This paper explores the task of automatic strategy detection from event-stream data collected from professional soccer matches. Concretely, we focus on discovering interesting event sequences that lead to an attempt on goal. We describe a data-driven approach for identifying patterns of movement that account for both spatial and temporal information which represent potential strategies.
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