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.
machine learning decision trees football classification sports
Birincil Dil | İngilizce |
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Konular | Yazılım Mühendisliği (Diğer) |
Bölüm | Research Articles |
Yazarlar | |
Yayımlanma Tarihi | 29 Aralık 2020 |
Gönderilme Tarihi | 27 Ekim 2020 |
Yayımlandığı Sayı | Yıl 2020 Cilt: 1 Sayı: 2 |
This work is licensed under a Creative Commons Attribution 4.0 International License.