Baseball Analytics

2026 · 2026 Competition

School: School of Computer and Information Sciences
Category: Data SciencePrimary

Project Overview

One Liner: Developing an application to provide pitch sequencing strategies for baseball teams

Abstract

The objective of this project is to develop an application that determines the most effective pitch sequencing strategies to maximize pitcher success against opposing batters. The system will analyze pitchers' arsenals, command profiles, and batter tendencies to recommend optimal pitch types and locations tailored to individual matchups.

The final product will include a pre-game scouting report that generates comprehensive pitch sequences for each opposing batter. We will also create a Live Game Feed for users to track model outputs during a game. The baseline functionality for this feature will require a user to enter pitch information manually. If time permits, we will automatically pull the information from the MLB Stats API and produce the outputs instead of solely relying on user input.

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Team Members

Seth Richards
Seth Richards
Lead
Andrew Chen
Andrew Chen
Dylan Ferareza
Dylan Ferareza
Mike Madden
Mike Madden
Lucas Duong
Lucas Duong
Nicolo Agbayani
Nicolo Agbayani

Advisors

Filippos Vokolos
Filippos Vokolos