Open AccessDEEP MULTILAYER NEURAL NETWORK FOR PREDICTING THE WINNER OF FOOTBALL MATCHES
Author(s) -
Sergei Anfilets,
Sergei Bezobrazov,
Vladimir Golovko,
Anatoliy Sachenko,
Myroslav Komar,
Raman Dolny,
Valery Kasyanik,
Pavlo Bykovyy,
Egor Mikhno,
Oleksandr Osolinskyi
Publication year - 2020
Publication title -
computing
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.184
H-Index - 11
eISSN - 2312-5381
pISSN - 1727-6209
DOI - 10.47839/ijc.19.1.1695
Subject(s) - oracle , football , league , computer science , artificial neural network , profitability index , artificial intelligence , machine learning , regularization (linguistics) , deep neural networks , data mining , physics , software engineering , finance , astronomy , political science , law , economics
In this work, we draw attention to prediction of football (soccer) match winner. We propose the deep multilayer neural network based on elastic net regularization that predicts the winner of the English Premier League football matches. Our main interest is to predict the match result (win, loss or draw). In our experimental study, we prove that using open access limited data such as team shots, shots on target, yellow and red cards, etc. the system has a good prediction accuracy and profitability. The proposed approach should be considered as a basis of Oracle engine for predicting the match outcomes.