In soccer, when analyzing the performance of a team one of the key events to analyze is that of shots and goal-scoring. With the availability of fine-grained player and ball tracking data, it is now possible to nd the common patterns a team uses via clustering multi-agent trajectories. The e ectiveness of these methods can be then quanti ed by using a "expected goal value" (EGV) model which was recently proposed. Using an entire season of player and ball tracking data from Prozone, we show a method of both "discovering" and "quantifying" goal scoring methods of a team, which we also use to compare the "goal-scoring styles" of teams.
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