Bayesian approach to classification of football match outcome
The football match outcome prediction particularly has gained popularity in recent years. It attract lots type of fan from the analyst expert, managerial of football team and others to predict the football match result before the match start.There are three types of approaches had been proposed to p...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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Penerbit UTHM
2018
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| Online Access: | http://eprints.uthm.edu.my/4569/1/AJ%202018%20%28799%29%20Bayesian%20approach%20to%20classification%20of%20football%20match%20outcome.pdf |
| _version_ | 1796869044835450880 |
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| author | Abdul Rahman, Muhammad Haleq Azhar Mustapha, Aida Fauzi, Rahmat Razali, Nazim |
| author_facet | Abdul Rahman, Muhammad Haleq Azhar Mustapha, Aida Fauzi, Rahmat Razali, Nazim |
| author_sort | Abdul Rahman, Muhammad Haleq Azhar |
| collection | UTHM |
| description | The football match outcome prediction particularly has gained popularity in recent years. It attract lots type of fan from the analyst expert, managerial of football team and others to predict the football match result before the match start.There are three types of approaches had been proposed to predict win, lose or draw; and evaluate the attributes of the football team. The approaches are statistical approach, machine learningapproach and Bayesian approach. This paper propose the Bayesian approaches within machine learning approaches such as Naive Bayes (NB), Tree Augmented Naive Bayes (TAN) and General Bayesian Network (K2) to predict the football match outcome. The required of football data is the English Premier League match results for three seasons; 2016 – 2017, 2015 – 2016 and 2014 – 2015 downloaded from http://www.football-data.co.uk. The experimental results showed that TAN achieved the highest predictive accuracy of 90.0 % in average across three seasons among others Bayesian approach (K2 and NB). The result from this research is hope that it can be used in future research for predicting the football match outcome. |
| first_indexed | 2024-03-05T21:48:56Z |
| format | Article |
| id | uthm.eprints-4569 |
| institution | Universiti Tun Hussein Onn Malaysia |
| language | English |
| last_indexed | 2024-03-05T21:48:56Z |
| publishDate | 2018 |
| publisher | Penerbit UTHM |
| record_format | dspace |
| spelling | uthm.eprints-45692021-12-07T07:44:22Z http://eprints.uthm.edu.my/4569/ Bayesian approach to classification of football match outcome Abdul Rahman, Muhammad Haleq Azhar Mustapha, Aida Fauzi, Rahmat Razali, Nazim QA273-280 Probabilities. Mathematical statistics TA329-348 Engineering mathematics. Engineering analysis The football match outcome prediction particularly has gained popularity in recent years. It attract lots type of fan from the analyst expert, managerial of football team and others to predict the football match result before the match start.There are three types of approaches had been proposed to predict win, lose or draw; and evaluate the attributes of the football team. The approaches are statistical approach, machine learningapproach and Bayesian approach. This paper propose the Bayesian approaches within machine learning approaches such as Naive Bayes (NB), Tree Augmented Naive Bayes (TAN) and General Bayesian Network (K2) to predict the football match outcome. The required of football data is the English Premier League match results for three seasons; 2016 – 2017, 2015 – 2016 and 2014 – 2015 downloaded from http://www.football-data.co.uk. The experimental results showed that TAN achieved the highest predictive accuracy of 90.0 % in average across three seasons among others Bayesian approach (K2 and NB). The result from this research is hope that it can be used in future research for predicting the football match outcome. Penerbit UTHM 2018 Article PeerReviewed text en http://eprints.uthm.edu.my/4569/1/AJ%202018%20%28799%29%20Bayesian%20approach%20to%20classification%20of%20football%20match%20outcome.pdf Abdul Rahman, Muhammad Haleq Azhar and Mustapha, Aida and Fauzi, Rahmat and Razali, Nazim (2018) Bayesian approach to classification of football match outcome. International Journal of Integrated Engineering, 10 (6). pp. 155-158. ISSN 2229-838X |
| spellingShingle | QA273-280 Probabilities. Mathematical statistics TA329-348 Engineering mathematics. Engineering analysis Abdul Rahman, Muhammad Haleq Azhar Mustapha, Aida Fauzi, Rahmat Razali, Nazim Bayesian approach to classification of football match outcome |
| title | Bayesian approach to classification of football match outcome |
| title_full | Bayesian approach to classification of football match outcome |
| title_fullStr | Bayesian approach to classification of football match outcome |
| title_full_unstemmed | Bayesian approach to classification of football match outcome |
| title_short | Bayesian approach to classification of football match outcome |
| title_sort | bayesian approach to classification of football match outcome |
| topic | QA273-280 Probabilities. Mathematical statistics TA329-348 Engineering mathematics. Engineering analysis |
| url | http://eprints.uthm.edu.my/4569/1/AJ%202018%20%28799%29%20Bayesian%20approach%20to%20classification%20of%20football%20match%20outcome.pdf |
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