BIG 12 OUTLOOK: 01.09.10

A quick primer for those of you who might be new to the site since I last did these:

1. As you can see above, the chief purpose of this feature is track the Big 12 standings in case you're lazy like me and don't want to go look them up.
2. I also use a variety of projection systems to offer real-time predicted outcomes of all upcoming games, updated biweekly after each "round" of conference games. In addition, I progressively track my cumulative pick record and tweak the system every off-season.
   
3. Finally, I offer commentary on the NCAA hopes of conference teams (won't start with this until a little later in the season).

You can expect these on Sunday (after Saturday games) and Thursday/Friday (after Big Monday, Super Tuesday and Wednesday games). Hit the jump to see what the conference looks like as we head into the first week of games, starting tomorrow.

Note: As any of these numbers change, I will bold and color-code them to indicate direction of change.
Team names that are colored indicate a change in seed.
(green = upward, red = downward)

*Predicted
**According to RealTimeRPI

Discussion

I'll be brief, since this part is so late in coming. Basically, my aim this year is to be more accurate, and I think incorporating a third statistical perspective — in the form of RealTimeRPI's GAMER model (see below) — instead of flipping a virtual coin, should help in that regard.

The first slice at prediction isn't too surprising. Kansas, Kansas State and Texas clearly have separated themselves from the rest of the Big 12 thus far. That dropoff after the Wildcats is not unusual, by the way. There was a similar dropoff last season in the first edition of this feature, after Kansas, Oklahoma and Missouri did the most damage in the non-conference season.

The next six teams will be in a dogfight for the next two months, for anywhere from three to five NCAA Tournament bids. I give Baylor the upper hand for now because of their guards, their post presence and their rugged schedule, but Texas Tech is in good shape if it can just figure out how to win on the road. Missouri probably will have to go at least 10-6 because of the weaker schedule, but the Tigers certainly are capable of that when eight of those games will come at home.

It's hard to know what to make of the Aggies, but their early non-con was good and I still think they have the necessary talent. But Derrick Roland's injury makes it a crapshoot until we have a larger data set by which to judge their reaction to that tragic event. As for Oklahoma State and Nebraska, get back to me when they actually beat an RPI Top 100 opponent.

(Note: This was written before Oklahoma State's win over Texas Tech.)

Iowa State is an enigma. Everyone keeps expecting them to break through and become the dark horse to end all dark horses, but I just don't see it. They had their chances and missed on all four of them. Colorado is improving, but the schedule just gets brutal from here. I don't see how they can have much success, but they should have more than last season. Oklahoma simply is a goddamn train wreck, and at this point, I'd be shocked if the Sooners even finished with a winning record.

Key

• G — RealTimeRPI GAMER (an advanced statistical prediction model, claiming 76.8 percent accuracy)
• P — Ken Pomeroy's rankings (he predicts a probability outcome for each game remaining)
• S — Sagarin composite rankings (home court advantage is taken into account)

I took the results and plugged them into this wonderful tool to generate the predicted records and seed order for all teams, for your viewing pleasure. It's slightly more scientific than just plugging in wins randomly, but less systematic than Pomeroy's system, so it's right up my alley. Hopefully, some readers will find this information useful/interesting/yet another way to waste time at work.

Predicted Outcomes