I just finished a PhD in math and advanced data science at the University of Washington, and I run @wnbadata, where I make short video explainers about women's basketball data and analytics.
I'm looking for data science work in basketball, especially women's basketball. Most of what I do is play by play analysis in R, and then figuring out how to convey the analysis in 45 seconds with a story and charts.
I am also open to creating paid content around basketball, sports analytics, and data science. Previously, I have worked with brands such as the WNBA, Apple TV, and Dunkman.
- wnba-analysis — curated projects, written up nice. Three models for predicting the 2026 WNBA playoffs (Bradley-Terry, Elo and XGBoost), what a steal is worth (ridge regression), and DPOY prediction.
- wnbadata — the working archive. one script per each of my 190+ videos since 2024, including the weirdest stat about every WNBA team, which was 15 videos in 16 days (scary).
- Current analyst and developer at Her Hoop Stats
- Former data intern at Sports Reference, writing SQL against historical basketball data
- Women in Sports Data Fellow with Philadelphia Phillies R&D
- Mentee at the MIT Sloan Sports Analytics Conference
- Paid content partner with the WNBA, explaining their AWS-powered shot quality metric to fans
- Created and taught Math 380: Communicating Mathematics Through Sports Data at UW, as instructor of record
R, Python (Django), SQL (MySQL). Bayesian inference, regression, machine learning (XGBoost), clustering, lots of ggplot2 :)