I think of Ken Pomeroy as a college basketball weatherman. For each game he gives the probability of victory. Like a weatherman, he takes historical data and rams it through a series of formulas that include some assumed constants, and out pops a probability. While you (and I, and I am sure Ken himself) don't put full faith in those probabilites, they are pretty decent indicators of how things are going.

Baylor... ouch.

Down by 10 with six minutes left; fight back to within two. The run started just a little late. The loss made even stone faced Josh Carter cry.
However, accoriding to the weather report, it was to be expected, and it didn't really have any impact on our long term forcast, which was lousy 5-11. Essentially we broke even.

One game later and we are (almost) back in business. The Texas win rocketed our long term forcast up to 7-9, with the probability of our predicted two losses at 0.35 (@ Nebraska) and 0.28 (Mizzou). Those are pretty low, but not terrible considering how they are derived. The probablies are based on historical data, which means the Mizzou 0.28 includes four games that have not been played and therefore only the probably of vicorty can be used. If we can convert those highly probably wins to actual wins, there should be some significat upward movement on that 0.28 (it also depends on what Mizzou does between now and then).

If that made no sense, don't worry. The bottom line is that with each win those numbers will move up.

Ken gives us a 0.58 tongiht.