My name is Gabe Schumm!

I recently defended my Ph.D. in computational physics and am seeking opportunities in data science and machine learning.

A collection of projects I’ve worked on over the years can be found below. Also check out my pitch visualizer, a light weight JavaScript application for analyzing trajectories.

Portfolio

Simulating MLB Pitch Tracjetories

A short primer on my pitch visualization tool.

NBA Matchup Predictor

Can a machine learning model outperform Las Vegas in predicting NBA matchups? Using team gamelog stats, I built a model to forecast game outcomes and compare its performance against the sportsbooks' predictions.

Tarik Skubal is on a Historic Pace

Skubal is on pace to become the first pitcher in modern history to lead his league in both K/9 and BB/9. Using the pybaseball library, I explored how his season compares to some of the most dominant of all time.

Evolution Olympic Swimming Gold Medal Times from 1912–2024

Athletes have gotten bigger, stronger, and smarter — and the Olympics provides a perfect stage to showcase this. Plotting the gold-medal winning times in two of the most iconic swimming events, we clearly see the impact of sports science on athelete performance.

Evolution of the NBA Shot Chart

The rise of the three point shot in the NBA is well documented and well understood. In this post, I explore this trend in further detail using shot chart data scraped from the NBA Stats website and managed using the peewee Python ORM.

Distribution of Annual Salaries and Total Contract Values for each of the Big Four Sports Leagues

Why do the types of contracts given out in each of the big four men's sports leagues differ so much? I explored this by looking at the distribution of salaries (annual and total) across all players in each league.