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Journal of Quantitative Analysis in Sports

An official journal of the American Statistical Association

Editor-in-Chief: Steve Rigdon, PhD

4 Issues per year


CiteScore 2016: 0.44

SCImago Journal Rank (SJR) 2015: 0.288
Source Normalized Impact per Paper (SNIP) 2015: 0.358

Online
ISSN
1559-0410
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Probability and Statistical Models for Racing

Victor S Lo / John Bacon-Shone
Published Online: 2008-04-28 | DOI: https://doi.org/10.2202/1559-0410.1103

Racing data provides a rich source of analysis for quantitative researchers to study multi-entry competitions. This paper first explores statistical modeling to investigate the favorite-longshot betting bias using world-wide horse race data. The result shows that the bias phenomenon is not universal. Economic interpretation using utility theory will also be provided. Additionally, previous literature have proposed various probability distributions to model racing running time in order to estimate higher order probabilities such as probabilities of finishing second and third. We extend the normal distribution assumption to include certain correlation and variance structure and apply the extended model to actual data. While horse race data is used in this paper, the methodologies can be applied to other types of racing data such as cars and dogs.

Keywords: favorite-longshot bias; ordering probability; running time distribution; horse race

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Published Online: 2008-04-28


Citation Information: Journal of Quantitative Analysis in Sports, ISSN (Online) 1559-0410, DOI: https://doi.org/10.2202/1559-0410.1103.

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©2011 Walter de Gruyter GmbH & Co. KG, Berlin/Boston. Copyright Clearance Center

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