> world_cup_2026 · forecast
Bawler runs the entire 48-team tournament 10,000 times, drawing every match outcome from our Poisson model on rolling xG, FIFA ranking, recent form, and home advantage. The percentages below are how often each nation reached each round across those simulations.
Updated every morning at 07:30 UK, then cryptographically anchored to the Bitcoin blockchain before kickoff — so the forecast at the top of each tournament day is provably the one we committed to before the matches were played.
Latest run: Friday, 19 June 2026
> contenders.top(10)
Probability of reaching each knockout round, ordered by P(Winner). Note: the field is genuinely open this time — no nation breaks 5%, which reflects the parity in the model and the new 48-team format adding two extra knockout rounds.
| # | Team | R16 | QF | SF | Final | Winner |
|---|---|---|---|---|---|---|
| 1 | 48.5% | 29.2% | 17.1% | 10.0% | 5.58% | |
| 2 | 47.4% | 27.8% | 16.2% | 9.68% | 5.42% | |
| 3 | 47.0% | 28.3% | 16.6% | 9.64% | 5.19% | |
| 4 | 47.0% | 27.8% | 16.1% | 9.13% | 5.11% | |
| 5 | 45.8% | 26.7% | 15.4% | 8.80% | 5.03% | |
| 6 | 45.8% | 26.5% | 15.1% | 8.76% | 4.74% | |
| 7 | 46.1% | 27.0% | 15.5% | 8.46% | 4.31% | |
| 8 | 44.0% | 25.2% | 13.9% | 7.83% | 4.17% | |
| 9 | 42.3% | 24.6% | 13.9% | 7.77% | 4.06% | |
| 10 | 48.8% | 27.0% | 14.8% | 7.96% | 4.02% |
> groups.advancement()
Top two from each of the 12 groups advance automatically. The eight best third-placed teams across all groups join them in the Round of 32. Each row shows the probability a team finishes top-2 in their group.
> all_48()
Click any team for the deep-dive page with its group fixtures, model breakdown, and round-by-round path.
| # | Team | Top 2 | R16 | QF | SF | Final | Winner |
|---|---|---|---|---|---|---|---|
| 1 | 66.0% | 48.5% | 29.2% | 17.1% | 10.0% | 5.58% | |
| 2 | 64.9% | 47.4% | 27.8% | 16.2% | 9.68% | 5.42% | |
| 3 | 63.6% | 47.0% | 28.3% | 16.6% | 9.64% | 5.19% | |
| 4 | 62.2% | 47.0% | 27.8% | 16.1% | 9.13% | 5.11% | |
| 5 | 62.5% | 45.8% | 26.7% | 15.4% | 8.80% | 5.03% | |
| 6 | 62.1% | 45.8% | 26.5% | 15.1% | 8.76% | 4.74% | |
| 7 | 63.6% | 46.1% | 27.0% | 15.5% | 8.46% | 4.31% | |
| 8 | 60.7% | 44.0% | 25.2% | 13.9% | 7.83% | 4.17% | |
| 9 | 55.7% | 42.3% | 24.6% | 13.9% | 7.77% | 4.06% | |
| 10 | 75.2% | 48.8% | 27.0% | 14.8% | 7.96% | 4.02% | |
| 11 | 63.3% | 44.9% | 25.0% | 14.3% | 7.72% | 3.98% | |
| 12 | 60.4% | 43.8% | 25.2% | 13.7% | 7.68% | 3.91% | |
| 13 | 64.6% | 45.8% | 25.1% | 13.4% | 7.31% | 3.86% | |
| 14 | 62.9% | 44.3% | 24.8% | 13.2% | 7.04% | 3.63% | |
| 15 | 73.8% | 47.6% | 25.4% | 13.1% | 6.44% | 3.49% | |
| 16 | 73.8% | 47.2% | 25.7% | 13.9% | 7.03% | 3.44% | |
| 17 | 60.6% | 40.1% | 20.8% | 10.2% | 5.03% | 2.60% | |
| 18 | 50.8% | 37.7% | 19.5% | 10.2% | 5.23% | 2.54% | |
| 19 | 55.8% | 39.2% | 20.5% | 10.5% | 5.22% | 2.54% | |
| 20 | 60.4% | 39.7% | 20.2% | 10.1% | 4.62% | 2.26% | |
| 21 | 58.4% | 39.6% | 20.1% | 9.95% | 4.37% | 2.16% | |
| 22 | 55.5% | 34.8% | 16.3% | 7.72% | 3.55% | 1.82% | |
