Okay, so today I decided to dive into the world of sports predictions, specifically for the Athletics vs. Yankees game. I’ve always been a bit of a stats nerd, and I figured, why not put that to some practical use?
First things first, I needed data. Lots of it. I started by scouring the web for any historical game data I could find between the two teams. I spent a good hour just grabbing wins, losses, scores, and any other stats I thought might be relevant.
Then came the messy part – cleaning up the data. It was all over the place! Different formats, missing information, you name it. I used a simple spreadsheet to organize everything. It wasn’t fancy, but it did the job. I made sure everything was consistent, so I could actually make sense of it.
Next, I started playing around with some basic calculations. I looked at things like:
- Average runs scored by each team.
- Winning percentages against each other.
- Recent performance – who’s hot and who’s not.
It was all pretty straightforward, nothing too complicated. My goal wasn’t to build some super-advanced AI model, just to get a general feel for the game’s likely outcome.
After crunching the numbers, I started seeing some patterns. I wrote down the result I * wasn’t a definitive answer, more like an educated guess based on the data.I am going to write down my own prediction result and the data I used to analyze.
The Result
Finally I got the prediction, and I compared that to the actual game result.I’m not going to lie, sometimes my predictions were way off, it is really hard to predict the game score, even though with a lot data.
But I was able to learn how to write the predictions, and this is the most important thing I’ve learned. I am planning to make more predictiions of other games, maybe next time my predictions will be more accurate!
