Prediction: Kansas at Texas

I think Kansas will be able to play the game at a faster pace than Texas typically plays.

I don’t think Kansas will be able to play the game as fast as they would prefer.

I think both teams will shoot a hair below 50 eFG% from the field.

I think both teams will get to the free throw line about 20 times.

I think if Robinson, Chalmers, and Jackson take the bulk of those free throw attempts, Kansas will at least match Texas’ production at the line.

I think Daniel Gibson will score 19 points on 17 shots.

I think Mario Chalmers and Brandon Rush will combine for 12 three-point attempts, making 5.

I think both teams will get about 40% of their offensive rebound opportunities.

I think PJ Tucker gets, at minimum, 12 rebounds.

I think both teams will turn the ball over on just over 20% of their possessions.

I think point differential between Jeff Hawkins and AJ Abrams will be very close to the point differential between the two teams.

I think that PJ Tucker will present such a unique set of complications for Brandon Rush that Rush can play well and still be less effective than Tucker.

I think it’s unlikely that Kansas wins this game.

I think it’s less likely that the outcome of the game is decided with more than 30 seconds left on the clock.

I think the game will be close enough that a bad call could impact its outcome.

I think that Brandon Rush takes and misses Kansas’ final shot.

I think PJ Tucker gets the rebound, is fouled, and makes at least one free throw.

I think Kansas throws the ball away attempting a long inbounds pass.

I think Texas wins 71-68.

Preview: Kansas at Texas, Part Four

Click here for Part One (Team Stats)
Click here for Part Two (Backcourts)
Click here for Part Three (Rush v. Tucker)

stats glossary

Post players

The efficiency of the Kansas frontcourt, and the five players’ cumulative production, has been somewhat hidden because none of them average 20 minutes a game in league play.

Player	eFG%	Pts/100	PPWS	%min
Wright	58.8	24.9	1.19	48.6
Kaun	66.7	19.7	1.23	45.5
Jackson	55.6	25.9	1.24	40.6
Giles	52.6	20.9	1.16	30.5
Moody	58.9	16.4	1.21	30.3
Aldridge	50.7	26.0	1.10	84.4
Buckman	52.7	21.5	1.17	73.3
Williams	26.7	6.6	0.70	23.8

Here are the cumulative scoring lines for the Kansas and Texas post players:

Player	eFG%	Pts/100	PPWS	%min
KU	58.7	22.0	1.21	39.1
UT	50.0	21.6	1.10	36.3

LaMarcus Aldridge will be a lottery pick whenever he declares for the draft. For whatever reason, his production in Big 12 play has matched neither his talent nor the excellent production he provided in non-conference play.

Player	FTA	FT%	FT Rate
Wright	21	57.1	14.1
Kaun	38	39.5	29.4
Jackson	34	79.4	42.9
Giles	29	65.5	50.0
Moody	23	56.5	46.4
Aldridge	66	65.2	31.6
Buckman	39	79.5	33.0
Williams	8	62.5	33.3

Brad Buckman and Darnell Jackson are excellent free throw shooters. Aldridge is adequate. CJ Giles has shot better from the line as of late, but is below 60% on the season as are Kaun, Wright, and Moody.

Since Texas can’t afford for either Buckman or Aldridge to get into foul trouble they most likely be unable to take full advantage of the biggest Jayhawks’ struggles from the foul line.

Player	OR%	DR%	TR%
Wright	10.4	17.2	14.1
Kaun	12.1	16.6	14.6
Jackson	14.2	21.1	17.9
Giles	12.1	20.4	16.6
Moody	9.9	13.5	11.8
Aldridge	10.7	18.0	14.5
Buckman	12.4	14.3	13.4
Williams	8.8	14.4	11.7

Here are the cumulative rebounding lines for the Kansas and Texas frontcourts:

Player	OR%	DR%	TR%
KU	11.8	17.8	15.0
UT	11.1	16.0	13.7

Just as we saw with scoring numbers, the Texas post players, against Big 12 opposition, have been no more productive as rebounders than have the Kansas post players. The marginal advantage Texas has on the glass over Kansas comes from PJ Tucker being a better rebounder than Brandon Rush.

Player	A/100	TO/100	S/100	BS/100
Wright	5.57	6.01	1.98	3.30
Kaun	1.43	0.95	2.11	3.76
Jackson	1.07	3.20	2.11	0.26
Giles	1.06	4.97	1.40	4.91
Moody	1.43	4.29	0.35	1.06
Aldridge	0.86	2.58	2.27	2.98
Buckman	3.64	4.79	1.47	3.27
Williams	0.51	1.52	1.51	0.00

Of the post players, only Julian Wright and Brad Buckman are credited with very many assists and both have assist-to-turnover ratios of less than one. Aldridge doesn’t turn the ball over very often considering how many touches he gets. Sasha Kaun almost never turns the ball over and gets a surprising number of steals for a man his size.

Again, the cumulative lines are roughly equal:

Player	A/100	TO/100	S/100	BS/100
KU	2.33	3.82	1.70	2.68
UT	1.93	3.34	1.85	2.71

Kansas wins the post matchup if…

1)They get either Aldridge or Buckman in foul trouble.

Texas wins the post matchup if…

1)Aldridge and Buckman outscore and outrebound the five Kansas post players.

