Sports on Paper

Canzhi Ye•podcasters.spotify.com

Sports

A deep dive into sports analytics research. Hosted by Canzhi Ye, former Brooklyn Nets basketball analytics associate.

Last refreshed: August 15th, 2025 at 4:52 AM ⓘ

Follow this podcast in the Metacast mobile app to refresh it and see new episodes.

Follow on

Apple Podcasts

Spotify

RSS

Podcasts are better in Metacast mobile app

Don't just listen to podcasts. Learn from them with transcripts, summaries, and chapters for every episode. Skim, search, and bookmark insights. Learn more

Episodes

8 - Kostya Medvedovsky, DARKO and assorted NBA analytics topics

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 more questions from Twitter. You can find Kostya on twitter: @kmedved [00:00:00] - DARKO [00:05:05] - exponential decay [00:08:10] - kalman filters [00:...

Jan 26, 2022•2 hr 22 min•Season 3Ep. 1

7 - Udit Ranasaria, Passing Value in Expectation

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 public tracking data based sports analytics, and Udit touched on some exciting new projects in the works. You can find him on twitter @uditranasaria P...

Mar 03, 2021•1 hr 38 min

6 - Asmae Toumi, Tony ElHabr, Marschall Furman, and Sydney Robinson, Weighted Assessment of Defender Effectiveness (Big Data Bowl WINNERS!)

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 work on a data project with others virtually during a pandemic before going deep on methods for defensive target probability over expectation (dTPOE) an...

Feb 23, 2021•1 hr 4 min

5 - Alex Stern, Algorithms in the War Room

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 hierarchical models. The project: https://www.kaggle.com/acs4wq/algorithms-in-the-war-room...

Jan 27, 2021•50 min•Season 2Ep. 2

4 - Charlie Gelman, Hip Reaction Time (Big Data Bowl), wrestling analytics

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-reaction-drill

Jan 21, 2021•1 hr 5 min•Season 2Ep. 1

3 - Dani Chu, NFL Route Identification

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 become public. The paper: https://arxiv.org/abs/1908.02423 The Josh Hermsmeyer article we mentioned: https://fivethirtyeight.com/features/can-nfl-coac...

Aug 08, 2019•1 hr 6 min•Season 1Ep. 3

2 - Kanaad Parvate, NBA shot policies, MDPs, Reinforcement Learning, etc

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_ssa...

Jul 11, 2019•52 min•Season 1Ep. 2

1 - Ryan Davis, Adjusted Plus-Minus and Friends

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 framework Paper: http://www.sloansportsconference.com/wp-content/uploads/2015/09/joeSillSloanSportsPaperWithLogo.pdf RAPM tutorial: https://twitter.com/rd11490/status/1128782945...

Jun 28, 2019•1 hr 6 min•Season 1Ep. 1

0 - Hello World!

Introducing the Sports on Paper podcast, hosted by Canzhi Ye. First real episode coming soon... Follow the pod on twitter @sportsonpaper!

Jun 21, 2019•1 min

Hosted on Spotify for Creators (Anchor)

For the best experience, listen in Metacast app for iOS or Android