Predicting shot locations in tennis using spatiotemporal data

Wei, Xinyu, Lucey, Patrick J., Morgan, Stuart, & Sridharan, Sridha (2013) Predicting shot locations in tennis using spatiotemporal data. 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. 221-228.

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Abstract

Over the past decade, vision-based tracking systems have been successfully deployed in professional sports such as tennis and cricket for enhanced broadcast visualizations as well as aiding umpiring decisions. Despite the high-level of accuracy of the tracking systems and the sheer volume of spatiotemporal data they generate, the use of this high quality data for quantitative player performance and prediction has been lacking. In this paper, we present a method which predicts the location of a future shot based on the spatiotemporal parameters of the incoming shots (i.e. shot speed, location, angle and feet location) from such a vision system. Having the ability to accurately predict future short-term events has enormous implications in the area of automatic sports broadcasting in addition to coaching and commentary domains. Using Hawk-Eye data from the 2012 Australian Open Men's draw, we utilize a Dynamic Bayesian Network to model player behaviors and use an online model adaptation method to match the player's behavior to enhance shot predictability. To show the utility of our approach, we analyze the shot predictability of the top 3 players seeds in the tournament (Djokovic, Federer and Nadal) as they played the most amounts of games.

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ID Code: 66576
Item Type: Conference Paper
Refereed: Yes
Additional URLs:
Keywords: Vision-based tracking systems, Spatiotemporal data, Tennis, Dynamic Bayesian Network, Shot predictability
DOI: 10.1109/DICTA.2013.6691516
ISBN: 9781479921263
Divisions: Current > Schools > School of Electrical Engineering & Computer Science
Current > QUT Faculties and Divisions > Science & Engineering Faculty
Copyright Owner: Copyright © 2013 by the Institute of Electrical and Electronic Engineers, Inc.
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Deposited On: 23 Jan 2014 22:27
Last Modified: 29 Jan 2014 05:01

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