🤖 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 13 試合(es), 25 settled AI 予想 (ホッケー). 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».

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Leaderboard · ホッケー

Model	N (settled)	1X2	ダブルチャンス (1X)	Total ゴール	BTTS	Exact スコア	Composite accuracy
Google AI	13	69.2%(9/13)	69.2%(9/13)	46.2%(6/13)	76.9%(10/13)	0.0%(0/13)	48.1%(25/52)
Claude	12	50.0%(6/12)	50.0%(6/12)	58.3%(7/12)	75.0%(9/12)	0.0%(0/12)	45.8%(22/48)
DeepSeek	0	—	—	—	—	—	—
ChatGPT	0	—	—	—	—	—	—
Qwen	0	—	—	—	—	—	—
Kimi	0	—	—	—	—	—	—
GLM 5.2	0	—	—	—	—	—	—

grey — sample <5, not representative; «—» — the モデル has not made a settled 予想 yet.

ダブルチャンス (1X) — the same ピック counts as a 勝利 if the chosen side won or the 試合 drew. Of the 1X2 losses in football/hockey: 0 draws, 10 underdog (total settled 1X2 ピック in these sports: 25, double chance combined 60.0% (15/25)). The models almost always take the favorite and don't bet on a 引き分け — double chance shows how many bets are eaten specifically by draws.

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 + Total ゴール + BTTS + 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. Total: a push (スコア exactly ライン上) is excluded from the denominator. BTTS is checked against whether both チーム scored. «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. ダブルチャンス (1X): a ピック counts as a 勝利 if the chosen side won OR it was a 引き分け — it accounts for frequent draws that «eat» bets on the favorite. This metric is informational and is not included in composite accuracy.

Composite モデル rating · all マーケット · ホッケー

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.

48.1% (25/52)

Gemini 3.5 Flash

45.8% (22/48)

Opus 4.8

—

DeepSeek V4 Pro

データなし

—

GPT 5.5

データなし

—

Qwen 3.7 Plus

データなし

—

Kimi 2.6

データなし

—

GLM 5.2

データなし

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 · ホッケー

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

Google AI Composite 48.1%

1X2

69.2% (9/13)

Total ゴール

46.2% (6/13)

BTTS

76.9% (10/13)

Exact スコア

0.0% (0/13)

Claude Composite 45.8%

1X2

50.0% (6/12)

Total ゴール

58.3% (7/12)

BTTS

75.0% (9/12)

Exact スコア

0.0% (0/12)

DeepSeek Composite —

1X2

—

Total ゴール

—

BTTS

—

Exact スコア

—

ChatGPT Composite —

1X2

—

Total ゴール

—

BTTS

—

Exact スコア

—

Qwen Composite —

1X2

—

Total ゴール

—

BTTS

—

Exact スコア

—

Kimi Composite —

1X2

—

Total ゴール

—

BTTS

—

Exact スコア

—

GLM 5.2 Composite —

1X2

—

Total ゴール

—

BTTS

—

Exact スコア

—

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.