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The determinants of success in Olympic and other multi-sport events


   Sport Industry Research Centre (SIRC)

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  Prof S Shibli, Dr G Ramchandani  Applications accepted all year round  Self-Funded PhD Students Only

About the Project

Proposed supervisory team:

Director of Studies: Professor Simon Shibli
Supervisor 1: Dr Girish Ramchandani

There is a long history of research that attempts to explain success in Olympic sport on the basis of macro-economic variables such as population and wealth as measured by Gross Domestic Product per capita. These simple regression models have traditionally explained around 50% of the variance in the dependent variables ’medals won’ or ’share of medals won’. However, as more nations take an increasingly proactive approach towards elite sport success, the explanatory power of macro-economic based models seems to be falling and the influence of sport-specific variables is increasing. Both Bernard and Busse (2004, 2008) and Forrest (2010) concur that lagged performance in previous games (t-1 to t-4) and nation-specific variables such as being the host nation impact positively and significantly on Olympic success. The proposed project will move existing knowledge in three key areas, as outlined below.

1. Different measures for the dependent variable
Traditionally the dependent variables used are either medals won or gold medals won, the latter of which is a proxy for ranking in the medals’ table. New research (Shibli, 2015) reveals that as the specificity of the dependent variable decreases - from gold medals, to total medals, to top eight places to the number of Olympians sent to the Games - so too does the explanatory power of traditional regression models. In short we are better at explaining broad measures rather than precise measures. This finding needs to be tested over a longer time series.

2. New sport specific variables
Our new research indicates that there are promising signs of new sport-specific variables adding to the efficacy of regression models. The notion of ’winning streaks, a proxy for nations taking a strategic approach to elite sport policy development has been shown to add around 4% to the explanatory power of regression models for total medals won. Similarly there is evidence that nations in receipt of ’wildcard’ entries for their Olympians are doing little more than making up the numbers. Consequently being in receipt of wildcards contributes positively to explaining the number of Olympians produced by a nation, but negatively in terms of medals (if any) such nations will win. We have strong hypotheses that new variables which require immense processing capability such as ’events contested’, ’medals contested’ and ’winning streaks in specific sports’ will yield new insight into how Olympic success is determined.

3. Replication in other multi-sport events
The final direction for this research is for it to be tested in new contexts such as the Olympic Winter Games and the Commonwealth Games, the latter of which we have a strong track record of research in since 2002.

Funding Notes

Home/EU and International students.

Please note there is no funding attached to this project. We are welcoming self-funded or sponsored students only.

All applicants should hold a good undergraduate degree (2:i or better) and ideally also a relevant Masters qualification.