Showing posts with label Jessie Sapp. Show all posts
Showing posts with label Jessie Sapp. Show all posts

Monday, October 19, 2009

Season Preview: Chris Wright

Chris Wright plays like a traditional point guard. He can penetrate and distribute the ball. Sure, he’s more inclined to shoot than what a pure point guard would be, by some people's definition. But his handle, quickness and passing ability place him as a point.

Chris Wright also plays for a team that previously didn’t need a traditional point guard. Jon Wallace led the team on and off the court for four years, and his game was much more suited to that of a pure long distance shooter. Georgetown won letting other players - actually, the whole team - create.

Has the offense adjusted to Chris Wright’s strengths, or is he being pigeon-holed into Jon Wallace’s role? Is the offense restricting what he can do? Is he restricting what the offense can do?

How can we measure the adaptability of the offense? And whether that role is holding back Wright or vice versa? Several key statistics might give us an indication:
  1. How does Wright’s split between 2pt and 3pt attempts differ from Wallace’s? Wallace was a shooter and Wright is a penetrator, so they ideally would have significantly different splits unless the system was forcing one of them to be something they weren’t. This can help us measure the adaptability of the offense.
  2. How does that same split compare with other Big East point guards? By focusing on those players who shoot similarly to Wright (strong 2pt, weaker 3pt %), it may become apparent as to whether other systems tailor themselves better than the Hoyas'.
  3. How much does Wright control the ball in comparison to Wallace? Again, this should help measure whether the system adapts. By all accounts, Wright should dominate the ball more.
  4. How much does Wright control the ball in comparison to other Big East points? Again, this should give a measure of how important the point guard is relative to other offenses in the Big East.
  5. How does Wright’s 2pt FG %, attempts, FT Rate and assist rate compare to other points in systems that play in a faster paced?
  6. Does Georgetown's offense generate more turnovers? Is that a bad thing for Chris Wright?

1. How does Wright’s split between 2pt and 3pt attempts differ from Wallace’s? Is the offense keeping Wright from driving?
Wright’s best attribute from a statistical standpoint is his ability to hit shots inside the arc. In conference, he hit 54% of his 2-pt FGAs and got to the line consistently. His biggest weakness was three point shooting, as he made just 31% of his attempts.

Wallace is a sharp contrast to that, making 40% of his threes in conference play and 49% of his twos. The latter is not a poor number, but given his number of attempts and his three point accuracy, it should have been his second option.

Over his career, Jon Wallace attempted 55% of his shots (including free throws in the equation – the % of FGs is higher) from three in Big East play. Last year, Chris Wright attempted only 29%. One may argue that that is still too many threes, but clearly the offense is not dictating that Wright take the same shots as the previous point guard. Even Jessie Sapp, a guard with a little more drive than shoot to his game, attempted 47% of his shots from three as a senior.

2. How does that same split compare with other BE points?
Looking across the starting point guards from every Big East team (and a few backups) last season, six players stand out as comparable to Wright in terms of his 2pt and 3pt shooting percentages. They are Edgar Sosa, Kemba Walker, Dominic James, Deonta Vaughn, Anthony Farmer and Eugene Harvey.

Of the seven point guards listed above (here including Wright), three of them have a shot selection problem of sorts: Deonta Vaughn, Edgar Sosa and to a lesser extent Dominic James. Despite not shooting particularly well from deep, Sosa and Vaughn shot around 50% percent of their shots from three and James nearly 40%.

In contrast, Eugene Harvey and Kemba Walker seemed to understand their weakness, shooting around 15% of their shots from three and going to the rack much more often. Anthony Farmer shot just under 20% of his attempts from behind the arc.

Wright falls in the middle with his 29%. You could argue he could shoot from three even less, but Wright did shoot well over 40% as a freshman (albeit in limited time). It simply doesn’t seem as if the system is forcing him to take the wrong kind of shot. If it is, then other systems (Cincy, Louisville and Marquette) seem to have a bigger problem.

3. How much does Wright control the ball in comparison to Wallace?
I came up with a junk stat for this, adding possession usage (which is dominated by shot attempts and turnovers) and assist rate. For example, a player with a 20% possession usage who also assisted on 22% of his teammates' FGs would post a 42 in this stat.

Wallace doesn’t break a 36 in conference play in any year that he played. Wright clocked in at 44 last year. While I did not check every player’s past Big East stats, Wright’s 44 is the highest of the Thompson era for a guard, with only Jessie Sapp’s junior (and best) year more or less matching it.

