Regression and Residual Analysis

with 2019-2020 NBA Player Statistics

Presenter: Bryce Jones

Co-Presenter(s):
Dustin Yan

Presenter Status: Undergraduate student

Academic Year: 19-20

Semester: Spring

Faculty Mentor: Elaine Newman

Department: Mathematics

Abstract:
Our motivation for this project is to see how impactful a NBA basketball player is to it’s team based on how many points they contribute per game. Additionally, we are testing to find out if there are correlations between other important game factors and their overall score performance. We analyzed the amount of points a player makes and see if it can be correlated based on their position, team, minutes played in a game, field goal percentage, 3-point field goal percentage, free throw percentage, rebounds per game, and player efficiency rating from ESPN 2019-2020 data. Using the statistical computer program R, full regression and residual analysis was completed alongside descriptions of useful graphs, plots, tables, and hypothesis tests.