Cargando…
Population, economic and geographic predictors of nations' medal tallies at the Pyeongchang and Tokyo Olympics and Paralympics
PURPOSE: Ranking of nations by medal tally is a popular feature of the Olympics, but such ranking is a poor measure of sporting prowess or engagement until the tallies are adjusted for major factors beyond the control of individual nations. Here we estimate and adjust for effects of total population...
Autores principales: | , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9428451/ https://www.ncbi.nlm.nih.gov/pubmed/36060630 http://dx.doi.org/10.3389/fspor.2022.931817 |
_version_ | 1784779121489870848 |
---|---|
author | Li, Feifei Hopkins, Will G. Lipinska, Patrycja |
author_facet | Li, Feifei Hopkins, Will G. Lipinska, Patrycja |
author_sort | Li, Feifei |
collection | PubMed |
description | PURPOSE: Ranking of nations by medal tally is a popular feature of the Olympics, but such ranking is a poor measure of sporting prowess or engagement until the tallies are adjusted for major factors beyond the control of individual nations. Here we estimate and adjust for effects of total population, economy expressed as gross domestic product per capita, absolute latitude and Muslim population proportion on total medal counts in female, male, mixed and all events at the Pyeongchang winter and Tokyo summer Olympics and Paralympics. METHODS: The statistical model was multiple linear over-dispersed Poisson regression. Population and economy were log-transformed; their linear effects were expressed in percent per percent units and evaluated in magnitude as the factor effects of two between-nation standard deviations (SD). The linear effect of absolute latitude was expressed and evaluated as the factor effect of 30° (approximately 2 SD). The linear effect of Muslim proportion was expressed as the factor effect of 100% vs. 0% Muslim. Nations were ranked on the basis of actual vs. predicted all-events medal counts. RESULTS: At the Pyeongchang Olympics, effects of population and economy were 0.7–0.8 %/% and 1.1–1.7 %/% (welldefined extremely large increases for 2 SD), factor effects of 30° of latitude were 11–17 (welldefined extremely large increases), and factor effects of 100% Muslim population were 0.08–0.69 (extremely large to moderate reductions, albeit indecisive). Effects at the Tokyo Olympics were similar in magnitude, including those of latitude, which were surprisingly still positive although diminished (large to very large increases). Effects at the Pyeongchang and Tokyo Paralympics were generally similar to those at the Olympics, but the effects of economy were diminished (large to very large increases). After adjustment of medal tallies for these effects, nations that reached the top-10 medalists in both winter games were Austria, Belarus, Kazakhstan, Slovakia and Ukraine, but only Azerbaijan reached the top-10 in both summer games. CONCLUSION: Adjusting medal counts for demographic and geographic factors provides a comparison of nations' sporting prowess or engagement that is more in keeping with the Olympic ideal of fair play and more useful for nations' Olympic-funding decisions. |
format | Online Article Text |
id | pubmed-9428451 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-94284512022-09-01 Population, economic and geographic predictors of nations' medal tallies at the Pyeongchang and Tokyo Olympics and Paralympics Li, Feifei Hopkins, Will G. Lipinska, Patrycja Front Sports Act Living Sports and Active Living PURPOSE: Ranking of nations by medal tally is a popular feature of the Olympics, but such ranking is a poor measure of sporting prowess or engagement until the tallies are adjusted for major factors beyond the control of individual nations. Here we estimate and adjust for effects of total population, economy expressed as gross domestic product per capita, absolute latitude and Muslim population proportion on total medal counts in female, male, mixed and all events at the Pyeongchang winter and Tokyo summer Olympics and Paralympics. METHODS: The statistical model was multiple linear over-dispersed Poisson regression. Population and economy were log-transformed; their linear effects were expressed in percent per percent units and evaluated in magnitude as the factor effects of two between-nation standard deviations (SD). The linear effect of absolute latitude was expressed and evaluated as the factor effect of 30° (approximately 2 SD). The linear effect of Muslim proportion was expressed as the factor effect of 100% vs. 0% Muslim. Nations were ranked on the basis of actual vs. predicted all-events medal counts. RESULTS: At the Pyeongchang Olympics, effects of population and economy were 0.7–0.8 %/% and 1.1–1.7 %/% (welldefined extremely large increases for 2 SD), factor effects of 30° of latitude were 11–17 (welldefined extremely large increases), and factor effects of 100% Muslim population were 0.08–0.69 (extremely large to moderate reductions, albeit indecisive). Effects at the Tokyo Olympics were similar in magnitude, including those of latitude, which were surprisingly still positive although diminished (large to very large increases). Effects at the Pyeongchang and Tokyo Paralympics were generally similar to those at the Olympics, but the effects of economy were diminished (large to very large increases). After adjustment of medal tallies for these effects, nations that reached the top-10 medalists in both winter games were Austria, Belarus, Kazakhstan, Slovakia and Ukraine, but only Azerbaijan reached the top-10 in both summer games. CONCLUSION: Adjusting medal counts for demographic and geographic factors provides a comparison of nations' sporting prowess or engagement that is more in keeping with the Olympic ideal of fair play and more useful for nations' Olympic-funding decisions. Frontiers Media S.A. 2022-08-17 /pmc/articles/PMC9428451/ /pubmed/36060630 http://dx.doi.org/10.3389/fspor.2022.931817 Text en Copyright © 2022 Li, Hopkins and Lipinska. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Sports and Active Living Li, Feifei Hopkins, Will G. Lipinska, Patrycja Population, economic and geographic predictors of nations' medal tallies at the Pyeongchang and Tokyo Olympics and Paralympics |
title | Population, economic and geographic predictors of nations' medal tallies at the Pyeongchang and Tokyo Olympics and Paralympics |
title_full | Population, economic and geographic predictors of nations' medal tallies at the Pyeongchang and Tokyo Olympics and Paralympics |
title_fullStr | Population, economic and geographic predictors of nations' medal tallies at the Pyeongchang and Tokyo Olympics and Paralympics |
title_full_unstemmed | Population, economic and geographic predictors of nations' medal tallies at the Pyeongchang and Tokyo Olympics and Paralympics |
title_short | Population, economic and geographic predictors of nations' medal tallies at the Pyeongchang and Tokyo Olympics and Paralympics |
title_sort | population, economic and geographic predictors of nations' medal tallies at the pyeongchang and tokyo olympics and paralympics |
topic | Sports and Active Living |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9428451/ https://www.ncbi.nlm.nih.gov/pubmed/36060630 http://dx.doi.org/10.3389/fspor.2022.931817 |
work_keys_str_mv | AT lifeifei populationeconomicandgeographicpredictorsofnationsmedaltalliesatthepyeongchangandtokyoolympicsandparalympics AT hopkinswillg populationeconomicandgeographicpredictorsofnationsmedaltalliesatthepyeongchangandtokyoolympicsandparalympics AT lipinskapatrycja populationeconomicandgeographicpredictorsofnationsmedaltalliesatthepyeongchangandtokyoolympicsandparalympics |