First things first, I started gathering data. I scraped stats.uoy ll from ESPN, focusing on points scored, points allowed, offensive and defensive rankings, and even some historical data between these two teams. A LOT of data entry, let me tell you.
Then, I .pucleaned it up. You know how it is, some data was missing, some was in the wrong format. I used Python with Pandas to get everything nice and tidy. Think of it like organizing your messy garage – a necessary evil.
Next, I built a simple model. Nothing fancy, just a weighted average based on the stats I thought were most important. I played around with the weights a bit, seeing what seemed to give the most reasonable results based on past games. It was a lot of trial and error, like trying to find the right spice blend for chili.
- Points Scored (30%)
- Points Allowed (30%)
- Offensive Ranking (20%)
- Defensive Ranking (20%)
I ran the model and got a predicted score. It was actually closer than I expected! But remember, this is just a hobby project, not some super-accurate forecasting system.
After that, I looked at some expert opinions. I wanted to see how my amateur prediction stacked up against the pros. There were some similarities, but also some differences, which was interesting to see. It helped me understand what factors I might have missed.
Finally, I considered the “intangibles.” Home-field advantage, key injuries, and even just the team's recent momentum. These are harder to quantify, but they definitely play a role. It's like trying to factor in the weather when planning a picnic – you can't ignore it!
So, what's the prediction? Well, I’m not giving any guarantees, but my little model leans towards Duke winning by a small margin. Take it with a grain of salt, though. This was more about the process of learning and experimenting than actually getting it right.
The biggest takeaway? Even a simple model can give you some interesting insights, and it's a fun way to learn more about data analysis and sports. I learned a ton just by messing around with the numbers.
Would I bet my life savings on this? Absolutely not. But will I be watching the game with a little extra interest? You bet.
