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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| Format: | Conference or Workshop Item |
| Language: | en |
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2023
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| 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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| _version_ | 1833419803434418176 |
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| author | Kang, Yue Teng Che Him, Norziha |
| author_facet | Kang, Yue Teng Che Him, Norziha |
| author_sort | Kang, Yue Teng |
| building | UTHM Library |
| collection | Institutional Repository |
| content_provider | Universiti Tun Hussein Onn Malaysia |
| content_source | UTHM Institutional Repository |
| continent | Asia |
| country | Malaysia |
| 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 |
| id | my.uthm.eprints-12485 |
| institution | Universiti Tun Hussein Onn Malaysia |
| language | en |
| publishDate | 2023 |
| record_format | eprints |
| 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 |
| spellingShingle | QA Mathematics Kang, Yue Teng Che Him, Norziha The Poisson Regression and Quasi-Poisson Regression Analysis on FIFA World Cup Games |
| title | 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_short | 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 |
| topic | QA Mathematics |
| 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 |
| url_provider | http://eprints.uthm.edu.my/ |