Eric Gay - AP
It has been a rough week for J'Covan Brown. (AP Photo/Eric Gay)
Can't the Texas Longhorns catch a break? In the last week Texas lost two very close games against Kansas State and Kansas, before picking up a critical win at home against Iowa State. A win against Kansas at home or Kansas State on the road would have been a nice addition to the Longhorn's resume. Fortunately, they will get a few more chances to pick up a big win against a ranked opponent before the season ends.
J'Covan Brown had a tough week shooting the ball, as I will detail below. Myck Kabongo played well in two of the three games, and Clint Chapman had a very solid week. Texas played better on offense against Kansas State and Kansas then they did against Iowa State. I am not sure that I would have predicted that, but just about anything can happen in a single game.
In this week's Inside the Numbers, I review the three games of the week, admire the lack of turnovers from J'Covan Brown, and look at Texas' disappointing record in close games.
Background information on the statistics is posted here and here.
|
CATEGORY |
TEXAS |
K-STATE |
DIFFERENCE |
|
FGA |
59 |
59 |
0 |
|
FTA |
21 |
39 |
-18 |
|
FGA + 0.475 x FTA |
69.0 |
77.5 |
-8.5 |
|
Off Rebs |
12 |
19 |
-7 |
|
TOs |
16 |
12 |
4 |
|
ORB - TO |
-4 |
7 |
-11 |
|
TS% |
0.580 |
0.542 |
0.038 |
|
ORB% |
46% |
51% |
|
|
TO% |
22% |
17% |
|
|
Points/100 |
110 |
119 |
|
Our standard rule of thumb is that a 0.01 differential in TS% is worth approximately 1.3 extra shots. Texas had a true shooting percentage advantage of 0.038. Kansas State had 8.5 extra shots (where "shots" means FGA+0.475xFTA). Kansas State's extra shots were enough to cover a true shooting percentage difference of 0.065, and thus they won. Where did these extra shots come from? Kansas State won both the turnover battle and the offensive rebounding battle by significant margins.
This game played out much in the way that you might expect. Texas and Kansas State typically draw a lot of fouls, and get a lot of offensive rebounds. Texas shot 21 free throws, which is a pretty high total. Kansas State shot 39 free throws, a number that is mind boggling. It is fortunate for Texas (and the rest of the Big XII) that Kansas State is lousy at shooting free throws.
Rodney McGruder was fantastic on offense, with 9.5 Points Above Median (PAM). Jamar Samuels was the only other K-State player with a PAM greater than 0 (he had 1.5). For Texas, Kabongo (5.0), Lewis (3.1), and McClellan (4.7) all made significant PAM contributions. Brown had a tough night shooting the ball, and ended up taking 42% of Texas' shots. This combination resulted with a PAM of -5.8 for Brown.
|
CATEGORY |
TEXAS |
KANSAS |
DIFFERENCE |
|
FGA |
61 |
56 |
5 |
|
FTA |
17 |
23 |
-6 |
|
FGA + 0.475 x FTA |
69.1 |
67.9 |
2.2 |
|
Off Rebs |
15 |
10 |
5 |
|
TOs |
9 |
6 |
3 |
|
ORB - TO |
6 |
4 |
2 |
|
TS% |
0.478 |
0.516 |
-0.038 |
|
ORB% |
38% |
27% |
|
|
TO% |
14% |
10% |
|
|
Points/100 |
105 |
110 |
|
This was such a disappointing loss. But if we take a step back, Texas played pretty well in this game. The Texas offense did well against Kansas' stingy defense. Kansas looks like they stand a pretty good chance to get a #1 seed for the NCAA tournament, and if they do it will be on the strength of their defense. Texas' 105 points per 100 possessions against Kansas was among the highest totals that any team has scored on Kansas all season. While Texas didn't shoot particularly well, they protected the basketball and got to 38% of the available offensive rebounds. Meanwhile, they rebounded 73% of the possible defensive rebounds. Defensive rebounding has been a problem for Texas all year, and winning the rebounding battle against Kansas was honestly pretty surprising. Additionally, the Texas big men held Thomas Robinson in check, holding him to a PAM of -1.2.
