NBA 3-Pointer Analysis

For this project, I chose to conduct research on a topic I have had plenty of experience following but had never examined as a data analyst. In the Spring of 2022, I took the Data Analysis course at the Pratt Institute, which gave me a broad overview of the different tools used in data analysis and the methods that can be applied to use them. The course heavily focused on statistical research methods in R, a tool I was excited to add to my technical background.

I chose to examine the correlation between the rise of 3-point shooting in the NBA and the decline of the center position — specifically, whether a center's ability to make 3-point shots had a significant effect on playing time. To approach this question, I collected NBA player statistic data with the help of Python and the BallDontLie API. After collecting the data, I used Pandas to clean and export it to a workable CSV format. Once ready, I conducted statistical analysis in R, plotting linear regressions and correlation matrices across different stat categories.

The findings were significant — my research showed a sharp decline in playing time for NBA centers who don't convert 3-point attempts efficiently. I presented my findings using Reveal.js in R, which allowed me to make the presentation interactive. To view the full project, click here.