When we last left off, we covered how LRMC works and how to implement it mathematically. With our understanding of LRMC, we are now prepared to implement a version of LRMC computationally for ranking CFB teams. To start with, let's fire up our Python notebook. »
You might wonder, why is it so difficult to calculate some of these metrics? We have games and data, right? While that may be true, there are several factors that serve to complicate things this season. »
Welcome back! Last post, I gave a high-level overview of my models that predict game winners vs. losers and the spread. As always with machine learning »
Greetings everyone! As a quick introduction, my name is Matt and I'm a machine learning engineer from the Pittsburgh area. This is my first of hopefully »
It's been awhile since I've done one of these. If you're familiar with my Talking Tech series, this entry will be much shorter. If you follow »
College football can be confusing. It feels like a 13 game regular season can have so many twists and turns that the team you are watching »
Welcome to By The Numbers, a series in which I plan to preview upcoming games using numerical analysis. I hope to make this a regular feature »
In the last edition of Talking Tech, we created our own rating system using an SRS algorithm. We're going to build off of that work to »