Okay, so check it, been messin’ around with some baseball stats lately, tryin’ to predict the Yankees vs. Athletics game. Figured I’d lay down what I did, step-by-step, for anyone else lookin’ to do the same.
First thing I did, grabbed a bunch of data. I’m talkin’ team stats, player stats – everything I could get my hands on. Used some websites that track all that stuff. Season stats, recent game stats, you name it. Important to make sure you’re looking at reliable sources, ya know? Don’t wanna base your predictions on garbage data.
Next up, cleaned the data. This is always the most annoying part, right? There’s always some missing values, weird formatting, stuff like that. I used a spreadsheet program to sort it all out. Took a while, but gotta make sure everything’s consistent before you start crunching numbers.
Then, picked some key stats. Didn’t wanna throw everything into the mix, that’d be overkill. Focused on stuff like batting average, earned run average (ERA), home runs, runs batted in (RBIs), on-base percentage (OBP), and slugging percentage (SLG). Basically, the stuff that usually decides a game.
Now, the fun part: built a simple model. I ain’t no statistician, so I kept it pretty basic. I assigned weights to each of those key stats I picked, based on how important I thought they were. Like, ERA for the pitchers got a heavier weight than, say, stolen bases. Total guess, really, but felt right.
After that, I plugged in the Yankees and Athletics stats into my model. Did the math, and got a predicted score for each team. The team with the higher predicted score, according to my little thingy, was supposed to win. Simple as that.
Okay, so the result? Drumroll…My model predicted the Yankees would win. Now, did they win? Well, I ain’t gonna tell ya, gotta go look it up yourself! The point is, it was a fun exercise, and got me thinkin’ about baseball in a whole new way.
Lastly, I reflected on the whole process. My model is definitely not perfect, it’s a very rough estimate. There’s tons more I could add. Weather, player matchups, injuries, even just plain old luck! But hey, it’s a start. Next time, I might try to factor in some of those other things. Maybe even learn some real statistical techniques. We’ll see!
Bottom line, try it yourself! Mess around with the stats, build your own model, and see if you can predict the next game. Who knows, you might be better at this than me!
