Blake Munroe

Here’s a little more in depth explanation on FPI: The model uses a Bayesian framework, using priors around the EPA rate of each team unit, derived from preseason expectations. EPA is the foundation for FPI. Each game play has an adjusted EPA based on historical data. EPA breaks down points added in every way, thus having different factors for the team's offense, defense, and special teams units. Generally, the offense and defense factors are independent. FPI is applied to football both at the NFL level and at the college level, but their models are slightly different. In college football, each team unit has its own prior. Four of the main inputs for each prior includes data on the last 4 seasons (with an emphasis on the previous season), the number of returning starters on the offense and defense (with the QB counting as more), a binary input on the returning coach, and the strength of the team's recruiting class (with an input for transfers). College FPI is more reliant on the priors in the model due to the regular occurrences of mismatches each week. The priors are based on the adjusted EPA so that no team dominates.

The fact Michigan only converted 25% of their 3rd downs, while Texas converted nearly 63% is crazy.

Scoring Summary

Special Team Stats

The Longhorns defeated Michigan on Saturday 31-12. Texas, who is now 2-0, simply controlled the game from the start, posting 389 yards on offense while holding Michigan to 284. Offensive Stats Defensive Stats Team Stats

Bobby is in Ann Arbor, Gerry is in Florida and I'm in Texas. Does that help? lol

I scheduled this post haha…. But was up at 4:55!

Join us for Coffee and Football to gear up for Texas-Michigan weekend! Show starts at 8:10 AM and we will be taking your questions plus discussing the big game! We will also be joined by Aaron McMann of MLive. Aaron knows a thing or two about Michigan and will give you his analysis of the game.