KU was originally in the group, and he still casts a smile upon the toddler Jays:

KANSAS
Sports Illustrated’s preseason pick to win it all is humming along, demolishing teams at home and showing encouraging toughness on the road (witness this week’s nail biter win at Oklahoma). What do we make of the no-shows by Darrell Arthur and Sherron Collins in Norman? The Jayhawks can make up for it and still win in a tough environment.

link.

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Here’s a glossary of terms thrown around on Phog Blog:

(Estimated) Team Possessions = FGA+(.44*FTA)+TO-OR

THE FOUR FACTORS

Effective Field Goal Perentage (eFG%) = (FGM+(0.5*3PTM))/FGA

Free Throw Rate (FT Rate) = (FTM*100)/FGA

Note: For teams, their opponents’ FT Rate is calculated as (FTA*100)/FGA on the assumption that, over time, you have minimal control over how well your opponents shoot free throws.

Turnover Percentage (TO%) = TO/Possessions

Offensive Rebounding Percentage (OR%) = OR/(teamOR+oppDR)

Note: individual offensive rebounding percentage = player’s OR/((teamOR+oppDR)*(player’s MIN/(teamMIN/5)))

or

Defensive Rebounding Percentage (DR%) = DR/(teamDR+oppOR)

Note: individual defensive rebounding percentage = player’s DR/((teamDR+oppOR)*(player’s MIN/(teamMIN/5)))

SOME INDIVIDUAL STATS

PPWS (Points Per Weighted Shot) = PTS/(FGA+(.44*FTA))
Pts/100 = Points per 100 individual possessions
A/100 = Assists per 100 individual possessions
TO/100 = Turnovers per 100 individual possessions
S/100 = Steals per 100 individual possessions
BS/100 = Blocked Shots per 100 individual possessions

Note: individual possessions = (Min/(teamMin/5))*teamPossessions

TEAM EFFICIENCY STATS

Offensive Efficiency (OE) = the number of points a team scores per 100 possessions
Defensive Efficiency (DE) = the number of points a team allows per 100 possessions

Efficiency ratings come in several flavors. If one of these words is used to describe an efficiency rating, it means the following:

Raw (OE or DE)= tells you what actually happened, without adjusting for the opponent or location
Adjusted = adjusted based on opponent rating and location in order to indicate how many points a team would score or allow per 100 possessions against an exactly average opponent. There are two types of adjustments.

• Season (AOE or ADE) = Explained in depth here. Essentially, all the ratings for all the teams are adjusted so that predictions based on the ratings best match the actual results.
• Single game (AGOE or AGDE) = Takes the opponent ratings, location, and score from a single game and tells you the ratings of a hypothetical team that would have gotten the same result.

Pythagorean Rating (Pyth) = a rating that supposedly tells what a team’s winning percentage would be over time against an average schedule. As always, a longer explanation is on Pomeroy’s site. The formula is:

AOE^11.5 / (AOE^11.5 + ADE^11.5) … AGOE and AGDE can be used in place of AOE and ADE

SCORE PREDICTIONS

Predictions based on efficiency ratings all use the same formula, listed below. More explanation can be found here. The only difference between the various predictions is in what values are used for the offensive and defensive efficiencies.

[TeamA predicted offensive efficiency] = [TeamA offensive efficiency] x [TeamB defensive efficiency] / [National average efficiency]

Home field advantage is accounted for by multiplying the home offense and the visiting defense by 1.014, and dividing the home defense and the visiting offense by the same.

