Getting Down to Brass Tacks with Rolando’s Numbers
So, the other day, I got stuck on this thing about “rolando stats”. It wasn’t even for anything super important, just trying to settle a pointless argument with a buddy about how good this guy actually was back in his prime. You know how it goes.
First thing I did was just hit the usual spots online. Typed in his name plus “stats”, “career numbers”, all that jazz. Easy enough, right? Wrong. What I got back was a real mess. One place had one set of numbers, another site had slightly different ones. Some didn’t even cover the same years, or they counted things differently. It was maddening.
Okay, I thought, I need to get organized. I started pulling data from maybe three or four sources that looked halfway decent. Just copied and pasted stuff into a spreadsheet at first. It looked like spaghetti. Different columns, different names for the same stat, missing data all over the place. You’d think something simple like game appearances would be consistent, but nope.
This needed a bit more effort.
I figured I’d try and clean it up. Spent a good hour just trying to line up the years correctly and standardize the stat names. Found myself doing a lot of manual checking, like going back to old match reports where I could find them, just to verify a single number sometimes. It felt like real detective work, but honestly, mostly just tedious.
Then I thought, maybe I could write a tiny script. Nothing fancy, just something quick to pull data from one or two places that seemed the most reliable and try to merge them. Fired up my editor, hacked together some basic stuff. It sorta worked, but kept breaking whenever one of the sites changed its layout even slightly. More trouble than it was worth, really.
Here’s what I ended up with:
- A spreadsheet that was better, but still full of holes and question marks.
- A half-broken script I probably won’t use again.
- A lot of wasted time.
And the funny thing? After all that, I still couldn’t definitively say I had the perfect stats for Rolando. The argument with my buddy? We just kinda dropped it. Wasn’t worth the headache.
It got me thinking, though. Reminded me of this project I worked on years ago. We were trying to track user behavior on some old platform. The data we were getting was just as messy. Different systems logging things differently, timestamps all over the place, stuff missing. We spent weeks, maybe months, just trying to make sense of it before we could even start analyzing anything useful. We built dashboards, wrote complex queries, had meetings about data definitions. In the end, the underlying data was so shaky, the insights we got were always questionable. Felt like building on quicksand.
Looking back, it’s kinda the same thing with these Rolando stats. You can spend ages trying to get the perfect picture, chasing down every little number. But sometimes the data’s just not there, or it’s unreliable. You gotta know when to say, “Good enough,” or just walk away. Otherwise, you just spin your wheels forever on something that doesn’t really matter that much in the grand scheme of things. Learned that lesson the hard way, I guess. Twice.
