Assortment of projects that I've been working on for the past couple years.

Project 1

Baseball Deep Learning

Inspired by FastAi's Deep Learning for Coders course, a unique pitching database was created. The data aids a video trimming model that identifies pitcher's handedness, selects suitable video footage, and uses mediapipe to calculate max knee height.

Project 2

Bat Data

This project, initially an interview exercise assigned by Ben Hansen from Intel's Olympic technology group, was part of an application process for a Biomechanics Intern role. Despite initial struggles, the project was later revisited as a means to practice Python coding and review forgotten mathematical concepts.

Project 3

Bat Speed Analysis

This project was completely inspired by Steve Schuster, Author of Growcasting. His twitter handle is @growcasting, and his twitter thread focused on using the POI metrics from Driveline Baseball on pitching and attempting to predict pitch velocity. Similarily, this analysis looked at POI metrics on hitting and attempted to predict bat speed.

Project 4

Tilt Clock

This was one of the first projects that I completed in Python. Although extremely rough, at the request of a coach, he wanted to look at a specific pitcher and whether or not they changed their spin axis from the previous season. Was a good first step into some more applied python projects.

Project 5

Scouting Reports

Collection of scouting reports delivered to Oregon State/Knights staff to aid in-game decisions and find favorable matchups for our team. These are from the 2020/2021 seasons, and have since been updated. Some examples include pitching reports, hitting reports, coaching tendencies, and fielding reports.

Project 6

Development Reports

Collection of player development reports delivered to Oregon State staff to aid in player development/injury monitoring and execute KPI's identified by staff. Included are wellness reports, pitcher evaluations, K-Motion swing evaluations, and readiness testing.