Salvato in:
| Autori principali: | , , |
|---|---|
| Natura: | Preprint |
| Pubblicazione: |
2025
|
| Soggetti: | |
| Accesso online: | https://arxiv.org/abs/2510.14723 |
| Tags: |
Aggiungi Tag
Nessun Tag, puoi essere il primo ad aggiungerne!!
|
| _version_ | 1866911215130771456 |
|---|---|
| author | MacDermott, Cormac Scarrott, Carl J. Ferguson, John |
| author_facet | MacDermott, Cormac Scarrott, Carl J. Ferguson, John |
| contents | Evaluating a country's sporting success provides insight into its decision-making and infrastructure for developing athletic talent. The Olympic Games serve as a global benchmark, yet conventional medal rankings can be unduly influenced by population size. We propose a Bayesian ranking scheme to rank the performance of National Olympic Committees by their "long-run" medals-to-population ratio. The algorithm aims to mitigate the influence of large populations and reduce the stochastic fluctuations for smaller nations by applying shrinkage. These long-run rankings provide a more stable and interpretable ordering of national sporting performance across games compared to existing methods. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2510_14723 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Bayes-ically fair: A Bayesian Ranking of the Olympic Medal Table MacDermott, Cormac Scarrott, Carl J. Ferguson, John Applications Evaluating a country's sporting success provides insight into its decision-making and infrastructure for developing athletic talent. The Olympic Games serve as a global benchmark, yet conventional medal rankings can be unduly influenced by population size. We propose a Bayesian ranking scheme to rank the performance of National Olympic Committees by their "long-run" medals-to-population ratio. The algorithm aims to mitigate the influence of large populations and reduce the stochastic fluctuations for smaller nations by applying shrinkage. These long-run rankings provide a more stable and interpretable ordering of national sporting performance across games compared to existing methods. |
| title | Bayes-ically fair: A Bayesian Ranking of the Olympic Medal Table |
| topic | Applications |
| url | https://arxiv.org/abs/2510.14723 |