Web Scraping NBA Stats in Python

In this project, you'll assume the role of a data analyst working on a machine learning project to predict the NBA's Most Valuable Player (MVP) for a given season. You'll focus on web scraping to gather the necessary data on NBA player and team statistics from 1991 onwards. Using Python libraries like requests, Beautiful Soup, and Selenium, you'll scrape data from multiple web pages, parse the relevant tables, and combine them into unified datasets. This project allows you to apply and enhance your web scraping skills in a practical, sports analytics context. You'll gain experience extracting data from both static and dynamically-loaded web pages. **Objective:** Scrape, parse, and combine multiple seasons of NBA player and team statistics to enable future machine learning analysis for predicting season MVPs.