Predicting the in-game status in soccer with machine learning using spatiotemporal player tracking data
Abstract An important structuring feature of a soccer match is the in-game status, whether a match is interrupted or in play. This is necessary to calculate performance indicators relative to the effective playing time or to find standard situations, ball actions, and other tactical structures in sp...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2022-09-01
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| Series: | Scientific Reports |
| Online Access: | https://doi.org/10.1038/s41598-022-19948-1 |