Miami had been 2nd until they just barely beat West Virginia. Miami certainly didn't look like a Top 10 team last night.
The equations:
mu0=(W*+1+.01*CAL)/(W*+L*+2+.02*CAL) where CAL = calendar days left in season (64 as of today), W* = number of wins of all type, and L* = number of losses of all type
OTW=(6+sqrt(mov))*mu(OPP)
W=(9+sqrt(mov))*mu(OPP)
SOW=(12+sqrt(mov))*mu(OPP)
OTL=(6+sqrt(MOL)*(mu(OPP)-1)
L=(9+sqrt(MOL)*(mu(OPP)-1)
SOL=(12+sqrt(MOL)*(mu(OPP)-1)
sigma0=sum of all OTW, W, SOW, OTL, L, & SOL
omega0=12*sigma/(W*+L*)
Iterations:
Generate a best-fit line of omega = slope*mu+(y-intercept)
Calculate the expected omega for each team based on the mu.
delta=(omega(calculated)-omega(expected))/(2*(omega(all teams max)-omega(all teams min)))
mu1=mu0+delta
Lather, rinse, repeat, until delta=0 (at least to three digits).
Now, if you can CORRECTLY explain to a reasonable panel of unbiased judges how that's biased toward Arkansas, I will send you a check for $1000. Actually, with the lessened award for an OT win, I should be being accused of bias AGAINST Arkansas.
If you don't like margin-of-victory, set it up and run it without it. For all I know, it may be so similar that MOV isn't needed. I think it's a needed component to ranking, and using the square-root of it provides a good deflator for runaway games. (Third- and fourth- roots are under consideration if something gets to looking too out-of-whack.)
Miami dropped from 76.34 before the game. Arkansas increased from 76.30 to 76.36. Miami-Ohio went from 45.95 to 45.96. Cincinnati dropped from 18.58 to 18.57. Somehow, it's just the way the math works out. (Miami-Ohio doesn't play West Virginia this year. Cincinnati did.)
For those interested, Colley (one of the BCS ranksters) allows you to "play god" and change games to see what-if and their effects.
http://www.colleyrankings.com/ Sometimes the effects are ones you wouldn't have imagined, even on teams that haven't played either of the teams you manipulate.