An Extreme-Value Model for Predicting the Results of Horse Races
Results of horse races in 1979-80 are analysed to see if the extreme-value distribution can model the times to run horse races: horses with the same bookmakers' odds of winning are classed as one group; the distribution of times for each group is extreme-value with location parameter β dependin...
Gespeichert in:
| Veröffentlicht in: | Applied Statistics 1984-01, Vol.33 (2), p.125-133 |
|---|---|
| 1. Verfasser: | |
| Format: | Artikel |
| Sprache: | eng |
| Schlagworte: | |
| Online-Zugang: | Volltext |
| Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
| container_end_page | 133 |
|---|---|
| container_issue | 2 |
| container_start_page | 125 |
| container_title | Applied Statistics |
| container_volume | 33 |
| creator | Henery, R. J. |
| description | Results of horse races in 1979-80 are analysed to see if the extreme-value distribution can model the times to run horse races: horses with the same bookmakers' odds of winning are classed as one group; the distribution of times for each group is extreme-value with location parameter β depending on the win odds; and the scale parameter θ is common to all groups. The model predicts that the win probability p for the group is p = exp ((β0 - β)/θ) for some constant β0, and this is borne out by the data. Only the tail of the empirical distribution functions is consistent with the model; however, it is essentially this tail which determines the win probabilities, so if the aim is to do just that the model will serve a useful purpose. |
| doi_str_mv | 10.2307/2347436 |
| format | Article |
| fullrecord | <record><control><sourceid>jstor_proqu</sourceid><recordid>TN_cdi_proquest_journals_1299677473</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><jstor_id>2347436</jstor_id><sourcerecordid>2347436</sourcerecordid><originalsourceid>FETCH-LOGICAL-c2804-7e2ac73efaea31bcc08f946c4b4e388db28e4c80e4d96482d3801955cfb998cf3</originalsourceid><addsrcrecordid>eNp1kF1LwzAUhoMoOKf4FwIKXnXmq01y5xjTCYqyqbclTU-0o2tm0qL791Y29Grn5oXDw_PCi9A5JSPGibxmXEjBswM0oCKTiVYyO0QDQniaaJaKY3QS45L0R4kYoJtxg6ffbYAVJG-m7gA_-hJq7HzAzwHKyrZV847bD8BziF3dRuwdnvkQ-4exEE_RkTN1hLNdDtHr7fRlMksenu7uJ-OHxDJFRCKBGSs5OAOG08JaopwWmRWFAK5UWTAFwioCotSZUKzkilCdptYVWivr-BBdbL3r4D87iG2-9F1o-sqcMq0zKYXkPXW1pWzwMQZw-TpUKxM2OSX57zz5bp6evNz5TLSmdsE0top_uFKSCkl6bLTFvqoaNvts-XyxmBCqqPj3LmPrw976H0tbes8</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>1299677473</pqid></control><display><type>article</type><title>An Extreme-Value Model for Predicting the Results of Horse Races</title><source>Jstor Complete Legacy</source><source>Periodicals Index Online</source><source>JSTOR Mathematics & Statistics</source><source>EBSCOhost Business Source Complete</source><creator>Henery, R. J.</creator><creatorcontrib>Henery, R. J.</creatorcontrib><description>Results of horse races in 1979-80 are analysed to see if the extreme-value distribution can model the times to run horse races: horses with the same bookmakers' odds of winning are classed as one group; the distribution of times for each group is extreme-value with location parameter β depending on the win odds; and the scale parameter θ is common to all groups. The model predicts that the win probability p for the group is p = exp ((β0 - β)/θ) for some constant β0, and this is borne out by the data. Only the tail of the empirical distribution functions is consistent with the model; however, it is essentially this tail which determines the win probabilities, so if the aim is to do just that the model will serve a useful purpose.