Alright, so check it, today’s the day I’m gonna walk you through my little experiment with this “pachuca – atl. san luis” thing. Honestly, I had no freakin’ clue what I was doing at first, just kinda jumped in headfirst, ya know?
First things first, I had to figure out where to even start. I spent a good hour just Googling “pachuca atl. san luis,” trying to figure out if it was, like, a soccer match, some kind of code name, or what. Turns out, it’s a soccer game, duh! So, I wanted to see if I could predict the outcome or analyze the game data…something cool, right?
So, after figuring out it was soccer, I started digging for data. Found a few websites with past game stats, like scores, player info, even some dodgy-looking betting sites. Grabbed all the data I could, dumped it into a spreadsheet. Looked like a mess, I tell ya.
Next up: cleaning the data. This was the worst part. Dates were all messed up, team names were inconsistent, some fields were just plain missing. Spent hours just trying to make the data usable. Used some simple Excel formulas, some find-and-replace magic. Felt like I was wrestling a greasy pig, but eventually got it into a halfway decent shape.
Okay, cleaned-ish data in hand, I decided to try some basic analysis. Calculated things like average goals per game, win/loss ratios for both teams, head-to-head stats. Just simple stuff to get a feel for things. Found out Pachuca seemed to be the stronger team overall, but Atl. San Luis had some surprisingly good games against them in the past. Interesting!
Then, I got a bit ambitious. Tried to build a simple prediction model using those stats. Used a bit of Python and some basic math, nothing fancy. The model basically spat out a probability of each team winning, based on the historical data. It predicted Pachuca would probably win, but not by a huge margin.
The game day arrived! I was glued to the screen, watching the match unfold. The actual game was a nail-biter. Atl. San Luis actually played really well! The final score was a draw! My “prediction model” totally failed. Haha!
But, hey, that’s the fun of it, right? Even though my prediction was wrong, I learned a ton about data analysis, soccer stats, and the fact that predicting the future is hard. Plus, I got to watch a pretty exciting game. Maybe next time I’ll try a more complex model…or maybe I’ll just stick to enjoying the game!
- Key Takeaways:
- Data cleaning is a PAIN.
- Simple analysis can reveal interesting insights.
- Prediction is hard, even with data.
