This repository contains an analysis of NBA player statistics using Linear Regression. The goal is to predict specific player performance metrics based on historical data. The analysis is designed to help understand the relationships between different performance indicators, such as points per game, assists, rebounds, and other key metrics.
The dataset used in this project is based on NBA player statistics, which includes various metrics such as:
Points per Game (PPG) Assists per Game (APG) Rebounds per Game (RPG) And others... Data is sourced from public NBA databases and is preprocessed to handle missing values, outliers, and normalization.