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Article: A comparison between two models for predicting ordering probabilities in multiple-entry competitions

TitleA comparison between two models for predicting ordering probabilities in multiple-entry competitions
Authors
KeywordsHorse-races
Logit model
Ordering probability
Running time distributions
Issue Date1994
PublisherWiley-Blackwell Publishing Ltd. The Journal's web site is located at http://www.blackwellpublishing.com/journal.asp?ref=0039-0526&site=1
Citation
Journal of the Royal Statistical Society. Series D: The Statistician, 1994, v. 43 n. 2, p. 317-327 How to Cite?
AbstractSUMMARY To predict ordering probabilities of a multiple-entry competition (e.g. a horse-race), two models have been proposed. Harville proposed a simple and convenient model that can easily be used in practice. Henery proposed a more sophisticated model but it has no closed form solution. In this paper, we empirically compare the two models by using a series of logit models applied to horse-racing data. In horse-racing, many previous studies claimed that the win bet fraction is a reasonable estimate of the winning probability. To consider complicated bet types which involve more than one position, ordering probabilities (e.g. P(horse i wins and horsej finishes 2nd)) are required. The Harville and Henery models assume different running time distributions and produce different sets of ordering probabilities. This paper illustrates that the Harville model is not always as good as the Henery model in predicting ordering probabilities. The theoretical result concludes that, if the running time of every horse is normally distributed, the probabilities produced by the Harville model have a systematic bias for the strongest and weakest horses. We concentrate on the horse-racing case but the methodology can be applied to other multiple-entry competitions.
Persistent Identifierhttp://hdl.handle.net/10722/86405
ISSN
2005 Impact Factor: 0.833

 

DC FieldValueLanguage
dc.contributor.authorLo, VSY-
dc.contributor.authorBacon-Shone, J-
dc.date.accessioned2010-09-06T09:16:27Z-
dc.date.available2010-09-06T09:16:27Z-
dc.date.issued1994-
dc.identifier.citationJournal of the Royal Statistical Society. Series D: The Statistician, 1994, v. 43 n. 2, p. 317-327-
dc.identifier.issn0039-0526-
dc.identifier.urihttp://hdl.handle.net/10722/86405-
dc.description.abstractSUMMARY To predict ordering probabilities of a multiple-entry competition (e.g. a horse-race), two models have been proposed. Harville proposed a simple and convenient model that can easily be used in practice. Henery proposed a more sophisticated model but it has no closed form solution. In this paper, we empirically compare the two models by using a series of logit models applied to horse-racing data. In horse-racing, many previous studies claimed that the win bet fraction is a reasonable estimate of the winning probability. To consider complicated bet types which involve more than one position, ordering probabilities (e.g. P(horse i wins and horsej finishes 2nd)) are required. The Harville and Henery models assume different running time distributions and produce different sets of ordering probabilities. This paper illustrates that the Harville model is not always as good as the Henery model in predicting ordering probabilities. The theoretical result concludes that, if the running time of every horse is normally distributed, the probabilities produced by the Harville model have a systematic bias for the strongest and weakest horses. We concentrate on the horse-racing case but the methodology can be applied to other multiple-entry competitions.-
dc.languageeng-
dc.publisherWiley-Blackwell Publishing Ltd. The Journal's web site is located at http://www.blackwellpublishing.com/journal.asp?ref=0039-0526&site=1-
dc.relation.ispartofJournal of the Royal Statistical Society. Series D: The Statistician-
dc.rightsPreprint This is the pre-peer reviewed version of the following article: [FULL CITE], which has been published in final form at [Link to final article]. Authors are not required to remove preprints posted prior to acceptance of the submitted version. Postprint This is the accepted version of the following article: [full citation], which has been published in final form at [Link to final article]. -
dc.subjectHorse-races-
dc.subjectLogit model-
dc.subjectOrdering probability-
dc.subjectRunning time distributions-
dc.titleA comparison between two models for predicting ordering probabilities in multiple-entry competitions-
dc.typeArticle-
dc.identifier.emailBacon-Shone, J: johnbs@hkucc.hku.hk-
dc.identifier.authorityBacon-Shone, J=rp00056-
dc.identifier.doi10.2307/2348347-
dc.identifier.hkuros12407-
dc.identifier.volume43-
dc.identifier.issue2-
dc.identifier.spage317-
dc.identifier.epage327-
dc.publisher.placeUnited Kingdom-

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