Web scraping for sports analytics

In the modern age of the internet, there are lots of websites that store a variety of valuable data. In the world of sports, many of this data is publicly available but not always in an easily accessible format. Web scraping is an automated process used to gather data from websites that allows us to access and collect large amounts of data directly from web pages if the information is not available for download. This workshop will 1) introduce the basics of web scraping 2) show how to webscrape sports related websites with Python, including examples and 3) discuss how to ensure you are scraping ethically.

Prerequisites: In order to perform the code we will be discussing, you need to have downloaded Python, the beautifulsoup4, selenium, pandas, and requests packages, and a web-driver of your choosing (preferably Chrome Driver).

Melanie Desroches is a senior at the University of Connecticut majoring in Statistics and minoring in Computer Science. She is currently working with the UConn Men’s Ice Hockey team to determine how prospects' performance will translate to the NCAA and more specifically, the Hockey East conference. Melanie is a hockey fan but also loves learning about a variety of different sports and how statistics can be used to answer questions within the sports world.