Preview: Kansas at Texas, Part Three

Click here for Part One
Click here for Part Two

stats glossary

Rush v. Tucker

One’s essentially a guard, the other’s essentially a forward. They’re both arguably the best players on their respective teams. If forced to make one overriding, potentially foolish prediction, I’d say that the player who makes this matchup of disparate types a mis-match will lead his team to victory.

Brandon Rush is a little more efficient from the field than PJ Tucker…

Player	eFG%	Pts/100	PPWS	%min
Rush	56.3	25.7	1.17	85.0
Tucker	51.0	27.8	1.11	85.8

…but Rush takes a lot more jump shots even though less than a quarter of his field goal attempts are three-point shots. Tucker’s free throw rate is solid in conference play, but well below his season rate.

Player	FTA	FT%	FT Rate
Rush	32	75.0	15.2
Tucker	54	75.9	26.8

Player	OR%	DR%	TR%
Rush	5.7	15.8	11.2
Tucker	9.2	22.7	16.2

Brandon Rush is a good rebounder for his size. PJ Tucker is a good rebounder for anybody’s size. The degree to which both players have an advantage on the glass over a typical college small forward is masked to some degree by playing alongside two good rebounders at all times.

Player	A/100	TO/100	S/100	BS/100
Rush	3.44	4.84	2.14	1.38
Tucker	4.66	4.94	2.80	0.42

Tucker is a better passer and ball-handler than Rush. Both are good defensive players, though Tucker has quicker hands and plays the passing lanes better. Rush has become an effective on-the-ball defender, using good lateral movement to keep smaller players in front him and his long arms to challenge their jump shots. When guarding his man off-the-ball, Rush can still get caught ball-watching and be slow to react.

Kansas wins this matchup if…

1)Rush makes the open three-point attempts he gets against Texas’ zone defense.
2)Rush can penetrate the Texas zone without turning the ball over excessively.

Texas wins this matchup if…

1)Tucker uses his superior strength to get Rush in foul trouble.
2)Tucker dominates Rush on the offensive glass.

Preview: Kansas at Texas, Part Two

Click here for Part One.

stats glossary

Backcourts

Make no mistake, these are the two best backcourts in the Big 12.

Player	eFG%	Pts/100	PPWS	%min
Robinson	41.4	20.1	1.03	76.0
Chalmers	54.7	27.4	1.23	75.0
Hawkins	58.5	14.4	1.19	37.5
Gibson	55.3	27.7	1.17	88.3
Paulino	63.9	25.4	1.34	73.5
Abrams	59.6	16.5	1.23	49.2

Daniel Gibson and Mario Chalmers both have the ability to create their own shot.Gibson is more likely to find space for himself beyond the arc (two-thirds of his field goal attempts in conference play are three-pointers), while Chalmers shoots
many more two-point shots and free throws.

Russell Robinson is a poor three-point shooter who also struggles to finish in the paint. He almost makes up for his poor field goal shooting with his excellent ability to get to the free throw line.

Kenton Paulino has taken full advantage of the attention his teammates have drawn this year, as well as the passing skills of Tucker and Buckman. I think he’s an all-conference candidate, but he’ll undoubtedly trail inefficient, volume scorers like Curtis Stinson and Terrell Everett in the voting.

Hawkins and Abrams are both good back up guards who rarely hurt their teams and, on a good night, knock down a couple of jump shots to provide some active help.

Player	FTA	FT%	FT Rate
Robinson	49	81.7	44.1
Chalmers	49	84.5	42.9
Hawkins	2	100	4.9
Gibson	51	70.6	24.0
Paulino	31	80.6	24.8
Abrams	6	83.3	9.6

Robinson and Chalmers do more damage at the line than Gibson and Paulino. Robinson and Chalmers do more damage at the line more than PJ Tucker. Robinson and Chalmers do more damage at the line more than Brad Buckman. Robinson and Chalmers do more damage at the line more often than LaMarcus Aldridge. Robinson and Chalmers do a lot of damage at the line.

Texas doesn’t typically allow that many free throw attempts, but they’ve been allowing more as the conference season has progressed.

Player	OR%	DR%	TR%
Robinson	7.0	7.4	7.2
Chalmers	0.6	7.8	4.5
Hawkins	1.2	9.3	5.6
Gibson	5.5	8.0	6.8
Paulino	1.9	4.7	3.3
Abrams	1.9	4.8	3.4

Robinson and Gibson boost their value a bit by helping out on the boards. None of the other guards in this game typically do more or less rebounding than is expected of perimeter players.

Player	A/100	TO/100	S/100	BS/100
Robinson	9.11	4.98	4.36	0.56
Chalmers	9.08	6.49	5.70	0.28
Hawkins	6.63	2.59	2.56	0.00
Gibson	4.94	2.47	1.90	0.95
Paulino	7.75	4.62	3.59	0.33
Abrams	9.59	2.95	1.95	0.00

The above numbers are more variable than the scoring or rebounding numbers. I think that has more to do with the systems the players play in than their relative abilities.

Kansas, as a team, assists on 64% percent of their field goals. Texas, as a team, assists on 56% of their field goals.

The Kansas guards turn the ball over more often than the Texas guards, but they play at a much faster pace (70.5 possessions per game vs. 64). The Kansas guards also create more turnovers than the Texas guards, but the Kansas guards play man-to-man almost exclusively while the Texas guards usually play as part of a 2-3 zone.

Kansas wins the backcourt matchup if…

1)Robinson and Hawkins knock down their open three-point opportunities.

