Okay, so I’ve been messing around with some data and machine learning stuff lately, and I thought I’d share what I did with this “Albot Shelton prediction” thing. It’s not rocket science, but it was kinda fun.
So, first, I started digging around to see what this whole thing was about. Turns out, it’s a tennis match between these two players, Radu Albot and Ben Shelton. They are supposed to play in some tournament called the Citi Open in Washington. The match is scheduled for Wednesday, July 31st, 2024, apparently.
I saw some chatter online about it being a “highly anticipated match.” Honestly, I don’t follow tennis that much, but it seemed like a good enough excuse to play with some numbers. I found out that Ben Shelton is the “second seed” and Radu Albot is a “qualifier” from Moldova. Whatever that means. Shelton is ranked No.14, and Albot is ranked No.152. I guess that means Shelton is expected to do better.
Next, I got into the “prediction” part. The internet said I should use “innovative machine learning and data.” Sounds fancy, but really, I just used some basic tools that are out there. Nothing too crazy.
- Gather data: First, I had to collect some data. I found some numbers about Albot and Shelton, like their rankings, maybe some past match results, and other stuff I could get my hands on.
- Clean up the mess: Of course, the data was all over the place. Different formats, missing pieces, you name it. So, I had to spend some time cleaning it up, making sure everything was consistent and usable.
- Pick a model: Then came the time to choose a machine learning model. There are tons of them out there, but I went with a simple one. I’m not trying to win any awards here, just having a little fun.
- Train the model: I fed the cleaned-up data to the model and let it do its thing. Basically, it’s trying to find patterns and relationships in the data to make predictions.
- Make the prediction: Finally, I used the trained model to predict the outcome of the Albot vs. Shelton match.
And you know what? The model says Shelton is more likely to win. I guess that’s not too surprising, given that he’s ranked much higher. The internet says Albot has +375 odds, which I think means he’s the underdog.
But hey, who knows? It’s just a prediction. Anything can happen in sports. Maybe Albot will pull off an upset. I’ll probably forget about this whole thing by tomorrow, but it was a fun little experiment. Maybe I’ll try it again with some other match sometime.
Anyway, that’s my little story about playing around with machine learning and tennis predictions. It wasn’t a big deal, but I thought I’d share. You never know, maybe it’ll inspire someone else to mess around with data and see what they can come up with. It’s pretty cool what you can do with just a little bit of data and some basic tools, even if you’re not a pro.