So, yes, Wright does control the ball more. But not to an overwhelming amount, and Greg Monroe actually led the team last year in this stat.

4. How much does Wright control the ball in comparison to other Big East points?
Using the same method as above, there are five Big East point guards who clearly dominated the ball more than Wright did.

Levance Fields and Johnny Flynn controlled the ball for their teams more than any other players, and for good reason. They were far and away the most dominant PGs in the conference.

Three others were significantly higher than Wright: Deonta Vaughn, Eugene Harvey and A.J. Price. Vaughn was a gunner on a team with no scoring help and Price is a sixth year senior whose talent level is near to Fields. That said, Eugene Harvey is not as talented an offensive player as Wright (in my opinion) yet he played a more central role in Seton Hall’s offense.

After that comes Wright and whole slew of point guards who were similarly involved in their offenses. Bringing up the rear was a motley crew of freshmen (Kemba Walker, Truck Bryant), pseudo-point guards (Wil Walker) and players that just aren’t very good (Malik Boothe, Anthony Farmer).

Wright did not dominate the offense like Fields or Flynn. He was used as much as a typical Big East point guard, and it may be argued that he is more talented than some of them. Then again, if he was underused by the system, so was Sharaud Curry or Corey Fisher or Truck Bryant. None of those guys are in the same offense, so while I wouldn’t rule it out, there’s certainly no specific evidence here supporting the base contention that Georgetown's offense is holding back Wright.

5. How does Wright’s 2pt FG %, attempts, FT Rate and assist rate compare to other points in systems that play in a faster paced?
The four top-paced teams in the Big East last year were Providence, Syracuse, Villanova and Seton Hall. While Flynn is a bit of an outlier, Harvey and Curry were somewhat similar to Wright, and Corey Fisher is not only statistically similar, but he’s also a sophomore McDonald’s All-American-level talent who came into his own last year.

Did getting up and down help these point guards, Fisher included?

Looking at these players, there is a common thread. They tended to outperform Wright at the free throw line – either by shooting accuracy or attempts or both; by garnering a higher assist percentage; and by turning the ball over less. It wasn’t universal, but it was true of three of the four.

I quickly ran correlations between pace and the above stats plus 2 pt FG % and my junk stat for point guard usage. Nothing came back as overly significant (and the sample size certainly was nothing to get excited about), but the two that came back with any useful correlation at all were FT Rate at 0.36 and TO Rate at -0.30. Assist Rate and PG usage came back as noise – at least in this sample, the teams that ran didn’t necessarily have their PGs more involved.

It’s not surprising that FT Rate came back most significantly correlated with pace: there’s a large number of fouls called on fast breaks. I would expect that for a guard, it is much more common to draw a foul on a fast break than on drive against an opponent already established. It seems Wright – who is already fairly adept at drawing fouls in an offense that is not designed to do so – would likely benefit from fast-breaking in that matter.

Of course, he would likely benefit as much from making more of his fouls shots – Fisher’s 76% from the line is the lowest of the foursome, while Wright shot 72% in conference.

6. Does the offense generate more turnovers? Does this mean it is a bad fit for Chris Wright?
It is a central tenet of Mike D’Antoni’s Seven Seconds or Less (SSOL) offense that shooting quicker means fewer turnovers. It makes sense – less ball handling means less time to make mistakes. Of course, it makes even more sense when you have Steve Nash doing the handling for five of those seven seconds.

By the same theory, Georgetown’s offense, which tends to take a bit longer in generating a good shot, should have higher turnovers on average. The offense trades more opportunities for turnovers for higher percentage shots.

The facts seem to support this notion, as the Hoyas’ offense has ranked 247th, 192nd, 213th, 35th, and 203rd in unadjusted turnover %. The 35th was Ashanti Cook and D.J. Owens’ senior year and proves that it is not impossible for the team to function at a high level of ball handling. However, turning the ball over has been a bigger and more consistent fault than everyone’s favorite whipping boy, rebounding.

This should actually mean that Wright is a better fit, based on his ball handling. Wright had a 22% turnover rate in conference play, which is not strong. But that’s still a number that Wallace only beats in his senior year, and not by much. In other words, Wright should help the Hoyas more than he would be hurt. In fact the only way he would be hurt by this is if for some reason his decision-making and handle are better in the open court than half-court.


