Ten minds.
One consensus.
Zero guessing.
We run every football match through multiple frontier AI models, then publish the consensus, the dissent, and the confidence behind it.
Every model gets the same match and context. We log their answers, score them after the final buzzer, and publish the leaderboard.
Form, schedule, expected goals, and match context are loaded into a structured prompt for every model.
Each active model forecasts scoreline, outcome, and confidence independently before kickoff.
We surface the majority pick, confidence bands, and where models disagree.
After full-time, picks are marked against the result and the public leaderboard updates.
To date · 1,715 fixtures
Random guess
33%
Home, draw or away: 3 outcomes
Always the home team
45%
Same 1,669 matches
AI council majority
50%
The result most models picked
When all AIs agree
62%
678 matches with a unanimous council
| # | Model | Hit rate | Brier | Last 10 matches |
|---|---|---|---|---|
| 01 |
Claude Sonnet 5
884/1715 decided
|
52% | 0.61 |
|
| 02 |
Gemini 3.8 Flash
855/1714 decided
|
50% | 0.61 |
|
| 03 |
DeepSeek V4 Pro
849/1715 decided
|
50% | 0.63 |
|
| 04 |
Grok 4.6
841/1715 decided
|
49% | 0.62 |
|
| 05 |
Qwen 3.8 Max
829/1715 decided
|
48% | 0.63 |
|
| 06 |
GPT-5.6 Luna
822/1715 decided
|
48% | 0.63 |
|
| 07 |
Mistral Medium 3.5
811/1715 decided
|
47% | 0.63 |
|
| 08 |
MiMo V2.6 Pro
783/1715 decided
|
46% | 0.64 |
|
| 09 |
Kimi K3
560/1152 decided
|
49% | 0.62 |
|
| 10 |
GLM 5.3
559/1152 decided
|
49% | 0.62 |
|
Push alerts when predictions refresh. Confidence bands and model disagreement — without clutter.
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