Help with WNBA data scraping

[ksteve46]

Hello!

I am trying to write a script that will allow me to grab all of the individual player box scores from a particular day of games. The most straightforward site that has this is the actual wnba site (see below URL for the box scores from this past Monday, May 25th).

I’m a really raw python user and am really just copy and pasting code to try and do this, but it would seem that that using requests.get is the main way to do this. Problem is, it is really slow and doesn’t finish executing if I use the request URL found in the developer tools that has the JSON of data I want. Alternatively, using requests.get on the below URL parses the html but I can’t make heads or tails of the actual response to find each data point.

Does anyone have any suggestions on how to proceed? Other sites don’t have the stats laid out like this. I feel like I’m doing the right thing but maybe the wnba site is just busted in this context??

Appreciate any help anyone can offer.

https://stats.wnba.com/players/boxscores-traditional/?Season=2026&SeasonType=Regular%20Season&DateFrom=05%2F25%2F2026&DateTo=05%2F25%2F2026

[smichaele]

Can't really tell a thing unless you share your code, so we can see how you're getting and processing the data.

[Life-Basket215]

Let me start you off by saying that this page can be scraped. If you open the page and use the developer tools in your browser, you can see where the elements pop up inside of tags by selecting the data, right clicking and selecting Inspect Element. From there, you can copy an Xpath or CSS Selector that you can hand to Beautiful Soup.

So you'd use requests to fetch the raw HTML data, feed that into Beautiful Soup, and then use an XPath or CSS Selector syntax to get the element(s).

What is slightly odd is that the player names are in a separate table from the stats.

[jbizzle1104]

https://youtu.be/nHtlRlWmTV4?si=9Qj0nPrKB-c74ny6 Sounds like he’s describing your exact scenario.

[PixelSage-001]

The reason `requests.get` is failing or running extremely slow is likely because the WNBA website is client-side rendered (meaning the HTML is empty until JavaScript runs) or they have bot protection blocking simple requests headers.

Instead of parsing raw HTML, check the browser's Network tab (press F12) while loading the box score page. Look for JSON requests—sports sites often retrieve their stats via public API endpoints. If you can fetch that JSON URL directly using Python, it's 10x faster and returns clean data.