Going Forward

There’s no doubt the offense has adjusted to some extent for Chris Wright. He’s using possessions and garnering assists at a faster rate than any JTIII-era Hoya guard before him, and he’s played just one and a half seasons.

There’s also no doubt that Wright is getting his opportunities more or less at the same pace as the rest of the league’s point guards. Should he be getting more? He certainly seems to have more natural talent than some of the point guards he is bunched with. On the other hand, the Big East guards who played a more central role in their teams’ offenses were either clearly superior performers or on teams that had less talent and needed their scoring and playmaking more.

The answer seems to be in tweaks rather than wholesale readjustments. DaJuan Summers used 25% of possessions and shots while he was on the floor last year, and posted an Offensive Rating below Wright’s while creating for others less than half as much. In other words, Wright, along with Freeman and Monroe, should be grabbing those shots and possessions. And yes, Wright should probably take it to the hoop a bit more.

But the biggest difference for Wright this year should be in skill development, not a change in role within the system or even a change to the system itself. Simply by improving his stroke from outside and at the line and reducing his turnovers, Wright can realize his potential to become All-Big East.

Monday, January 26, 2009

Recap: Seton Hall 65, Georgetown 60

Sorry for the tardy post - real life is getting very busy for me these days.


There was an ugly incident in Newark, NJ on Sunday, masquerading as a college basketball game. In the end, the Seton Hall Pirates played less-poorly to pull out a five point win, their first against Georgetown since 2004.

Let's run the numbers:

TEMPO-FREE BOX SCORE

. Visitor Home
. GU Seton Hall
. 1st Half 2nd Half Total 1st Half 2nd Half Total
Pace 30 32 62

Effic. 88.1 101.6 95.4 84.8 120.0 103.3

eFG% 42.0 29.6 35.6 39.3 46.2 42.6
TO% 35.9 18.5 27.0 19.6 9.2 14.3
OR% 53.3 50.0 51.5 29.4 45.0 37.8
FT Rate 28.0 74.1 51.9 14.3 88.5 50.0

Assist Rate 60.0 57.1 58.8 54.5 66.7 60.9
Block Rate 5.6 0.0 2.4 6.7 20.0 13.3
Steal Rate 9.8 3.1 6.4 16.3 6.2 11.1

2FG% 60.0 33.3 46.7 61.1 52.2 56.1
3FG% 10.0 16.7 13.6 0.0 0.0 0.0
FT% 85.7 85.0 85.2 100.0 65.2 70.4

Well, the Hoyas made their free throws and got half of their own missed shots . . . and that's about all the good news from yesterday.

If you tuned in to the game to watch a shooting exhibition, you came away disappointed. Georgetown made 3/22 3 FG (2/5 by J. Sapp, 1/17 by everyone else) - not to be outdone, Seton Hall went 0/13 3FG (0/10 by J. Hazell). While some of those missed shots were rushed as the shot clock was winding down, a number were open shots in the rhythm of the offense. The Hoyas also shot poorly from outside against WVU (2/16 3FG), and as I pointed out in that game recap, the offense tends to break down when there is no scoring from beyond the arc.

The Hoyas also were very sloppy with the ball in the 1st half, committing 12 turnovers on 32 offensive possessions. The fact that they lead at the half is attributable to their defense, and to making 2 pt. jumpers (5/8) rather than inside shots (4/7 on dunks, layups and tip-ins), which is usually not a sustainable strategy.

It wasn't, but not in the way you'd expect.

Georgetown was able to get more 2-pt shots from close in during the 2nd half, but many consisted of out-of-control drives: the Hoyas were 3/10 on dunks, layups and tip-ins in the 2nd half, and 2/5 on 2-pt jumpers. Coupled with more cold outside shooting (2/12 3FG, both made by Sapp), G'town became dependent upon getting to the FT line (17/20 FT), but couldn't make enough defensive stops to win the game.

