Baseball

This project aimed to visualize the efficacy of pitch types in every iterable combination of balls, strikes, outs, baserunners, pitcher & batter handedness, and pitcher velocity and spinrate capabilities. The result was a R ShinyApp dashboard that provides real-time calculations based on the inputs provided. 

This project, similar to the pitch efficacy visualizer, aimed to calculate stolen base probabilities and expected gains from attempts based on Catcher Pop Time, Runner Speed, Game Situation, Pitcher Delivery Time, and Pitcher Pickoff Tendencies. From there, a recommendation of whether or not to attempt a steal and the result of "Expected Runs Added" is outputted. 

This project was a part of the 2025 Cincinnati Reds Hackathon, a competition in which contestants were tasked with modeling expected playing time for the 2024 mlb season using only the provided 2021-2023 Baseball Savant pitch-by-pitch dataset. In this competition, my team and I defeated numerous Ivy League, Doctorate, Master's students and prestigious analytics organizations from around the country en route to a finalist nomination. 

This project embarked on an exploratory analysis of the effects of shifts and shades in the infield and outfield, modeling how batting averages and expected batting averages of individual and the league-wide collective of batters in the MLB were affected when facing shifts and shades while batting.