Abstract:

This study was conducted with the aim of predicting the end of the season of Spain (La Liga) Soccer League through the artificial neural networks (ANN) model developed by means of 8 different input variables specific to soccer. In the study, the goals of 1140 games performed in 3 seasons in the La Liga, fixed ball goals, the number of short and long pass variables were analyzed. In the La Liga, it was determined that seasonal data for 2015/2016 and 2016/2017 were as input variables, and seasonal data for 2017/2018 were output variables. The data analyzed in the study were separated randomly for training and testing purposes. The league order of the teams was modeled with numerical values between 0 (zero) and 1 (one). According to the results of the analysis conducted through the ANN model, the end-of-season team order in the La Liga was estimated at high accuracy for several teams (above 99%) in the test dataset. It was also determined that the goals scored and defeated, the fixed ball goals, which is one of the important parameters in soccer, and the number of passes (short and long passes) were also effective in determining the order of the teams in the league at the end of the season. As a result, it is considered that competition analysis through ANN provides objective implications to coaches, which will have positive effect on the technical and tactical development of teams.

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