Transforming complex datasets into actionable insights through advanced analytics and innovative solutions
Interactive SQL interface for querying 4 seasons of MLB Statcast data covering 2021-2024. Features sample queries and a recursive query calculating a batter vs pitcher running slashline.
Explore Database →Advanced clustering analysis identifying "Gold Standard" starts in MLB. Used multi-stage k-means clustering to discover elite pitcher performance patterns and early-game indicators that predict success through 27+ batters.
View Research Paper →Interactive R Shiny application for retail trade area analysis. Generates sales data based on store locations and block group proximity, then creates interactive maps allowing users to define custom trade areas and export shapefiles and CSV mappings.
Deep dive into stolen base success factors using advanced statistical modeling. Analyzes game situation, pitcher timing, and catcher effectiveness.
Coming SoonMy love for analytics started with the Tampa Bay Rays. Growing up watching them build from absolutely nothing into a competitive team, I got hooked on how smart use of data could turn disadvantages into strengths. Those late 2000s Rays teams showed me that with the right approach, you could compete with anyone.
I've spent my career in the grocery industry working as a Fraud Analyst, Pricing Analyst, and Senior Real Estate Analyst. Each role taught me something different about finding patterns in data and turning insights into real business decisions.
I'm pretty avid in OOTP online leagues, consistently turning around struggling teams into playoff contenders. When I couldn't make my high school's baseball team, I joined the newly formed lacrosse team as a goalie, eventually playing three years as a defender at the University of South Florida. I still try to stay active with running, and at home I'm completely owned by my two cats, Nugget and Maple.