AstroDebugger - Exploring the Imapct of Travel on performance

Welcome to AstroDebugger, a data science project created by our team of four college students for Rice Datathon 2024. Despite being a mix of experience levels, with only one seasoned data scientist guiding the way, we presented an ambitious project that reflects our collective passion for learning and exploration.

Inormation About Rice Datathon 2024

datathon.rice.edu/

Competition on devpost

Objective

The primary goal of AstroDebugger was to investigate the impact of travel on the performance of baseball teams, utilizing data science techniques. The primary performance metric that we used was On-base Plus Slugging (OPS), providing a full view of offensive capabilities.

What is On-base Plus Slugging (OPS)?

OPS is a commonly used performance metric for baseball teams.It measures a players ability to get on base and the their ability to hit the ball.

Key Features

Linear Regression Modelling:

AstroDebugger primary model utilized linear regression techniques to analye the provided data. Utilizing linear regressions allowed us to uncover patterns and relationships between travel variables and the OPS performance metric.

Acknowledgements

AstroDebugger wouldn't have been possible without the collaborative efforts of the team. We extend our gratitude to Rice University and all their sponsors for hosting the hackathon and providing the platform for learning and exploration.

Thank you to all the sponsors of the Rice datathon!