Okay, so I’ve been trying to get a handle on predicting Knicks games. It’s tough, man! But I figured, why not try to build something myself, even if it’s super basic? So I started messing around with some data.
First, I grabbed some recent game results. I just went online and found a site that listed their scores, wins, losses, and who they played. Nothing fancy, just the basic stuff. I copied it all into a spreadsheet – yeah, I know, super high-tech, right?
My Super Simple “Prediction” Method
- I looked at the last 10 games. Wins and losses, that’s it.
- I calculated the win percentage. So, like, if they won 6 out of 10, that’s 60%.
- I figured out who the opponent was and did the same for them.
Then, the “magic” happened. I basically just compared the win percentages. If the Knicks had a higher percentage, I “predicted” a win. If the opponent had a higher percentage, I “predicted” a loss. I know, it’s incredibly simplistic, but it was a start!
I tested this out on a few past games, just to see how bad it was. Surprisingly, it wasn’t completely terrible. I mean, it was wrong a lot, but it got some right. It felt like it was slightly better than just flipping a coin.
Of course, this doesn’t account for anything like injuries, home-court advantage, or, you know, actual basketball strategy. It’s just a super rough number crunch. I need to find a better way to get a lot more of the detailed game data, for free is preferable.
But hey, it was a fun little experiment. I learned a bit about organizing data, even if my “prediction engine” is basically a glorified calculator. I’ll keep tinkering with it, maybe add some more factors. Who knows, maybe one day I’ll actually crack the code… or at least get a little bit closer than pure chance!
