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Strategic Multi-Agent Learning for Interpretable Action Valuation of All Players in Football
Valuing player actions in football requires accounting for strategic interactions among 22 players, including off-ball movements and defensive positioning. Existing reinforcement-learning-based methods commonly aggregate decisions at the team level or estimate player values independently, leaving st
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