Last updated on 2026-06-24
My model for World Cup match win probabilities is based on the FIFA rankings which are based on an Elo ranking system. I made adjustments to each team’s ranking score based on the geography. It is well established that teams from the continent of play perform better than those who have to travel farther. I do give consideration to where team players are based for club play. Below is the basic analysis of model accuracy. The blue bars represent the distribution of expected results and the red bars represent the actual model performance.
The model is right on target. This means that the FIFA rankings and my adjustments are good indicators of the chances a team has of winning the match.
With that, here are the second round probabilities based on rankings updated from the first round results. Scores will be updated periodically throughout the round.
| Home | Away | ||||
|---|---|---|---|---|---|
| 56% | Czechia | 1 | 1 | South Africa | 44% |
| 72% | Switzerland | 4 | 1 | Bosnia and Herzegovina | 28% |
| 63% | Canada | 6 | 0 | Qatar | 37% |
| 61% | Mexico | 1 | 0 | Korea | 39% |
| 86% | Brazil | 3 | 0 | Haiti | 14% |
| 28% | Scotland | 0 | 1 | Morocco | 72% |
| 62% | USA | 2 | 0 | Australia | 38% |
| 57% | Türkiye | 0 | 1 | Paraguay | 43% |
| 65% | Germany | 2 | 1 | Côte d’Ivoire | 35% |
| 76% | Ecuador | 0 | 0 | Curaçao | 24% |
| 69% | Netherlands | 5 | 1 | Sweden | 31% |
| 31% | Tunisia | 0 | 4 | Japan | 69% |
| 75% | Uruguay | 2 | 2 | Cabo Verde | 25% |
| 83% | Spain | 4 | 0 | Saudi Arabia | 17% |
| 62% | Belgium | 0 | 0 | IR Iran | 38% |
| 25% | New Zealand | 0 | 3 | Egypt | 75% |
| 41% | Norway | 3 | 2 | Senegal | 59% |
| 86% | France | 3 | 0 | Iraq | 14% |
| 76% | Argentina | 2 | 0 | Austria | 24% |
| 33% | Jordan | 1 | 2 | Algeria | 67% |
| 85% | England | 0 | 0 | Ghana | 15% |
| 34% | Panama | 0 | 1 | Croatia | 66% |
| 77% | Portugal | 5 | 0 | Uzbekistan | 23% |
| 71% | Colombia | 1 | 0 | Congo DR | 29% |