What is Ranking Theory?

So if I'm going to be spending all this time talking about Ranking Theory and which teams aren't dropping enough to fit the theory and all that, I should probably explain just what Ranking Theory is and why I'm doing it.  In short, Ranking Theory was developed largely as a joke during last year's bowl season.  After having followed college football for the past 10 years or so, I noticed trends between different weeks' rankings.  There were certain drops that happened, some teams kept on getting preferential treatment.  What I came up with was the following idea:

Relative to next week's polls, all teams remain in the same order with the following exceptions: after a loss the drop is 5-7 slots, unless they were a preseason favorite, then they lose 4 for the first loss, 9 for the second loss. If they're not a preseason favorite, 8-10 for the second loss. Mid-major teams lose 8-10 per loss, and unless they're already in the Top 25, need minimum 5 wins and/or national/network hype to get ranked.  In addition, add 1 in for a loss to an unranked team and 2 for a home loss.

This is the first year of Ranking Theory, so I'm still working the kinks out in it.  It's fairly simple how I determine what fit and what didn't - just pull up this week's polls and last week's polls.  Check the teams that lost and the current ranking.  The format that I use when reporting it is as follows:

Team (AP Ranking/USA Today Ranking)
Ending spots:
Team (New AP Ranking/USA Today Ranking)

To determine whether a team fit or not, I apply those previous criteria.  Take Tennessee from Week 6.
Tennessee (8/7)
Ending spots:
Tennessee (17/18)

This was their second loss of the season - had they been a preseason fave, the expected drop would be 9 slots.  However, they weren't, so the expected drop should be 8-10.  However, they dropped 9/11.  Pretty close.  However, that 11 is a little severe, so the +2 home loss comes into play.  This gives the expected drop as 10-12.  So it's not entirely accurate, but it comes close enough.  (I've given thought of extending the window for a second loss to 7-10, but, like the BCS, I only change my formula once a season.  Unlike the BCS, I'm right at least some of the time.)  Is it arbitrary?  Yeah, it is.  I still haven't figured out what I'm defining as a preseason favorite - but then again, none of them have lost yet, so I haven't had a chance to see that in action.  However, since it's an arbitrary method designed to predict arbitrary methods, I don't see a huge problem with that.  Hope that helps.