Trader at Fanatics Betting & Gaming. Turning data into edge.
I'm Leo — a data-driven sports trader who loves chasing edges and finding exploits.
Studied Economics and Data Science. Built the analytical foundation that would later become my edge in sports markets.
Spent my college summers working at a salmon processing plant in Alaska. Long hours, hard work, and the kind of grit you can't learn in a classroom.
The summer after college, I went door to door. Learned resilience, persuasion, and how to handle rejection — skills that translate to everything.
Found my calling at the intersection of data, sports, and markets. Started applying quantitative methods to find edges in betting markets.
Now working as a Trader, bringing it all together — data science, market intuition, and relentless work ethic.
Fanatics Betting & Gaming
Market operations supporting the pricing, integrity, and availability of sportsbook markets across professional and collegiate sports. Monitoring live and pre-match markets, reviewing line movements, conducting customer bet reviews, and building SQL-based reporting workflows to track performance and surface pricing anomalies.
University of Washington
Combined economics theory with practical data science skills. Focused on statistical modeling and quantitative analysis.
Building an automated trading bot targeting +EV opportunities on Polymarket sports markets. The system integrates sportsbook odds APIs to identify mispriced prediction market contracts, executing both market-making and market-taking strategies.
Cross-references sportsbook lines with Polymarket prices to find positive expected value opportunities.
Provides liquidity by placing bids and asks around fair value derived from sharp sportsbook odds.
Aggressively takes mispriced contracts when edge exceeds threshold based on real-time odds movement.
YouTube channel covering sports betting strategy, data-driven analysis, and prediction market insights. Currently on hold — can't create sports betting content while working at Fanatics.
Each matchup simulates an NFL game using nfelo power ratings (from nfeloapp.com) blended with offense, defense, and total DVOA (Football Outsiders) to calculate a true fair-value spread. The DVOA matchup factors in how each offense performs against the opponent's specific defense. Home field is worth ~2.6 points.
The posted spread is based on that fair value, but it's intentionally biased up to ±4 points. Your job is to spot when the line is off. When you see a big misprice, bet heavy — when it looks fair, bet small or skip.
Scores are generated from a historical NFL score distribution so they land on realistic key numbers (3s and 7s). After each bet, you'll see the fair value spread — compare it to the posted line to see whether you had the edge.
Game results use realistic NFL variance (~13.5 pt std dev). Green = covered, Red = didn’t. Think like a sharp.