About
Our Mission
Walk-Off Labs builds products that help baseball teams turn data into actionable insights. We're a small group of engineers and academics with deep expertise in statistics, machine learning, and game theory.
The Problem We Solve
Every team in baseball has access to sophisticated matchup models and probability estimates. The tools exist. The data exists. But most teams aren't using them optimally.
Traditional approaches look at individual matchups in isolation. They tell you the probability of an outcome, but they don't tell you how to sequence decisions across an entire game to maximize your chances of winning.
Our Approach
We use game theory and Markov Decision Process (MDP) solvers to find optimal strategies. Instead of asking "what's the best play right now?", we ask "what sequence of decisions gives us the best chance to win the game?"
Our platform, Perfect Game, takes the Bayesian matchup models that teams are already using and finds the optimal way to act on them.
Our Team

Tristan Mott
Research Scientist
Brigham Young University
Tristan researches advanced statistical methods and machine learning applications for sports analytics.

Caleb Bradshaw
Research Engineer
Walk-Off Labs
Caleb is a software engineer specializing in building systems that apply Walk-Off Labs' cutting edge research.

David Grimsman
Professor of Computer Science
Brigham Young University
David has expertise in game theory and multi-agent systems.

Chris Archibald
Professor of Computer Science
Brigham Young University
Chris specializes in artificial intelligence, game playing, and decision making under uncertainty.