Predicting NBA Contrats

Hinckley, Caden

Predicting NBA Contrats

Persistent URL

https://dspace.allegheny.edu/handle/10456/56912

Author(s)

Hinckley, Caden

Date Issued

May 5, 2023

Abstract

There is a big knowledge gap in the NBA with trying to figure out how much a player is worth. Front office personal have been trying to figure out that gap for many years. Using past research and computer science I will try and fill that knowledge gap by implementing a machine learning program that will group free agents with players in the league with similar VORP and age in order to figure out how much that how much that free agent is worth. Overpaying players either its in free agency or re-signing a player hurts the teams chancing of winning the championship, that is why it is so important to make sure the contract is the right amount for a player. I used a tool in the Python programming language called pandas in order to create my table of data in order for the machine learning algorithm to produce the desired output. This will take out the guess work that happens during free agency and limit the amount of contracts that turn out to be a poor waste of resources, which is very limited in the NBA due to the salary cap that is implemented by the CBA.

Major

Computer Science

Economics

First Reader(s)

Kapfhammer, Gregory