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Hierarchical Absorbing Markov Chain Models for Pooling Sparse Combat Sequence Data
By viewing tactics in no-gi Brazilian jiu-jitsu (NGJJ) as discrete states, we estimate the transition probabilities of tactical progression, while simultaneously exploring the effects of weight categories on these dynamics with a hierarchical absorbing Markov chain model. We further cluster the weig
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