Stanford's coach, David Shaw, took the opportunity of his weekly roundtable with the media to point out the flaws in the BCS. Is there any validity to his criticisms? Let's take a look at them one by one.
First, he says all he has heard is that the computers don't like Stanford. Is this true and if so, is it justified?
Before the Oregon game, the BCS computer average had Stanford #8 with a high of #3 and a low of #10. My regular algorithm had them #5 and my BCS algorithm #10. The lower rankings were due primarily to their weak schedule to that point, #62 in the FBS according to my regular algorithm. So, it isn't that the computers didn't like Stanford, it is just that they didn't like them as much as some other teams that played a tougher schedule to that point. After the Oregon game, Stanford's schedule jumped to #36 in my regular algorithm, so had they won they would have been more liked by the computers and moved up.
Second, he says that to have Virginia Tech ahead of Stanford means the computers value the ACC more than the Pac-12. That isn't necessarily the case, instead the computers value Virginia Tech's schedule more than Stanford's. This is indirectly making a statement about the ACC and Pac-12 though, and unfortunately for the Pac-12, they didn't do well out of conference this year so this view is somewhat justified.
Regarding individual schedules, my BCS algorithm presently has Virginia Tech's schedule #34 and Stanford's #69. Now, this will improve for Stanford after they play Notre Dame, but they are being hurt by playing 4-7 and #85 San Jose State and 3-8 and #94 Duke. They are also being hurt by the BCS computers not being able to use margin of victory which is why my regular algorithm rates Stanford higher than my BCS algorithm.
As far as the Pac-12 vs ACC goes, my regular algorithm has the Pac-12 with a 72.241 average and the ACC with 69.602. However, my BCS algorithm has the ACC ahead 78.170 to 77.501. The difference again is due to margin of victory not being used in the BCS algorithm. Since they don't look at margin of victory, they focus on just wins/losses and the ACC is 30-14 out of conference while the Pac-12 is 21-12, slightly worse. This accounts for the difference.
Third, he mentions results of Virginia Tech and Stanford games against common opponent Duke. Stanford won 44-14 at Duke while Virginia Tech won only 14-10. This is a very valid point, but like I mentioned above, the BCS computers can't reflect that, which is to me the really big flaw in the BCS. In my opinion, if you completely ignore the score but only look at who won/lost, you are unable to give a team enough credit when playing a weak opponent, and you also give a team too much credit when they have a close win over a weak team.
Fourth, he mentions quality losses, Stanford's to Oregon and Virginia Tech's to Clemson. If one uses the BCS average, Oregon is #7 and Clemson #9, so this is a bit of a push. However, if a system like mine is used that incorporates scores, Oregon is #4 and Clemson is #31 (their schedule is weaker than Stanford's was before the Oregon game), so Coach Shaw has an excellent point here.
So yes, Coach Shaw makes some good points, but the root of the problem is that the BCS computers can't incorporate margin of victory. This means a team like Stanford that has won a bunch of games easily, played a decent but not great schedule, and lost their most important game, get penalized perhaps unfairly. Boise State can make many of the same complaints.
So it boils down to if you want a system that focuses on wins/losses alone, or one that actually tries to rate the teams where they should be such that game results are predicted well. The history of my algorithms, and Jeff Sagarin's by the way too, is that to predict games well a system has to use the score. Unfortunately, the BCS doesn't agree and we are stuck with the handicapped computers which will continue to result in the problems we have today.