“Last 10″ = uses the average of the two teams’ last 10 Adjusted Game Efficieny ratings
Trendline = A 2nd-order polynomial trendline is fit to the season-long graph of individual AGOE and AGDE ratings. The trendline’s value as of the latest game is used in the equation.
Streaks = This tries to take a middle ground between two “streak” predicitons. The last N AGOE and AGDE ratings are averaged, where N is between 5 and 10, with the value of N selected to maximize the home team’s predicted margin of victory. Then the reverse is done, but N is selected to maximize the visiting team’s margin of victory. The two predictions are then averaged.Recommended further reading for those interested is available from the invaluable Ken Pomeroy (some of these are the same links from above):

• Efficiency ratings
• Pythagorean Rating
• The Four Factors
• Miscellaneous

If any of the above is unclear or incomplete, please ask about it in the comments and we’ll be glad to try and do better.

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Shoot me an email if you’re willing to sell your student ticket on Saturday for a “reasonably high” price.

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Pomeroy’s ratings of the conferences place the Big 12 last out of the BCS conferences, but still well above any of the mid majors. After a cursory review, it looks like Colorado is way way worse than any other team in any BCS conference. How does Pomeroy calculate conference PR? I averaged the ratings earlier and didn’t get his number. What happens to the Big 12 if we remove CU?

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I’m not sure there’s much to be drawn from the box score that wasn’t visible to the eye last night. It was, as they say, a game of two halves.

1st HALF

Team	eFG%	OR%	TO%	FT Rate	FT%	PPP
KU	48.4	23.5	12.2	6.3	100	1.00
OU	25.9	21.7	20.8	20.7	66.7	0.56

Unable to get the ball in the basket during the first half, Oklahoma made a concerted effort to attack the rim in the second half. This was a sound tactical decision (they can’t guard you if you’re shooting free throws and all) and happily (for Oklahoma, who tend to make free throws) coincided with the officials’ decision to call fouls on any and all contact. At least until the last two minutes when a couple of Jayhawks knocked a driving Nate Carter to the floor without repercussion and Sasha kaun got smacked across the face while laying the ball in the basket. No blood, no foul transmuted in the latter case into, Blood, no foul.

The officials turned a free-flowing if not especially well-played game into a free throw shooting contest and a free throw shooting contest chills the blood of any Kansas fan.

2nd HALF

Team	eFG%	OR%	TO%	FT Rate	FT%	PPP
KU	41.2	40.0	32.4	117.6	62.5	0.92
OU	50.0	40.9	18.7	61.3	78.9	1.23

Perhaps the officials were carrying out a subversive mission to undermine tempo-free stats. Each team had four more possessions in the stop-and-start second half but I don’t think anyone watching would be comfortable describing the second twenty minutes as the game’s “faster” half.

Kansas managed but five more field goal attempts than turnovers in the second half, and, aided by Oklahoma’s intentional fouling in the final minute, shot almost twice as many free throws as field goals in the second half.

GAME

Team	eFG%	OR%	TO%	FT Rate	FT%	PPP
KU	45.9	31.3	22.9	44.9	64.7	0.96
OU	38.3	31.1	19.7	31.7	76.0	0.92

That’s five games in a row that opponents have failed to shoot even 39 eFG% against Kansas. Preventing the other team from making shots covers up a lot of ills, especially when you rebound the vast majority of those missed shots. Oklahoma had a good night on the offensive glass relative to Kansas’s opponents, but were still 16% off their own offensive rebounding average in conference play.

On a night when Sherron Collins and Darrell Arthur post a double ziggy and Brandon Rush appeared not to want to have the basketball in his hands for any length of time, I’m not convinced that Jeff Capel found a formula for slowing down Kansas. Then again, it’ll only take one bad night against some team’s collection of junk defenses for us to ask ourselves all over again why Kansas can’t win in mid-March.

As unpleasant as it was to watch, either one or two more made shots in the first half, or a couple more made free throws or a couple fewer turnovers in the second half and the Jayhawks would have won by a similar margin as in Manhattan.

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If you haven’t already, read this.

Now then, if you’ve bothered to return (and I don’t blame you if you haven’t)…

Oklahoma’s overall defensive efficiency ranking (15th in the country per Pomeroy) flatters to deceive.