INDIVIDUAL NET POINTS STATS

GU Off Poss Individ Def Individ
Player Poss Used ORtg Pts Prod Poss DRtg Pts Allow Net Pts
Summers, DaJuan 54 17.6 64.1 11.3 50 105.3 10.5 +0.8
Monroe, Greg 56 7.2 180.1 13.0 55 98.5 10.8 +2.2
Wright, Chris 60 12.2 76.3 9.3 59 99.0 11.7 -2.4
Freeman, Austin 43 8.7 64.1 5.5 44 90.6 8.0 -2.4
Sapp, Jessie 57 8.2 97.0 8.0 57 87.2 9.9 -2.0
Mescheriakov, Nikita 4 0.1 200.0 0.1 5 120.0 1.2 -1.1
Clark, Jason 22 3.5 29.5 1.0 21 98.4 4.1 -3.1
Vaughn, Julian 9 1.2 200.0 2.5 9 77.6 1.4 +1.1
Wattad, Omar 20 5.0 85.3 4.3 20 77.3 3.1 +1.2
TOTALS 65 63.8 86.5 55.2 64 95.0 60.8 -5.6

Seton Hall Off Poss Individ Def Individ
Player Poss Used ORtg Pts Prod Poss DRtg Pts Allow Net Pts
MITCHELL, Robert 64 13.4 133.3 17.9 65 94.2 12.2 +5.6
GARCIA, John 40 7.2 80.9 5.9 40 63.4 5.1 +0.8
HARVEY, Eugene 50 7.9 71.7 5.7 49 101.8 10.0 -4.3
HAZELL, Jeremy 59 23.1 90.5 20.9 60 77.4 9.3 +11.6
GAUSE, Paul 55 7.9 96.4 7.6 57 89.5 10.2 -2.6
THEODORE, Jordan 28 2.1 205.3 4.2 29 77.0 4.5 -0.2
DAVIS, Mike 3 0.0 - 0.0 5 200.0 2.0 -2.0
CAJUSTE, Matt 5 0.0 - 0.0 3 141.7 0.9 -0.9
WALTERS, Brandon 16 1.5 48.6 0.7 17 114.5 3.9 -3.2
TOTALS 64 63.0 99.7 62.8 65 89.2 58.0 +4.8

Jessie Sapp was modestly efficient in the game, and did so while using 14% of available possessions (8.2/57). He was also the most effective defensive starter for the Hoyas. Hopefully, this is a sign that he's coming out of his mid-season funk.

Greg Monroe (Player of the Game) was his usual efficient offensive self, although in suprisingly few possessions used (13%). This was the first time since the Savannah St. game that Monroe used less than 20% of the possessions he played; also, Greg finished with no assists in the game - he had had at least 1 assist in each half played since the game against FIU.

Julian Vaughn played well in limited minutes, and Omar Wattad game some serviceable relief.

And that's about it for the Hoyas.


Today's tip-of-the-cap goes to Robert "Stix" Mitchell, one of only three positive contributors for the Pirates. While J. Hazell got his through quantity (39% poss used!), Mitchell shot an efficient 8/11 on 2FG to produce 18 points for Seton Hall.


HD BOX SCORE

GU vs Seton Hall
01/25/09 2:00 p.m. at Newark, N.J. - Prudential Center
Final score: Seton Hall 65, GU 60

GU Min +/- Pts 2PM-A 3PM-A FTM-A FGA A Stl TO Blk OR DR PF
Summers, DaJuan 30:24 - 4 12/49 0- 2 1- 6 9-11 8/39 0/12 0/50 6/54 1/34 2/26 4/30 3
Monroe, Greg 33:00 - 5 17/53 6- 7 0- 0 5- 7 7/43 0/ 8 0/55 1/56 0/35 2/30 5/30 2
Wright, Chris 36:03 -11 11/51 2- 7 0- 3 7- 7 10/47 3/11 1/59 3/60 0/38 0/34 2/33 3
Freeman, Austin 25:27 - 9 4/36 1- 6 0- 3 2- 2 9/35 1/ 9 2/44 3/43 0/26 3/24 1/23 4
Sapp, Jessie 36:04 + 3 8/58 1- 3 2- 5 0- 0 8/48 4/14 0/57 3/57 0/37 2/31 7/36 3
Mescheriakov, Nikita 03:55 + 0 2/ 6 1- 1 0- 1 0- 0 2/ 8 0/ 2 0/ 5 0/ 4 0/ 3 0/ 6 0/ 2 0
Clark, Jason 13:52 - 3 0/16 0- 0 0- 1 0- 0 1/13 1/ 5 0/21 2/22 0/12 1/ 8 0/10 1
Vaughn, Julian 07:00 + 0 4/ 7 2- 2 0- 0 0- 0 2/ 9 0/ 1 0/ 9 0/ 9 0/ 6 0/ 5 1/ 7 2
Wattad, Omar 14:15 + 4 2/24 1- 2 0- 3 0- 0 5/18 1/ 6 1/20 1/20 0/14 3/11 1/14 4
TOTALS 40:00 60 14-30 3-22 23-27 52 10/17 4/64 20/65 1/41 17/33 23/37 22
. 0.467 0.136 0.852 0.588 0.062 0.308 0.024 0.515 0.622

