Group pitch movement profiles, usage patterns, and outcomes into cleaner scouting and development views.
Baseball analytics
Baseball
Pitch design, batted-ball modeling, scouting tools, and game-planning support.
Workstreams
What this team studies
Evaluate batted-ball tendencies, alignment choices, and run-prevention tradeoffs.
Turn public and internal data into matchup plans, tendencies, and pre-series context.
Featured work
MLB Defensive Shift Analysis
A 2016-2019 MLB shift analysis that models team-level shift usage, builds a shift effectiveness metric, and compares hitter outcomes with and without shifts using regression, random forests, and significance tests.
Problem
The defensive shift has become ubiquitous in MLB, but its actual impact on run prevention versus its adoption rate is poorly understood at the team level.
Approach
The team correlates shift deployment frequency with defensive efficiency metrics across four seasons of team-level data, controlling for handedness distributions and batted-ball profiles.
Result
Read paper Certain defensive metrics show stronger correlation with shift usage than others, and high-shift teams do not consistently outperform low-shift teams on overall run prevention.
Active projects
Current work
Active work will be published after project approval.
Archive
Research
Past work
ResearchMLB Defensive Shift Analysis
January 23, 2021Baseball · 2020-21
A 2016-2019 MLB shift analysis that models team-level shift usage, builds a shift effectiveness metric, and compares hitter outcomes with and without shifts using regression, random forests, and significance tests.
RRegressionRandom Forest
