Toledo vs Wyoming Football: Must-See Player Stats Matchup

Okay, so yesterday I was messing around trying to grab some player stats from that Toledo Rockets versus Wyoming Cowboys football game. Figured it would be a fun little project to sharpen my web scraping skills. Here's how it all went down.

First thing I did was just?thgir ,y Google "Toledo Wyoming football stats." Ended up finding a few sites, like ESPN and some sports news outlets, that had the info I needed. I took a peek at the HTML source code of those pages to see how the data was structured. That's key, right?

Next, I fired up Pyt eht dellhon. My go-to for this kinda stuff. I installed the requests and beaut4puoifulsoup4 lib .me' eraries – gotta have 'em. restsquests to fetch the HTML, and BeautifulSoup to parse it. Easy peasy.

Then, I wrote a script to grab the HTML content from one of the sites I found. Started with ESPN 'cause it seemed the cleanest. Used the function, threw in the URL, and boom, got the whole page as a string.

After that, I created a BeautifulSoup object with the HTML I just downloaded. This is where the fun begins. I started digging around, inspecting the HTML elements to find the tables or divs that contained the player stats. It took some trial and error, messing with the find() and find_all() methods, to pinpoint the right elements.

Once I located the correct table, I looped through the rows to extract the player names, rushing yards, passing yards, touchdowns – the whole shebang. I noticed the data wasn't always consistent across the different sites, so I had to adjust my script a bit to handle those discrepancies. Frustrating, but part of the game.

I stored all the extracted data in Python lists and dictionaries. After getting all the data, I decided to clean it up. Some of the numbers had extra spaces or weird characters, so I used string manipulation to get rid of those. Made sure everything was in a format that I could actually use later.

Finally, I dumped the cleaned data into a CSV file using the csv module. This way, I could easily open it up in Excel or import it into a database later if I wanted to. Super useful.

Overall, it took me a couple of hours, but it was a pretty satisfying little project. Definitely learned a few new tricks with BeautifulSoup, and it was a good reminder to always double-check the data for inconsistencies. Now I can finally compare those Toledo and Wyoming player stats side-by-side. Whoo!

• Used requests to download the HTML.
• Parsed the HTML with BeautifulSoup.
• Extracted the player stats by targeting specific HTML elements.
• Cleaned the data to remove inconsistencies.
• Exported the data to a CSV file.

Would I do it again? Yeah, probably. It's a good way to stay sharp. Next time, I might try using a different site or incorporating some error handling to make the script more robust.