Analyst
Builds models in R for player evaluation and opponent preparation, and tests them on games they have not seen before trusting them.
Sports analytics · Player evaluation · Operations
I build models and reports that help teams evaluate players and prepare for opponents. Head of Hockey Analytics for the Madison Capitols, and a Finance and Information Systems student at the University of Wisconsin-Madison.
Currently working onNFL Big Data Bowl
I come at sport from three sides: as an analyst, as an operator who has built and run a business, and as a competitor.

I'm interested in how teams are built and run, in any sport: how players are valued, how rosters come together and how a staff prepares for the next opponent. My work so far is in hockey; my playing background is in baseball, football and wrestling; my studies are in finance and information systems.
Builds models in R for player evaluation and opponent preparation, and tests them on games they have not seen before trusting them.
Founded a marine services business with five-figure revenue and more than 50 customers, and manages a marina crew of more than ten.
Four-year varsity pitcher and two-time captain who also played football and wrestled. Now pitching and playing outfield for UW-Madison Club Baseball.



Baseball photos: Smokinjoez
Oct 2026 – Present
Madison Capitols · USHL · Internship · Madison, WI
May 2024 – Present
Jet Marine Management · Seasonal · Fontana, WI
May 2023 – Present
Gordy's Marine · Seasonal · Fontana, WI
Work done for a team uses licensed data and is internal to that team, so it is described here without results.
Rates every team in a league on offense and defense after adjusting for the opponents it has faced, then produces a one-page report for each upcoming opponent: projected matchup, strengths, weak spots and a side-by-side profile.
A study of roughly 250 performance metrics that separates repeatable team traits from game-to-game noise, then checks which traits carry over to results in games they never saw.
An elastic-net model across every league game that identifies which parts of play go with winning and which lead to a positive expected-goal differential, re-fitted repeatedly so only durable signals are reported.
A model that estimates the probability an NBA shot is made, using engineered features such as shot distance, shot-clock pressure, catch-and-shoot attempts and defender proximity.
Four sports organizations at the University of Wisconsin-Madison, all since September 2026.
Selected member
Applying data and modeling to questions across sports.
Selected member
The business side of sport: front offices, finance and strategy.
Selected member
Consulting projects for organizations in sport.
Pitcher and outfielder
Competitive club baseball for the University of Wisconsin-Madison.
First article in progress.
Research write-ups, graphics and interactive apps across sports will be published here.
Reports coming soon.
Player and team scouting reports across sports will be posted here.
Bachelor of Business Administration, May 2028
Finance, Investment & Banking · Information Systems
Valedictorian · U.S. Presidential Scholar · AP Scholar with Distinction





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