Okay, so I’ve been messing around with some baseball data lately, trying to see if I could predict how the Diamondbacks (Dbacks) would do. It’s just for fun, nothing serious, but I figured I’d share my little experiment.
First, I grabbed a bunch of past game data. I mean, a lot of data – scores, player stats, who played against who, the whole nine yards. It took a while to find it all and get it into a format I could actually use, you know, like a big spreadsheet.
Then, I started playing around with different ways to look at the numbers. I’m no statistician, so I kept it pretty simple. I looked at things like batting averages, runs scored, and earned run averages (ERA) for the pitchers. My thinking was, if a team scores a lot of runs and their pitchers don’t give up many, they’re probably gonna win, right?
- I focused on the Dbacks’ players first, seeing how they’d been performing individually.
- Then I compared those stats to the teams they were going to play against.
- I even tried to factor in things like home-field advantage, ’cause that seems to matter.
After a while, I had a messy spreadsheet full of numbers and some really basic formulas. It wasn’t pretty, but it gave me some predictions. Basically, I took the Dbacks’ average performance and compared it to their opponents’, and that gave me a guess at who would win.
The Results?
Well, let’s just say it was a mixed bag. Some predictions were surprisingly accurate! I actually guessed a few wins and losses correctly. But others? Way off. Like, I had them winning games they got totally crushed in, and vice versa. So, my “system” definitely needs some work.
It was a fun little project, though. I learned a lot about how much data goes into these kinds of predictions, and it made me appreciate how hard it is to actually predict sports outcomes. Maybe I’ll keep tinkering with it, see if I can improve my accuracy. But for now, I wouldn’t bet any money based on my predictions!