Seton Hall Min +/- Pts 2PM-A 3PM-A FTM-A FGA A Stl TO Blk OR DR PF
MITCHELL, Robert 40:00 + 5 20/65 8-11 0- 1 4- 6 12/54 3/15 0/65 2/64 2/30 4/37 3/35 2
GARCIA, John 24:43 +14 5/44 2- 5 0- 0 1- 1 5/39 2/15 1/40 3/40 1/14 2/25 4/16 5
HARVEY, Eugene 30:58 + 0 7/49 3- 6 0- 0 1- 2 6/40 2/14 0/49 3/50 0/23 0/28 2/28 1
HAZELL, Jeremy 37:20 + 6 23/61 5-11 0-10 13-17 21/51 1/16 3/60 2/59 0/29 3/36 4/34 2
GAUSE, Paul 33:50 - 3 6/51 3- 6 0- 1 0- 0 7/48 5/16 2/57 2/55 0/27 2/35 2/30 2
THEODORE, Jordan 17:52 +12 4/34 2- 2 0- 1 0- 0 3/23 1/10 1/29 0/28 0/11 1/12 0/13 0
DAVIS, Mike 02:02 - 9 0/ 1 0- 0 0- 0 0- 0 0/ 0 0/ 0 0/ 5 0/ 3 0/ 3 0/ 1 0/ 3 5
CAJUSTE, Matt 03:42 + 2 0/ 6 0- 0 0- 0 0- 0 0/ 4 0/ 2 0/ 3 0/ 5 0/ 4 0/ 2 0/ 6 0
WALTERS, Brandon 09:33 - 2 0/14 0- 0 0- 0 0- 1 0/11 0/ 4 0/17 0/16 1/ 9 1/ 9 0/10 3
TOTALS 40:00 65 23-41 0-13 19-27 54 14/23 7/65 12/64 4/30 14/37 16/33 20
. 0.561 0.000 0.704 0.609 0.108 0.188 0.133 0.378 0.485

Efficiency: Seton Hall 1.016, GU 0.923
eFG%: Seton Hall 0.426, GU 0.356
Substitutions: Seton Hall 24, GU 24

2-pt Shot Selection:
Dunks: Seton Hall 0-0, GU 0-0
Layups/Tips: Seton Hall 16-28, GU 7-17
Jumpers: Seton Hall 7-13, GU 7-13

Fast break pts: Seton Hall 14 (0.304), GU 0 (0.000)
Seconds per off. poss: Seton Hall 18.5, GU 18.9

-------------------------------------------------------------------------------------

As I mentioned at the top, I'm super busy these days and the updates of stats and Big East HD box scores are falling behind. I'll try to make a push to get caught up tonight, but things may be lagging for a week or so until I can get some free time.

Thursday, January 22, 2009

Recap: WVU 75, Georgetown 58

The Hoyas were thoroughly routed tonight by a strong defensive effort by the Mountaineers tonight. Georgetown last held a lead at 15-14 with 10:16 left in the 1st half, but it was all West Virginia after that, with the visitors outscoring the Hoyas 61-43 the rest of the way.

Let's run the numbers:

TEMPO-FREE BOX SCORE

. Home Visitor
. GU West Virginia
. 1st Half 2nd Half Total 1st Half 2nd Half Total
Pace 34 35 69

Effic. 76.0 89.7 83.2 90.6 123.4 107.6

eFG% 47.9 35.2 41.2 45.2 64.5 54.8
TO% 32.2 22.4 27.3 23.4 22.4 23.0
OR% 21.4 39.1 32.4 31.6 57.1 42.4
FT Rate 20.8 74.1 49.0 9.7 22.6 16.1

Assist Rate 36.4 44.4 40.0 50.0 44.4 46.7
Block Rate 15.0 0.0 7.7 17.6 11.1 14.3
Steal Rate 14.6 11.2 12.9 11.7 5.6 8.6

2FG% 58.8 44.4 51.4 40.0 73.7 56.4
3FG% 14.3 11.1 12.5 36.4 33.3 34.8
FT% 60.0 65.0 64.0 100.0 57.1 70.0
Neither team plays at a particularly fast pace this season, and the game was just a few possessions faster than expected.

