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Hitter Evaluation Report

Comprehensive offensive analytics through distribution analysis

Project Overview

Using R as a tool and Trackman CSVs as my data, I aimed to make a report that analyzed hitters through comprehensive statistical distributions and visualizations, going beyond simple averages to reveal true hitting patterns.

R Programming Trackman Data Statistical Distributions

Project Description

For one of my first baseball coding projects, I aimed to investigate hitter performance. When coding my hitter evaluation report, I wanted to use R to read a Trackman CSV and display statistics and plots indicating a hitter's success. In the report's creation, I cared about looking at exit velocity, launch angle, contact, hard hits, whiff, in-zone whiff, and chase.

Why Distribution Analysis Matters

Beyond Averages
I find it useful to look at complete distributions rather than only averages. For example, with launch angles, a lot of ground balls and pop flies could result in a line drive average launch angle, even if the hitter does not hit a lot of line drives. Distributions reveal the full story of a player's performance patterns.
Quartile Analysis
The report displays the distributions of exit velocity and launch angle, including quartiles. This provides a more complete picture of consistency and range, showing not just what a player does on average, but how they perform across all their swings.
Multi-Dimensional Visualization
I have plotted exit velocity against launch angle so coaches can see how hard each hitter hits the ball with respect to different launch angles. This relationship is crucial for understanding the quality of contact and optimal swing paths.

Key Analytical Components

Exit Velocity Distribution

Complete distribution analysis including quartiles, revealing consistency and power across all contact events rather than just average exit velocity.

Launch Angle Distribution

Full distribution showing the true nature of batted ball profile, identifying ground ball, line drive, and fly ball tendencies that averages can obscure.

EV vs. Launch Angle Plot

Scatter plot visualization showing the relationship between exit velocity and launch angle for each batted ball.

Contact Quality Metrics

Analysis of hard hit rate, contact percentage, and overall quality of contact to evaluate offensive production capability.

Swing Decision Metrics

Evaluation of in-zone whiff rates and chase rates to assess plate discipline and pitch recognition abilities.

Example Output: Arizona Wildcats 2024

The following output is for the Arizona Wildcats' 2024 season, demonstrating how the report provides comprehensive hitter evaluations through statistical distributions and visualizations. My code works with any Trackman CSV, making it adaptable for any team or league.

Arizona Wildcats 2024 Hitter Evaluations