Prediction of football club winning rate using Bayesian model algorithm / Adam Khairul Anuar

This research explores football analytics in light of technological advancements. Football, a globally popular and financially significant sport, attracts substantial investments, especially in successful clubs. The study delves into Bayesian modeling for predicting football club winning rates, emph...

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Main Author:	Khairul Anuar, Adam
Format:	Thesis
Language:	English
Published:	2023
Subjects:	Bayesian statistics
Online Access:	https://ir.uitm.edu.my/id/eprint/95528/1/95528.pdf
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id	my-uitm-ir.95528
record_format	uketd_dc
spelling	my-uitm-ir.955282024-05-31T02:53:33Z Prediction of football club winning rate using Bayesian model algorithm / Adam Khairul Anuar 2023 Khairul Anuar, Adam Bayesian statistics This research explores football analytics in light of technological advancements. Football, a globally popular and financially significant sport, attracts substantial investments, especially in successful clubs. The study delves into Bayesian modeling for predicting football club winning rates, emphasizing the potential of integrating technology like multi-camera tracking and video assistance refereeing. Despite technological progress, a gap exists in fully incorporating big data into football analytics, which this research aims to address through Bayesian models. Objectives involve studying, developing, and evaluating the accuracy of a Bayesian model for predicting winning rates. The methodology includes preliminary studies, model prototyping, and evaluation using data from sources like Kaggle. Key results showcase a robust confusion matrix with metrics like True Positives, True Negatives, False Positives, False Negatives, Precision, Recall, and Accuracy. The evaluation involves K-fold cross-validation, indicating superior performance compared to Single Train-Test Split. Recommendations include continuous model training, detailed features, collaboration with experts, and exploring alternative algorithms. In essence, this research contributes to football analytics, offering a reliable Bayesian model for match outcome prediction. 2023 Thesis https://ir.uitm.edu.my/id/eprint/95528/ https://ir.uitm.edu.my/id/eprint/95528/1/95528.pdf text en public degree Universiti Teknologi MARA, Terengganu College of Computing, Informatics and Media Fadzal, Ahmad Nazmi
institution	Universiti Teknologi MARA
collection	UiTM Institutional Repository
language	English
advisor	Fadzal, Ahmad Nazmi
topic	Bayesian statistics
spellingShingle	Bayesian statistics Khairul Anuar, Adam Prediction of football club winning rate using Bayesian model algorithm / Adam Khairul Anuar
description	This research explores football analytics in light of technological advancements. Football, a globally popular and financially significant sport, attracts substantial investments, especially in successful clubs. The study delves into Bayesian modeling for predicting football club winning rates, emphasizing the potential of integrating technology like multi-camera tracking and video assistance refereeing. Despite technological progress, a gap exists in fully incorporating big data into football analytics, which this research aims to address through Bayesian models. Objectives involve studying, developing, and evaluating the accuracy of a Bayesian model for predicting winning rates. The methodology includes preliminary studies, model prototyping, and evaluation using data from sources like Kaggle. Key results showcase a robust confusion matrix with metrics like True Positives, True Negatives, False Positives, False Negatives, Precision, Recall, and Accuracy. The evaluation involves K-fold cross-validation, indicating superior performance compared to Single Train-Test Split. Recommendations include continuous model training, detailed features, collaboration with experts, and exploring alternative algorithms. In essence, this research contributes to football analytics, offering a reliable Bayesian model for match outcome prediction.
format	Thesis
qualification_level	Bachelor degree
author	Khairul Anuar, Adam
author_facet	Khairul Anuar, Adam
author_sort	Khairul Anuar, Adam
title	Prediction of football club winning rate using Bayesian model algorithm / Adam Khairul Anuar
title_short	Prediction of football club winning rate using Bayesian model algorithm / Adam Khairul Anuar
title_full	Prediction of football club winning rate using Bayesian model algorithm / Adam Khairul Anuar
title_fullStr	Prediction of football club winning rate using Bayesian model algorithm / Adam Khairul Anuar
title_full_unstemmed	Prediction of football club winning rate using Bayesian model algorithm / Adam Khairul Anuar
title_sort	prediction of football club winning rate using bayesian model algorithm / adam khairul anuar
granting_institution	Universiti Teknologi MARA, Terengganu
granting_department	College of Computing, Informatics and Media
publishDate	2023
url	https://ir.uitm.edu.my/id/eprint/95528/1/95528.pdf
_version_	1804889962675437568

Prediction of football club winning rate using Bayesian model algorithm / Adam Khairul Anuar

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