🤖 AI benchmark: hit-rate of 7 models
Seven external AI models (Hermes contour) independently analyze the same matches — predicting the outcome (1X2), total (Over/Under), both teams to score (BTTS) and the exact score. Here we honestly compare their predictions against the real result after the final whistle and combine everything into a single accuracy rating. An informational and analytical snapshot, not betting advice.
Leaderboard
| Model | N (settled) | 1X2 | Double chance (1X) | Exact score | Composite accuracy |
|---|---|---|---|---|---|
 ChatGPT
|
263 | 65.0%(171/263) | 74.6%(47/63) | 17.2%(35/203) | 44.2%(206/466) |
 Claude
|
2166 | 61.3%(1328/2166) | 77.6%(612/789) | 21.8%(412/1887) | 42.9%(1740/4053) |
 Kimi
|
1109 | 60.8%(674/1109) | 73.8%(253/343) | 20.3%(196/964) | 42.0%(870/2073) |
 Google AI
|
2806 | 60.3%(1691/2804) | 74.7%(735/984) | 20.0%(552/2764) | 40.3%(2243/5568) |
 GLM 5.2
|
1285 | 59.5%(765/1285) | 74.4%(302/406) | 19.5%(246/1261) | 39.7%(1011/2546) |
 DeepSeek
|
175 | 60.6%(106/175) | 56.1%(23/41) | 18.5%(32/173) | 39.7%(138/348) |
 Qwen
|
1237 | 59.3%(733/1237) | 75.0%(267/356) | 16.8%(196/1166) | 38.7%(929/2403) |
grey — sample <5, not representative; «—» — the model has not made a settled prediction yet.
Double chance (1X) — the same pick counts as a win if the chosen side won or the match drew. Of the 1X2 losses in football/hockey: 680 draws, 743 underdog (total settled 1X2 picks in these sports: 2982, double chance combined 75.1% (2239/2982)). The models almost always take the favorite and don't bet on a draw — double chance shows how many bets are eaten specifically by draws.
Composite accuracy — the share of correct predictions across all shown markets together: (sum of correct picks) ÷ (sum of all settled picks) across the markets 1X2 + Exact score. Each market-pick weighs equally. This is hit-rate, not profitability — for money/ROI by model see /ai-agent. «Exact score» — the full final score was guessed correctly (H and A matched); for tennis, sets are compared; predictions with no recognized score do not count toward the denominator. Double chance (1X): a pick counts as a win if the chosen side won OR it was a draw — it accounts for frequent draws that «eat» bets on the favorite. This metric is informational and is not included in composite accuracy. On «All sports» we don't show total and BTTS — they're tied to the sport and make no sense in a mixed pool.
Composite model rating · all markets
Bar height = the model's composite accuracy across all applicable markets on the current sample. Sorted from best to worst.
Bars are AI models by version; grey/dimmed — sample <5, not representative. The snapshot is informational, not betting advice.
Accuracy by market
Where each model is strong: one mini-bar per applicable market, with the percentage and (hits/sample).
ChatGPT
Composite 44.2%
Claude
Composite 42.9%
Kimi
Composite 42.0%
Google AI
Composite 40.3%
GLM 5.2
Composite 39.7%
DeepSeek
Composite 39.7%
Qwen
Composite 38.7%
The model's favorite by 1X2 = the max of P1/X/P2 in its probabilities; for sports without a draw (tennis, volleyball, etc.) the «X» option doesn't participate. grey — sample <5, not representative. Not betting advice.