- I graduated Magna Cum Laude with a 3.969 GPA (nice) from Duke University in the class of 2022
- I was a data and scouting analyst for the Duke Men's Basketball Team
- I was a co-founder of the Duke Sports Analytics Club
- 2024 NCAA March Madness Machine Learning Mania 2nd place winner
- 2023 NCAA March Madness Machine Learning Mania 7th place winner
- 2022 NFL Big Data Bowl college winner
- 2016-Present Consensus Draft Boards
- Syracuse Football Analytics Blitz 2021 runner-up/Room 4 winner
- Determining optimal run/pass ratios in the NFL
- Articles on Open Source Football
- Altering expected points added (EPA) for opponent while using dynamic rolling windows
- Exploring stability and predictive power of penalty rates
- College basketball shiny application
- Display team or player shot charts by game
- Duke 2020 DataFest competition winner for best visualizations
- College basketball tracking data
- Expected FG% based on shot distance, defender locations, time on shot clock, etc.
- Quantifying off-ball player "gravity" using barycentric coordinates
- Predicting baseball performance from vision and athletic assessments
- Basic tutorials and walkthroughs for the Duke Sports Analytics Club
- An initial exploration of publicly available college basketball data
- Getting started with common sports data sources like
nflfastRandkenpomRas well as basic web-scraping
gamezoneRis an R package for working with NCAA Men's Basketball play-by-play data from STATS LLC's GameZone. The package allows users to scrape team and master schedules as well as play-by-play data with shot locations into a tidy format. The main benefit of gamezoneR is the volume of shot location data available (typically 170,000+ in a season)- NFL draft prospect data from ESPN dating back to 1967
- Text analysis for over 4,000 prospects
- ESPN draft prospect grades and positional ranks
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