2)Robinson and Chalmers get to the free throw line.

3)The Jayhawk guards play the high quality defense which has stymied every guard in the conference (save Thomas Gardner in Columbia).

Texas wins the backcourt matchup if…

1)Paulino, Gibson, and Abrams don’t turn the ball over against the Kansas pressure.

2)Ball movement creates open three-point opportunities for Paulino.

3)Gibson is, on this night, a better offensive player than Robinson and/or Chalmers are defensive players.

Preview: Kansas at Texas, Part One

I've got too many tables for a single preview post, so here's the breakdown:

Part One: Team stats
Part Two: Backcourts
Part Three: Rush v. Tucker
Part Four: Frontcourts
Part Five: Prediction

Stats glossary

Team Stats

Kansas has almost closed the efficiency gap with Texas. The Jayhawks are more reliant
on their defense while the Longhorns have the best offense in the conference by a considerable margin.

Team	PPP	Opp PPP	Diff
KU	1.09	0.86	+0.23
UT	1.18	0.93	+0.25

There’s not a lot of difference between the two teams in terms of field goal offense and defense or rebounding.

Team	eFG%	FTRate	OR%	TO%
KU Off	53.2	28.6	39.5	23.2
UT Def	44.8	27.2	29.8	20.5

Texas has more of the possessions in their games end with a shot attempt than does Kansas. The Jayhawks and their opponents are more likely to turn the ball over.

Team	eFG%	FTRate	OR%	TO%
KU Def	43.4	30.4	29.7	23.8
UT Off	53.3%	26.2	42.1	19.3

It will be incumbent upon the Jayhawks to force Texas into more turnovers. An average Texas possession in conference play is worth 1.18 points to the Longhorns. Over a 67 possession game (Kansas plays at about 70 possessions a game; Texas plays at 64.), there’s a difference of 3 turnovers between the turnover rate Kansas forces on average and the average rate at which Texas turns the ball over. That’s three-and-a-half points the Jayhawks could gain on Saturday.

On the other hand, Texas will likely do a better job of keeping Kansas off the free throw line (their lack of depth forbids them from getting into foul trouble) than the typical conference opponent and could pick up an equal number of points versus the season averages.

Despite the evidence presented in the Field House on Saturday by the Missouri Tigers, I still contend that the Baylor Bears are the worst team in the Big 12. Working toward that contention, I offer the offensive and defensive efficiency numbers from each and every Baylor game this season.

Opp	PPP	Opp PPP	Diff/100
at TT	0.97	1.27	-30
OSU	0.71	0.99	-28
at CU	0.75	1.25	-50
UT	0.84	1.21	-37
OU	0.78	1.27	-49
at A&M	0.99	1.07	-8
KSU	1.06	1.08	-2
at NU	0.72	1.02	-30
MU	1.32	0.98	+34
at OU	0.77	1.15	-38
at UT	0.89	1.27	-38
A&M	0.86	0.93	-7

Baylor has only been competitive in four games against three teams this season. They are last in the league in both offensive (though they do score 3 points more per 100 possessions than the average Kansas opponent in conference play) and defensive efficiency.

Kansas is better than Baylor in every statistical category. Every time a shot is attempted, Kansas is more likely to make the shot and more likely to rebound a missed shot. Kansas attempts more free throws and makes a higher percentage of their attempts than Baylor. Baylor gives their opponents more opportunities from the free throw line, force fewer turnovers, and turn the ball over slightly more often than Kansas.

Seven of the first eight players in Baylor’s rotation are less efficient scorers than Russell Robinson (who is at least 10% less efficient than any of his teammates). The eighth, Curtis Jerrells, is a promising young player but unlikely to get the best of Kansas’ perimeter defenders.

Prediction: Kansas 82 Baylor 48

Preview: Iowa State at Kansas

Most everything I wrote in my preview for the game in Ames still holds true. Iowa State puts their opponents on the line a lot, doesn’t force many missed field goal attempts, allows a ton of offensive rebounds, and attempts to make up for all of this by creating more turnovers than they commit.

On a night when their opponent misses a bunch of free throws and Curtis Stinson gets hot, the Cyclones can look fairly good. However, their method is not a recipe for consistent success.

I think everyone concedes that Kansas will have a tremendous advantage along the frontcourt, though Rahshon Clark is a far better player than he’s generally credited. Thus, I’ll spend my time today comparing the backcourts.

I’ll be using the players’ stats from conference play only. This is for simplicity’s sake. I’m not attempting to make any conclusions about any player’s true talent, just their production over a roughly equal period of time against roughly equal competition. It also helps that the two offenses have been equally productive in conference play. Kansas has averaged 1.09 points per possession (and 70 possessions per game) and Iowa State has averaged 1.10 points per possession (and 69.5 possessions per game).

First of all, Stinson and Blalock play a higher percentage of their team’s minutes than does the Jayhawk duo of Chalmers and Robinson.

