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 · 1,242 fixtures
Random guess
33%
Home, draw or away: 3 outcomes
Always the home team
45%
Same 1,200 matches
AI council majority
49%
The result most models picked
When all AIs agree
61%
463 matches with a unanimous council
| # | Model | Hit rate | Brier | Last 10 matches |
|---|---|---|---|---|
| 01 |
Claude Sonnet 5
633/1242 decided
|
51% | 0.61 |
|
| 02 |
DeepSeek V4 Pro
610/1242 decided
|
49% | 0.63 |
|
| 03 |
Gemini 3.8 Flash
596/1241 decided
|
48% | 0.61 |
|
| 04 |
Grok 4.6
594/1242 decided
|
48% | 0.62 |
|
| 05 |
Mistral Medium 3.5
589/1242 decided
|
47% | 0.63 |
|
| 06 |
Qwen 3.8 Max
587/1242 decided
|
47% | 0.64 |
|
| 07 |
GPT-5.6 Luna
577/1242 decided
|
47% | 0.63 |
|
| 08 |
MiMo V2.5 Pro
569/1242 decided
|
46% | 0.64 |
|
| 09 |
Kimi K3
320/679 decided
|
47% | 0.63 |
|
| 10 |
GLM 5.3
312/679 decided
|
46% | 0.63 |
|
Push alerts when predictions refresh. Confidence bands and model disagreement — without clutter.
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