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SciSports: Learning football kinematics through two-dimensional tracking data

Two-dimensional positional data during entire matches. The data provided to us was two-dimensional positional data during entire matches. We developed methods based on Newtonian mechanics and the Kalman filter, Generative Adversarial Nets and Variational Autoencoders.

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Cite this as

Anatoliy Babic, Harshit Bansal, Gianluca Finocchio, Julian Golak, Mark Peletier, Jim Portegies, Clara Stegehuis, Anuj Tyagi, Roland Vincze, William Weimin Yoo (2024). Dataset: SciSports: Learning football kinematics through two-dimensional tracking data. https://doi.org/10.57702/gw8ypw3d

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Additional Info

Field	Value
Created	December 16, 2024
Last update	December 16, 2024
Defined In	https://doi.org/10.48550/arXiv.1808.04550
Author	Anatoliy Babic
More Authors	Harshit Bansal Gianluca Finocchio Julian Golak Mark Peletier Jim Portegies Clara Stegehuis Anuj Tyagi Roland Vincze William Weimin Yoo
Homepage	https://arxiv.org/abs/1808.01544