Research on predicting football matches based on handicap data and BPNN

Research Article
Open access

Research on predicting football matches based on handicap data and BPNN

Jiahao Hu 1*
  • 1 Dalian University of Technology, Dalian, Liaoning 116620, China    
  • *corresponding author hu1124666055@163.com
Published on 31 January 2024 | https://doi.org/10.54254/2755-2721/31/20230118
ACE Vol.31
ISSN (Print): 2755-273X
ISSN (Online): 2755-2721
ISBN (Print): 978-1-83558-287-9
ISBN (Online): 978-1-83558-288-6

Abstract

Football is one of the most influential sports in the world, and billions of people around the globe pay much attention to the football matches. With the growing popularity of football and the continuous development of the football betting industry, the prediction of the outcomes of football matches has become a hot topic in the commercial operations of sports especially footballs in recent years. It is also an important subject of academic research. In this paper, we develop a football match result prediction model based on the back propagation neural network. We take the German Bundesliga competitions as the research object in this paper. In addition to utilizing historical statistic data and team attributes from previous matches, we also incorporate a new dataset, known as handicap data, which refers to the odds data of the football matches, as the input layer of the BPNN (back propagation neural networks) for prediction. We also innovatively use varying numbers of hidden nodes, which greatly improves the prediction accuracy and stability of the model. Experimental results indicate that the average prediction accuracy of this football match prediction model is around 57.2%, with the highest prediction accuracy reaching 59.8% and the lowest prediction accuracy at 53.8%. The prediction model demonstrates relative stability, with no significant fluctuations in prediction accuracy.

Keywords:

Football Match Win-Draw-Lose Prediction, Back Propagation Neural Networks, Handicap Data, Machine Learning

Hu,J. (2024). Research on predicting football matches based on handicap data and BPNN. Applied and Computational Engineering,31,29-35.
Export citation

References

[1]. Xia Fei. (2017). Application research of BP neural network in predicting football match outcomes. Chongqing Normal University Press, Chongqing.

[2]. Rahul Baboota, Harleen Kaur. (2019). Predictive analysis and modelling football results using machine learning approach for English premier league. International Journal of Forecasting, 35:741-755.

[3]. Fátima Rodrigues, Ângelo Pinto. (2022). Prediction of football match results with machine learning. Procedia Computer Science, 204:463-470.

[4]. Fu Yu. (2018). Neural network for predicting football match outcomes. Science and Technology Review, 23:238.

[5]. Wang Yiqi, Zhao Hongrun, Zhao Hongwen, Xu Xichen. (2021). Research on football match prediction based on social network analysis and BP neural network. Journal of Weifang Engineering Vocational College, 34(3):104-108.

[6]. Huang Yi. (2021). Prediction of football match results by using neural network. Microcomputer Applications, 37(11):137-140.

[7]. Ao Xiqin, Gong Yujie, Li Jian. (2016). Prediction of football match outcomes based on odds data. Journal of Chongqing Technol Business Univ (Nat Sci Ed), 33(6):85-89.

Cite this article

Hu,J. (2024). Research on predicting football matches based on handicap data and BPNN. Applied and Computational Engineering,31,29-35.

Data availability

The datasets used and/or analyzed during the current study will be available from the authors upon reasonable request.

Disclaimer/Publisher's Note

The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of EWA Publishing and/or the editor(s). EWA Publishing and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

About volume

Volume title: Proceedings of the 2023 International Conference on Machine Learning and Automation

ISBN：978-1-83558-287-9(Print) / 978-1-83558-288-6(Online)
Editor：Mustafa İSTANBULLU
Conference website: https://2023.confmla.org/
Conference date: 18 October 2023
Series: Applied and Computational Engineering
Volume number: Vol.31
ISSN：2755-2721(Print) / 2755-273X(Online)

© 2024 by the author(s). Licensee EWA Publishing, Oxford, UK. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license. Authors who publish this series agree to the following terms:
1. Authors retain copyright and grant the series right of first publication with the work simultaneously licensed under a Creative Commons Attribution License that allows others to share the work with an acknowledgment of the work's authorship and initial publication in this series.
2. Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the series's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgment of its initial publication in this series.
3. Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work (See Open access policy for details).

References

[1]. Xia Fei. (2017). Application research of BP neural network in predicting football match outcomes. Chongqing Normal University Press, Chongqing.

[2]. Rahul Baboota, Harleen Kaur. (2019). Predictive analysis and modelling football results using machine learning approach for English premier league. International Journal of Forecasting, 35:741-755.

[3]. Fátima Rodrigues, Ângelo Pinto. (2022). Prediction of football match results with machine learning. Procedia Computer Science, 204:463-470.

[4]. Fu Yu. (2018). Neural network for predicting football match outcomes. Science and Technology Review, 23:238.

[5]. Wang Yiqi, Zhao Hongrun, Zhao Hongwen, Xu Xichen. (2021). Research on football match prediction based on social network analysis and BP neural network. Journal of Weifang Engineering Vocational College, 34(3):104-108.

[6]. Huang Yi. (2021). Prediction of football match results by using neural network. Microcomputer Applications, 37(11):137-140.

[7]. Ao Xiqin, Gong Yujie, Li Jian. (2016). Prediction of football match outcomes based on odds data. Journal of Chongqing Technol Business Univ (Nat Sci Ed), 33(6):85-89.

For authors
Guide for authors Policies for authors Aims and scope Subscription Open access policy
For editors
Policies for editors Editorial board
For reviewers
Policies for reviewers Privacy policy

Cookies are used by this site.
Copyright © 2024 EWA Publishing, its licensors, and contributors. All rights reserved, including text and data mining, AI training, and similar technologies.