In the second episode we discuss two papers by our guest Daniel Daly-Grafstein and Luke Bornn: Rao-Blackwellizing field goal percentage (published in JQAS and available at: http://www.lukebornn.com/papers/dalygrafstein_jqas_2019.pdf) and Using In-Game Shot Trajectories to Better Understand Defensive Impact in the NBA (available at: https://arxiv.org/pdf/1905.00822.pdf).

Daniel is currently a soccer data analyst at Sportlogiq, an sports AI company that, in soccer, focuses on generating tracking data using computer vision.  The papers discussed in this episode were part of Daniel’s Master's degree in statistics at Simon Fraser University. In the fall Daniel is going to be starting his PhD in Statistics at the University of British Columbia.

Additional resources mentioned in the show:

• Daniel's GitHub repository: https://github.com/danieldalygrafstein/nba-raoblackwellizing-field-goal


• Sloan conference papers by: (1) Rachel Marty and Simon Lucey: A data-driven method for understanding and increasing 3-point shooting percentage (http://www.sloansportsconference.com/wp-content/uploads/2017/02/1505.pdf) and (2) Rachel Marty: High-resolution shot capture reveals systematic biases and an improved method for shooter evaluation (http://www.sloansportsconference.com/wp-content/uploads/2018/02/1005.pdf)

Also you should read the wikipedia page on the Rao-Blackwell theorem: https://en.wikipedia.org/wiki/Rao%E2%80%93Blackwell_theorem

This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit statthinksportsanalytics.substack.com