Player	%min
Stinson	91.8
Blalock	88.5
Chalmers	73.4
Robinson	74.8

Thus, even though the Jayhawk guards are more efficient than their Cyclone counterparts, they aren’t necessarily more productive:

Player	Pts/100	PPWS	eFG%	FT%	FT Rate
Stinson	32.5	1.13	53.0	72.7	21.6
Blalock	20.7	1.08	49.6	80.0	20.7
Chalmers	27.9	1.26	57.0	81.0	39.5
Robinson	22.2	1.07	42.6	86.4	46.9

Russell Robinson has a unique scoring profile. There are only two other players in the conference who play as much as Robinson and have a lower eFG%: Jason Horton and JamesOn Curry. In fact, there are only seven players, besides Robinson, who are permitted to play even half of their team’s minutes while shooting as poorly as Robinson from the field. Of those seven, Curry has the highest PPWS, 0.93. Robinson’s is 1.07. Why? They are 20 players in the Big 12 who have attempted a shot as often as has Robinson. Of those 20, Joseph Jones makes more free throws per shot attempt (FT Rate) than Robinson.

Russell Robinson has made only 25.9% of his three-point attempts and 44.4% of his two-point attempts and he’s still a league average scorer. With even a modest improvement in his shooting Robinson will become a dangerous all-around player.

The rest of Robinson’s game has already solidified into usefulness, as seen below.

Player	A/100	TO/100	A/TO	S/100	BS/100
Stinson	9.30	5.68	1.64	4.13	0.00
Blalock	8.21	5.36	1.53	3.39	0.00
Chalmers	10.16	6.98	1.45	6.29	0.42
Robinson	8.52	3.91	1.95	3.91	0.21

However many more assists Chalmers and Robinson get from having quality big men who can (usually) finish, a luxury Stinson and Blalock certainly don’t posses, is countered by the assists that other Jayhawks earn. Stinson and Blalock have two teammates who average three or more assists per 100 possessions: Rahshon Clark (3.00) and Jiri Hubalek (3.33). Chalmers and Robinson have two teammates who average six or more assists per 100 possessions: Jeff Hawkins (6.50) and Julian Wright (6.05).

I see no reason to believe that Iowa State can expect to have an advantage in terms of backcourt play on Saturday, especially when you consider that Stinson and Blalock front a defense that allows 20% more points per game than Kansas. Nor do I have reason to believe that Iowa State's frontcourt is preparing for the game of their collective life.

Prediction: Kansas 84 Iowa State 72

Big 12 Individual Leaders

These stats are from conference games (through February 8th) only. They are tempo free: per 100 possessions for points, assists, steals, and blocks; per opportunity for rebounds. I have included a column indicating the percentage of possible minutes each player has played so that you might weigh their efficiency against the volume of their contributions.

First, of course, comes scoring. Players are ranked by points per 100 possessions. I have also included each player's points per weighted shot (PPWS) to give an idea of their efficiency.

Player	Team	Pts/100	PPWS	%min
Roby	CU	38.5	1.14	79.4
Gardner	MU	36.2	1.15	84.9
Jones	A&M	35.3	1.19	72.1
Martin	KSU	33.6	1.15	81.4
Stinson	ISU	32.5	1.13	91.8
Law	A&M	32.4	1.15	93.6
Jackson	TT	31.0	1.18	97.8
Boggan	OSU	30.8	1.23	68.1
Gibson	UT	29.6	1.25	92.5
Everett	OU	28.4	1.09	89.2
Tucker	UT	28.1	1.13	90.0
Rush	KU	27.9	1.19	83.6
Chalmers	KU	27.9	1.26	73.4
Gray	OU	27.4	1.11	75.8
Copeland	CU	27.1	1.17	64.2
Clark	ISU	27.0	1.15	68.5

As a point of reference, the league average is 1.07 points per weighted shot.

Below, I've listed everybody in the league who has played at least 40% of their team's minutes and scored 1.2 or more points per weighted shot.

Player	Team	PPWS	%min
Abrams	UT	1.52	47.2
Neal	OU	1.37	52.2
Paulino	UT	1.32	71.9
Walker	A&M	1.27	63.7
Kaun	KU	1.27	46.0
Chalmers	KU	1.26	73.4
Gibson	UT	1.25	92.5
Stewart	KSU	1.24	66.8
Jackson	KU	1.24	44.9
Boggan	OSU	1.23	68.1
Harris	OSU	1.23	53.0
Kirk	A&M	1.21	69.4
Johnson	OSU	1.21	55.7

The Texas backcourt scores extremely efficiently.

We also see how much Oklahoma depends on Michael Neal to maximize their offense. The first table of this post shows that Everett and Gray are barely above the league average in PPWS. Bookout is below average (1.04). Austin Johnson sports the lowest PPWS of anyone playing half their team's minutes in the Big 12 (0.62). This is why, as evidenced in Lawrence, the Sooners need everything to go right in order to beat a decent team.

Please keep in mind, when looking at the rebounding stats, that rebounds don't occur in a vacuum. Texas and Oklahoma are easily the best rebounding teams in the conference. Multiple players on both those teams have solid rebound rates, thus supressing individual rates somewhat.

