🤖 AI benchmark: hit-rate of 7 models

Prematch En direct (in-play)

Seven external AI models (Hermes contour) independently analyze the same matchs — predicting the résultat (1X2), total (Plus de/Moins de), both équipes to score (BTTS) and the exact score. Here we honestly compare their pronostics against the real result after the final whistle and combine everything into a single accuracy rating. An informational and analytical snapshot, not betting advice.

⚠️ Data is still accumulating — counting starts from 09.07.2026, so all models are compared on the same events (early test pronostics are excluded). The sample is still small and not representative. Right now the snapshot holds 124 match(es), 493 settled AI pronostics (Volley-ball). The figures below are N, not «a percentage you can trust»: the more matchs are played out, the more reliable the snapshot becomes. We show it transparently from day one, not only once the sample becomes «convenient».

Tous les sports Football Tennis Basketball Volley-ball Hockey Tennis de table

Leaderboard · Volley-ball

Model	N (settled)	1X2	Exact score	Composite accuracy
Kimi	63	65.1%(41/63)	31.9%(15/47)	50.9%(56/110)
ChatGPT	18	66.7%(12/18)	18.2%(2/11)	48.3%(14/29)
Claude	104	64.4%(67/104)	20.5%(17/83)	44.9%(84/187)
DeepSeek	13	76.9%(10/13)	7.7%(1/13)	42.3%(11/26)
Google AI	131	64.1%(84/131)	19.8%(26/131)	42.0%(110/262)
Qwen	82	69.5%(57/82)	7.9%(6/76)	39.9%(63/158)
GLM 5.2	82	65.9%(54/82)	11.0%(9/82)	38.4%(63/164)

grey — sample <5, not representative; «—» — the modèle has not made a settled pronostic yet.

Composite accuracy — the share of correct pronostics sur all affiché marchés together: (sum of correct pronostics) ÷ (sum of all settled pronostics) sur the marchés 1X2 + Exact score. Each marché-pronostic weighs equally. This is hit-rate, not profitability — for money/ROI by modèle see /ai-agent. «Exact score» — the full final score was guessed correctly (H and A matched); pronostics with no recognized score do not count toward the denominator.

Composite modèle rating · all marchés · Volley-ball

Bar height = the modèle's composite accuracy sur all applicable marchés on the current sample. Sorted from best to worst.

50.9% (56/110)

Kimi 2.6

48.3% (14/29)

GPT 5.5

44.9% (84/187)

Opus 4.8

42.3% (11/26)

DeepSeek V4 Pro

42.0% (110/262)

Gemini 3.5 Flash

39.9% (63/158)

Qwen 3.7 Plus

38.4% (63/164)

GLM 5.2

Bars are AI models by version; grey/dimmed — sample <5, not representative. The snapshot is informational, not betting advice.

Accuracy by marché · Volley-ball

Where each modèle is strong: one mini-bar per applicable marché, with the percentage and (hits/sample).

Kimi Composite 50.9%

1X2

65.1% (41/63)

Exact score

31.9% (15/47)

ChatGPT Composite 48.3%

1X2

66.7% (12/18)

Exact score

18.2% (2/11)

Claude Composite 44.9%

1X2

64.4% (67/104)

Exact score

20.5% (17/83)

DeepSeek Composite 42.3%

1X2

76.9% (10/13)

Exact score

7.7% (1/13)

Google AI Composite 42.0%

1X2

64.1% (84/131)

Exact score

19.8% (26/131)

Qwen Composite 39.9%

1X2

69.5% (57/82)

Exact score

7.9% (6/76)

GLM 5.2 Composite 38.4%

1X2

65.9% (54/82)

Exact score

11.0% (9/82)

The modèle's favorite by 1X2 = the max of P1/X/P2 in its probabilities; for sports without a nul (tennis, volleyball, etc.) the «X» option doesn't participate. grey — sample <5, not representative. Not betting advice.