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The Poisson Regression and Quasi-Poisson Regression Analysis on FIFA World Cup Games

The FIFA World Cup's surging popularity has attracted a diverse fan base, including passionate enthusiasts in Malaysia. This widespread interest has motivated researchers to delve into the details of the tournament, using it as a crucial platform for predictions, team performance evalua...

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Main Authors: Kang, Yue Teng, Che Him, Norziha
Format: Conference or Workshop Item
Language:English
Published: 2023
Subjects:
QA Mathematics
Online Access:http://eprints.uthm.edu.my/12485/1/P17880_012cee6c36971a5dc5ed3405996a084d.pdf
http://eprints.uthm.edu.my/12485/
https://smpu.uthm.edu.my/uploads/P17880_012cee6c36971a5dc5ed3405996a084d.pdf
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spelling my.uthm.eprints.124852025-02-24T02:02:32Z http://eprints.uthm.edu.my/12485/ The Poisson Regression and Quasi-Poisson Regression Analysis on FIFA World Cup Games Kang, Yue Teng Che Him, Norziha QA Mathematics The FIFA World Cup's surging popularity has attracted a diverse fan base, including passionate enthusiasts in Malaysia. This widespread interest has motivated researchers to delve into the details of the tournament, using it as a crucial platform for predictions, team performance evaluations, and an exploration of international football competition at its top. This study aims to predict number of goals in World Cup matches, employing Poisson and quasi-Poisson regression models. The optimal model is determined through a comprehensive assessment, considering AIC, BIC, standard error, and p-values. Utilizing a dataset from Kaggle, originally sourced from the official FIFA website, the findings consistently associate variables such as goal inside the penalty area, goal outside the penalty area, left inside channel, right channel, attempted defensive line breaks, completed defensive line breaks, yellow cards, passes, and own goals with a raised probability of number of goals. Significantly, the quasi-Poisson model exhibits a superior fit, as evidenced by its lower AIC value of -50.0853 and a reduced deviance value of 38.7935. Consequently, the quasi-Poisson regression model emerges as a more suitable choice than the Poisson regression model, particularly for addressing the overdispersion inherent in the data. 2023 Conference or Workshop Item PeerReviewed text en http://eprints.uthm.edu.my/12485/1/P17880_012cee6c36971a5dc5ed3405996a084d.pdf Kang, Yue Teng and Che Him, Norziha (2023) The Poisson Regression and Quasi-Poisson Regression Analysis on FIFA World Cup Games. In: ENHANCED KNOWLEDGE IN SCIENCES AND TECHNOLOGY. https://smpu.uthm.edu.my/uploads/P17880_012cee6c36971a5dc5ed3405996a084d.pdf
institution Universiti Tun Hussein Onn Malaysia
building UTHM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Tun Hussein Onn Malaysia
content_source UTHM Institutional Repository
url_provider http://eprints.uthm.edu.my/
language English
topic QA Mathematics
spellingShingle QA Mathematics
Kang, Yue Teng
Che Him, Norziha
The Poisson Regression and Quasi-Poisson Regression Analysis on FIFA World Cup Games
description The FIFA World Cup's surging popularity has attracted a diverse fan base, including passionate enthusiasts in Malaysia. This widespread interest has motivated researchers to delve into the details of the tournament, using it as a crucial platform for predictions, team performance evaluations, and an exploration of international football competition at its top. This study aims to predict number of goals in World Cup matches, employing Poisson and quasi-Poisson regression models. The optimal model is determined through a comprehensive assessment, considering AIC, BIC, standard error, and p-values. Utilizing a dataset from Kaggle, originally sourced from the official FIFA website, the findings consistently associate variables such as goal inside the penalty area, goal outside the penalty area, left inside channel, right channel, attempted defensive line breaks, completed defensive line breaks, yellow cards, passes, and own goals with a raised probability of number of goals. Significantly, the quasi-Poisson model exhibits a superior fit, as evidenced by its lower AIC value of -50.0853 and a reduced deviance value of 38.7935. Consequently, the quasi-Poisson regression model emerges as a more suitable choice than the Poisson regression model, particularly for addressing the overdispersion inherent in the data.
format Conference or Workshop Item
author Kang, Yue Teng
Che Him, Norziha
author_facet Kang, Yue Teng
Che Him, Norziha
author_sort Kang, Yue Teng
title The Poisson Regression and Quasi-Poisson Regression Analysis on FIFA World Cup Games
title_short The Poisson Regression and Quasi-Poisson Regression Analysis on FIFA World Cup Games
title_full The Poisson Regression and Quasi-Poisson Regression Analysis on FIFA World Cup Games
title_fullStr The Poisson Regression and Quasi-Poisson Regression Analysis on FIFA World Cup Games
title_full_unstemmed The Poisson Regression and Quasi-Poisson Regression Analysis on FIFA World Cup Games
title_sort poisson regression and quasi-poisson regression analysis on fifa world cup games
publishDate 2023
url http://eprints.uthm.edu.my/12485/1/P17880_012cee6c36971a5dc5ed3405996a084d.pdf
http://eprints.uthm.edu.my/12485/
https://smpu.uthm.edu.my/uploads/P17880_012cee6c36971a5dc5ed3405996a084d.pdf
_version_ 1825163116864864256
score 13.244413

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