Offensive rebounding:

Player	Team	OR%	%min
Gray	OU	14.6	75.8
Young	MU	14.6	68.4
Jackson	KU	14.6	44.9
Freeman	CU	14.6	43.1
Maric	NU	13.4	65.8
Diarra	KSU	13.2	71.0
Diene	BU	13.1	58.4
Bookout	OU	12.6	85.0
Dorisseau	NU	12.2	77.8
Boggan	OSU	12.2	68.1
Taggart	ISU	11.9	53.2
Kaun	KU	11.4	46.0

Defensive rebounding:

Player	Team	DR%	%min
Maric	NU	23.9	65.8
Tucker	UT	23.6	90.0
Clark	ISU	21.4	68.5
Jones	A&M	20.3	72.1
Jackson	KU	19.7	44.9
Monds	OSU	19.6	51.1
Johnson	OSU	18.6	55.7
Lowhorn	TT	17.6	54.2
Aldridge	UT	17.4	82.5
Ashby	CU	16.6	43.6
Rush	KU	16.4	83.6
Kaun	KU	16.4	46.0
Gray	OU	16.0	75.8
Wilkinson	NU	15.8	74.7
Boggan	OSU	15.7	68.1
Wright	KU	15.7	41.1
Kirk	A&M	15.6	69.4

Total rebounding (Again, as with the team stats, I don't how to quantify the relative value of an offensive rebound to a defensive rebound thus good offensive rebounders are likely underrated in the list below.):

Player	Team	TR%	%min
Maric	NU	18.5	65.8
Jackson	KU	17.4	44.9
Tucker	UT	16.8	90.0
Gray	OU	15.3	75.8
Johnson	OSU	15.0	55.7
Jones	A&M	14.6	72.1
Young	MU	14.6	68.4
Kaun	KU	14.1	46.0
Clark	ISU	14.0	68.5
Boggan	OSU	14.0	68.1
Lowhorn	TT	13.8	54.2
Aldridge	UT	13.6	82.5

Assists:

Player	Team	A/100	A/TO	%min
Abrams	UT	11.51	3.44	47.2
Everett	OU	10.26	1.31	89.2
Chalmers	KU	10.16	1.45	73.4
Brown	OSU	10.16	2.64	60.5
Stinson	ISU	9.30	1.64	91.8
Stewart	KSU	8.63	1.89	66.8
Paulino	UT	8.53	1.75	71.9
Robinson	KU	8.52	1.95	74.8
Blalock	ISU	8.21	1.53	88.5
Dora	TT	8.13	2.00	74.2
Hall	CU	7.66	1.79	71.4
Jerells	BU	7.40	1.35	71.5

Granted, it stems in large part from the abilities of his teammates and the attention they draw, but AJ Abrams might be the efficiency MVP of the Big 12. His 11.5 A/100, 75.0 eFG%, and 3.44 A/TO all lead the league.

Steals:

Player	Team	S/100	%min
Chalmers	KU	6.29	73.4
Stinson	ISU	4.13	91.8
Robinson	KU	3.91	74.8
Paulino	UT	3.87	71.9
Jones	A&M	3.65	72.1
Maric	NU	3.65	65.8
Roby	CU	3.64	79.4
Godbold	OU	3.54	70.3
Blalock	ISU	3.39	88.5
White	NU	3.27	52.5
Everett	OU	3.19	89.2
Aldridge	UT	3.16	82.5

When it comes to taking the ball away in conference play, there's Mario Chalmers and every body else. The difference in steal rate between Chalmers and Stinson is slightly greater than the difference between Stinson and the 37th ranked player in steal rate, Jason Dorisseau (1.99 S/100).

I didn't realize how few shots have been blocked in Big 12 play. Here's the top 9, only six of whom play half their team's minutes:

Player	Team	BS/100	%min
Diene	BU	4.22	58.4
Ashby	CU	4.05	43.6
Copeland	CU	3.75	64.2
Diarra	KSU	3.58	71.0
Gray	OU	3.28	75.8
Buckman	UT	3.06	73.9
Kaun	KU	3.01	46.0
Wright	KU	2.62	41.1
Aldridge	UT	2.53	82.5

You’ll see more complete examinations of individual players’ tempo-free stats in the KU-Iowa State preview later today. I have the numbers for everybody who has played 100 minutes in Big 12 play. If there’s someone or something about which you’re curious, please, just ask.

Big 12 Team Efficiency Stats (through February 8)

Here are the teams ranked 1-12 by the difference between their points per possession and their opponents’ points per possession.

Team	PPP	Opp PPP	Diff
UT	1.19	0.89	+0.30
KU	1.09	0.89	+0.20
OU	1.07	0.95	+0.12
CU	1.07	1.04	+0.03
ISU	1.10	1.08	+0.02
KSU	0.98	0.98	0.00
TAMU	1.02	1.05	-0.03
NU	0.94	1.00	-0.06
OSU	1.00	1.07	-0.07
TT	0.94	1.05	-0.11
MU	0.97	1.11	-0.14
BU	0.91	1.13	-0.22

Below is a look at the difference between each team’s eFG% and the eFG% they allow.

Team	eFG%	Opp eFG%	Diff
UT	55.5	44.2	+11.3
KU	52.9	42.6	+10.3
OU	51.0	46.3	+5.3
KSU	47.7	45.0	+2.7
CU	49.6	47.6	+2.0
OSU	51.1	51.6	-0.5
TT	47.0	49.3	-2.3
ISU	50.7	55.2	-4.5
TAMU	50.6	55.3	-4.7
BU	45.4	51.3	-5.9
MU	47.6	54.0	-6.4
NU	42.7	50.9	-8.2

It’s in the above table that one can start to see how teams score and allow points..

The following table might need a little more explanation. A team’s free throw rate (FT Rate) equals the number of made free throws per 100 shot attempts. A team’s free throw rate allowed (Opp FT Rate) equals the number of free throw attempts they allow their opponents per 100 field goal attempts.

I’ve ranked the teams by their point differential on free throws per 100 field goal attempts. (By multiplying the free throw rate allowed (Opp FT Rate) by the opponents’ free throw percentage (Opp FT%), then subtracting that number from the free throw rate (FT Rate).

