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.

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PDF) Predicting Football Match Results with Data Mining Techniques

Technical and Tactical Command Decision Algorithm of Football Matches Based on Big Data and Neural Network

A public data set of spatio-temporal match events in soccer competitions

Predicting the in-game status in soccer with machine learning using spatiotemporal player tracking data

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