Applying Decision Tree Techniques to Classify European Football Teams

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Journal of Soft Computing and Artificial Intelligence
Volume:1 Issue:2
Applying Decision Tree Techniques to Classify European Football Teams

Applying Decision Tree Techniques to Classify European Football Teams

Authors : Bünyamin Fuat YILDIZ

Pages : 86-91

View : 56 | Download : 11

Publication Date : 2020-12-29

Article Type : Research Paper

Abstract :Machine learning techniques are powerful tools used in all aspects of science. However, these techniques are relatively new in sports. This study was carried out to measure the accuracy of decision trees in the classification of football teams. We applied five types of decision tree algorithms to classify elite football teams in Spain, Italy, and England to determine whether decision tree techniques are robust in classifying elite football teams. The findings show that the accuracy rate is above 77 percent for each of the decision trees. The key qualities that cause branching in decision trees may constitute a criterion for the targeting of football authorities. More research is required to determine which machine learning techniques are more efficient in classifying football teams.
Keywords : machine learning, decision trees, football, classification, sports

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