Forecasting number of corner kicks taken in association football using compound Poisson distribution
This article presents a holistic compound Poisson regression model framework to forecast number of corner kicks taken in association football. Corner kick taken events are often decisive in the match outcome and inherently arrive in batch with serial clustering pattern. Providing parameter estimates...
Gespeichert in:
Veröffentlicht in: | arXiv.org 2023-11 |
---|---|
Hauptverfasser: | , , , |
Format: | Artikel |
Sprache: | eng |
Schlagworte: | |
Online-Zugang: | Volltext |
Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
container_end_page | |
---|---|
container_issue | |
container_start_page | |
container_title | arXiv.org |
container_volume | |
creator | Yip, Stan Zou, Yinghong Ronald Tsz Hin Hung Ka Fai Cedric Yiu |
description | This article presents a holistic compound Poisson regression model framework to forecast number of corner kicks taken in association football. Corner kick taken events are often decisive in the match outcome and inherently arrive in batch with serial clustering pattern. Providing parameter estimates with intuitive interpretation, a class of compound Poisson regression including a Bayesian implementation of geometric-Poisson distribution is introduced. With a varying shape parameter, the corner counts serial correlation between matches is handled naturally within the Bayesian model. In this study, information elicited from cross-market betting odds was used to improve the model predictability. Margin application methods to adjust market inefficiency in raw odds are also discussed. |
format | Article |
fullrecord | <record><control><sourceid>proquest</sourceid><recordid>TN_cdi_proquest_journals_2614933530</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>2614933530</sourcerecordid><originalsourceid>FETCH-proquest_journals_26149335303</originalsourceid><addsrcrecordid>eNqNy8EKwjAQBNAgCBb1HxY8CzVpq55F8ejBu6RpKmvb3ZpN_t8KfoCnGZg3M5VpY3bbQ6H1Qq1FXnme62qvy9Jkqrlw8M5KRHoCpaH2AbgFx4Gm1qHrBKLtPAESWBF2aCMyQcsca9v3kOR7dTyMnKiBG-OkCBqUGLBOX7xS89b24te_XKrN5Xw_Xbdj4HfyEh8vToGm6aGrXXE0pjS5-U99ALeSR5I</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2614933530</pqid></control><display><type>article</type><title>Forecasting number of corner kicks taken in association football using compound Poisson distribution</title><source>Free E- Journals</source><creator>Yip, Stan ; Zou, Yinghong ; Ronald Tsz Hin Hung ; Ka Fai Cedric Yiu</creator><creatorcontrib>Yip, Stan ; Zou, Yinghong ; Ronald Tsz Hin Hung ; Ka Fai Cedric Yiu</creatorcontrib><description>This article presents a holistic compound Poisson regression model framework to forecast number of corner kicks taken in association football. Corner kick taken events are often decisive in the match outcome and inherently arrive in batch with serial clustering pattern. Providing parameter estimates with intuitive interpretation, a class of compound Poisson regression including a Bayesian implementation of geometric-Poisson distribution is introduced. With a varying shape parameter, the corner counts serial correlation between matches is handled naturally within the Bayesian model. In this study, information elicited from cross-market betting odds was used to improve the model predictability. Margin application methods to adjust market inefficiency in raw odds are also discussed.</description><identifier>EISSN: 2331-8422</identifier><language>eng</language><publisher>Ithaca: Cornell University Library, arXiv.org</publisher><subject>Parameter estimation ; Poisson density functions ; Poisson distribution ; Regression models ; Statistical analysis</subject><ispartof>arXiv.org, 2023-11</ispartof><rights>2023. This work is published under http://creativecommons.org/licenses/by-nc-nd/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>776,780</link.rule.ids></links><search><creatorcontrib>Yip, Stan</creatorcontrib><creatorcontrib>Zou, Yinghong</creatorcontrib><creatorcontrib>Ronald Tsz Hin Hung</creatorcontrib><creatorcontrib>Ka Fai Cedric Yiu</creatorcontrib><title>Forecasting number of corner kicks taken in association football using compound Poisson distribution</title><title>arXiv.org</title><description>This article presents a holistic compound Poisson regression model framework to forecast number of corner kicks taken in association football. Corner kick taken events are often decisive in the match outcome and inherently arrive in batch with serial clustering pattern. Providing parameter estimates with intuitive interpretation, a class of compound Poisson regression including a Bayesian implementation of geometric-Poisson distribution is introduced. With a varying shape parameter, the corner counts serial correlation between matches is handled naturally within the Bayesian model. In this study, information elicited from cross-market betting odds was used to improve the model predictability. Margin application methods to adjust market inefficiency in raw odds are also discussed.