| 23 | 58.1% | 37.9% | 18.5% | 8.54% | 3.85% | 1.71% | |
| 24 | 47.5% | 33.2% | 16.4% | 7.77% | 3.53% | 1.51% | |
| 25 | 46.0% | 30.9% | 14.3% | 6.53% | 2.86% | 1.45% | |
| 26 | 68.1% | 39.9% | 18.2% | 8.05% | 3.31% | 1.29% | |
| 27 | 47.4% | 32.8% | 16.0% | 7.22% | 3.06% | 1.24% | |
| 28 | 56.1% | 35.2% | 15.7% | 6.51% | 2.67% | 1.17% | |
| 29 | 51.8% | 32.8% | 14.7% | 6.41% | 2.67% | 1.09% | |
| 30 | 47.9% | 29.8% | 12.5% | 5.39% | 2.18% | 0.81% | |
| 31 | 48.8% | 29.2% | 12.5% | 4.75% | 1.79% | 0.76% | |
| 32 | 49.7% | 30.5% | 12.5% | 4.99% | 1.88% | 0.71% | |
| 33 | 43.3% | 28.2% | 12.0% | 4.84% | 1.79% | 0.66% | |
| 34 | 47.1% | 28.6% | 11.4% | 4.20% | 1.50% | 0.54% | |
| 35 | 39.4% | 24.4% | 9.64% | 3.74% | 1.45% | 0.45% | |
| 36 | 30.5% | 18.9% | 7.23% | 2.74% | 1.05% | 0.44% | |
| 37 | 28.7% | 17.6% | 6.22% | 2.20% | 0.87% | 0.32% | |
| 38 | 31.3% | 19.1% | 6.70% | 2.34% | 0.72% | 0.27% | |
| 39 | 39.4% | 21.9% | 7.84% | 2.52% | 0.74% | 0.27% | |
| 40 | 32.0% | 20.3% | 7.37% | 2.69% | 0.88% | 0.26% | |
| 41 | 31.6% | 17.5% | 6.05% | 2.17% | 0.74% | 0.22% | |
| 42 | 24.9% | 16.0% | 6.03% | 1.91% | 0.60% | 0.17% | |
| 43 | 21.9% | 13.0% | 4.24% | 1.37% | 0.41% | 0.17% | |
| 44 | 29.2% | 18.0% | 6.63% | 2.37% | 0.68% | 0.17% | |
| 45 | 30.3% | 16.5% | 5.59% | 1.71% | 0.44% | 0.13% | |
| 46 | 25.3% | 14.2% | 4.63% | 1.36% | 0.30% | 0.12% | |
| 47 | 26.6% | 15.1% | 5.17% | 1.78% | 0.44% | 0.12% | |
| 48 | 20.2% | 11.3% | 3.47% | 1.00% | 0.29% | 0.09% |
> how_we_call_it()
For each of the 2,256 possible matchups in the tournament, Bawler's model produces a full Win/Draw/Loss probability triple from rolling xG, FIFA ranking, recent form, opponent strength, and a small home-advantage prior.
We then simulate the entire 48-team tournament 10,000 times — group stage, Round of 32, Round of 16, Quarter-finals, Semi-finals, Final. Group standings are decided on points, goal difference, then goals scored. Knockout draws are split between extra time and penalties with a small bias toward the pre-match favourite (~55%, matching historical shootout data).
Why no team is above 5%. The field is unusually open this year — FIFA's expanded 48-team format adds an extra knockout round (Round of 32) compared to the 2022 tournament, which means even the strongest contender has to win six knockouts in a row. Six 65% favourites still multiply to just 7.5%, and most knockouts are tighter than that. Bookmakers compress this with overround and the “favourite-longshot bias” — our forecast doesn't, so it reads as flatter. The probabilities reflect genuine uncertainty rather than confidence theatre.
Why you can trust the numbers above didn't change after the fact. Every morning at 07:30 UK we snapshot the day's forecast and hash-anchor it to the Bitcoin blockchain via OpenTimestamps. The proof is published before any of that day's matches kick off, and anyone can independently verify, offline, that we couldn't have edited the numbers after results came in. See /verify for the proof files and the verification walkthrough.