Another thing that was surprising was how well both teams protected the basketball. Texas turned the ball over in only 14% of their possessions. Kansas topped this, turning the ball over in 10% of their possessions. Kansas has struggled with turnovers this season, but they didn't against Texas.
As in the Kansas State game, J'Covan Brown struggled with his shot. He also shot a lot, taking 42% of the Texas shots. As a result, he ended up with a PAM of -4.2. But Brown played well in other ways. He avoided turnovers, a subject I will look more closely at in the next section. Brown also grabbed an estimated 17.5% of the defensive rebounds while he was on the court, and made a few key defensive plays, coming up with 3 steals, including a very nice play breaking up a Kansas fast break.
Clint Chapman, Sheldon McClellan, and Jaylen Bond all had very good games. Chapman has emerged as the most reliable of the Texas big men. He had an excellent game against Kansas, with a PAM of 3.2 and a defensive rebounding percentage of 22%. Bond did well in limited minutes, with a PAM of 2.7 and a defensive rebounding percentage of 25%. Additionally, he played outstanding defense on Thomas Robinson. McClellan led Texas with a PAM of 5.3. He also did good work on the defensive glass, with a defensive rebounding percentage of 15%.
Tyshawn Taylor played well, with a PAM of 4.5, 4 assists, and 0 turnovers. Taylor has struggled with turnovers this season, but in this game he didn't give away any possessions. In a game that was this close, every possession matters.
|
CATEGORY |
TEXAS |
IOWA ST |
DIFFERENCE |
|
FGA |
55 |
60 |
-5 |
|
FTA |
18 |
16 |
2 |
|
FGA + 0.475 x FTA |
63.6 |
67.6 |
-4 |
|
Off Rebs |
12 |
12 |
0 |
|
TOs |
15 |
11 |
4 |
|
ORB - TO |
-3 |
1 |
-4 |
|
TS% |
0.488 |
0.407 |
0.081 |
|
ORB% |
35% |
29% |
|
|
TO% |
23% |
17% |
|
|
Points/100 |
93 |
83 |
|
I may or may not have watched this game over an Internet stream. Texas didn't shoot the ball particularly well, but Iowa State's shooting was even worse. A lot of this was good defense on the part of Texas; Royce White ended up with a PAM of -5.4, Chris Allen had a PAM of -5.6 and the Iowa State PAM leader was Chris Babb with 1.3. As a team, Iowa State had a true shooting percentage of 0.407, so Texas' advantage in shooting efficiency was substantial and decisive. This game was briefly close at the end, but a few free throws by J'Covan Brown and a Myck Kabongo steal sealed the victory for Texas.
Myck Kabongo was the most efficient scorer for Texas, with a PAM of 3.9. Brown again struggled with his shooting efficiency, ending up with a true shooting percentage of 0.327 and a PAM of -5.6. Brown also turned the ball over 5 times (21% of his possessions), making this one of his worst games of the season. As a team Texas turned the ball over in 23% of their possessions, which made this game a fair bit closer than it should have been.
Texas held down the defensive glass, rebounding 71% of the possible rebounds while on defense. They also did a nice job rebounding on the offensive end. A number of Longhorns helped out on the glass. Below I have tabulated the rebounding percentages for each of the Longhorns. I particularly want to highlight the good work done by Lewis, Wangmene, Bond, and Holmes.
| Player | ORB% | DRB% |
| Lewis | 8.1% | 16.8% |
| Wangmene | 13.1% | 21.7% |
| Brown | 0.0% | 5.3% |
| Kabongo | 0.0% | 5.3% |
| Chapman | 7.4% | 9.1% |
| Gibbs | 0.0% | 0.0% |
| Bond | 25.2% | 27.9% |
| McClellan | 0.0% | 10.8% |
| Holmes | 9.8% | 32.5% |
I use a statistic I call Points Above Median (PAM) to combine shooting efficiency and shooting volume. PAM compares how many points a player scored to how many points we would expect him to score with the same number of shots, taken only from the field, and made at the NCAA median value of eFG%. By this measure, J'Covan Brown had pretty poor performances against both Kansas State and Kansas. Against Kansas State, Brown had a PAM of -5.8, while against Kansas he had a PAM of -4.2. Negative values of PAM aren't good. A negative PAM generally indicates that a player has used shots that could probably have been used more efficiently by someone else.