I don’t know if this is the best way to rank the teams. Obviously, teams have little control over how their opponents shoot from the free throw line. These rankings do show the points gained or lost per 100 possessions. I’ve included all relevant free throw percentages as well, so that readers might make their own adjustments.

Team	FT Rate	Opp FT Rate	FT%	Opp FT%	Diff
TT	29.8	23.7	70.1	74.4	+12.2
NU	30.8	28.1	72.4	67.2	+11.9
KU	29.4	32.2	71.2	65.9	+8.2
UT	24.8	26.6	73.4	65.6	+4.4
KSU	27.8	38.4	66.8	69.1	+1.3
MU	24.7	36.5	67.9	67.8	+0.0
OSU	25.3	39.0	72.7	69.6	-1.8
OU	21.2	33.9	65.2	71.0	-2.9
TAMU	27.3	48.4	67.8	68.7	-5.9
BU	18.2	37.7	61.4	68.1	-7.5
ISU	23.7	51.7	78.6	65.3	-10.0
CU	18.6	41.0	58.8	70.7	-10.3

Teams are ranked below by offensive rebound percentage plus defensive rebound percentage. I have no idea of the relative value of an offensive and defensive rebound, so this seemed the simplest solution.

Team	OR%	DR%	RebRate
UT	41.5	72.5	114
OU	43.1	70.0	113.1
KU	38.4	67.7	106.1
KSU	36.2	67.6	103.8
NU	34.8	65.9	100.7
CU	38.8	61.6	100.4
OSU	36.5	62.5	99.0
MU	35.5	60.6	96.1
TAMU	28.7	66.6	95.3
ISU	34.1	59.0	93.1
BU	29.8	60.4	90.2
TT	30.0	58.5	88.5

Should offensive rebounds be more valuable (they occur more rarely, so that would make intuitive sense to me), Oklahoma State and Colorado would both rank as better rebounding teams than Nebraska.

The rankings here are simply opponents’ turnover percentage minus the team’s turnover percentage.

Team	TO%	Opp TO%	Diff
ISU	18.0	27.1	+9.1
TAMU	19.9	25.7	+5.8
UT	20.2	21.7	+1.5
CU	20.3	20.9	+0.6
KU	22.5	22.5	+0.0
NU	24.6	23.9	-0.7
OU	23.7	22.4	-1.3
TT	23.8	22.4	-1.4
MU	24.7	21.2	-3.5
OSU	25.8	22.2	-3.6
BU	22.9	19.2	-3.7
KSU	23.8	19.8	-4.0

Here we see how Iowa State maintains their mediocrity despite rebounding so poorly, and allowing their opponents to outscore them both from the floor and the line. They create the most turnovers while rarely turning the ball over themselves.

Tempo-free stats for individuals coming tomorrow...

Preview: Kansas at Nebraska

Conventional wisdom seems to think that Nebraska is much better in the absence of Joe McCray. Tonight in Lincoln, Kansas will have the benefit of neither the seven horrible shots McCray missed in Lawrence nor the four turnovers he committed. Though I have no way to quantify it, I feel safe in assuming that the Nebraska players have more fun playing five-on-five than watching a fat man ignore his four teammates in order to freelance unsuccessfully.

In the three games following McCray's suspension-turned-dismissal, Nebraska has scored 1.08, 1.02, and 1.02 points per possession. In the five conference games in which McCray played, the Cornhuskers averaged 0.92 points per possession. I would not credit McCray’s absence with the entirety of the offensive improvement. Those last three games have been played against Missouri, Oklahoma State, and Baylor. In conference play, those teams give up 1.09, 1.10, and 1.16 points per possession, respectively, to conference opponents other than Nebraska.

Thus, it’s an open question as to whether Nebraska’s offense or its schedule has improved over the last three games especially when you consider that Baylor held Nebraska to 35.1 eFG% in their game at Lincoln. Missouri, last night, is the only other Big 12 team to shoot less than 51 eFG% against the Bears, and the Tigers still managed to shoot 48.4 eFG%.

Furthermore, Nebraska doesn’t match up very well with Kansas. The Cornhuskers shoot 43.4 eFG% and allow 51.4 eFG% in conference play. Kansas shoots 53.6 eFG% and allows 43.1 eFG%. Nebraska doesn’t make up much of that difference at the free throw line. Kansas has maintained a decent-sized advantage at the free throw line in conference play. Nebraska's good offensive rebounding performances have come in the three games in which they’ve shot below 40 eFG%. Kansas, even after Taj Gray's domination of the offensive glass, are the third-best defensive rebounding team in the conference. Both teams generally break even on turnovers.

Individually, Nebraska's best offensive player, Wes Wilkinson, has thus far failed to maintain the excellent three-point shooting he demonstrated during the non-conference schedule. Jeff Hawkins and Christian Moody are the only players in the Kansas rotation who haven't improved their shooting percentage in conference play. Charles Richardson is the only Cornhusker with an assist-to-turnover ratio better than 1 in conference play. Of Kansas's four primary ball-handlers, only Brandon Rush has an assist-to-turnover ratio worse than 1 in conference play.

There is a tremendous talent gap between Kansas and Nebraska, but I think everybody agrees that the gap isn’t 42 points. The question entering tonight’s game is, how much of that 42-point gap can Nebraska eliminate tonight in Lincoln?

