Fuzzy-Based Model for Predicting Football Match Results

Authors

  • Omomule T.G. Dept. of Computer Science, Adekunle Ajasin University, Akungba Akoko, Ondo State, Nigeria
  • Ibinuolapo A. J. Dept. of Computer Science, Adekunle Ajasin University, Akungba Akoko, Ondo State, Nigeria
  • Ajayi O.O. Dept. of Computer Science, Adekunle Ajasin University, Akungba Akoko, Ondo State, Nigeria

Keywords:

Football, Betting, Prediction, Financial, Matches, Fuzzy Logic

Abstract

Predicting the outcome of football matches has been an interesting challenge for which it is realistically impossible to successfully do so for several bettors and football fans across the world. Despite this, there are significant loss in financial resources expended on the correct prediction of football matches. This paper proposes a prediction model for football matches using Fuzzy Logic. In the proposed system, results of matches between two football teams are generated based on the providence of several parameters associated with every football team. Fuzzy Logic Gaussian Membership function (Gmf) technique is adopted for the computation of membership grade for each input parameter. Datasets were obtained from the twenty (20) football teams in the English Premier League, 2017/2018 Season and were used to test the system predictability. The proposed model was implemented using MATLAB version R2017. Evaluation results showed the practicability of the system to the prediction of football outcomes based on the consideration of many input parameters for higher prediction accuracy when compared to reported literatures.

 

References

O.O. Ajayi, “Implementing a Score-Time based Model for Handling Deadlocks in Football Group Matches”, International Journal of Computer Applications (0975 – 8887), Vol. 122, Issue. 21, pp. 29-33, 2015.

G. Baio, and M. Blangiardo, “Bayesian Hierarchical Model for Prediction of Football Results”, Journal of Applied Statistics, vol.37, Issue 2, pp.253-264, 2010

D. Buursma, “Predicting Sports Event from Past Result: Towards Effective Betting on Football Matches”. Preceding 14thTwente Student Conference on IT. University of Twente, Faculty Electrical Engineering, Mathematics and Computer Science, Netherlands, pp. 1-7, 2011

D. Enke, M. Grauer. And N. Mehdiyev, “Stock Market Prediction with Multiple Regression, fuzzy type-2 Clustering and Neural Networks”, Procedia Computer Science, vol. 6 (2011) 201–206, 2011.

E. Esme, and M.S. Kiran, “Prediction of Football Match Outcomes Based on Bookmakers Odds by Using K-Nearest Neighbour Algorithm”, International Journal of Machine Learning and Computing, Vol. 8, Issue 1, pp. 26-32, 2018

O. Farzin, E. Parinaz, and S.M. Faezeh, “Football result prediction with Bayesian network in Spanish league-Barcelona Team”. International Journal of Computer Theory and Engineering, vol. 5, Issue. 5, pp. 812-815, 2013

A. Gangal, A. Talnikar, A. Dalvi, V. Zope, and A. Kulkarni, “Analysis and Prediction of Football Statistics using Data Mining Techniques”. International Journal of Computer Applications, Vol.132, Issue.5, pp. 8-11, 2015

FIFA, “Laws of the Game”. FIFA-Strasse 20, 8044 Zurich, Switzerland, 1992

K.Y. Huang, and W.L. Chang, “A Neural Network Method for Prediction of 2006 World Cup Football Game”. 2010 International Joint Conference on Neural Networks (IJCNN), pp. 1 –8, 2010

C.P. Igiri, and E.O. Nwachukwu, “An Improved Prediction System for Football Match Result”. IOSR Journal of Engineering. Vol. 4, Issue 12, pp. 12-20, 2014

A.P. Rotshtein, M. Posner, and A.B. Rakityanskaya, “Football Predictions based on a Fuzzy model with Genetic and Neural Tuning”, Cybernetics and Systems Analysis, Vol. 41, Issue. 4, pp. 619–630, 2005

V. Vaidehi, S. Monica, S. M. Sheik Safeer, M. Deepika, S. Sangeetha, “A Prediction System Based on Fuzzy Logic”, Proceedings of the World Congress on Engineering and Computer Science, San Francisco, USA, pp. 1-6, 2008

A. Yezus, “Predicting Outcome of Football Matches using Machine Learning”, A Term Paper, Mathematics and Mechanics Faculty, Saint-Petersburg State University, pp. 1-12, 2014

L.M. Hvattum, and H. Arntsen, “Using Elo Ratings for Match Result Prediction in Association Football”, International Journal of Forecasting, Vol. 26, Issue. 3, pp. 460–470, 2010.

V. Sillanpaa, and O. Heino, “Forecasting Football Match Results- A Study on Modelling Principles and Efficiency of Fixed-Odds Betting Markets in Football”. Thesis submitted to the Department of Information and Service Economic, School of Business, Aalto University, pp. 1-124, 2013

F.I. Amadin, and J.C. Obi, “English Premier League (EPL) Soccer Matches Prediction using an Adaptive Neuro-Fuzzy Inference System (ANFIS)”, Transactions on Machine Learning and Artificial Intelligence, Vol. 3, Issue 2, pp. 1-7, 2015

J. Bih, “Paradigm Shift - An Introduction to Fuzzy Logic”, IEEE Potentials, Vol. 25, Issue 1, pp. 6–21, 2006

L. B. Bhajantri, “Fuzzy Logic Based Fault Detection in Distributed Sensor Networks”, International Journal of Scientific Research in Computer Science and Engineering, Vol.6, Issue.2, pp.27-32, 2018

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Published

2020-02-28

How to Cite

[1]
O. T.G., I. A. J., and A. O.O., “Fuzzy-Based Model for Predicting Football Match Results”, Int. J. Sci. Res. Comp. Sci. Eng., vol. 8, no. 1, pp. 70–80, Feb. 2020.

Issue

Section

Research Article

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