PDF] Soft Computing-Based Result Prediction of Football Games

The current work concludes with the recommendation of soft-computing techniques as a powerful approach, either for the creation of result prediction models of diverse sport championships, or as effective data extrapolation mechanisms in case of limited available statistics. Soft computing methods for result prediction of football games based on fuzzy rules, neural networks and genetic programming techniques, are proposed in the article. The models are taking into account the following features of football teams: difference of infirmity factors; difference of dynamics profile; difference of ranks; host factor; personal score of the teams. Testing shows that the proposed models achieve a satisfactory estimation of the actual game results. The current work concludes with the recommendation of soft-computing techniques as a powerful approach, either for the creation of result prediction models of diverse sport championships, or as effective data extrapolation mechanisms in case of limited available statistics.

Computers, Free Full-Text

PDF) A Machine Learning Framework for Sport Result Prediction

Sports match prediction model for training and exercise using attention- based LSTM network - ScienceDirect

PDF) Predicting Football Match Results with Data Mining Techniques

PDF) Predicting Football Match Results with Data Mining Techniques

Applied Sciences, Free Full-Text

Guest Editorial 'Statistical Modelling for Sports Analytics' - Andreas Groll, Marica Manisera, Gunther Schauberger, Paola Zuccolotto, 2018

Predicting outcome of soccer matches using machine learning - PDF Free Download

Dolores: a model that predicts football match outcomes from all over the world

Entropy, Free Full-Text

Sports analytics in the NFL: classifying the winner of the superbowl