Baseball · Research
MLB Defensive Shift Analysis
2020-21Updated Jan 23, 2021Archived
Project Overview
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 & Objective
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.
Analytical 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.
Key Result & Impact
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.
Tech Stack & Tools
RRegressionRandom Forest
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