Intro to Scraping Basketball Reference data
<p><em>A short tutorial on how to scrape data from </em><a href="https://www.basketball-reference.com/" rel="noopener ugc nofollow" target="_blank"><em>https://www.basketball-reference.com/</em></a><em> (or any other sports-reference.com site) with python</em></p>
<p><img alt="" src="https://miro.medium.com/v2/resize:fit:700/0*UBWb9XbWbwIcpcZU" style="height:518px; width:700px" /></p>
<p>Photo by <a href="https://unsplash.com/@echaparro?utm_source=medium&utm_medium=referral" rel="noopener ugc nofollow" target="_blank">Edgar Chaparro</a> on <a href="https://unsplash.com/?utm_source=medium&utm_medium=referral" rel="noopener ugc nofollow" target="_blank">Unsplash</a></p>
<p>Sports-Reference.com is precisely where sports fandom and data science converge. It’s a massive, structured warehouse of clean sports data. Thus, it’s often the starting blocks for academic data science projects.</p>
<p><a href="https://medium.com/analytics-vidhya/intro-to-scraping-basketball-reference-data-8adcaa79664a"><strong>Click Here</strong></a></p>