.9% | 1.4% | -0.5 |
| France | 9.4% | 9.1% | -0.3 |
| Germany | 5.6% | 5.3% | -0.3 |
| Colombia | 4.9% | 4.6% | -0.3 |
Most likely bracket the favourites' path
Ranking & path click a row
The 12 groups live standings · who advances
Sorted by points from games already played. The figure on the right is the model's chance each team reaches the knockouts — it already accounts for the 8-best-third-placed-teams rule. Green = very likely, red = very unlikely.
Group-stage matches times in WEST (UTC+1)
📈 Extra analysis
🆚 Match Lab head-to-head, live
🏆 Build your World Cup you decide
1. Set the score of every remaining group match (−/+ the goals, from the model's prediction); the tables and who qualifies update live.
2. Now the knockouts — the model picks each winner, but tap the other team to send your pick through, all the way to your champion.
🎲 Roll a tournament one full simulation
One possible World Cup — group tables, every knockout result and the champion. Roll again for another timeline.
✅ Results so far predicted vs actual
😱 Biggest surprises model's worst calls
🏅 Model vs FIFA ranking does the model agree?
🎯 Does it actually work? track record
The honest test: for every major tournament since 2002, the model is retrained on only what was known before that tournament kicked off and then predicts it blind — exactly how you'd have used it in real time. That's 2,691 matches across 67 editions (World Cups, Euros, Copa América, Nations League, Asian & African Cups, Gold Cups). Verdict: 56% of results called correctly (RPS 0.190) vs the naive base rate's 44% (0.231).
| Competition | Matches | Model | Naive | RPS |
|---|---|---|---|---|
| UEFA Nations League | 658 | 54% | 43% | 0.195 |
| Africa Cup of Nations | 493 | 51% | 43% | 0.189 |
| FIFA World Cup | 422 | 58% | 44% | 0.197 |
| Gold Cup | 340 | 64% | 53% | 0.175 |
| UEFA Euro | 246 | 50% | 38% | 0.207 |
| AFC Asian Cup | 230 | 61% | 44% | 0.180 |
| Copa América | 222 | 54% | 45% | 0.186 |
| Confederations Cup | 80 | 68% | 44% | 0.164 |
And zooming in on two tournaments the model had never seen when it was trained:
👟 Golden Boot top scorer
⚽ Anatomy of a goal every international goal
🟨 Discipline cards so far
📉 Elo through history drag the year
🕰️ Historical facts 1872–2026
Biggest win ever: Australia 31-0 American Samoa (2001-04-11) · top international scorer: Cristiano Ronaldo (121 goals) · 49,443 matches, 145,323 goals.
Biggest upsets ever (underdog won, by Elo):
| Year | Match | Tournament | Δelo |
|---|---|---|---|
| 1980 | Luxembourg 3-2 South Korea | Friendly | +770 |
| 2009 | Bolivia 2-1 Brazil | FIFA World Cup qualifica | +536 |
| 2016 | Georgia 1-0 Spain | Friendly | +526 |
| 2023 | Kazakhstan 3-2 Denmark | UEFA Euro qualification | +522 |
| 2007 | Equatorial Guinea 1-0 Cameroon | African Cup of Nations q | +520 |
| 2010 | Niger 1-0 Egypt | African Cup of Nations q | +515 |
👟 Shooting first wins 53.1% of shootouts · penalty kings: Padania 100% · Indonesia 91% · Ethiopia 88% · Guinea 80%. ⚽ Goals/match in the 2020s: 2.71 · home wins in the 2020s: 51.1%.
⚔️ Beat the Machine you vs the model
Predict the upcoming matches — tap the model's call to fill it in, or set your own with −/+. Locked at kickoff. Points stack up: ✅ right result +10 · ⚽ each team's exact goals +5 · 📏 goal difference +5 · 🎯 exact score +5 (perfect = 30). The model plays too — can you beat it? Sign in with Google to make your picks, choose a username and climb the global leaderboard.
Data-driven model, just for fun. ⚽ Data: International football results 1872–2026.