But there is more to basketball than shooting. One of the underrated things about Brown's fantastic season is how well he is doing at avoiding turnovers. While Brown struggled with turnovers against Iowa State, this was pretty unusual. Brown is turning the ball over on the season in less than 11% of the possessions that he uses. This is a fairly low rate. A typical turnover rate for an NCAA team is between 18% and 22%. This means that most teams turn the ball over in roughly one out of five possessions, where as on the season Brown only turns the ball over in one out of ten possessions. Against Kansas State, Brown turned the ball over in 3.0% of the possessions that he used, while in the Kansas game he turned the ball over in 6.4% of the possessions that he used. This is a big part of the reason why Rick Barnes trusts Brown with the basketball. But not giving the ball away, Brown has earned that trust.
So how much is Brown's protection of the basketball worth in these two games? Let's assume that instead of his low turnover percentages against Kansas State and Kansas, Brown instead turned the ball over in 18% of the possessions that he used. If this had happened, Brown would have most likely turned the ball over between 5 and 6 times in each of these two games. On average, each turnover that a team avoids leads to one extra shot, and one extra shot is typically worth about one extra point. So by protecting the basketball, Brown earned Texas roughly 4 to 5 extra shots in the Kansas State game (worth about 4 or 5 points), and roughly 3 to 4 extra shots in the Kansas game (worth 3 to 4 points). By avoiding turnovers, Brown essentially "paid back" his team for most (but not all) of his negative PAM totals. This is not to say that Brown had great games against Kansas State and Kansas. But they also weren't as bad as they initially appear when looking at his shooting percentages.
We can extend this analysis to look at Brown's season as a whole. Brown has 40 turnovers on the year (as of Sunday January 22). He has used an estimated 377 of Texas' possessions. With an 18% turnover rate, Brown would have been expected to turn the ball over about 68 times. So Brown's low turnover total has given Texas about 28 extra shots over 19 games, which is good for about 1.5 extra shots per game. Even when his shots aren't falling, his ability to protect the basketball has a tangible value.
After losing a couple of close games this week, Texas' record in the season on games decided by five points or less is now at zero wins and four losses. How does this compare with the rest of the Big XII? I tabulated every Big XII team's record in close games as of Sunday, January 22. For our purposes here, a close game is defined as any game that goes to overtime or is decided by five points are less. The records for each Big XII team in close games is listed in the table below.
| Team | Wins | Losses |
| Texas | 0 | 4 |
| Kansas | 2 | 0 |
| Baylor | 4 | 1 |
| Missouri | 2 | 0 |
| Iowa St | 2 | 0 |
| Kansas St | 3 | 2 |
| Oklahoma | 2 | 2 |
| Oklahoma St | 4 | 2 |
| Texas A&M | 2 | 0 |
| Texas Tech | 2 | 0 |
Texas' 0-4 record in close games is worse than that of any other Big XII team. Not winning a single close game goes a long way towards explaining how a team that is rated so highly in the kenpom.com and SRS ratings would have the record that Texas currently has.
If we take a step back, this 0-4 record is kind of a fluke. In Barnes' entire time at Texas, the Longhorns have 69 wins and 55 losses in close games, good for a winning percentage of 56%. This may not seem particularly good, but as a point of comparison over the same period of time Duke is 53-43 in close games, which is a 55% winning percentage.
Close games are kind of a crap-shoot, when you really get down to it. We often assign more meaning to them then they really deserve. Of course the matter, that is not what I am trying to say. They can have a big effect on a team's record. For example, Texas' 8-2 record in close games in the 2007-2008 season played a pretty significant role in helping that team earn 31 wins and a trip to the regional final round of the NCAA tournament. But generally these things tend to even out over time. Close games are often more or less a coin flip.
