Okay, so check it out, today I’m gonna spill the beans on this little project I was messing around with, right? It’s called “phillies foul ball”. Don’t ask me why, the name just kinda stuck.
First things first, I had this idea kicking around in my head about trying to, like, predict where a foul ball might land during a Phillies game. Total long shot, I know, but hey, gotta start somewhere, right?
So, I started gathering data. Lots and lots of data. Stuff like:
- Batter stats: Which way they usually hit? How hard? You know, the usual baseball jargon.
- Pitch type: Fastball? Curveball? Slider? All that jazz.
- Wind conditions: Is it blowing in? Out? Sideways? Makes a big difference.
- Previous foul ball locations: Where have they landed before? Gotta see the patterns.
Next up, the coding part. I ain’t no data scientist or nothing, so I just used Python ’cause it’s what I know, you feel me? I used libraries like Pandas to wrangle the data and Matplotlib to try and visualize some of it. Honestly, the visuals weren’t that helpful, just a bunch of scatter plots all over the place.
Then I tried a couple of different models. I messed around with some basic machine learning algorithms, nothing too fancy. I tried a linear regression, just to see what would happen. Then I fiddled with a decision tree, hoping it could pick up on some of the more complex relationships. Spoiler alert: neither one worked particularly well. I mean, I was basically just throwing stuff at the wall to see what would stick, you know?
The hardest part was dealing with the randomness. Baseball is just inherently unpredictable. A batter could swing and miss completely, or they could get a piece of it and send it flying into the stands in a totally unexpected direction. Trying to account for all that variability was a real headache.
The Results (Or Lack Thereof)
Alright, so, the big reveal… did I manage to predict where foul balls would land? Nah, not even close. My “model” was about as accurate as flipping a coin. Maybe even less accurate, haha!
But hey, that’s okay. I learned a ton in the process. I got more comfortable working with data, I got some practice with Python, and I got a better appreciation for just how unpredictable baseball can be.
Would I do it again? Probably. Maybe I’ll try a different approach next time. Or maybe I’ll just stick to watching the game and catching foul balls with my bare hands. That seems to be more reliable at this point!
The biggest takeaway? Don’t be afraid to tackle a project, even if you’re not sure you can pull it off. You might not succeed, but you’ll definitely learn something along the way. And that’s what it’s all about, right?
