Okay, so yesterday I was messing around trying to see if I could get some stats on the Fernandez vs. Tomljanovic match. I mean, I was just curious, you know?
First thing I did was Google around for some APIs. Found a few sports data APIs, but a lot of them were either pay-to-play or just kinda clunky. I wanted something simple, something that wouldn’t take me hours to set up. I ended up settling on scraping data directly from a sports website. I know, I know, scraping isn’t ideal, but hey, it was quick and dirty.
Here’s where things got interesting:
- Scraping the Data: I used Python with Beautiful Soup and Requests. I started by inspecting the webpage source to figure out the HTML structure where the match stats were located. Then, I wrote a script to fetch the page, parse the HTML, and extract the specific data points I wanted, like aces, double faults, first serve percentage, etc. It took a little fiddling to get the selectors right, but eventually, I got a decent chunk of data.
- Cleaning the Data: The scraped data was a mess, as you can imagine. Lots of extra spaces, weird characters, and inconsistent formatting. I used regular expressions and string manipulation in Python to clean it up. I had to convert some values to integers or floats, and handle missing data (some stats were just not available).
- Analyzing the Data: This was the fun part! I loaded the cleaned data into Pandas DataFrames. From there, I could easily calculate some basic stats for each player. Things like total points won, break point conversion rate, and even a simple comparison of their serve performance.
Honestly, it was a bit of a hacky process, but it worked! I got a decent little report on the match. I could see that Fernandez had more aces, but Tomljanovic had a better first serve percentage. It wasn’t rocket science, but it was cool to see the numbers behind the game.
It was a fun little project, and it reminded me how powerful even simple scripting can be. Plus, I learned a bit more about web scraping and data cleaning along the way. Not bad for a Sunday afternoon, right?
I’m thinking next time I’ll try to find a proper API to avoid the scraping hassle. But for now, I’m happy with my little experiment. Maybe I’ll even try to predict the next match based on these stats… who knows!