</description><identifier>ISSN: 0035-9254</identifier><identifier>EISSN: 1467-9876</identifier><identifier>DOI: 10.2307/2347436</identifier><identifier>CODEN: APSTAG</identifier><language>eng</language><publisher>Oxford: Royal Statistical Society</publisher><subject>Applications ; Applied statistics ; Arithmetic mean ; Betting ; Disabilities ; Distribution functions ; Empirical distribution ; Estimate reliability ; Exact sciences and technology ; Extreme‐value ; Gambling ; Horse races ; Mathematics ; Modeling ; Probabilities ; Probability and statistics ; Sciences and techniques of general use ; Statistical variance ; Statistics ; Win probability</subject><ispartof>Applied Statistics, 1984-01, Vol.33 (2), p.125-133</ispartof><rights>Copyright Royal Statistical Society</rights><rights>1984 Royal Statistical Society</rights><rights>1985 INIST-CNRS</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c2804-7e2ac73efaea31bcc08f946c4b4e388db28e4c80e4d96482d3801955cfb998cf3</citedby></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.jstor.org/stable/pdf/2347436$$EPDF$$P50$$Gjstor$$H</linktopdf><linktohtml>$$Uhttps://www.jstor.org/stable/2347436$$EHTML$$P50$$Gjstor$$H</linktohtml><link.rule.ids>314,780,784,803,832,4024,27869,27923,27924,27925,58017,58021,58250,58254</link.rule.ids><backlink>$$Uhttp://pascal-francis.inist.fr/vibad/index.php?action=getRecordDetail&idt=8871470$$DView record in Pascal Francis$$Hfree_for_read</backlink></links><search><creatorcontrib>Henery, R. J.</creatorcontrib><title>An Extreme-Value Model for Predicting the Results of Horse Races</title><title>Applied Statistics</title><description>Results of horse races in 1979-80 are analysed to see if the extreme-value distribution can model the times to run horse races: horses with the same bookmakers' odds of winning are classed as one group; the distribution of times for each group is extreme-value with location parameter β depending on the win odds; and the scale parameter θ is common to all groups. The model predicts that the win probability p for the group is p = exp ((β0 - β)/θ) for some constant β0, and this is borne out by the data. Only the tail of the empirical distribution functions is consistent with the model; however, it is essentially this tail which determines the win probabilities, so if the aim is to do just that the model will serve a useful purpose.</description><subject>Applications</subject><subject>Applied statistics</subject><subject>Arithmetic mean</subject><subject>Betting</subject><subject>Disabilities</subject><subject>Distribution functions</subject><subject>Empirical distribution</subject><subject>Estimate reliability</subject><subject>Exact sciences and technology</subject><subject>Extreme‐value</subject><subject>Gambling</subject><subject>Horse races</subject><subject>Mathematics</subject><subject>Modeling</subject><subject>Probabilities</subject><subject>Probability and statistics</subject><subject>Sciences and techniques of general use</subject><subject>Statistical variance</subject><subject>Statistics</subject><subject>Win probability</subject><issn>0035-9254</issn><issn>1467-9876</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>1984</creationdate><recordtype>article</recordtype><sourceid>K30</sourceid><recordid>eNp1kF1LwzAUhoMoOKf4FwIKXnXmq01y5xjTCYqyqbclTU-0o2tm0qL791Y29Grn5oXDw_PCi9A5JSPGibxmXEjBswM0oCKTiVYyO0QDQniaaJaKY3QS45L0R4kYoJtxg6ffbYAVJG-m7gA_-hJq7HzAzwHKyrZV847bD8BziF3dRuwdnvkQ-4exEE_RkTN1hLNdDtHr7fRlMksenu7uJ-OHxDJFRCKBGSs5OAOG08JaopwWmRWFAK5UWTAFwioCotSZUKzkilCdptYVWivr-BBdbL3r4D87iG2-9F1o-sqcMq0zKYXkPXW1pWzwMQZw-TpUKxM2OSX57zz5bp6evNz5TLSmdsE0top_uFKSCkl6bLTFvqoaNvts-XyxmBCqqPj3LmPrw976H0tbes8</recordid><startdate>19840101</startdate><enddate>19840101</enddate><creator>Henery, R. J.