DEFENSIVE EFFICIENCY

Team	Overall	Big 12	At-risk
OU	0.917	1.024	1.061
KU	0.849	0.877	0.929

“At-risk” constitutes all road and neutral games plus home losses in both of these cases.

It would be nice for Oklahoma were they a really good defensive team because (this is the part I write twice a week in this space:) they don’t figure to score very easily against Kansas.

OKLAHOMA OFFENSE v. KANSAS DEFENSE

(Big 12 games only)

Team	eFG%	OR%	TO%	FT Rate	FT%	PPP
OU off	47.7	37.1	19.4	25.3	73.9	1.06
KU def	43.0	27.9	22.8	36.3	64.5	0.88

Kansas leads the league in field goal defense and defensive rebounding. Oklahoma relies on their offensive rebounding to make up for their poor field goal shooting. They’re sort of like Kansas State with slightly worse three-point shooting and a higher turnover rate. Kansas State couldn’t get to a point per possession in either meeting with Kansas.

OKLAHOMA DEFENSE v. KANSAS OFFENSE

(Big 12 games only)

Team	eFG%	OR%	TO%	FT Rate	FT%	PPP
OU def	47.7	32.1	20.2	41.3	72.2	1.02
KU off	55.6	38.1	19.8	22.4	66.7	1.15

Oklahoma’s defensive profile is pretty average across the board with the exception of the high number of free throws they allow their opponents to attempt. Both creating and converting free throw opportunities remains Kansas’s greatest offensive weakness. If the Sooners give up two free throw attempts for every five Kansas field goal attempts, the Jayhawks will discover a previously untapped vein of point scoring opportunities. Here’s hoping they make some of them.

Oklahoma plays at a much slower pace (just under 62 possessions per game) than the Jayhawks (just under 70 possessions per game). The respective Iowa State games demonstrated the broad effect that dictating pace can have on a team’s performance.

The difference in talent and performance between Kansas and Oklahoma is such that Oklahoma cannot even afford to split the difference between the two teams’ preferred paces of play. They must keep this game at 62 possessions or less to have a chance to win. Nobody’s thoroughly reduced possessions against Kansas since the game in Ames.

Prediction: Kansas 74 Oklahoma 61

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1. Ohio State (29) 26-3 772
2. UCLA (2) 25-3 742
3. Kansas 25-4 680
4. Florida 25-4 646
5. Wisconsin 26-4 628
6. Texas A&M 24-4 608
7. Memphis 25-3 607
8. North Carolina 24-5 584
9. Nevada 26-2 526
10. Georgetown 22-5 515
11. Southern Illinois 25-5 451
12. Pittsburgh 24-5 447
13. Washington State 23-5 412
14. Duke 22-7 303
15. Texas 21-7 272
16. Butler 26-5 222
17. Notre Dame 22-6 217
18. Oregon 22-7 181
19. Louisville 21-8 170
20. Air Force 23-6 141
21. Marquette 22-8 137
21. Virginia Tech 20-8 137
23. Vanderbilt 19-9 100
24. USC 21-8 90
25. Virginia 19-8 86

UNC dropped to 8th?

UPDATE: AP Poll below. UT is 15th in both polls.

1. Ohio State (62) 26-3 1,786
2. UCLA (10) 25-3 1,729
3. Kansas 25-4 1,580
4. Wisconsin 26-4 1,503
5. Florida 25-4 1,488
6. Memphis 25-3 1,422
7. Texas A&M 24-4 1,408
8. North Carolina 24-5 1,381
9. Georgetown 22-5 1,225
10. Nevada 26-2 1,160
11. Southern Illinois 25-5 1,057
12. Pittsburgh 24-5 984
13. Washington State 23-5 974
14. Duke 22-7 775
15. Texas 21-7 708
16. Louisville 21-8 653
17. Oregon 22-7 466
18. Butler 26-5 457
19. Vanderbilt 19-9 317
20. Marquette 22-8 299
21. Virginia Tech 20-8 293
22. Notre Dame 22-6 279
23. USC 21-8 254
24. Maryland 22-7 247
25. Air Force 23-6 236

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Conner Teahan, a highly regarded 6′5″ SG out of Rockhurst High School in KC has committed to play basketball for KU. 

