Scraping statistics of NCAA Basketball Players

Data is scrapped from https://basketball.realgm.com/ and https://www.sports-reference.com/ using BeautifulSoup.

Introduction

Each year, the National Basketball Associaton (NBA) holds an annual draft, where 60 players get selected and ther remaining 30-40 players are left undrafted. Majority of these players come from NCAA Basketball. In this project, I scraped data of NCAA Basketball players', such as their on-court statistics, amongst other things such as their age, height, weight, position, etc.

The next part of the project can be found in my other repository, where I tried to predict how players will fair in the draft based on the data scraped in this repository.

Getting Started

Prerequisites

Python 3.8, conda and pip.

Installation

conda install jupyter
conda install -c anaconda numpy pandas
conda install -c conda-forge beautifulsoup4 requests

Running the workflow

Web Scraping

The web scraping of data between the years 2005 - 2019 can be executed simply with: python scraping.py To scrape other years, the script can be edited in scraping.py. However, the code might not work properly due to the differences in HTML layout patterns in https://www.sports-reference.com/ for earlier years (before 2005).

Author

Chua Jing Yang