</description><subject>Parameter estimation</subject><subject>Poisson density functions</subject><subject>Poisson distribution</subject><subject>Regression models</subject><subject>Statistical analysis</subject><issn>2331-8422</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2023</creationdate><recordtype>article</recordtype><sourceid>BENPR</sourceid><recordid>eNqNy8EKwjAQBNAgCBb1HxY8CzVpq55F8ejBu6RpKmvb3ZpN_t8KfoCnGZg3M5VpY3bbQ6H1Qq1FXnme62qvy9Jkqrlw8M5KRHoCpaH2AbgFx4Gm1qHrBKLtPAESWBF2aCMyQcsca9v3kOR7dTyMnKiBG-OkCBqUGLBOX7xS89b24te_XKrN5Xw_Xbdj4HfyEh8vToGm6aGrXXE0pjS5-U99ALeSR5I</recordid><startdate>20231106</startdate><enddate>20231106</enddate><creator>Yip, Stan</creator><creator>Zou, Yinghong</creator><creator>Ronald Tsz Hin Hung</creator><creator>Ka Fai Cedric Yiu</creator><general>Cornell University Library, arXiv.org</general><scope>8FE</scope><scope>8FG</scope><scope>ABJCF</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>BGLVJ</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>HCIFZ</scope><scope>L6V</scope><scope>M7S</scope><scope>PHGZM</scope><scope>PHGZT</scope><scope>PIMPY</scope><scope>PKEHL</scope><scope>PQEST</scope><scope>PQGLB</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>PTHSS</scope></search><sort><creationdate>20231106</creationdate><title>Forecasting number of corner kicks taken in association football using compound Poisson distribution</title><author>Yip, Stan ; Zou, Yinghong ; Ronald Tsz Hin Hung ; Ka Fai Cedric Yiu</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-proquest_journals_26149335303</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2023</creationdate><topic>Parameter estimation</topic><topic>Poisson density functions</topic><topic>Poisson distribution</topic><topic>Regression models</topic><topic>Statistical analysis</topic><toplevel>online_resources</toplevel><creatorcontrib>Yip, Stan</creatorcontrib><creatorcontrib>Zou, Yinghong</creatorcontrib><creatorcontrib>Ronald Tsz Hin Hung</creatorcontrib><creatorcontrib>Ka Fai Cedric Yiu</creatorcontrib><collection>ProQuest SciTech Collection</collection><collection>ProQuest Technology Collection</collection><collection>Materials Science & Engineering Collection</collection><collection>ProQuest Central (Alumni Edition)</collection><collection>ProQuest Central UK/Ireland</collection><collection>ProQuest Central Essentials</collection><collection>ProQuest Central</collection><collection>Technology Collection</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central Korea</collection><collection>SciTech Premium Collection</collection><collection>ProQuest Engineering Collection</collection><collection>Engineering Database</collection><collection>ProQuest Central (New)</collection><collection>ProQuest One Academic (New)</collection><collection>Publicly Available Content Database</collection><collection>ProQuest One Academic Middle East (New)</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Applied & Life Sciences</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central China</collection><collection>Engineering Collection</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Yip, Stan</au><au>Zou, Yinghong</au><au>Ronald Tsz Hin Hung</au><au>Ka Fai Cedric Yiu</au><format>book</format><genre>document</genre><ristype>GEN</ristype><atitle>Forecasting number of corner kicks taken in association football using compound Poisson distribution</atitle><jtitle>arXiv.org</jtitle><date>2023-11-06</date><risdate>2023</risdate><eissn>2331-8422</eissn><abstract>This article presents a holistic compound Poisson regression model framework to forecast number of corner kicks taken in association football. Corner kick taken events are often decisive in the match outcome and inherently arrive in batch with serial clustering pattern. Providing parameter estimates with intuitive interpretation, a class of compound Poisson regression including a Bayesian implementation of geometric-Poisson distribution is introduced. With a varying shape parameter, the corner counts serial correlation between matches is handled naturally within the Bayesian model. In this study, information elicited from cross-market betting odds was used to improve the model predictability. Margin application methods to adjust market inefficiency in raw odds are also discussed.</abstract><cop>Ithaca</cop><pub>Cornell University Library, arXiv.org</pub><oa>free_for_read</oa></addata></record> |
fulltext | fulltext |
identifier | EISSN: 2331-8422 |
ispartof | arXiv.org, 2023-11 |
issn | 2331-8422 |
language | eng |
recordid | cdi_proquest_journals_2614933530 |
source | Free E- Journals |
subjects | Parameter estimation Poisson density functions Poisson distribution Regression models Statistical analysis |
title | Forecasting number of corner kicks taken in association football using compound Poisson distribution |
url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-02-21T21%3A58%3A01IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest&rft_val_fmt=info:ofi/fmt:kev:mtx:book&rft.genre=document&rft.atitle=Forecasting%20number%20of%20corner%20kicks%20taken%20in%20association%20football%20using%20compound%20Poisson%20distribution&rft.jtitle=arXiv.org&rft.au=Yip,%20Stan&rft.date=2023-11-06&rft.eissn=2331-8422&rft_id=info:doi/&rft_dat=%3Cproquest%3E2614933530%3C/proquest%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=2614933530&rft_id=info:pmid/&rfr_iscdi=true |