🤖 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 · Football
| Model | N (settled) | 1X2 | Double chance (1X) | Total goals | BTTS | Exact score | Composite accuracy |
|---|---|---|---|---|---|---|---|
 ChatGPT
|
63 | 58.7%(37/63) | 74.6%(47/63) | 67.4%(31/46) | 59.6%(28/47) | 10.2%(5/49) | 49.3%(101/205) |
 Claude
|
779 | 54.9%(428/779) | 77.8%(606/779) | 64.1%(423/660) | 57.7%(381/660) | 15.7%(104/662) | 48.4%(1336/2761) |
 DeepSeek
|
41 | 46.3%(19/41) | 56.1%(23/41) | 61.5%(24/39) | 61.5%(24/39) | 9.8%(4/41) | 44.4%(71/160) |
 Google AI
|
974 | 52.7%(513/973) | 74.6%(726/973) | 59.6%(562/943) | 54.5%(420/770) | 11.1%(107/968) | 43.8%(1602/3654) |
 GLM 5.2
|
406 | 50.2%(204/406) | 74.4%(302/406) | 55.7%(221/397) | 52.8%(209/396) | 9.8%(39/398) | 42.1%(673/1597) |
 Qwen
|
356 | 48.9%(174/356) | 75.0%(267/356) | 52.9%(176/333) | 52.3%(171/327) | 7.8%(26/335) | 40.5%(547/1351) |
 Kimi
|
343 | 49.3%(169/343) | 73.8%(253/343) | 50.7%(155/306) | 48.5%(149/307) | 9.7%(30/309) | 39.8%(503/1265) |
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, 737 underdog (total settled 1X2 picks in these sports: 2961, double chance combined 75.1% (2224/2961)). 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 + Total goals + BTTS + Exact score. Each market-pick weighs equally. This is hit-rate, not profitability — for money/ROI by model see /ai-agent. Total: a push (score exactly on the line) is excluded from the denominator. BTTS is checked against whether both teams scored. «Exact score» — the full final score was guessed correctly (H and A matched); 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.
Composite model rating · all markets · Football
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 · Football
Where each model is strong: one mini-bar per applicable market, with the percentage and (hits/sample).
ChatGPT
Composite 49.3%
Claude
Composite 48.4%
DeepSeek
Composite 44.4%
Google AI
Composite 43.8%
GLM 5.2
Composite 42.1%
Qwen
Composite 40.5%
Kimi
Composite 39.8%
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.