The Best Are Always the Best: COVID-19 Lockdown Stringency and the Dispersion of Olympic Medal Outcomes

📅 2026-08-17
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🤖 AI Summary
This study investigates the impact of COVID-19 lockdown stringency on national Olympic performance and medal distribution. Analyzing data from 99 countries alongside the Oxford Stringency Index through OLS regression and ANOVA, we find that while lockdowns did not alter global average competitive standards, they significantly exacerbated medal dispersion in men’s events among non-traditional sporting powers. Specifically, high-stringency conditions increased this dispersion three- to six-fold. These findings reveal that external shocks preserve established competitive hierarchies while amplifying performance uncertainty for disadvantaged teams. Consequently, this work provides novel evidence regarding the heterogeneous effects of public health emergencies on equity in elite sports competition, highlighting how systemic disruptions disproportionately affect marginal participants without necessarily diminishing overall global performance levels.
📝 Abstract
We ask whether COVID-19 lockdown stringency altered national Olympic performance between Rio 2016 and Tokyo 2020, using the Oxford Stringency Index and the 99 countries that won a medal in either edition. As in \citet{liu2024}, mean performance is unaffected: stringency is insignificant in every OLS and ANOVA specification. The distribution is not. Among the 84 non-traditionally dominant nations, medal changes are three to six times more dispersed in high-stringency countries; the difference is absent among dominant nations and concentrated in men's events. A common shock left the competitive hierarchy intact while sharply raising outcome uncertainty for smaller Olympic teams.
Problem

Research questions and friction points this paper is trying to address.

COVID-19 lockdown stringency
Olympic medal outcomes
performance dispersion
competitive hierarchy
Innovation

Methods, ideas, or system contributions that make the work stand out.

Lockdown Stringency
Medal Dispersion
Outcome Uncertainty
Oxford Stringency Index
Competitive Hierarchy
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Fernando Delbianco
Departamento de Economía, Universidad Nacional del Sur (UNS), Bahía Blanca, Argentina; Instituto de Matemática Bahía Blanca (INMABB), CONICET, Bahía Blanca, Argentina
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Federico Fioravanti
Associate Professor, GATE, Saint Étienne School of Economics, Jean Monnet University
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Fernando Tohmé
Departamento de Economía, Universidad Nacional del Sur (UNS), Bahía Blanca, Argentina; Instituto de Matemática Bahía Blanca (INMABB), CONICET, Bahía Blanca, Argentina