Ball movement in a soccer game can be measured as a trajectory on two dimentional plane, which summarizes the tactic or strategy of game players. This paper gives a first step to extract knowledge about strategy of soccer game by using clustering of trajectory data, which consists of the following two steps. First, we apply a pairwise comparison of two trajectories using multiscale matching. Next, we apply rough-set based clustering technique to the similarity matrix obtained by the pairwise comparisons. Experimental results demonstrated that the method could discover some interesting pass patterns that may be associated with successful goals.
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