After noting that population and gross domestic product (GDP) per capita were consistent predictors in previous research, these authors assembled a set of 144 potential predictors and used correlations among them to select population, GDP per capita, host country (prior, current and future), a civil-liberties index and absolute latitude as the main predictors of various measures of medal success in each Olympics between 20. Of the numerous studies of factors affecting nations' medal tallies in the summer Olympics, the most comprehensive is that of Grancay and Dudas (2018). Appropriate adjustment is also important for nations whose Olympic-funding decisions include consideration of performance of their athletes relative to that of other nations. ![]() Much of the popular media analysis of Olympic medal tallies is superficial, and academic efforts to move beyond this are vital to understanding structures, advantages and impediments to sports throughout the world. ![]() Ranking of nations based on medal tallies is an interesting feature of the Olympics, but such a ranking is a poor measure of sporting prowess or engagement until the tallies are adjusted for major factors beyond the control of individual nations. 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.Ĭonclusion: 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. 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). 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). 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). Nations were ranked on the basis of actual vs. The linear effect of Muslim proportion was expressed as the factor effect of 100% vs. The linear effect of absolute latitude was expressed and evaluated as the factor effect of 30° (approximately 2 SD). 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). Methods: The statistical model was multiple linear over-dispersed Poisson regression. 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. 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.
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