It was a great week for Texas Tech, as the Red Raiders went 2-0 against Iowa State and Kansas State. Kyler Edwards seemed to find himself offensively, helping the squad to a better offensive showing than the week before in losses to Baylor and West Virginia. Here’s what the analytics say heading into the third week of conference play. Keep in mind that the Big 12-SEC Challenge against Kentucky is on Saturday, so Texas Tech’s road trip to TCU tonight is the only Big 12 action we’ll see this week.
ESPN Basketball Power Index
BPI predicts the margin of victory for a team against an “average” team on a neutral court. Here is how the Big 12 stacks up nationally.
BPI predicts individual game outcomes as well. Here are Texas Tech’s odds to win each conference game. I’ve added a column showing the difference in predicted win percentage from last week.
|Opponent||Chance to Win (%)||Difference|
|@ Oklahoma St||57.1||8.9%|
|@ Iowa St||53.5||9%|
In all 13 of its remaining conference games, Texas Tech’s odds improved from last week. The average remaining win percentage is 59.6 percent, which we can use to calculate the probability of Texas Tech’s final conference record (I excluded possible records with less than a 4 percent chance of happening).
“KenPom” is one of the most widely cited and well respected models for college basketball. Here is how KenPom has the Big 12 a couple weeks into conference play.
|National Rank||Team||KenPom Rating|
Sagarin is a model that predicts outcomes for many sports, including college basketball. Here’s how it has the Big 12.
|National Rank||Team||Sagarin Rating|
Eric Haslam has a model that predicts outcomes for every team in the country if it were to play any other team in the country on a home court, at a neutral site, or on the road. Here are his score predictions for Texas Tech’s two games this week.
- Texas Tech 63, TCU 59
- Texas Tech 69, Kentucky 62
Haslam also had this note about Texas Tech on Twitter, which helps illustrate how much two really solid performances have boosted the Red Raiders’ standing among these models.
Texas Tech is back in our top-25, climbing eight spots to #20 after scoring a +28.3 efficiency rating in a 20-point win over #69 Iowa State. It was Tech's second-best effort all year. The Red Raiders are at their highest ranking at https://t.co/4XOkZfzYg4 since December 14th. pic.twitter.com/6Kesgn6WIz
— Erik Haslam (@haslametrics) January 19, 2020
- NET rating: 25
- This is up 10 spots from last week, further validating Tech’s rise among other analytical models. Other notable teams in NET rating: Baylor 1, West Virginia 9, Louisville 10
- RPI rating: 72
- Texas Tech’s RPI isn’t very good, but it’s up 21 spots from last week. In addition to it not being a very quality metric to begin with, it will continue to rise so I wouldn’t panic. Other notable teams in RPI: West Virginia 1, Kansas 2, Louisville 5, Baylor 7
- Bracket Matrix: 9 seed
- This is down two seeds from last week, but obviously there’s a lot of sorting out to do before the bracket is finalized. Baylor and Kansas are the top two overall seeds in the country right now, with West Virginia listed as a 2 seed in the matrix.
The angle of this weekly post is a Big 12 preview, but it’s hard to ignore Saturday’s looming matchup with Kentucky. Here’s what the analytics have to say about this weekend’s showdown in Lubbock.
- BPI gives Tech a 71 percent chance to beat Kentucky and has the Red Raiders as 6-point favorites. BPI lists Kentucky as the 24th best team in the country with a BPI score of 10.6.
- Kentucky is 10th in Sagarin national rankings (Tech is 19th) and 21st in KenPom (Tech is 19th)
- Haslam gives Tech a 7-point edge
- The analytical models have been fairly close to the closing line in Vegas so far this season. Far be it from me to give anybody gambling advice, but if you partake in such matters, take note that BPI and Haslam are very close in this respect. Sagarin will have a score prediction the day of the game. If you can get Tech -3 or better (compared to models favoring them by 6 or 7), that’s pretty good value. The line may even move towards Kentucky after it opens, as many in the betting public may like the idea of taking Kentucky as an underdog (how often do bettors really get to do that?). No clue where the line opens or closes, but I like noting such things.
Speaking of betting lines and analytical models, I have been tracking how most of these models do for Texas Tech against the spread. I’ll have seven data points by next week’s article and will start tallying weekly results with a running total so y’all can see which models are more accurate when predicting the outcome of Tech basketball games.