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2 - Kanaad Parvate, NBA shot policies, MDPs, Reinforcement Learning, etc
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My guest today is Kanaad. He is a friend of mine from Berkeley, and he is a Cavs and RL enthusiast. We talk about a fascinating paper from the 2018 Sloan Sports Analytics Conference. The main idea is that by modeling each possession as a Markov Decision Process, it becomes easy to build a simulator that can help us answer questions like "How much more efficient would a team be if they took 20% fewer midrange shots early in the shot clock?"
The paper: http://www.lukebornn.com/papers/sandholtz_ssac_2018.pdf
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