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Predicting the in-game status in soccer with machine learning using spatiotemporal player tracking data
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 spatiotempo...
| Autores principales: | , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Nature Publishing Group UK
2022
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9522646/ https://www.ncbi.nlm.nih.gov/pubmed/36175432 http://dx.doi.org/10.1038/s41598-022-19948-1 |