Alright, so today I’m gonna walk you through how I pulled player stats for the Kansas City Royals vs. Yankees game. It wasn’t too bad, but had a couple of hiccups along the way.
First off, I started by trying to find a reliable API. I spent a good hour just Googling around for sports APIs that offered MLB stats. There are a bunch out there, some free, some paid. I ended up settling on one that had a free tier that seemed decent enough for my needs. I ain’t paying for nothin’ unless I absolutely have to, ya know?
Once I had the API figured out, the next step was to actually get the data. I used Python for this, ’cause it’s what I’m most comfortable with. I installed the `requests` library, which is super handy for making HTTP requests. The first thing I did was just try to hit the API endpoint for the game and see what came back. This involved:
Importing the `requests` library.
Crafting the URL for the API endpoint (which involved figuring out the game ID…more on that later).
Making a GET request to the URL.
Printing the JSON response to see what I got.
It was a big ol’ mess of JSON, but at least I knew I was getting something. The response had all sorts of stuff in it: team names, scores, innings, and, most importantly, player stats.
Now, here’s where things got a little tricky. The API didn’t just give me the player stats directly. I had to dig through the JSON to find the relevant sections. It was nested like crazy! I used Python’s built-in JSON library to parse the response and then iterated through the different sections to find the hitting and pitching stats for each team. It looked something like this:
import requests
import json
api_url = "YOUR_API_URL_HERE" # Replace with your actual API URL
response = *(api_url)
data = *(*)
# Now the fun begins...digging through the JSON
The hardest part was figuring out the structure of the JSON. I basically just kept printing out different sections of the data until I found what I was looking for. It was a bit of a brute-force approach, but it worked.
Once I had the player stats, I needed to format them in a way that was easy to read. I decided to create a simple table with columns for player name, batting average, RBIs, home runs, etc. I used Python’s string formatting to create the table rows. Something like this:
# And then loop through the player stats to print each row
The real pain was getting the game ID from the API. The API didn’t provide a direct endpoint to get the game ID for a specific team matchup on a specific date. I had to first get a list of all games for that day, and then filter that list to find the game that matched the Royals and Yankees. This involved making another API request and then looping through the results. It was kind of a roundabout way of doing things, but it was the only way I could figure it out with this particular API.
Finally, after a couple of hours of coding and debugging, I had a script that would pull the player stats for the Royals vs. Yankees game and print them to the console. It wasn’t pretty, but it got the job done. I could then easily copy and paste the data into a spreadsheet or whatever I needed it for.
Lessons Learned:
Choosing the right API is crucial. Some APIs are easier to use than others.
Understanding the structure of the JSON response is key to extracting the data you need.
Python is your friend!
Don’t be afraid to brute-force your way through things when you’re starting out.
That’s pretty much it. Not the most elegant solution, but hey, it worked! Maybe next time I’ll try a different API or a different approach. But for now, I’m happy with the results.
