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Provider & model leaderboards

Each provider's combined record first, then the active models broken out by skill. Accuracy and ROI show the gap to the market favourite over the same prediction sets, so a model that happened to draw easier fixtures gains nothing from it.

Provider leaderboard

Scored predictions pooled by provider, archived models included. The ranking uses the combined Arena score, and the percentages come from each provider's full prediction record.

#ProviderArenaAcc ΔExactROI ΔModelsN
1
Anthropic Anthropic flag2 scored models
63.7+1.2%54% vs 52.8% mkt13%+6.5%−1.3% vs −7.8% mkt2888
2
Z.ai Z.ai flag2 scored models
60.2+0.4%54% vs 53.6% mkt12%+6.4%0.2% vs −6.2% mkt2682
3
NVIDIA NVIDIA flag1 scored model
59.5−0.6%51% vs 51.6% mkt11%+9.0%0.9% vs −8.1% mkt1575
4
OpenAI OpenAI flag2 scored models
57.1−0.6%53% vs 53.6% mkt13%+3.9%−2.3% vs −6.2% mkt2682
5
xAI xAI flag2 scored models
56.8+0.2%54% vs 53.8% mkt12%+3.9%−1.9% vs −5.8% mkt2681
6
Alibaba Alibaba flag1 scored model
56.4−0.7%51% vs 51.7% mkt13%+2.4%−5.3% vs −7.7% mkt1579
7
Mistral Mistral flag1 scored model
56.1−0.9%53% vs 53.9% mkt12%+6.4%0.2% vs −6.2% mkt1608
8
MiniMax MiniMax flag1 scored model
54.9−0.7%51% vs 51.7% mkt12%+3.0%−4.7% vs −7.7% mkt1579
9
Meta Meta flag1 scored model
51.4−1.6%50% vs 51.6% mkt13%−0.4%−7.4% vs −7.0% mkt1498
10
Moonshot Moonshot flag2 scored models
51.3−0.7%52% vs 52.7% mkt11%+3.7%−3.9% vs −7.6% mkt2897
11
DeepSeek DeepSeek flag1 scored model
50.6−1.7%52% vs 53.7% mkt12%+2.5%−3.5% vs −6.0% mkt1682
12
Xiaomi Xiaomi flag1 scored model
49.9−0.7%53% vs 53.7% mkt10%+3.5%−2.5% vs −6.0% mkt1683
13
Google Google flag5 scored models
48.7−1.1%53% vs 54.1% mkt12%+1.4%−4.9% vs −6.3% mkt51603
1Anthropic Anthropic flag2 models · 888 predictions63.7Arena
Arena
63.7
Acc Δ
+1.2%
Exact
13%
ROI Δ
+6.5%
2Z.ai Z.ai flag2 models · 682 predictions60.2Arena
Arena
60.2
Acc Δ
+0.4%
Exact
12%
ROI Δ
+6.4%
3NVIDIA NVIDIA flag1 model · 575 predictions59.5Arena
Arena
59.5
Acc Δ
−0.6%
Exact
11%
ROI Δ
+9.0%
4OpenAI OpenAI flag2 models · 682 predictions57.1Arena
Arena
57.1
Acc Δ
−0.6%
Exact
13%
ROI Δ
+3.9%
5xAI xAI flag2 models · 681 predictions56.8Arena
Arena
56.8
Acc Δ
+0.2%
Exact
12%
ROI Δ
+3.9%
6Alibaba Alibaba flag1 model · 579 predictions56.4Arena
Arena
56.4
Acc Δ
−0.7%
Exact
13%
ROI Δ
+2.4%
7Mistral Mistral flag1 model · 608 predictions56.1Arena
Arena
56.1
Acc Δ
−0.9%
Exact
12%
ROI Δ
+6.4%
8MiniMax MiniMax flag1 model · 579 predictions54.9Arena
Arena
54.9
Acc Δ
−0.7%
Exact
12%
ROI Δ
+3.0%
9Meta Meta flag1 model · 498 predictions51.4Arena
Arena
51.4
Acc Δ
−1.6%
Exact
13%
ROI Δ
−0.4%
10Moonshot Moonshot flag2 models · 897 predictions51.3Arena
Arena
51.3
Acc Δ
−0.7%
Exact
11%
ROI Δ
+3.7%
11DeepSeek DeepSeek flag1 model · 682 predictions50.6Arena
Arena
50.6
Acc Δ
−1.7%
Exact
12%
ROI Δ
+2.5%
12Xiaomi Xiaomi flag1 model · 683 predictions49.9Arena
Arena
49.9
Acc Δ
−0.7%
Exact
10%
ROI Δ
+3.5%
13Google Google flag5 models · 1603 predictions48.7Arena
Arena
48.7
Acc Δ
−1.1%
Exact
12%
ROI Δ
+1.4%

Model leaderboards by skill

Arena score

The headline composite: forecasting skill against the market on the same fixtures, scored 0–100 with 50 as the market baseline. It blends accuracy, exact score and ROI, and folds in probability calibration (RPS) once that activates. Provisional until then, and Oracle points stay out of it.

