To lead or not to lead: analysis of the sprint in track cycling

Moffatt Joanne, Scarf Phil (), Passfield Louis, McHale Ian G. and Zhang Kui
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Moffatt Joanne: Salford Business School, University of Salford, Salford, M5 4WT, UK
Scarf Phil: Salford Business School, University of Salford, Salford, M5 4WT, UK
Passfield Louis: School of Sport & Exercise Sciences, University of Kent at Medway Chatham, Kent ME4 4AG, UK
McHale Ian G.: Salford Business School, University of Salford, Salford, M5 4WT, UK
Zhang Kui: Wuhan Polytechnic University, Wuhan 430023, Hubei, China

Journal of Quantitative Analysis in Sports, 2014, vol. 10, issue 2, 161-172

Abstract: This paper uses a statistical analysis of match sprint outcomes to guide tactical decisions in this highly tactical contest and to provide competitors and coaches with a potential, marginal gain. Logistic regression models are developed to predict the probability of the leading rider winning at different points of the race, based on how the race proceeds up to each point. Key tactics are successfully identified from the models, including how the leading rider might hold the lead and how the following rider might optimize overtaking.

Keywords: logistic regression; strategy; tactics (search for similar items in EconPapers)
Date: 2014
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DOI: 10.1515/jqas-2013-0112

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