Champion probability — 10,000 runs of the World Cup
We ran the 2026 World Cup ten thousand times. For matches that have already been played, the actual result is locked in. Remaining fixtures and every knockout tie are simulated from each team's current strength. The board refreshes hourly — every result tilts it.
Who will win the World Cup 2026?
Who lifts the trophy?
Path through the tournament — top 24
to see all rounds
| # | TEAM | R16 | QF | SF | FINAL | WIN |
|---|---|---|---|---|---|---|
| 1 | France | 98% | 66% | 46% | 30.0% | 17.1% |
| 2 | Spain | 84% | 76% | 42% | 24.9% | 14.5% |
| 3 | England | 89% | 60% | 37% | 22.4% | 13.0% |
| 4 | Argentina | 84% | 64% | 38% | 18.3% | 10.0% |
| 5 | Brazil | 86% | 57% | 37% | 18.8% | 8.9% |
| 6 | Belgium | 72% | 54% | 28% | 12.9% | 5.9% |
| 7 | Portugal | 53% | 35% | 20% | 9.3% | 5.0% |
| 8 | Netherlands | 47% | 31% | 17% | 8.0% | 4.6% |
| 9 | United States | 83% | 35% | 16% | 7.7% | 3.6% |
| 10 | Germany | 54% | 43% | 18% | 9.0% | 3.6% |
| 11 | Mexico | 63% | 24% | 14% | 7.2% | 3.2% |
| 12 | Croatia | 46% | 37% | 15% | 7.0% | 2.6% |
| 13 | Morocco | 82% | 32% | 15% | 5.9% | 2.5% |
| 14 | Colombia | 64% | 27% | 14% | 5.6% | 2.1% |
| 15 | Switzerland | 71% | 25% | 8% | 2.9% | 0.9% |
| 16 | Senegal | 37% | 11% | 5% | 2.1% | 0.8% |
| 17 | Canada | 90% | 31% | 10% | 2.8% | 0.6% |
| 18 | Japan | 36% | 11% | 4% | 1.2% | 0.4% |
| 19 | Austria | 28% | 14% | 5% | 1.2% | 0.3% |
| 20 | Ecuador | 29% | 9% | 3% | 0.9% | 0.2% |
| 21 | Australia | 74% | 16% | 3% | 0.7% | 0.2% |
| 22 | Norway | 16% | 11% | 2% | 0.5% | 0.1% |
| 23 | Egypt | 16% | 6% | 1% | 0.2% | 0.1% |
| 24 | Sweden | 17% | 3% | 1% | 0.1% | 0.0% |
Method — updated every hour
Each team's current strength and the quality of its opponents — the same calibrated prediction model behind the predictions hub.
Every group fixture sampled 10,000 times. Played matches lock in the real result. Standings: points → goal difference → goals scored → random tiebreaker. Top-2 + 8 best 3rd-placed advance.
R32 → R16 → QF → SF → Final. Draws collapsed by model probability ratio. Pairings re-randomised per round (bracket-fair abstraction) until FIFA's exact seeding plan is final.
Current run: 72 real results locked in, remainder sampled from model. Re-runs hourly via ISR.
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Common questions about the Monte Carlo board
How does the World Cup 2026 simulator work?›
We run the tournament from current state forward 10,000 times. Each run samples every fixture independently from our Onside AI. For matches already played, the actual result is locked in with certainty. Aggregating across runs gives each team a probability of reaching every round and winning the trophy.
Which team has the best chance of winning World Cup 2026?›
The top tier is tightly packed — the leading contenders are separated by barely a percentage point, and no team is above ~13%. These probabilities refresh hourly and shift with every result. The live top-24 board above shows the current order and exact percentages.
Why 10,000 simulations specifically?›
10k is far past the convergence threshold for a 32-team bracket — per-team probabilities stabilise within a fraction of a percent. The bigger uncertainty is in the per-match model, not the sample size. We keep the 10k framing because "we ran the World Cup ten thousand times" is the line that earns links.
Does the simulator use actual FIFA bracket structure?›
Until FIFA publishes the exact 2026 R32 mapping (1A vs 3rd-place, 1C vs 3rd-place, etc.), we use a "fair re-pair per round" abstraction — surviving teams randomly matched at each KO round. This is statistically valid for aggregate champion probability but slightly off on specific path lengths. We will swap to the real bracket the moment FIFA fixes it.
When does the simulator update?›
Hourly via Next.js dynamic rendering. Each visit re-runs the 10,000 simulations against the latest results, so the board self-sharpens as games are played. By the SF round, only two matches are sampled — champion probabilities become very precise.
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