0 recs | 10 comments
Absolutely huge win
Hopefully this will be the turning point on our season, as finally we played hard and beat a good team ( who I think we are better than, even though they beat us earlier). If we can turn this into an upset of Mizzou or Baylor or even both ( wishful thinking) that would be huge. I like our chances against mizzou though. We need to not fall behind by so much like we have in our losses in conference play, since we’ve shown we can outplay teams- those huge runs we give up.
It all starts with J’Covan though. He needs to be lights out the next 2 games, he needs to hit literally every open shot he gets, and continue to get to the line. McClellan also needs to be more involved. Other than that I love how this team is growing up, hopefully this team – chapman and wangmene+ our incoming class will be enough to make it far in march in spite of Barnes’ coaching.
Mclovin1035 - January 25, 2012
Amazingly
Ken Pomeroy barely dinged Texas for its 3 game losing streak. He still has the Horns ranked 24th overall, expecting losses @Baylor, vs. Mizzou (by 1), and @KU. He predicts wins vs. Baylor and K-State at home, and if that happens, I think Texas gets into the tourney (also with 1-2 wins in the B12 tourney).
One other interesting stat from my Twitter feed, Eric Bossi: J’Covan Brown is now 30-98 from the floor over the last five games. 18-70 over his last three. Good win for Texas with him slumping badly.
jc25 - January 25, 2012
That is what you would expect, given how Pomeroy's rankings work
Close losses to good teams aren’t going to lower your Pomeroy rank.
http://kenpom.com/blog/index.php/weblog/ratings_explanation/
Key quote from that link:
Maybe I can do a future explanation on this for Inside the Numbers, but the Pomeroy rankings have some similarities with SRS. The approach is different, but the results end up being pretty similar because they basically look at margin of victory and strength of schedule.
Reggieball - January 25, 2012
Excellent Analysis As Usual
One thing I’ve wondered about when looking at “close game” outcomes is the impact of officiating (i.e. 5 second inbound call last year vs. AZ). One subjective call by an official can swing a game by several points and thus can effect the outcome. Obviously there is no way to pin losses on officials and fans always have a bias toward their team when it comes to evaluating officiating. The argument can always be made that calls even out over the course of a game or that if a team had a big enough lead they wouldn’t have to worry about a few bad calls. So I guess there is no real question here. Just seems like when you are talking about games with less than 5 pt margin that officiating can be a factor.
gcinthewoods - January 25, 2012
Officials
Hmm. I suspect that you are right in that officials can have a big impact in close games, for the exact reason that you state.
I don’t believe that bad calls even out over the course of a game. Over the course of a season, sure, but in a single game the sample is just too small to assume that bad calls are going to even out.
This is worth a bit more thought. There are two types of “bad” calls that we might consider.
1. Truly bad calls, like the 5 second call against Arizona. This is one where the official clearly messed up.
2. 50/50 calls, where the call could reasonably go either way. The blocking vs. charge call, for example, often is one of these. So are some plays where the ball goes out of bounds.
If we want to analyze this, we need approach each one in different ways. We can think of truly bad calls as sort of like a lightning strike. We might model them as rare and random events that can occur at any time, perhaps with a Poisson distribution. The 50/50 calls are sort of like coin flips. They could be biased coin flips (based on ref preference, home team, style of play, etc.), but probably we attack them with a binomial distribution.
(Sorry about the probability theory, but I am thinking this through as I type. If it turns out to be interesting enough I might expand it into a section on one of my weekly posts.)
So anyway, how often do we expect these events to occur. There are probably only a few truly screwed up calls per game, and I would guess less than 10 50/50 calls. In most games, one team is likely to gain an advantage just by randomly sampling from the probability distributions involved. That advantage could be worth several points or more, depending on how things go. In a close game that will matter, as you rightly point out.
Take the 5 second call against the Arizona game. That call cost Texas a possession, and on average a possession is worth about 1 point in the final score of the game. In that game, Texas lost by 1 point, so this random officiating screw up matters.
