Abstract

This article evaluated football/Soccer results (victory, draw, loss) prediction in Brazilian Football Championship using various machine learning models based on real-world data from the real matches. The models were tested recursively and average predictive results were compared. The results showed that logistic regression and support vectors machine yielded the best results, exhibiting superior average accuracy performance in comparison to others classifiers (KNN and Random Forest), with 49.77% accuracy (logistic Regression), almost 17% better than a random decision (benchmark) which has 33% of success chance. In addition, a ranking of the features’ relative importance was made to orient the use of Data.

#artificial-intelligence #sports #big-data #machine-learning #football