Thanks for asking. It is a very simple idea I played around with in my first book, and it has been remarkably accurate this year, calling MSU, PSU, Wisconsin within a point. Off in the Rutgers game by 7.

1. It assumes turnover neutrality.

2. It looks to net yards per pass attempt, on offense and defense, to yield a team strength number.

3. These numbers are sack adjusted, because the NCAA lumps sack yardage in with run yardage.

4. At this juncture of the season, UM's offensive YPPA is 7.54. That's pretty good. Their defensive YPPA is 3.54. Maybe the best number I have seen since looking at this stuff. That's a NYYPA of 4.00. This is a final four quality number.

5. Indiana is 5.80 on O and 6.86 on D for a minus 1.06. That shows a team that is 5.3 points below an average team on a neutral field. The delta is 5.06. That is UM's # is 5.06 higher.

6. In terms of points (a lot of trial and error to fit the outcomes of games) that represents a 25.3 point differential, not adjusting for home field or about 28-29 points in Ann Arbor.

7. As an aside Bill Connelly has UM winning the game by 28.7 points.

Numerous footnotes.

1. Why YPPA? because I was looking for a single variable idea and I read a footnote many years ago (Pete Palmer?) that net YPPA was the only single variable that tended to predict NFL games. After I had played around with this, I found another guy, Bud Goode (deceased) who worked with NFL teams and he believed this was the best single metric for prediction. Goode, I am guessing, did not confront how the NFL put sack numbers to the side, however, keeping them out of run and pass yards.

2. Why no run yards in the equation, like ED Feng and other stat guys do? Because I think run yards are baked into NYPPA. I think looking to relative numbers and not gross passing yards, tends to include the efficiency of a team's run game. Hence, I think looking to all yards gained tends to have "too much running factored in it." Ed doesn't agree with me, but, this year at least NYPPA has been a spot-on metric, better than the multi-variable ideas I have looked at. Admittedly, I haven't studied this carefully. I am old but I still have to make a living. 

3. Why 5 as a multiplier? This is a very crude number that I played around with and it tended to fit/solve the equation in prior games at that time. It would be great to see the NYPPA numbers for every team in the country, but that's more work than I can do. I wish someone else would take that one on. But I have done a few years of BT data, and with occasional outliers, the NYPPA attempt numbers and standings match right up by the end of the season. Usually the outliers have had crazy TO numbers or have exceptional/dreadful special teams.

4. About 5 other footnotes about run yards, pass yard, fumbles, interceptions, but I suspect I am boring you, assuming anyone is still breathing in this particular dimension.in the first place.

CR