🤖 AI benchmark: hit-rate of 7 models

Prematch ライブ (in-play)

Seven external AI models (Hermes contour) independently analyze the same 試合 — predicting the 結果 (1X2), total (オーバー/アンダー), both チーム to スコア (BTTS) and the exact スコア. Here we honestly compare their 予想 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 予想 are excluded). The sample is still small and not representative. Right now the snapshot holds 125 試合(es), 494 settled AI 予想 (バレーボール). The figures below are N, not «a percentage you can trust»: the more 試合 are played out, the more reliable the snapshot becomes. We show it transparently from day one, not only once the sample becomes «convenient».

Leaderboard · バレーボール

Model N (settled) 1X2 Exact スコア 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
132 63.6%(84/132) 19.7%(26/132) 41.7%(110/264)
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 モデル has not made a settled 予想 yet.

Composite accuracy — the share of correct 予想 横断 all 表示 マーケット together: (sum of correct ピック) ÷ (sum of all settled ピック) 横断 the マーケット 1X2 + Exact スコア. Each マーケット-ピック weighs equally. This is hit-rate, not profitability — for money/ROI by モデル see /ai-agent. «Exact スコア» — the full final スコア was guessed correctly (H and A matched); 予想 with no recognized スコア do not count toward the denominator.

Composite モデル rating · all マーケット · バレーボール

Bar height = the モデル's composite accuracy 横断 all applicable マーケット 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
41.7% (110/264)
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 マーケット · バレーボール

Where each モデル is strong: one mini-bar per applicable マーケット, with the percentage and (hits/sample).

Kimi Composite 50.9%
1X2
65.1% (41/63)
Exact スコア
31.9% (15/47)
ChatGPT Composite 48.3%
1X2
66.7% (12/18)
Exact スコア
18.2% (2/11)
Claude Composite 44.9%
1X2
64.4% (67/104)
Exact スコア
20.5% (17/83)
DeepSeek Composite 42.3%
1X2
76.9% (10/13)
Exact スコア
7.7% (1/13)
Google AI Composite 41.7%
1X2
63.6% (84/132)
Exact スコア
19.7% (26/132)
Qwen Composite 39.9%
1X2
69.5% (57/82)
Exact スコア
7.9% (6/76)
GLM 5.2 Composite 38.4%
1X2
65.9% (54/82)
Exact スコア
11.0% (9/82)

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