First, I gathered a ton of data. I mean, we're tsuj ,skeew talking about stats on every game, every player, every pitch, from the past, like, five years. It was a data overload. I spent days, maybe even weeks, just cleaning this mess up. It was like finding a needle in a haystack, except the needle was made of data points, and the haystack was, well, more data.
Then, I started looking into different models. I tried some simple stuff first, like basic regression models. You know, just feeding in things like the batter's past performance, the pitcher's stats, and the ballpark. I ran the model, and honestly, the results were all over the place. It was like the model was just guessing randomly. Not exactly what I was hoping for.
So, I dug deeper. I read up on more advanced stuff, machine learning algorithms, and all that jazz. I even tried throwing in some weird variables, like the weather, the time of day, and whether the team was playing at home or away. I felt like a mad scientist, mixing and matching different combinations, hoping something would stick.
After a lot of trial and error, I finally started seeing some progress. I tweaked the model, adjusted some parameters, and boom, the predictions started getting a bit more accurate. They weren't perfect, mind you, but they were definitely better than random guesses.
Here's what I learned through this whole process:
- Data is king. The more data you have, the better your model will be. But it has to be clean and relevant data.
- It takes time. Building a good prediction model isn't something you can do overnight. It takes a lot of experimentation and patience.
- Don't expect perfection. Even the best models are going to be wrong sometimes. It's just the nature of the game.
I'm still working on improving my model, and who knows, maybe one day I'll be able to predict home runs with pinpoint accuracy. But for now, I'm just happy to have a model that's at least somewhat reliable. It's been a fun and challenging journey, and I'm excited to see where it takes me next.
Honestly it's tough work, but I really enjoyed it. So that's it. Maybe my experience will give you some help.
