Date of Completion

Spring 4-25-2024

Thesis Advisor(s)

Daniel Watt; Stephen Camilli

Honors Major

Mathematics/Actuarial Science

Disciplines

Data Science | Probability | Statistical Models | Statistical Theory

Abstract

The building of a tool to be utilized by UConn’s Division I baseball team that will generate a game plan for when different relievers should be used against different parts of the opponent’s lineup to achieve the lowest total expected value of runs allowed for the remainder of the game based on game situations and matchup probabilities. The tool will also examine and determine situations that may be vital enough to the outcome of the game to bring in a better reliever normally saved for later in the game.

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