The MLB Arbitration Analyzer is an interactive salary projection tool built using historical MLB arbitration and performance data from 2021–2025. The underlying data was organized and cleaned in Excel, then analyzed in RStudio, where separate statistical models were developed for hitters, starting pitchers, and relief pitchers. The final models were integrated into an interactive R Shiny application that uses a player’s prior salary, service time, and performance metrics to project a Team Offer, Midpoint, and Player Ask.
The MLB Lineup Optimizer is an interactive tool built to recommend the best starting lineup for a specific opposing pitcher. Using hitter and pitcher data from 2024–2026, the app evaluates individual matchups, selects the strongest starting nine, and creates a recommended batting order. The project was built in RStudio and integrated into an interactive R Shiny application.
Using FanGraphs and Spotrac data, I built an Excel database measuring cumulative surplus value for MLB players on contracts of four or more years from 2020 through 2026, comparing their production against salary earned during those contract years.
Surplus Value = (total fWAR accumulated during contract × price of WAR) − contract earnings through 2026, with $10,000,000 as the standard market value for one WAR.
In this study, I built Excel databases using FanGraphs and Spotrac data to calculate surplus value for active MLB players and all 30 teams based on 2026 performance and salary data, then highlighting both positive and negative surplus value outcomes.
Surplus Value = (2026 fWAR × Price of WAR) - Salary Obligation, with $10,000,000 as the standard market value for one WAR.
Pitch Plotting Project
In this project, I analyzed TrackMan pitch-level data from two games to evaluate pitcher performance, pitch characteristics, and arsenal effectiveness. I cleaned and organized the dataset in Excel before building visualizations in Tableau.
The analysis incorporated pitch location, velocity, spin rate, strike percentage, CSW%, and pitch type to identify trends in command, swing-and-miss ability, pitch sequencing, and overall arsenal effectiveness.
The button below leads to a collection of my earlier work. While I no longer agree with some of the methodology and conclusions in these projects, I’ve kept them as a record of my growth and development as a baseball analyst.
Feel free to browse the projects below to see how my analytical and technical approach has evolved over time.