</creator><general>Royal Statistical Society</general><general>Blackwell</general><general>Royal Statistical Society, etc</general><scope>IQODW</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>FMSEA</scope><scope>HAGHG</scope><scope>ICWRT</scope><scope>K30</scope><scope>PAAUG</scope><scope>PAWHS</scope><scope>PAWZZ</scope><scope>PAXOH</scope><scope>PBHAV</scope><scope>PBQSW</scope><scope>PBYQZ</scope><scope>PCIWU</scope><scope>PCMID</scope><scope>PCZJX</scope><scope>PDGRG</scope><scope>PDWWI</scope><scope>PETMR</scope><scope>PFVGT</scope><scope>PGXDX</scope><scope>PIHIL</scope><scope>PISVA</scope><scope>PJCTQ</scope><scope>PJTMS</scope><scope>PLCHJ</scope><scope>PMHAD</scope><scope>PNQDJ</scope><scope>POUND</scope><scope>PPLAD</scope><scope>PQAPC</scope><scope>PQCAN</scope><scope>PQCMW</scope><scope>PQEME</scope><scope>PQHKH</scope><scope>PQMID</scope><scope>PQNCT</scope><scope>PQNET</scope><scope>PQSCT</scope><scope>PQSET</scope><scope>PSVJG</scope><scope>PVMQY</scope><scope>PZGFC</scope></search><sort><creationdate>19840101</creationdate><title>An Extreme-Value Model for Predicting the Results of Horse Races</title><author>Henery, R. J.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c2804-7e2ac73efaea31bcc08f946c4b4e388db28e4c80e4d96482d3801955cfb998cf3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>1984</creationdate><topic>Applications</topic><topic>Applied statistics</topic><topic>Arithmetic mean</topic><topic>Betting</topic><topic>Disabilities</topic><topic>Distribution functions</topic><topic>Empirical distribution</topic><topic>Estimate reliability</topic><topic>Exact sciences and technology</topic><topic>Extreme‐value</topic><topic>Gambling</topic><topic>Horse races</topic><topic>Mathematics</topic><topic>Modeling</topic><topic>Probabilities</topic><topic>Probability and statistics</topic><topic>Sciences and techniques of general use</topic><topic>Statistical variance</topic><topic>Statistics</topic><topic>Win probability</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Henery, R. J.</creatorcontrib><collection>Pascal-Francis</collection><collection>CrossRef</collection><collection>Periodicals Index Online Segment 05</collection><collection>Periodicals Index Online Segment 12</collection><collection>Periodicals Index Online Segment 28</collection><collection>Periodicals Index Online</collection><collection>Primary Sources Access—Foundation Edition (Plan E) - West</collection><collection>Primary Sources Access (Plan D) - International</collection><collection>Primary Sources Access & Build (Plan A) - MEA</collection><collection>Primary Sources Access—Foundation Edition (Plan E) - Midwest</collection><collection>Primary Sources Access—Foundation Edition (Plan E) - Northeast</collection><collection>Primary Sources Access (Plan D) - Southeast</collection><collection>Primary Sources Access (Plan D) - North Central</collection><collection>Primary Sources Access—Foundation Edition (Plan E) - Southeast</collection><collection>Primary Sources Access (Plan D) - South Central</collection><collection>Primary Sources Access & Build (Plan A) - UK / I</collection><collection>Primary Sources Access (Plan D) - Canada</collection><collection>Primary Sources Access (Plan D) - EMEALA</collection><collection>Primary Sources Access—Foundation Edition (Plan E) - North Central</collection><collection>Primary Sources Access—Foundation Edition (Plan E) - South Central</collection><collection>Primary Sources Access & Build (Plan A) - International</collection><collection>Primary Sources Access—Foundation Edition (Plan E) - International</collection><collection>Primary Sources Access (Plan D) - West</collection><collection>Periodicals Index Online Segments 1-50</collection><collection>Primary Sources Access (Plan D) - APAC</collection><collection>Primary Sources Access (Plan D) - Midwest</collection><collection>Primary Sources Access (Plan D) - MEA</collection><collection>Primary Sources Access—Foundation Edition (Plan E) - Canada</collection><collection>Primary Sources Access—Foundation Edition (Plan E) - UK / I</collection><collection>Primary Sources