Abstract
In recent years, many professional sports clubs have adopted camera-based tracking technology that captures the location of both the players and the ball at a high frequency. Nevertheless, the valuable information that is hidden in these performance data is rarely used in their decision-making process. What is missing are the computational methods to analyze these data in great depth. This paper addresses the task of automatically discovering patterns in offensive strategies in professional soccer matches. To address this task, we propose an inductive logic programming approach that can easily deal with the relational structure of the data. An experimental study shows the utility of our approach.
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Notes
- 1.
By cover, we mean that a clause, in combination with BK, can be used to derive that the target predicate T is true for a given example.
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Acknowledgments
Jan Van Haaren is supported by the Agency for Innovation by Science and Technology (IWT). Vladimir Dzyuba is supported by the Research Foundation Flanders (FWO) by means of the project “Instant Interactive Data Exploration”. Jesse Davis is partially supported by the Research Fund KU Leuven (OT/11/051), EU FP7 Marie Curie Career Integration Grant (#294068) and FWO-Vlaanderen (G.0356.12).
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Van Haaren, J., Dzyuba, V., Hannosset, S., Davis, J. (2015). Automatically Discovering Offensive Patterns in Soccer Match Data. In: Fromont, E., De Bie, T., van Leeuwen, M. (eds) Advances in Intelligent Data Analysis XIV. IDA 2015. Lecture Notes in Computer Science(), vol 9385. Springer, Cham. https://doi.org/10.1007/978-3-319-24465-5_25
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