Analyzing and predicting events in soccer and tennis using spatiotemporal data

In this paper, we summarize our recent work in analyz- ing and predicting behaviors in sports using spatiotemporal data. We specifically focus on two recent works: 1) Predicting the location of shot in tennis using Hawk-Eye tennis data, and 2) Clustering spatiotemporal plays in soccer to discover the methods in which they get a shot on goal from a professional league.

[1]  Peter Carr,et al.  Characterizing Multi-Agent Team Behavior from Partial Team Tracings: Evidence from the English Premier League , 2012, AAAI.

[2]  H. Kuhn.  The Hungarian method for the assignment problem , 1955 .

[3]  Yaser Sheikh,et al.  Representing and Discovering Adversarial Team Behaviors Using Player Roles , 2013, 2013 IEEE Conference on Computer Vision and Pattern Recognition.

[4]  Peter Carr,et al.  Assessing team strategy using spatiotemporal data , 2013, KDD.

[5]  Sridha Sridharan,et al.  Large-Scale Analysis of Formations in Soccer , 2013, 2013 International Conference on Digital Image Computing: Techniques and Applications (DICTA).