Access—Foundation Edition (Plan E) - EMEALA</collection><collection>Primary Sources Access & Build (Plan A) - APAC</collection><collection>Primary Sources Access & Build (Plan A) - Canada</collection><collection>Primary Sources Access & Build (Plan A) - West</collection><collection>Primary Sources Access & Build (Plan A) - EMEALA</collection><collection>Primary Sources Access (Plan D) - Northeast</collection><collection>Primary Sources Access & Build (Plan A) - Midwest</collection><collection>Primary Sources Access & Build (Plan A) - North Central</collection><collection>Primary Sources Access & Build (Plan A) - Northeast</collection><collection>Primary Sources Access & Build (Plan A) - South Central</collection><collection>Primary Sources Access & Build (Plan A) - Southeast</collection><collection>Primary Sources Access (Plan D) - UK / I</collection><collection>Primary Sources Access—Foundation Edition (Plan E) - APAC</collection><collection>Primary Sources Access—Foundation Edition (Plan E) - MEA</collection><jtitle>Applied Statistics</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Henery, R. J.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>An Extreme-Value Model for Predicting the Results of Horse Races</atitle><jtitle>Applied Statistics</jtitle><date>1984-01-01</date><risdate>1984</risdate><volume>33</volume><issue>2</issue><spage>125</spage><epage>133</epage><pages>125-133</pages><issn>0035-9254</issn><eissn>1467-9876</eissn><coden>APSTAG</coden><abstract>Results of horse races in 1979-80 are analysed to see if the extreme-value distribution can model the times to run horse races: horses with the same bookmakers' odds of winning are classed as one group; the distribution of times for each group is extreme-value with location parameter β depending on the win odds; and the scale parameter θ is common to all groups. The model predicts that the win probability p for the group is p = exp ((β0 - β)/θ) for some constant β0, and this is borne out by the data. Only the tail of the empirical distribution functions is consistent with the model; however, it is essentially this tail which determines the win probabilities, so if the aim is to do just that the model will serve a useful purpose.</abstract><cop>Oxford</cop><pub>Royal Statistical Society</pub><doi>10.2307/2347436</doi><tpages>9</tpages></addata></record> |
| fulltext | fulltext |
| identifier | ISSN: 0035-9254 |
| ispartof | Applied Statistics, 1984-01, Vol.33 (2), p.125-133 |
| issn | 0035-9254 1467-9876 |
| language | eng |
| recordid | cdi_proquest_journals_1299677473 |
| source | Jstor Complete Legacy; Periodicals Index Online; JSTOR Mathematics & Statistics; EBSCOhost Business Source Complete |
| subjects | Applications Applied statistics Arithmetic mean Betting Disabilities Distribution functions Empirical distribution Estimate reliability Exact sciences and technology Extreme‐value Gambling Horse races Mathematics Modeling Probabilities Probability and statistics Sciences and techniques of general use Statistical variance Statistics Win probability |
| title | An Extreme-Value Model for Predicting the Results of Horse Races |
| url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2024-12-25T02%3A26%3A39IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-jstor_proqu&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=An%20Extreme-Value%20Model%20for%20Predicting%20the%20Results%20of%20Horse%20Races&rft.jtitle=Applied%20Statistics&rft.au=Henery,%20R.%20J.&rft.date=1984-01-01&rft.volume=33&rft.issue=2&rft.spage=125&rft.epage=133&rft.pages=125-133&rft.issn=0035-9254&rft.eissn=1467-9876&rft.coden=APSTAG&rft_id=info:doi/10.2307/2347436&rft_dat=%3Cjstor_proqu%3E2347436%3C/jstor_proqu%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=1299677473&rft_id=info:pmid/&rft_jstor_id=2347436&rfr_iscdi=true |