Canzhi Ye 공개
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I was joined by Kostya Medvedovsky, the creator of the basketball projection system DARKO. We went into the weeds about the methodology behind DARKO and answered questions from Twitter about it. We then picked Kostya's brain on a wide range of NBA analytics ideas, mostly focused on topics that involve predicting things. Finally, we answered some mo…
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I was joined by Udit Ranasaria who was part of a team that worked on the Passing Value in Expectation project for the Big Data Bowl. They went deep into the tracking data and built physics-based models for ball and player trajectory to estimate passing value, for all possible passes - not just the ones that happened. We also opined on the state of …
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In this episode, I was joined by the winners of the Big Data Bowl 2021, although we recorded this well before the results were announced. We talked about their project called Weighted Assessment of Defender Effectiveness which uses tracking data to allocate credit to individual defenders in coverage on pass plays. We touch on what it was like to wo…
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I was joined by Alex Stern, a current data science master's student and football analytics researcher at the University of Virginia. We talk about his Big Data Bowl project that goes to beyond the box score to quantify the value of defensive backs. The work extends upon the winning Big Data Bowl project from last year to include some cool Bayesian …
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I was joined by Charlie Gelman, a recent computer science and stats graduate from Duke. We talk about his Big Data Bowl project about defensive backs playing in press man coverage. Bonus segment at the end about wrestling analytics. 0:24 Intro, background 4:00 Paper 54:00 Wrestling analytics The project: https://www.kaggle.com/charlesgelman/hip-rea…
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I was joined by Dani Chu, a graduate student in statistics at Simon Fraser University and part of the team that won the NFL's inaugural Big Data Bowl. We talk about his fascinating research done on NFL tracking data to identify routes. We also speculate and think wishfully about the metrics that could be developed if the tracking data were to ever …
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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 m…
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A discussion with Twitter friend Ryan Davis (@rd11490) of a seminal paper in the field of NBA analytics, "Improved NBA Adjusted +/- Using Regularization and Out-of-Sample Testing." Afterwards, we share ideas on ways to further improve RAPM.(00:00) paper discussion(29:00) additional topics on player evaluation with RAPM frameworkPaper: http://www.sl…
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