Deriving player types from soccer event data as a means to improve tactical flexibility
In order to improve tactical flexibility in team sports, it is important to build a squad with a broad range of player types. We developed a process to identify player types in soccer based on the event data of an entire Bundesliga season. The process is based on a) the derivation of meaningful player features from the raw data and b) a clustering algorithm applied to the features. The resulting types can be used to assess and improve tactical flexibility in soccer.
© Copyright 2022 Proceedings of the 9th International Performance Analysis Workshop and Conference & 5th IACSS Conference. PACSS 2021. Advances in Intelligent Systems and Computing, vol 1426. Published by Springer. All rights reserved.
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| Notations: | sport games technical and natural sciences |
| Tagging: | Algorithmus |
| Published in: | Proceedings of the 9th International Performance Analysis Workshop and Conference & 5th IACSS Conference. PACSS 2021. Advances in Intelligent Systems and Computing, vol 1426 |
| Language: | English |
| Published: |
Cham
Springer
2022
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| Online Access: | https://doi.org/10.1007/978-3-030-99333-7_12 |
| Pages: | 78-81 |
| Document types: | article |
| Level: | advanced |