Built Around Baseball, Data, and Better Decisions

Baseball has been a major part of my life, and that experience has shaped the way I approach analytics. My background spans college baseball, the Appalachian League, and the MLB Draft League, where I’ve worked across scouting, player evaluation, game preparation, and baseball technology. Those experiences have helped me understand both the analytical side of the game and how information needs to be communicated to coaches and players to actually be useful.

My work combines that baseball background with experience in Python, R, SQL, Shiny, machine learning, and data visualization. I’ve built automated reporting systems, scouting reports, interactive dashboards, predictive models, and other tools designed to turn large amounts of baseball data into clear, actionable information. Currently, I work as a Data Analyst with Queens University of Charlotte while pursuing an M.S. in Sports Analytics at Syracuse University.

Long term, I’m interested in continuing to grow within baseball analytics, particularly in research and development, player evaluation, and decision support. The goal is not just to build more advanced models, but to develop tools and analysis that answer meaningful baseball questions and can make an impact on the field.