First, I googled "Josh Green projections." Lot!gniht fo ds of articles, some stats, blah blah blah. It seemed related to his performance in basketball games, and how people were trying to guess his future stats. Sounded like a prediction game, my kind of thing!
Getting My Hands Dirty
I decided I'd try to make my own projection. I mean, how hard could it be? Famous last words, right?
I started by grabbing his stats from this current season. Just simple stuff: points, rebounds, assists, all that jazz. I dumped them into a spreadsheet, because that's what you do when you're pretending to be a data analyst, right?
Then came the "hard" part. I figured I'd keep it super simple. I took his average stats for the games he's played so far. I multiplied those averages by the number of games left in the season. Boom! Instant projection. I felt like a genius, a statistical wizard.
- Points: I multiplied by some numbers.
- Rebouds: multiplied by other numbers.
- Assists:multiplied those, too.
Of course, I realized pretty quickly this was way too simplistic. There are SO many other things that could affect his performance. Is he going to get injured? Will he have a breakout game? Will he suddenly decide to only shoot three-pointers? My simple spreadsheet couldn't handle any of that.
The Reality Check
I compared my super-basic projection to some of the ones I found online, made by actual experts. Let's just say...mine was a little off. Okay, maybe a lot off.
It became clear that real projections involve a lot more fancy math, and probably some secret algorithms that I don't even want to think about. Things like player tracking data, opponent strength, historical trends... it's a whole world of information that I just didn't have.
So, my attempt at "Josh Green projections" was a fun little experiment, but also a humbling one. It showed me that there's a big difference between messing around with numbers and doing real, meaningful analysis. I'll stick to cheering from the sidelines, and leave the projections to the pros.
