Large-scale analysis of formations in soccer

Wei, Xinyu, Sha, Long, Lucey, Patrick, Morgan, Stuart, & Sridharan, Sridha (2013) Large-scale analysis of formations in soccer. In de Souza, Paulo, Engelke, Ulrich, & Rahman, Ashfaqur (Eds.) Proceedings of the 2013 International Conference on Digital Image Computing: Techniques and Applications (DICTA), IEEE, Wrest Point, Hobart, TAS, pp. 133-140.

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Due to the demand for better and deeper analysis in sports, organizations (both professional teams and broadcasters) are looking to use spatiotemporal data in the form of player tracking information to obtain an advantage over their competitors. However, due to the large volume of data, its unstructured nature, and lack of associated team activity labels (e.g. strategic/tactical), effective and efficient strategies to deal with such data have yet to be deployed. A bottleneck restricting such solutions is the lack of a suitable representation (i.e. ordering of players) which is immune to the potentially infinite number of possible permutations of player orderings, in addition to the high dimensionality of temporal signal (e.g. a game of soccer last for 90 mins). Leveraging a recent method which utilizes a "role-representation", as well as a feature reduction strategy that uses a spatiotemporal bilinear basis model to form a compact spatiotemporal representation. Using this representation, we find the most likely formation patterns of a team associated with match events across nearly 14 hours of continuous player and ball tracking data in soccer. Additionally, we show that we can accurately segment a match into distinct game phases and detect highlights. (i.e. shots, corners, free-kicks, etc) completely automatically using a decision-tree formulation.

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ID Code: 66574
Item Type: Conference Paper
Refereed: Yes
Keywords: Spatiotemporal data, Player tracking, Soccer, Analysis of formations, Spatiotemporal bilinear basis model
DOI: 10.1109/DICTA.2013.6691503
ISBN: 9781479921263
Divisions: Current > Schools > School of Electrical Engineering & Computer Science
Current > QUT Faculties and Divisions > Science & Engineering Faculty
Copyright Owner: Copyright © 2013 IEEE
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Deposited On: 23 Jan 2014 22:22
Last Modified: 29 Jan 2014 04:54

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