Thursday, June 11, 2026
Friday, June 12, 2026
Saturday, June 13, 2026 TODAY
Sunday, June 14, 2026
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Tuesday, June 16, 2026
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Thursday, June 18, 2026
Friday, June 19, 2026
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Wednesday, July 1, 2026
Thursday, July 2, 2026
Friday, July 3, 2026
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Monday, July 6, 2026
Tuesday, July 7, 2026
Thursday, July 9, 2026
Friday, July 10, 2026
Saturday, July 11, 2026
Sunday, July 12, 2026
Tuesday, July 14, 2026
Wednesday, July 15, 2026
Sunday, July 19, 2026
📋 Projected Group Winners
🗓️ Projected Knockout Bracket
Round of 32 16 matches
Round of 16 8 matches
Quarter-Finals 4 matches
Semi-Finals 2 matches
Final 1 matches
🔍 Match Insights
🎯 Biggest Upsets
🏟️ Host Nation Advantage Monitor
| # | Team | P | W | D | L | Pts | Exp. W | Δ |
|---|---|---|---|---|---|---|---|---|
| 1 | USA | 0 | 0 | 0 | 0 | 0 | — | — |
| 2 | Mexico | 1 | 1 | 0 | 0 | 3 | 0.79 | +0.21 |
| 3 | Canada | 1 | 0 | 1 | 0 | 1 | 0.59 | -0.59 |
🔥 Group Stage — Elo Strength Map
📈 Tournament Progression — Top 12 Survival Curves
🏆 World Cup Prediction
| # | Team | Group | R16 | Final | WC 🏆 |
|---|---|---|---|---|---|
| 1 | Spain | 100% | 81% | 34.5% | 24.2% |
| 2 | Argentina | 99% | 76% | 26.8% | 17.3% |
| 3 | France | 97% | 70% | 18.9% | 10.4% |
| 4 | England | 98% | 67% | 14.6% | 7.3% |
| 5 | Brazil | 97% | 63% | 10.7% | 4.9% |
| 6 | Portugal | 96% | 61% | 10.3% | 4.7% |
| 7 | Colombia | 95% | 61% | 9.8% | 4.7% |
| 8 | Ecuador | 98% | 57% | 7.1% | 3.0% |
| 9 | Netherlands | 95% | 57% | 7.1% | 2.8% |
| 10 | Germany | 97% | 56% | 6.3% | 2.8% |
| 11 | Mexico | 97% | 55% | 5.6% | 2.2% |
| 12 | Croatia | 95% | 53% | 5.4% | 2.1% |
| 13 | Japan | 93% | 51% | 4.8% | 1.8% |
| 14 | Norway | 89% | 50% | 5.0% | 1.8% |
| 15 | Turkey | 87% | 48% | 5.0% | 1.6% |
| 16 | Switzerland | 98% | 52% | 4.4% | 1.5% |
| 17 | Belgium | 96% | 51% | 4.1% | 1.5% |
| 18 | Uruguay | 94% | 50% | 4.2% | 1.5% |
| 19 | Senegal | 82% | 40% | 2.1% | 0.7% |
| 20 | Morocco | 87% | 39% | 1.7% | 0.5% |
| 21 | Canada | 95% | 41% | 1.6% | 0.5% |
| 22 | Austria | 79% | 36% | 1.8% | 0.4% |
| 23 | Paraguay | 75% | 34% | 1.5% | 0.4% |
| 24 | South Korea | 88% | 35% | 1.0% | 0.2% |
| 25 | United States | 63% | 26% | 0.9% | 0.2% |
| 26 | Scotland | 78% | 31% | 0.9% | 0.2% |
| 27 | Iran | 83% | 32% | 0.8% | 0.2% |
| 28 | Algeria | 62% | 25% | 0.7% | 0.2% |
| 29 | Australia | 55% | 22% | 0.6% | 0.1% |
| 30 | Czechia | 67% | 21% | 0.3% | 0.1% |
| 31 | Panama | 68% | 24% | 0.3% | 0.1% |
| 32 | Sweden | 55% | 18% | 0.3% | 0.1% |
| 33 | Egypt | 64% | 20% | 0.2% | 0.1% |
| 34 | Ivory Coast | 62% | 19% | 0.2% | 0.0% |
| 35 | Uzbekistan | 50% | 17% | 0.2% | 0.0% |