Based just on each team’s season averages, Nebraska could be expected to eliminate about two-thirds of the margin of their defeat in Lawrence. In conference play, Kansas is +19 points per 100 possessions. Nebraska is -2. Nebraska has struggled to slow down the tempo against the better teams they’ve played (Kansas, Colorado, Iowa State) that prefer a faster pace. If Kansas can get 68 possessions out of the game, they would, on average, score 14 more points than Nebraska. Factor in the home-court advantage which most quantify as roughly four points, and the Jayhawks are still a ten point favorite.

However, if Nebraska figures out a way to slow the game down significantly (reduce the pace by 15% or more from Kansas’s 72 possession average in conference play), the can narrow the Kansas advantage to eight points. That’s the range wherein a hot or cold shooting night by either team or a couple of fortunate breaks can affect a game’s outcome rather than the margin of victory. Nobody in the Big 12 has managed to limit Kansas to fewer than 63 possessions so far this year and Oklahoma needed 22 offensive rebounds to do that. As long as Kansas rebounds a respectable number of Nebraska’s misses, they will create enough chances for their superior offensive players to post a point total that Nebraska cannot match.

Prediction: Kansas 71 Nebraska 60

Preview: Oklahoma at Kansas

Oklahoma is on a winning streak for the same reason Kansas is on a winning streak: they’ve been making more shots, especially those taken from beyond the three-point line. After failing to shoot better than 50 eFG% in their first four conference games, Oklahoma hasn’t shot worse than 57.4 eFG% in their last three games, including an outstanding 61.4 eFG% performance against Texas.

Kansas will have to hold Oklahoma closer to 50 eFG% on Sunday in order to win the game as Oklahoma must be expected to control at least one factor of the game: rebounding. The Sooners have out-rebounded each of their conference opponents. On the season, they rank first in the nation in offensive rebounding and third in the nation in defensive rebounding.

Kansas can’t be expected to maintain their excellent 71.5 DR% against Oklahoma (though the Jayhawks did get 77.5% of the defensive rebounds against Colorado, the best offensive rebounding team they’ve played in conference this year). Furthermore, offensive rebounding has been feast-or-famine for the Jayhawks since conference play began. They grabbed half the available offensive rebounds in Boulder, 47.1% of them in Columbia, and 46.2% against Texas Tech Monday night. Against Nebraska, they got only a third of the potential offensive rebounds, only 28.2% against Kansas State, and a mere 23.1% at both Texas A&M and Iowa State.

Oklahoma has shown a slight vulnerability on their defensive glass. Texas A&M got 41.9% of the offensive rebound opportunities in their first meeting with the Sooners and Texas got 34.3% of the offensive rebound opportunities in their loss in Norman. If Kansas can get around a third of the offensive rebounds and 65% of the defensive rebounds, they’ll be in good shape.

I assume that Kansas will defend Taj Gray and Kevin Bookout much like they defended Leon Powe and DeVon Hardin of Cal. The Jayhawks will give help when necessary, but be more willing to let the Oklahoma big men shoot a contested shot inside of ten feet than leave the guards open on the perimeter. Even if the guards are open momentarily, Gray and Bookout won’t necessarily find them. Gray’s averaging only one assist per game. Bookout has one assist on the season (569 minutes played).

Kansas took control of the game against Cal with CJ Giles and Julian Wright playing together in the frontcourt. There’s good reason to be skeptical that those two can be similarly effective against the more physical Oklahoma forwards. Then again, Darnell Jackson was not available for the California game but figures to play significant minutes on Sunday, and Kevin Bookout is far slower than either Hardin or Powe so Sasha Kaun could be more of a factor than he was against Cal.

The Jayhawks must also get back to forcing turnovers. They’ve only converted 13.7% of their opponents’ possessions into turnovers over the last two games. Only Michael Neal, who mostly catches and shoots, and Nate Carter, who doesn’t do much with the ball at all, have taken good care of the ball. Terell Everett has turned the ball over 5 times a game in conference play. Gray, Bookout, and their backup Taylor Griffin turn it over 4 times a game and guards David Godbold and Austin Johnson contribute another three-and-a-half turnovers per game. All these turnovers occur in a 62 possession per game context.

Conceding a significant rebounding advantage to Oklahoma, Kansas can still win the game by shooting a little better, defending a little better, creating a couple more turnovers than they commit, and picking up a couple extra points at the free throw line.

If Kansas wins this game they will consolidate the value of their earlier road wins and establish themselves as the second best team in the Big 12. The Jayhawks have played well enough for long enough that they should be expected to beat a decent team at home. Oklahoma is not the most favorable matchup for Kansas, but I still think that the Jayhawks are much susceptible to big, athletic wing players than pure post or perimeter players. Everett, Neal, Bookout, and Gray are too good to shut down, but Kansas’s superior depth of talent should be able to limit Oklahoma’s chances and create enough chances of their own to win the game.

Prediction: Kansas 71 Oklahoma 64

Big 12 Team Efficiency Stats

Stats from conference games (through February 1st) only.

Here is how the teams rank simply by the difference between their points per possession and their opponents’ points per possession.

Team	PPP	Opp PPP	Diff
UT	1.18	0.88	+0.30
KU	1.11	0.90	+0.21
OU	1.07	0.94	+0.13
CU	1.09	1.02	+0.07
KSU	0.97	0.97	0.00
ISU	1.09	1.09	0.00
TAMU	1.02	1.03	-0.01
NU	0.94	1.01	-0.07
OSU	0.99	1.07	-0.08
MU	0.98	1.10	-0.12
TT	0.95	1.08	-0.13
BU	0.87	1.15	-0.28

No surprises.

