Roshan Shah | Polygence
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Symposium

Of Rising Scholars

Fall 2025

Roshan will be presenting at The Symposium of Rising Scholars on Saturday, September 27th! To attend the event and see Roshan's presentation.

Go to Polygence Scholars page
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Polygence Scholar2025
Roshan Shah's profile

Roshan Shah

Class of 2026Whittier, California

About

Projects

  • "Research Question: How does competitive balance vary across professional sports, and what is the path for the NBA to become more competitive?" with mentor Molly (May 31, 2025)
  • "Backboards & Dashboards: Using analytics to understand sports performance" with mentor Sejal (July 9, 2024)

Project Portfolio

Research Question: How does competitive balance vary across professional sports, and what is the path for the NBA to become more competitive?

Started Sept. 6, 2024

Abstract or project description

Description: This research project will evaluate the competitive balance in sports leagues, specifically within the NBA. I will be collecting data from the NBA and other leagues to measure and compare competitive balance. Additionally, I will be exploring why competitive balance may change over time within a league and vary between leagues. This research is important because competition drives entertainment in sports, and games are better to watch as a fan if they are more competitive. The NBA has enacted a few changes to drive competition in the league (e.g., in-season tournament), and my goal is to evaluate the impact of these changes and understand where the NBA sits in the competitive landscape.

Project Portfolio

Backboards & Dashboards: Using analytics to understand sports performance

Started May 28, 2024

Portfolio item's cover image

Abstract or project description

Is the saying “defense wins championships” true or false in basketball? How much does a team's home court advantage really matter? Which teams rely on 3-point shooting most heavily as part of their offensive strategy? Whether you're an athlete or a sports fan, learn how data analysis can drive increased performance for sports teams. In this pod, you will learn how to acquire a basketball dataset from the web, perform basic data cleaning and analysis in Python, and create compelling visualizations conveying basketball statistics and trends. While the initial lessons will focus on basketball data, the skills learned can be applied to any sport. Toward the end of the course, you will hone in on a specific research question which can be examined and answered using your newly acquired data analysis skills! You will learn how to build a low-code, Python-based interactive web app using a framework called Streamlit.