| 36 | Bosnia-Herzegovina | 48% | 10% | 0.1% | 0.0% |
| 37 | Tunisia | 26% | 7% | 0.0% | 0.0% |
| 38 | South Africa | 15% | 2% | 0.0% | 0.0% |
| 39 | Qatar | 11% | 1% | 0.0% | 0.0% |
| 40 | Haiti | 14% | 2% | 0.0% | 0.0% |
| 41 | Curaçao | 6% | 1% | 0.0% | 0.0% |
| 42 | New Zealand | 24% | 4% | 0.0% | 0.0% |
| 43 | Cape Verde Islands | 21% | 5% | 0.0% | 0.0% |
| 44 | Saudi Arabia | 20% | 4% | 0.0% | 0.0% |
| 45 | Iraq | 14% | 3% | 0.0% | 0.0% |
| 46 | Jordan | 30% | 9% | 0.1% | 0.0% |
| 47 | Congo DR | 26% | 7% | 0.1% | 0.0% |
| 48 | Ghana | 10% | 2% | 0.0% | 0.0% |
🔭 External Forecast — Klement 2026
Panmure Liberum publishes a pre-tournament winner prediction using socioeconomic indicators (GDP per capita, population, climate) and FIFA rankings. 3/3 correct (2014–2022)
2026 pick: Netherlands beats Spain (SF, pens) and Portugal in the Final. Biggest surprise: Japan beats Brazil (R32). source →
| Team | Klement pick | Model WC % |
|---|---|---|
| Netherlands | 🏆 Champion | 2.8% |
| Portugal | Runner-up | 4.7% |
| Spain | Semi-final | 24.2% |
| England | Semi-final | 7.3% |
| France | Quarter-final | 10.4% |
| Argentina | Quarter-final | 17.3% |
| Japan | Quarter-final ⚡ | 1.8% |
⚡ Klement's biggest predicted upset: Japan beats Brazil in the Round of 32. Spain reaches the SF but loses on penalties to the Netherlands. Model gives Spain a 24.2% WC chance vs. 2.8% for the Netherlands.
📊 Current Elo Rankings
| # | Team | Elo | Δ Total | Δ Week | Strength |
|---|---|---|---|---|---|
| 1 | Spain | 2157 | — | — | |
| 2 | Argentina | 2115 | — | — | |
| 3 | France | 2063 | — | — | |
| 4 | England | 2024 | — | — | |
| 5 | Brazil | 1991 | — | — | |
| 6 | Portugal | 1989 | — | — | |
| 7 | Colombia | 1982 | — | — | |
| 8 | Netherlands | 1948 | — | — | |
| 9 | Ecuador | 1938 | — | — | |
| 10 | Germany | 1932 | — | — | |
| 11 | Norway | 1914 | — | — | |
| 12 | Croatia | 1912 | — | — | |
| 13 | Turkey | 1911 | — | — | |
| 14 | Japan | 1906 | — | — | |
| 15 | Belgium | 1894 | — | — | |
| 16 | Uruguay | 1892 | — | — | |
| 17 | Switzerland | 1891 | — | — | |
| 18 | Mexico | 1884 | +3 | — | |
| 19 | Senegal | 1860 | — | — | |
| 20 | Paraguay | 1834 | — | — | |
| 21 | Austria | 1830 | — | — | |
| 22 | Morocco | 1827 | — | — | |
| 23 | South Korea | 1799 | +13 | — | |
| 24 | Scotland | 1782 | — | — | |
| 25 | Canada | 1778 | -10 | — | |
| 26 | Australia | 1777 | — | — | |
| 27 | Algeria | 1772 | — | — | |
| 28 | Iran | 1772 | — | — | |
| 29 | Panama | 1730 | — | — | |
| 30 | United States | 1726 | — | — | |
| 31 | Uzbekistan | 1714 | — | — | |
| 32 | Sweden | 1712 | — | — | |
| 33 | Czechia | 1699 | -13 | — | |
| 34 | Egypt | 1696 | — | — | |
| 35 | Ivory Coast | 1695 | — | — | |
| 36 | Jordan | 1680 | — | — | |
| 37 | Congo DR | 1652 | — | — | |
| 38 | Tunisia | 1628 | — | — | |
| 39 | Iraq | 1607 | — | — | |
