Pitch Data Analysis

Overview

This project used pitch-level TrackMan data from two games to analyze pitchers. I first organized the raw dataset in Excel, separating pitches by pitcher and pitch type and summarizing each arsenal using pitch count, average velocity, average spin rate, strike percentage, and CSW%.

I then imported the organized data into Tableau and built a separate visualization for each pitcher. Using the TrackMan horizontal and vertical pitch-location coordinates, I created scatter plots that placed every recorded pitch at its location relative to home plate. I recreated the strike-zone boundaries directly in Tableau so each pitch could be viewed in context of whether it was located in the zone, on an edge, or outside the zone. The plots were then separated by pitch type, allowing all pitch types to be evaluated individually.

Alongside each location plot, I built a statistical table displaying the pitcher's arsenal and the average velocity, average spin rate, strike%, and CSW% for each pitch type. This made it possible to connect the location of individual pitches with measurable outcomes.

For example, identifying breaking balls that generated whiffs below the zone, fastballs that produced swings-and-misses inside the zone, or pitches that consistently missed competitive locations. These types of observations formed the basis of the pitcher evaluations included in the project.

Finally, I used the location plots and pitch-level metrics together to write an individual evaluation for each of the pitchers, focusing on specific characteristics of their arsenal, including velocity, strike throwing, whiff generation, command, pitch usage, and effectiveness by pitch type.