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Probability and Statistical Models for Racing

Author

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  • Lo Victor S

    (Fidelity Investments)

  • Bacon-Shone John

    (University of Hong Kong)

Abstract

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.

Suggested Citation

  • Lo Victor S & Bacon-Shone John, 2008. "Probability and Statistical Models for Racing," Journal of Quantitative Analysis in Sports, De Gruyter, vol. 4(2), pages 1-14, April.
    • Handle: RePEc:bpj:jqsprt:v:4:y:2008:i:2:n:11
    DOI: 10.2202/1559-0410.1103
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    References listed on IDEAS

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    1. Donald B. Hausch & William T. Ziemba & Mark Rubinstein, 1981. "Efficiency of the Market for Racetrack Betting," Management Science, INFORMS, vol. 27(12), pages 1435-1452, December.
    2. Hausch, Donald B. & Ziemba, W.T. (ed.), 2008. "Handbook of Sports and Lottery Markets," Elsevier Monographs, Elsevier, edition 1, number 9780444507440.
    3. Busche, Kelly & Hall, Christopher D, 1988. "An Exception to the Risk Preference Anomaly," The Journal of Business, University of Chicago Press, vol. 61(3), pages 337-346, July.
    4. Ruth N. Bolton & Randall G. Chapman, 2008. "Searching For Positive Returns At The Track: A Multinomial Logit Model For Handicapping Horse Races," World Scientific Book Chapters, in: Donald B Hausch & Victor SY Lo & William T Ziemba (ed.), Efficiency Of Racetrack Betting Markets, chapter 17, pages 151-171, World Scientific Publishing Co. Pte. Ltd..
    5. Ali, Mukhtar M, 1977. "Probability and Utility Estimates for Racetrack Bettors," Journal of Political Economy, University of Chicago Press, vol. 85(4), pages 803-815, August.
    6. Victor S. Y. Lo & John Bacon-Shone & Kelly Busche, 1995. "The Application of Ranking Probability Models to Racetrack Betting," Management Science, INFORMS, vol. 41(6), pages 1048-1059, June.
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    Cited by:

    1. Murphy, John T., 2012. "Exploring complexity with the Hohokam Water Management Simulation: A middle way for archaeological modeling," Ecological Modelling, Elsevier, vol. 241(C), pages 15-29.

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