Predicting Soccer Events from Optical Tracking Data

Date

2018-01-01

Author

Ozdemir, Esref
Alemdar, Hande

Metadata

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This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

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In this study, an automated method for predicting soccer events such as corner kick, free kick, goals and penalties has been developed using optical tracking data with random forest classifier. The study was conducted on a dataset of 140 matches from Turkish Football Federation Super League 2017-2018 season. The average accuracy on validation set is %93.8 and %91.4 on a separate held-out test set.

URI

https://hdl.handle.net/11511/118138

DOI

https://doi.org/10.1109/siu.2018.8404561

Conference Name

26th IEEE Signal Processing and Communications Applications Conference (SIU)

Collections

Department of Computer Engineering, Conference / Seminar

Citation Formats

E. Ozdemir and H. Alemdar, “Predicting Soccer Events from Optical Tracking Data,” presented at the 26th IEEE Signal Processing and Communications Applications Conference (SIU), İzmir, Türkiye, 2018, Accessed: 00, 2025. [Online]. Available: https://hdl.handle.net/11511/118138.