Does relatedness drive the diversification of countries’ success in sports?

ABSTRACT

Research Question: The sources of countries’ success in sporting events have been investigated for a long time. In addition to socioeconomic factors, sport specialization and competitive balance have been identified as impacting medal yields. Nevertheless, there remains little understanding of how countries become successful in sports they did not succeed in before.

Research methods: We argue that the concept of related diversification, which is particularly popular in Evolutionary Economic Geography, can also be applied to sports and can help to explain in which sports countries become successful. We substantiate our argument with an empirical study of the evolution of national medal portfolios covering 61 sports at the Olympic Summer Games between 1896 and 2016 using this framework.

Results and findings: Our empirical findings quantify the relatedness of sports emerging from physical, financial, cultural, and organizational similarities. We confirm that diversification processes based on countries’ existing strengths in particular sports are a (small) driving force behind the Olympic success of countries and help to explain their success in sports in which they have been previously unsuccessful.

Implications: Our results highlight how examining hidden opportunities for diversification by incorporating sport-relatedness in a competitive positioning strategy can be informative for sport policy makers.

KEYWORDS:

• Relatedness
• Olympic Games
• diversification
• sport policy
• elite sport

Disclosure statement

No potential conflict of interest was reported by the author(s).

Notes

1 In this paper, the notion of ‘entry’ always describes the development of success/capabilities in a specific field (industry, sport, etc.) in which the entity (country, region) did not succeed previously. ‘Diversification’ is nearly synonymous in that respect. Diversification into a specific new activity can be called an ‘entry.’

2 74 out of 77 Jamaican Olympic medals were awarded in sprinting. 89 out of 102 Kenyan Olympic medals were awarded in endurance (800m to marathon) or 4 × 400 m relay (Olympic.org).

3 Bronze medals are awarded to both semi-finalists in some sports with knock-out system, like Judo and Taekwondo.

4 See Appendix 1 for a documentation of the aggregation.

5 De Bosscher et al. (2008) and Lui and Suen (2008) show that weighted and unweighted medal counts are highly correlated.

6 The non-random connections (ϕ>1) are inputted to the force-directed drawing algorithm (Fruchterman-Reingold), i.e. more similar sports are plotted more closely to each other. For all visualizations we use the statistical software R (package ‘igraph’ for network visualization [Csardi & Nepusz, 2006]).

7 This value has been chosen for purely aesthetic reasons.

8 Contrary to our measure, they divide the number of medal-winning countries by the number of participating countries in each sport. We believe that our measure is more reliable, as the entry barriers for participation are extremely different (sprinting vs. sailing), which might artificially increase the competitive imbalance for sprinting relative to sailing.

9 Population and GDP data are retrieved from the World Bank (2018). Gaps for few countries are filled with United Nations Data (2018) and the Taiwanese national statistics (2018). Population data are extrapolated with the previous and/or posterior growth rate for few missing country–year observations.

10 Raw coefficients in brackets. Coefficients transformed to odds ratios are written in percentages.

11 $e^{0.184}=1.202$. Calculation of odds-ratio from the log-odds (coefficients).

12 A few outliers with very large coefficients are excluded from Figure 3.