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 · 1,230 fixtures
Random guess
33%
Home, draw or away: 3 outcomes
Always the home team
45%
Same 1,188 matches
AI council majority
49%
The result most models picked
When all AIs agree
62%
458 matches with a unanimous council
| # | Model | Hit rate | Brier | Last 10 matches |
|---|---|---|---|---|
| 01 |
Claude Sonnet 5
628/1230 decided
|
51% | 0.61 |
|
| 02 |
DeepSeek V4 Pro
604/1230 decided
|
49% | 0.63 |
|
| 03 |
Gemini 3.8 Flash
592/1229 decided
|
48% | 0.61 |
|
| 04 |
Grok 4.6
588/1230 decided
|
48% | 0.62 |
|
| 05 |
Mistral Medium 3.5
583/1230 decided
|
47% | 0.63 |
|
| 06 |
Qwen 3.8 Max
582/1230 decided
|
47% | 0.64 |
|
| 07 |
GPT-5.6 Luna
571/1230 decided
|
46% | 0.63 |
|
| 08 |
MiMo V2.5 Pro
565/1230 decided
|
46% | 0.64 |
|
| 09 |
Kimi K3
316/667 decided
|
47% | 0.63 |
|
| 10 |
GLM 5.3
307/667 decided
|
46% | 0.63 |
|
Push alerts when predictions refresh. Confidence bands and model disagreement — without clutter.
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