Thierno Thioune, Babacar Mbaye Ndiaye · 2026 · arXiv (Cornell University)
DOI: 10.48550/arxiv.2610.28344 · cited by 0 works (OpenAlex) · open-access PDF
与此相关的机制是相当有效的(arXiv:2610.06967)开发了一种斯托加斯特的优化框架,其中足球表现将GDP/人口基于潜在的潜力与隐藏的平均逆转效能过程相结合。该框架被应用到参与AFCON 2025的24个国家队的跨部分,该框架针对涵盖所有六个联盟的全球样本进行了评估。本论文提出了相同的方法。第一,GDP在整个2026年世界杯的48个球队中扩展到非洲,而不改变底层模式。使用GDP,人口,FIFA排名数据和完整的比赛结果,它评估了框架与六个联盟的全球样本相比。第二,联合国的两个结果出现了。
Machine translation (Meta M2M100); the English original follows.
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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