He chose KU over offers from Wichita State, among others.  He was receiving significant interest from Kansas State and Ole Miss as well.  Teahan will walk on at KU, which makes this even more amazing.

One final note: Teahan plays for the same KC Pump-n-Run team as KU Signee Tyrel Reed and prospect and a top 2008 KU target Travis Teleford.

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Welcome visitors from Sports Illustrated. If you like what you see, please add Phog Blog to your favorites and tell your friends.

I posted an efficiency laden preview of the Ohio St vs. Wisconsin game over at yocohoops. I’m going to do the same thing here for the KU-OU game, but with less explanation of the numbers, since you PB readers have had a couple posts to get used to them. For reference, here is the original post that explains what I’m doing. There’s not going to be a lot of analysis, just numbers and graphs. Sorry about that, but I feel Hoopinion and Chalmersfan do a much better job of that than I do.

After the break, for both teams I’ve included a graph that charts the offensive and defensive ratings for each game of the season. Keep in mind that for the defensive rating, lower is better. For both offense and defense, I’ve included a trendline showing roughly how each unit has progressed over the year. Also, the dotted line shows the national average efficiency.

I’ve also included the average ratings for their last ten games, to give a snapshot of how the team is playing right now. To give these numbers some context, I show where this would rank in the full-season stats, and what team’s full-season rating is the closest. (more…)

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This post will be good for about 15 hours, so get while the getting is good. A quick and dirty projection of next week’s rankings.

1. Wisconsin - Lost…twice…and lost a player. Next week: 6th

2. Ohio State - Nearly peed the bed against Penn State…again…beat a Wisconsin team missing its leading rebounder by a point at home. Next week: moving to their rightful position as the greatest team in all of basketball.

3. Florida - Lost to LSU, sans Glen Big Baby Davis. What’s worse, they got only 23 rebounds. I guess they have an excuse because they have the SEC locked up and have for weeks now, it seems, but one must wonder whether the listless play will carry over into the tournament. If any future Florida foes are watching, here’s how you beat them: zone them, get Joachim frustrated and hope that Humpty isn’t hot. Next week: 4th

4. UCLA - Two solid wins this week, which is about all you can ask for. Next week: 2nd. The only true lock for a one seed, in my opinion, but this means very little. Next week: 2nd (but they’ll get some more first place votes)

5. UNC - A pull-away victory over NCSU and a give-away loss at Maryland. If Maryland were a better team and if they hadn’t had a 12 point lead with less than 10 to play, this wouldn’t have been a bad loss. Still, they’ll get a pass and probably stay a one seed without another slip-up. Next week: 6th

6. KU - A solid win at Huggyville in the biggest game in Manhattan in the last twenty years and another pasting of a conference foe in the Phog v. Iowa State. Next week: 3rd

7. Memphis - I don’t know where to put these guys. I’ve got to think that it says something that KU is pounding better opponents by more. Next week: 7th. I think they’ve hit their ceiling. I said that a few weeks ago.

8. A&M - The Aggies got the job done…it just wasn’t that tough of job. Next week: 8th.

So by the twisted crimson and blue reasoning above, KU should be in pretty good shape for a one seed. But in this coastally biased world in which we livin, I wouldn’t be surprised to see them stuck at 6th.

Here’s the Phog Blog projected top ten for next week.

1. An Ohio State University
2. UCLA
3. KU
4. Florida
5. UNC
6. Wisconsin
7. Memphis
8. A&M
9. Georgetown
10. Nevada (Idaho State Champions)

Placing 3, 4, 5 and 6 wasn’t easy, so this is my vote people.