Below is a look at the difference between each team’s eFG% and the eFG% they allow.

Team	eFG%	Opp eFG%	Diff
UT	56.3	44.2	+12.1
KU	55.0	43.7	+11.3
OU	52.5	46.4	+6.1
KSU	48.8	43.7	+5.1
CU	48.9	46.5	+2.4
OSU	51.6	52.1	-0.5
MU	49.0	51.9	-2.9
TAMU	50.6	54.6	-4.0
TT	47.2	51.4	-4.2
ISU	50.6	58.0	-7.4
NU	44.7	52.4	-7.7
BU	42.3	54.2	-11.9

In this table, one can start to see how teams score and allow points differently. Colorado and Kansas State are only the eight and ninth best shooting teams in the conference, respectively, but they’re still more efficient than the opposition whenever a field goal is attempted.

Iowa State’s eFG% allowed is quite the outlier.

The following table might require a little more explanation. A team’s free throw rate (FT Rate) equals the number of made free throws per 100 shot attempts. A team’s free throw rate allowed (Opp FT Rate) equals the number of free throw attempts they allow their opponents per 100 field goal attempts.

I’ve ranked the teams by multiplying the free throw rate allowed (Opp FT Rate) by the opponents’ free throw percentage (Opp FT%), then subtracting that number from the free throw rate (FT Rate). The resulting number represents the number of points each team gains on or loses to their opponents per 100 field goal attempts.

Team	FT Rate	Opp FT Rate	FT%	Opp FT%	Diff
TT	31.5	24.2	70.4	73.8	+13.6
NU	32.1	31.1	71.1	65.3	+11.8
KU	34.0	36.0	70.8	65.6	+10.4
UT	20.6	23.6	68.9	65.6	+5.1
MU	28.0	33.9	68.4	74.5	+2.8
OSU	22.0	34.3	73.0	67.6	-1.2
KSU	25.2	41.6	63.3	69.8	-3.8
OU	20.1	34.4	62.5	70.8	-4.2
TAMU	24.9	45.5	66.5	66.1	-4.9
CU	19.0	39.7	60.3	69.3	-8.5
BU	17.4	40.9	59.6	66.0	-9.6
ISU	25.9	56.3	81.5	65.7	-11.1

Again, Iowa State is a huge outlier. Despite shooting 81.5% from the line and having their opponents make only 65.7% of their free throw attempts, the Cyclones give up more than a point per 10 field goal attempts to their opponents because they let them shoot so many free throws.

Both Colorado and Oklahoma could increase their offensive efficiency just by approaching mediocrity at the free throw line.

Texas Tech and Nebraska’s rankings underscore how little production they get from their field goal attempts.

Kansas demonstrates a fairly thorough shooting efficiency, leading the league in field goal defense and free throw rate, ranking second in field goal offense, and third in free throw differential. Their worst shooting ranking is seventh in free throw rate allowed.

Teams are ranked below by offensive rebound percentage + defensive rebound percentage. I have no idea of the relative value of an offensive and defensive rebound, so this seemed the simplest solution.

Team	OR%	DR%	RebRate
OU	43.2	70.4	113.6
UT	39.3	69.7	109.0
KU	37.1	71.5	108.6
KSU	33.2	68.0	101.2
OSU	37.8	63.1	100.9
CU	40.3	59.9	100.2
NU	32.7	65.5	98.2
TAMU	31.2	66.9	98.1
TT	33.0	60.3	93.3
MU	32.7	60.2	92.9
ISU	33.1	59.1	92.2
BU	29.5	62.2	91.7

Should offensive rebounds be more valuable (as they occur more rarely, that would make intuitive sense to me), Oklahoma State and Colorado would both rank as better rebounding teams than Kansas State. I’m fairly comfortable that Oklahoma, Texas, and Kansas are the three best rebounding teams in the conference and that Texas Tech, Missouri, Iowa State, and Baylor are the worst.

I did not expect to see Kansas leading the conference in defensive rebounding percentage. I will be quite impressed if they hold on to that rank through Sunday's game.

The rankings below are based upon opponents’ turnover percentage minus the team’s turnover percentage.

Team	TO%	Opp TO%	Diff
ISU	17.8	27.5	+9.7
TAMU	20.0	24.3	+4.3
UT	19.0	23.2	+4.2
CU	17.5	21.0	+3.5
OU	23.3	22.5	-0.8
NU	24.6	23.2	-1.4
KU	22.6	21.0	-1.6
MU	23.2	20.3	-2.9
BU	21.3	18.2	-3.1
KSU	22.5	18.8	-3.7
TT	24.4	20.7	-3.7
OSU	26.1	21.2	-4.9

We see how Iowa State maintains their mediocrity despite rebounding so poorly, allowing so many free throw attempts, and allowing so many attempted shots to go in the basket. They (by a wide margin) create the most turnovers while rarely turning the ball over themselves.

We also see where Texas separates themselves (statistically) from Kansas. The Longhorns and Jayhawks rank first and second in eFG% differential, fourth and third in free throw differential, second and third in rebound rate, but third and seventh in turnover differential. That accounts for the extra bit of efficiency the Longhorns possess.