| 40 | Bosnia-Herzegovina | 1605 | +10 | — | |
| 41 | Cape Verde Islands | 1578 | — | — | |
| 42 | Saudi Arabia | 1576 | — | — | |
| 43 | New Zealand | 1562 | — | — | |
| 44 | Haiti | 1548 | — | — | |
| 45 | Ghana | 1510 | — | — | |
| 46 | South Africa | 1508 | -3 | — | |
| 47 | Curaçao | 1434 | — | — | |
| 48 | Qatar | 1421 | — | — |
✔ Elo DQ Check 48 teams vs eloratings.net · MAD 1.1 pts
| Team | Our Elo | eloratings.net | Delta |
|---|---|---|---|
| Czechia | 1699 | 1712 | -13 |
| South Korea | 1799 | 1786 | +13 |
| Bosnia-Herzegovina | 1605 | 1616 | -11 |
| Canada | 1778 | 1767 | +11 |
| Mexico | 1884 | 1881 | +3 |
| South Africa | 1508 | 1511 | -3 |
| Algeria | 1772 | 1772 | +0 |
| Argentina | 2115 | 2115 | +0 |
| Australia | 1777 | 1777 | +0 |
| Austria | 1830 | 1830 | +0 |
| Belgium | 1894 | 1894 | +0 |
| Brazil | 1991 | 1991 | +0 |
| Cape Verde Islands | 1578 | 1578 | +0 |
| Colombia | 1982 | 1982 | +0 |
| Congo DR | 1652 | 1652 | +0 |
Showing top 15 by absolute delta · 48 total teams compared
⚙️ How the Model Learns
(lower = better; 0 = perfect)
– = underconfident
Reliability Diagram (Calibration Chart)
📐 Running Brier Score
Mean squared probability error across all completed matches — lower is better. The dashed red line marks 0.667, the score a random 33%/33%/33% model achieves on every match. Staying below it means the model adds information. Updated nightly.
Running avg after 3 matches: 0.487 · Random baseline: 0.667
⚽ Score Distribution — Predicted vs Actual
Predicted: Poisson tipp frequency across all 72 fixtures. Actual: results from 3 completed matches. Scores above 3 are capped at 3. Sorted by goal difference — home-favourable left, away-favourable right.
📊 Predicted Scoreline Types by Stage
How the model's predicted scorelines change as the tournament progresses. In the group stage, a wide range of results is expected — including draws. By the Round of 16 and beyond, the field has levelled: Elo gaps narrow, draws are impossible, and the tie-break pushes nearly every match towards a 2:1 result.
📡 Model & Data Drift Monitor
Data drift — the tournament's actual statistics (goals per match, draw rate, host-nation results) diverging from the model's built-in assumptions. Model drift — the five PDCA parameters shifting from their defaults in response. The chart tracks each parameter's percentage deviation from its starting value, updated nightly. A flat line means the assumption held. A rising or falling line means the tournament data is pulling the model.
Confidence calibration — is the model over- or underconfident?
net_bias > 0: model assigns probabilities that are systematically too extreme (overconfident). net_bias < 0: probabilities are too flat (underconfident). The purple dashed line shows how elo_scale adjusts in response — rising elo_scale softens the probability curve.