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Article: A comparison between two models for predicting ordering probabilities in multi-entry competitions
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TitleA comparison between two models for predicting ordering probabilities in multi-entry competitions
 
AuthorsLo, VSY
Bacon-Shone, J
 
KeywordsOrdering probabilities
Running time distributions
Horse races
 
Issue Date1992
 
PublisherUniversity of Hong Kong. Dept. of Statistics.
 
CitationResearch Report, n. 17, p. 1-17 [How to Cite?]
 
AbstractTo predict ordering probabilities of a multi-entry comlpetition (e.g. horse race), two models have been proposed. Harville (1973) proposed a simple and convenient model that people can easily use in practice. Henery (1981) proposed a more sophisticated model but it has no closed form solution. In this paper, we empirically compare the two models 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 more complicated bet types (e.g. exacta, place & show), ordering probabilities (e.g. P(horse i wins and horse j finishes second)) are required. The Harville and Henery model assume different running time distribution 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 extreme cases (the strongest and weakest horses). We concentrate on horse-racing case but the methodology can he applied to other multi-entry competitions.
 
DC FieldValue
dc.contributor.authorLo, VSY
 
dc.contributor.authorBacon-Shone, J
 
dc.date.accessioned2010-06-02T04:42:15Z
 
dc.date.available2010-06-02T04:42:15Z
 
dc.date.issued1992
 
dc.description.abstractTo predict ordering probabilities of a multi-entry comlpetition (e.g. horse race), two models have been proposed. Harville (1973) proposed a simple and convenient model that people can easily use in practice. Henery (1981) proposed a more sophisticated model but it has no closed form solution. In this paper, we empirically compare the two models 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 more complicated bet types (e.g. exacta, place & show), ordering probabilities (e.g. P(horse i wins and horse j finishes second)) are required. The Harville and Henery model assume different running time distribution 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 extreme cases (the strongest and weakest horses). We concentrate on horse-racing case but the methodology can he applied to other multi-entry competitions.
 
dc.description.naturepostprint
 
dc.identifier.citationResearch Report, n. 17, p. 1-17 [How to Cite?]
 
dc.identifier.urihttp://hdl.handle.net/10722/60981
 
dc.language.isoeng
 
dc.publisherUniversity of Hong Kong. Dept. of Statistics.
 
dc.rightsAuthor holds the copyright
 
dc.rightsCreative Commons: Attribution 3.0 Hong Kong License
 
dc.subjectOrdering probabilities
 
dc.subjectRunning time distributions
 
dc.subjectHorse races
 
dc.titleA comparison between two models for predicting ordering probabilities in multi-entry competitions
 
dc.typeArticle
 
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<item><contributor.author>Lo, VSY</contributor.author>
<contributor.author>Bacon-Shone, J</contributor.author>
<date.accessioned>2010-06-02T04:42:15Z</date.accessioned>
<date.available>2010-06-02T04:42:15Z</date.available>
<date.issued>1992-06</date.issued>
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<description.abstract>To predict ordering probabilities of a multi-entry comlpetition (e.g. horse race), two models have been proposed. Harville (1973) proposed a simple and convenient model that people can easily use in practice. Henery (1981) proposed a more sophisticated model but it has no closed form solution. In this paper, we empirically compare the two models 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 more complicated bet types (e.g. exacta, place &amp; show), ordering probabilities (e.g. P(horse i wins and horse j finishes second)) are required. The Harville and Henery model assume different running time distribution and produce different sets of ordering probabilities. This paper illustrates that the&quot; 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 extreme cases (the strongest and weakest horses). We concentrate on horse-racing case but the methodology can he applied to other multi-entry competitions.</description.abstract>
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<rights>Creative Commons: Attribution 3.0 Hong Kong License</rights>
<subject>Ordering probabilities</subject>
<subject>Running time distributions</subject>
<subject>Horse races</subject>
<title>A comparison between two models for predicting ordering probabilities in multi-entry competitions</title>
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