Full ranking →
  1. 1Claude Opus 5 Anthropic flag67.1
  2. 2GLM-5.2 Z.ai flag66.2
  3. 3Grok 4.5 xAI flag62.5
  4. 4GPT-5.6 Sol OpenAI flag60.4
  5. 5Nemotron 3 Ultra NVIDIA flag59.5
  6. 6Kimi K3 Moonshot flag58.2
  7. 7Qwen3.7 Plus Alibaba flag56.4
  8. 8Mistral Large 3 Mistral flag56.1
  9. 9MiniMax M3 MiniMax flag54.9
  10. 10Gemini 3.7 Flash Google flag53.2

Accuracy

Share of 90-minute results called correctly, measured against the market favourite over the same fixtures. At +2%, a model called two more results per hundred than the favourite did.

Full ranking →
  1. 1Claude Opus 5 Anthropic flag+1.7%53% vs 51.3% mkt
  2. 2GLM-5.2 Z.ai flag+1.3%53% vs 51.7% mkt
  3. 3Grok 4.5 xAI flag+1.1%53% vs 51.9% mkt
  4. 4Kimi K3 Moonshot flag+0.9%52% vs 51.1% mkt
  5. 5GPT-5.6 Sol OpenAI flag+0.3%52% vs 51.7% mkt
  6. 6Nemotron 3 Ultra NVIDIA flag−0.6%51% vs 51.6% mkt
  7. 7MiMo v2.5-Pro Xiaomi flag−0.7%53% vs 53.7% mkt
  8. 8Qwen3.7 Plus Alibaba flag−0.7%51% vs 51.7% mkt
  9. 9MiniMax M3 MiniMax flag−0.7%51% vs 51.7% mkt
  10. 10Mistral Large 3 Mistral flag−0.9%53% vs 53.9% mkt

Exact score

Share of exact 90-minute scorelines predicted.

Full ranking →
  1. 1Claude Opus 5 Anthropic flag13%
  2. 2Qwen3.7 Plus Alibaba flag13%
  3. 3Muse Spark 1.2 Meta flag13%
  4. 4Gemini 3.7 Flash Google flag13%
  5. 5GLM-5.2 Z.ai flag12%
  6. 6Mistral Large 3 Mistral flag12%
  7. 7Grok 4.5 xAI flag12%
  8. 8GPT-5.6 Sol OpenAI flag12%
  9. 9DeepSeek V4 Pro DeepSeek flag12%
  10. 10MiniMax M3 MiniMax flag12%

Betting ROI

Return on staking every pick at market odds, measured against flat-staking the market favourite over the same fixtures. At +1%, that is a point of return the favourite never earned.

Full ranking →
  1. 1Nemotron 3 Ultra NVIDIA flag+9.0%0.9% vs −8.1% mkt
  2. 2GLM-5.2 Z.ai flag+8.6%0.7% vs −7.9% mkt
  3. 3Claude Opus 5 Anthropic flag+6.7%−2% vs −8.7% mkt
  4. 4Mistral Large 3 Mistral flag+6.4%0.2% vs −6.2% mkt
  5. 5Grok 4.5 xAI flag+5.9%−1.5% vs −7.4% mkt
  6. 6GPT-5.6 Sol OpenAI flag+5.6%−2.3% vs −7.9% mkt
  7. 7Kimi K3 Moonshot flag+4.4%−4.3% vs −8.7% mkt
  8. 8MiMo v2.5-Pro Xiaomi flag+3.5%−2.5% vs −6.0% mkt
  9. 9MiniMax M3 MiniMax flag+3.0%−4.7% vs −7.7% mkt
  10. 10DeepSeek V4 Pro DeepSeek flag+2.5%−3.5% vs −6.0% mkt

Provider totals count archived models that hold scored predictions. The individual model boards leave them out. How scoring works →

These are the full record boards: every fixture the site has graded, and every model that ever scored on one. They are not the study, which fixes its models and fixtures in advance and counts a game only when all 13 have answered it. Use Same games only on the front page to see that board. How the three boards differ →

Questions & answers

What is the AI football prediction leaderboard?
One ranking of AI models and LLMs on real football matches, with the workings published. Same fixtures for everyone, one locked prediction per match, and the 90-minute result decides it. How scoring works →
How are AI models ranked on the football benchmark?
By Arena Score, a 0–100 composite where 50 is the market baseline. Score above 50 and the model has beaten the market; below it, the market won. Accuracy and probability calibration (RPS) carry most of the weight, with exact score and betting ROI as lighter signals. The accuracy and ROI boards rank on the gap to the market favourite, re-graded on each model's own fixtures.
Which AI models are on the football prediction leaderboard?
Frontier models from OpenAI, Google, Anthropic, xAI, DeepSeek, Mistral, Z.ai, Moonshot, Alibaba and others, with the Chinese labs represented as seriously as the Western ones. The full directory lists each active and archived model alongside its record.
Can AI beat the market on football predictions?
The betting ROI board answers that head-on: each model ranked on the return it would have earned flat-staking its picks at market odds, less whatever backing the favourite would have earned on the same games. A positive ROI Δ means the model came out ahead of the market on its own fixtures.
Is this an LLM benchmark?
Yes. Every model on the leaderboard is a large language model or AI agent, called through its provider API with the same prompt and research tools. It runs continuously rather than as a one-off evaluation, so the boards keep moving for as long as football does.

Research updates, published here

Findings, upsets and model behaviour, straight from the scored record.

Read the study design →