File Download
Supplementary

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

TitleA comparison between two models for predicting ordering probabilities in multi-entry competitions
Authors
KeywordsOrdering probabilities
Running time distributions
Horse races
Issue Date1992
PublisherUniversity of Hong Kong. Dept. of Statistics.
Citation
Research Report, 1992, 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.
Persistent Identifierhttp://hdl.handle.net/10722/60981

 

DC FieldValueLanguage
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.identifier.citationResearch Report, 1992, n. 17, p. 1-17en_HK
dc.identifier.urihttp://hdl.handle.net/10722/60981-
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.en_HK
dc.language.isoengen_HK
dc.publisherUniversity of Hong Kong. Dept. of Statistics.en_HK
dc.relation.ispartofResearch Report-
dc.rightsAuthor holds the copyright-
dc.rightsCreative Commons: Attribution 3.0 Hong Kong License-
dc.subjectOrdering probabilitiesen_HK
dc.subjectRunning time distributionsen_HK
dc.subjectHorse racesen_HK
dc.titleA comparison between two models for predicting ordering probabilities in multi-entry competitionsen_HK
dc.typeArticleen_HK
dc.description.naturepostprint-
dc.identifier.issue17-
dc.identifier.spage1-
dc.identifier.epage17-

Export via OAI-PMH Interface in XML Formats


OR


Export to Other Non-XML Formats