Tyler James Burch
Lead Data Analyst, Baseball Analytics
Boston Red Sox
Applying research methods, statistics, machine learning, and Bayesian modeling to solve problems in professional baseball analytics.
Baseball Analytics
Advanced statistical modeling and machine learning applications in professional baseball operations and player evaluation.
Data Science
Expertise in Python, R, machine learning, and Bayesian methods for complex analytical challenges.
Technical Computing
Experience writing scalable software for some of the world's largest datasets, on some of the world's fastest computers.
Research Background
Earned a Ph.D. in particle physics, and completed postdoctoral research in machine learning and physics simulation.
Recent Blog Posts
March Madness 2026 — Interactive Forecast Dashboard
Live Bayesian bracket predictions for the 2026 NCAA Tournament, updated daily.
Forecasting March Madness 2026 - Latent Skills Models
Building a Bayesian offense-defense model for the 2026 NCAA Tournament, finding a Simpson's paradox hiding in the correlation, and what...
2024 Rewind: Orthogonal Polynomial Regression in Bambi
A deep dive into what orthogonal polynomials actually do under the hood, contributed to Bambi's examples