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KU signee Cole Aldrich will participate in the McDonald’s All America Game in March.  This honor is quite an accomplishment for Aldrich, who played through injuries last summer and slipped on the polls of some pundits.  At one time, Aldrich was universally recognized as the top center prospect in the 2007 class, but he dropped on most scouting lists.  On Scout.com, he fell to fourth, behind, among others, DeAndre Jordan.  Jordan didn’t make the McD’s roster.  Aldrich has had a strong senior year, apparently demonstrating that he is still a dominant center in the eyes of the selection committee.

Scout.com national recruiting director Dave Telep praised Aldrich for his work ethic and demonstrated improvement.  “At Kansas I expect him compete for playing time, slide right into Self’s offensive style and eventually be an anchor inside for the Jayhawks,” Telep wrote.

This truly is a “Super-Sized” honor!

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WEEKEND WRAP-UP

The quiet before the storm.

KU, A&M, Texas Tech, and Nebraska all won at Home as projected (vs. Iowa St, Baylor, Okie St, and Mizzou respectively). k-state won at Colorado as projected.

The only movement in the REAL Standings came with UT picking up ½ game by winning an at-risk contest at Norman. In doing so, they remained in the mix for the conference championship. Wins this week at Home vs. A&M and at KU would assure UT of at least a share of the title for second consecutive season.

REAL STANDINGS as of February 25, 2007

1. 13.5-2.5

Kansas (12-2)

(at risk game at OU)

2. 13-3

Texas A&M (12-2)

(projected L at UT)

3. 12-4

Texas (11-3)

(projected L at KU)

4. 10.5-5.5

k-state (9-5)

(at risk game at Okie St)

5. 8-8

Texas Tech (7-7)

(projected L at ISU)

6. 7.5-8.5

Nebraska (5-8)

(at risk game at CU)

7. 7-9

Mizzou (6-8)

(projected L at A&M)

8. 6.5-9.5

Oklahoma (6-8)

(projected loss at k-state; at risk gamevs. KU)

9. 6-10

Iowa St (5-9)

(projected L at NU)

10. 5.5-10.5

Oklahoma St (5-8)

(projected L’s at Baylor, at NU; at risk game vs. k-state)

11. 4-12

Baylor (3-11)

(projected L at Tech)

12. 2.5-13.5

Colorado (2-12)

(projected L at Mizzou; at risk game vs. NU)

UPCOMING GAMES

The Mid-week Big XII Games, with IQ (Interest Quotient) are:

MONDAY

1. KU at Oklahoma***1/2 (8:00p.m.) No projection-at risk game

Easy pickin’s for the Jayhawks? Maybe. But a Must win on the Road if the Hawks are serious about defending their conference championship. They better come to play, because OU will be desperate for a W after losing four in a row.

TUESDAY

2. k-state at Okie St*** (8:00p.m.) No projection-at risk game

Okie St has gone from contender to pretender to sack of manure. They get a chance to play spoiler here. And k-state just might be ripe to be spoiled, playing as they will be for its NCAA seed.

WEDNESDAY

3. Colorado at Mizzou* (6:00p.m.) Projected W: Mizzou

Is this game REALly necessary?

4. Baylor at Texas Tech** (7:00p.m.) Projected W: Tech

Baylor goes for the season sweep over the Boys of Knight. Tech needs to keep winning not only to prevent that ignominious occurrence from-uh, occurring–but to cement their invitation to the Big Dance.

5. Iowa St at Nebraska** (7:00p.m.) Projected W: Nebraska

NU still hoping to finish at the coveted .500 mark in conference play. They have to win out, but their remaining games are all winnable-this game, at CU, and Okie St in that snow make-up affair.

6. A&M at UT**** (8:00p.m.) Projected W: UT

Elimination Game. Unless KU falls at Norman, the loser of this game is either out of the race (UT) or dependent on the kindness of others (A&M). This will be as much fun as you can legally have watching basketball in February.

–Mark

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