WorldCupArena: Fine-Grained Evaluation of Language Models and Deep-Research Agents on Football Forecasting
Predicting a football match before kickoff requires more than knowing past results: a model must use changing information and make a clear prediction before the answer is available. We present WorldCupArena, a dynamic benchmark for language models and deep-research agents. The 2026 FIFA World Cup is its first evaluation, and the same process can be reused for future leagues and cups. Before each match, a model either receives a common evidence package or searches for information itself. It predicts the result and score, likely players and events, match statistics, and the outcome of the compet
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Paper → model → repo connections mined from source citations (Tier-1 exact match).
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- PossiblePossibly related (embedding) · 62%Goal26 Research Examines AI and Human Predictions Across More Than 50,000 FIFA World Cup 2026 Brackets - EIN News →
- PossiblePossibly related (embedding) · 56%Comparing AI predictions before the World Cup final →
- FuzzySimilar title/name (fuzzy) · 87%NirDiamant/GenAI_Agents →
“Fuzzy title match (0.94): “WorldCupArena: Fine-Grained Evaluation of Language Models an” ≈ “NirDiamant/GenAI_Agents””
- FuzzySimilar title/name (fuzzy) · 84%Unity-Technologies/ml-agents →
“Fuzzy title match (0.92): “WorldCupArena: Fine-Grained Evaluation of Language Models an” ≈ “Unity-Technologies/ml-agents””
- FuzzyOverlapping authors or contributors · 62%bytedance/deer-flow →
“Shared author/contributor keys: wang”
- FuzzyOverlapping authors or contributors · 62%ray-project/ray →
“Shared author/contributor keys: wang”
- FuzzySimilar title/name (fuzzy) · 59%datawhalechina/hello-agents →
“Fuzzy title match (0.73): “WorldCupArena: Fine-Grained Evaluation of Language Models an” ≈ “datawhalechina/hello-agents””
- LinkedLinked via arxiv author · 85%Zhaokai Wang →
“WorldCupArena: Fine-Grained Evaluation of Language Models and Deep-Research Agents on Football Forecasting”
