Performance indicator selection using decision trees in elite handball
The aim was to analyze the performance indicators in the European Men's Handball Championship using decision trees as artificial intelligence models. The observational methodology was used. The sample was composed of 87 matches from the 2016 and 2018 Men's European Handball National Championships. As the most important result, the model identified three relevant variables to achieve high precision to predict handball results. In conclusion, the use of these models allow to greatly reduce the complexity in the analysis of the performance indicators in handball.
© Copyright 2023 Revista Internacional de Medicina y Ciencias de la Actividad Física y del Deporte. Universidad de Madrid. All rights reserved.
| Subjects: | |
|---|---|
| Notations: | sport games |
| Tagging: | künstliche Intelligenz |
| Published in: | Revista Internacional de Medicina y Ciencias de la Actividad Física y del Deporte |
| Language: | English Spanish |
| Published: |
2023
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| Online Access: | https://doi.org/10.15366/rimcafd2022.88.003 |
| Volume: | 22 |
| Issue: | 88 |
| Pages: | 753-764 |
| Document types: | article |
| Level: | advanced |