Finding Interesting Pass Patterns from Soccer Game Records

This paper presents a novel method for finding interesting pass patterns from soccer game records. Taking two features of the pass sequence "temporal irregularity and requirements for multiscale observation" into account, we have developed a comparison method of the sequences based on multiscale matching. The method can be used with hierarchical clustering, that brings us a new style of data mining in sports data. Experimental results on 64 game records of FIFA world cup 2002 demonstrated that the method could discover some interesting pass patterns that may be associated with successful goals.

[1]  Brian Everitt,et al.  Cluster analysis , 1974 .

[2]  Yoshiaki Shirai,et al.  Tracking players and a ball in video image sequence and estimating camera parameters for 3D interpretation of soccer games , 2002, Object recognition supported by user interaction for service robots.

[3]  HongJiang Zhang,et al.  Automatic parsing of TV soccer programs , 1995, Proceedings of the International Conference on Multimedia Computing and Systems.

[4]  David G. Lowe,et al.  Organization of smooth image curves at multiple scales , 1988, International Journal of Computer Vision.

[5]  Naonori Ueda,et al.  A matching algorithm of deformed planar curves using multiscale convex/concave structures , 1991, Systems and Computers in Japan.

[6]  Jun-ichi Hasegawa,et al.  Visualization of dominant region in team games and its application to teamwork analysis , 2000, Proceedings Computer Graphics International 2000.

[7]  Farzin Mokhtarian,et al.  Scale-Based Description and Recognition of Planar Curves and Two-Dimensional Shapes , 1986, IEEE Transactions on Pattern Analysis and Machine Intelligence.