Perhaps the best thing a team can do is be good enough to avoid close games. Here the comparison with Duke is interesting. Duke and Texas have essentially the same winning percentages in close games over the last 13.5 years. The key advantage Duke has is that they have played in far fewer close games. 28 fewer over the time period that I examined, or approximately 2 fewer close games per season. That is two fewer games where a bad bounce or bad call can cause you to lose. I was going to write about this in the column, but I decided to cut it.
Reggieball - January 25, 2012
Appreciate Your Thoughts
You hit on some of the things I had thought about but didn’t expand on like the 50/50 calls, supposed home court officiating advantage, etc. Because of the somewhat subjective nature of many calls, it seems like they could potentially be a factor, if not a major factor, in <5 pt games. Don’t know that this can ever be quantified mathematically although I’m sure if there was a way you would find it. The Duke comparison though is one very good way to look at it.
gcinthewoods - January 25, 2012
question for the stat gurus
Do Barnes’ teams ever run true bread and butter pick and rolls? I tried to watch this closely last night and I didn’t see a single play that looked like a designed pick and roll. Obviously we do a ton of screening and a lot of perimeter screening from our big men, but they never seem to be rolling to the rim off the screen. Am I just missing them?
It seems like a pick and roll with Cove and Holmes would be really effective. Holmes shoots and finishes well. Cove has the perfect skill set to run a pick and roll.
Do we run them? if not, is Barnes just philosophically opposed?
nugwhitt - January 25, 2012
Pick and roll
Texas does have a pick and roll set that seems to be called from the sideline. They seem to use it heavily in some games (I recall it being used heavily in the NC State game, where it was very effective), and hardly at all in others. Barnes seems to have gotten away from it in recent weeks, as Texas has been up against teams that play good pick and roll defense. He deploys it a lot against teams with poor pick and roll defense.
I don’t think it is something that Texas runs very well, often times. Texas is very susceptible to hard hedging or doubling of the ball off the pick and roll. My feeling is that the screener isn’t anticipating this hedge and slipping to the basket fast enough. Instead they are trying to complete the screen, even when their man leaves them to double. I wrote about this at one point (not about the Texas problems with the pick and roll, but how it works generally). This video shows how you “should” play the pick and roll against very aggressive hedging or doubling defenses.
There were a few examples of good pick and rolls between Brown and Holmes in the Kansas game.
Reggieball - January 26, 2012
very interesting
thanks for the great reply. I’m glad to hear that It is at least an element of our offense in the right matchups. I would think with a young team that struggles to find an offensive identity, the pick and roll would be a mainstay. I guess its tough to stick with it if they don’t execute well against stingy D.
I’d love to see one of those clinic videos that shows what the objectives are in Barnes’ offense. To me it just always feels like we’re clogging up the lane by setting off ball screens for our guards as they run away from the rim. The guards are receiving passes off of screens with their momentum taking them in the wrong direction, which seems to neutralize any separation that they got from their defender (or they take the off balance 3s as the body is spinning around). It must be effective for Barnes to keep with it, but I don’t always get what he’s trying to accomplish.
nugwhitt - January 27, 2012
Barnes offensive objectives
Shameless self promotion time. I have written somewhere in the neighborhood of 7000 words about the Barnes offense, and how it is supposed to work. My study was based on what they ran last year, which is a little different from this year, but the 1-4 set at least is basically the same.
Here is a post on Rick Barnes 1-4.
Here is a post on what I have called the flex set, although its not exactly a real flex. Texas isn’t running this set this year, as far as I can tell, but some of the principles are also in the 1-4.
Another look at the double screen action away from the ball, using the Utah Jazz. Texas runs this a lot. It is covered in the 1-4 article, but more details about the double screen and how it should be read are here.
Another screening away from the ball action in Barnes offense is described here. This is based on footage from this season.
Finally, some of Barnes concepts are also discussed here, in the context of how his offense complements what J’Covan Brown can do.
Reggieball - January 27, 2012
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