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Economic resources, sporting efficiency and uncertainty: a global test on the 2026 FIFA world cup

Thierno Thioune, Babacar Mbaye Ndiaye · 2026 · arXiv (Cornell University)

DOI: 10.48550/arxiv.2610.28344 · cited by 0 works (OpenAlex) · open-access PDF

Japanese

関連するメカニズムはかなり効率的である(arXiv:2610.06967)サッカーのパフォーマンスは、潜在的な平均逆転パフォーマンスプロセスと潜在的なGDP/人口ベースの潜在的パフォーマンスを組み合わせたストーカスティック最適化フレームワークを開発しました。このフレームワークは、AFCON 2025に参加する24の国家チームのクロスセクションに適用されました。この論文は、完全な48チーム2026FIFAワールドカップに同じ方法論を適用し、アフリカを超えて分析を拡張します。GDP、人口、FIFAランキングデータ、および完全なトーナメント結果を使用して、このフレームワークは、6つの連合をカバーするグローバルサンプル

Machine translation (Meta M2M100); the English original follows.

Abstract

A related paper (arXiv:2610.06967) developed a stochastic optimization framework in which football performance combines GDP/population-based potential with a latent mean-reverting efficiency process. The framework was applied to a cross-section of the 24 national teams participating in AFCON 2025. This paper applies the same methodology to the full 48-team 2026 FIFA World Cup, extending the analysis beyond Africa without modifying the underlying model. Using GDP, population, FIFA ranking data, and complete tournament outcomes, it evaluates the framework against a global sample spanning all six confederations. Two findings emerge. First, GDP and population explain only 9 percent of single-tournament performance variance, compared with 33 percent for FIFA points. This gap is consistent with the model's distinction between systematic performance and match-specific idiosyncratic shocks. Second, using the less noisy FIFA-points measure, the African pattern persists globally: Morocco, Senegal, Argentina, Croatia, Portugal, and Uruguay emerge as leading GDP-relative over-performers. Conversely, several major economies, including the United States, Germany, Japan, and South Korea, underperform their GDP-implied potential. As in the related paper, we interpret the residual as a symmetric, non-structurally identified conditional performance residual, rather than an SFA-consistent efficiency estimate. We also quantify the extent to which its cross-country variance mechanically reflects the underlying performance measure. The GDP-rank/simulated-performance-rank correlation is robust to the choice of the model's unidentified dynamic parameters across a wide grid.

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Topics: Football, Ranking (information retrieval), Econometrics, Sample (material), Tournament, Population

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