There is an axiom that I trot out from time to time, and that is that nobody can stop the Georgetown offense when the team gets hot shooting from outside. While this is obviously a great simplification, and actually wasn't very strongly demonstrated last season, it does seem to hold true this year. The logical inverse of this statement (anyone can stop the Georgetown offense when the team goes cold from outside) was demonstrated tonight, as the Hoyas made only 2/16 3FG for the game, and ended with easily their least efficient offensive effort of the season - previously vs. Wichita St.

If you will forgive a chart in the middle of this recap (click image to enlarge):



I won't go into much detail here about offensive performance - if you are even a semi-regular visitor, I hope you check the team performance charts linked on the right - but it is simply the number of points scored minus expected points scored, based on Ken Pomeroy's stats. It can be thought of as a measure of offensive efficiency, adjusted for the quality of the opponent's defense. The red dots represent Hoyas games this season before tonight, and the blue dot is tonight's performance.

What makes this especially interesting is that G'town is scoring a lower percentage of their points on 3FG this season than any previous in the JTIII era.


Now that is not to say that there weren't other important factors in tonight's game:
  • the very high turnover rate in the 1st half
  • the poor defensive rebounding in the 2nd half
  • the high shooting efficiency allowed in the 2nd half

All in all, a forgettable effort by the Blue and Gray tonight.


INDIVIDUAL NET POINTS STATS

GU Off Poss Individ Def Individ
Player Poss Used ORtg Pts Prod Poss DRtg Pts Allow Net Pts
Summers, DaJuan 65 12.7 87.2 11.1 64 116.0 14.8 -3.8
Wright, Chris 51 11.9 91.0 10.8 49 107.9 10.6 +0.2
Monroe, Greg 62 15.4 89.5 13.8 62 94.2 11.7 +2.1
Freeman, Austin 61 9.6 86.9 8.4 62 94.3 11.7 -3.3
Sapp, Jessie 34 2.3 140.0 3.2 35 95.6 6.7 -3.5
Mescheriakov, Nikita 4 0.0 - 0.0 3 133.3 0.8 -0.8
Clark, Jason 45 9.5 31.7 3.0 43 117.3 10.1 -7.1
Vaughn, Julian 8 4.3 16.0 0.7 7 178.3 2.5 -1.8
Sims, Henry 3 1.5 66.7 1.0 3 56.0 0.3 +0.7
Wattad, Omar 17 1.2 200.0 2.4 17 84.7 2.9 -0.5
TOTALS 70 68.4 79.4 54.4 69 104.5 72.1 -17.7

West Virginia Off Poss Individ Def Individ
Player Poss Used ORtg Pts Prod Poss DRtg Pts Allow Net Pts
Butler, Da'Sean 65 17.4 118.6 20.7 66 83.7 11.0 +9.6
Ebanks, Devin 58 12.2 80.7 9.9 57 82.8 9.4 +0.4
Ruoff, Alex 64 9.7 141.2 13.7 65 80.1 10.4 +3.2
Bryant, Darryl 45 10.6 86.1 9.1 44 91.5 8.1 +1.0
Smith, Wellington 45 9.7 100.7 9.8 47 69.4 6.5 +3.3
Thoroughman, Cam 9 0.0 - 0.0 10 74.6 1.5 -1.5
Jones, Kevin 29 4.0 102.5 4.1 30 75.8 4.6 -0.4
Flowers, John 30 4.1 117.5 4.8 31 60.8 3.8 +1.1
TOTALS 69 67.7 106.3 72.0 70 79.0 55.3 +16.7

Sorry, no comments for individual players tonight (I'm running late), so just a few more bullet points:
  • The continuing disappearance of J. Sapp is starting to become the storyline of the season for me. Sapp actually played an efficient game at both ends tonight, but used only 7% of possessions played (2.3/34). As the only senior and one of only two upperclassmen in the rotation, this regression is a big problem.
  • The rest of the starters were all generally inefficient, albeit in different ways - D. Summers: 1/7 3FG, C. Wright: 3 TOs, G. Monroe: 4/10 2FG & 4 TOs, A. Freeman: 1/4 2FG, 0/2 3FG.
  • The bench, mostly J. Clark with some O. Wattad on the side, didn't provide much assistance. I should say that Wattad played well.
  • Dare I say . . . free Henry Sims?
I'm not giving a Player of the Game out tonight, since I don't have to if I don't want to. So there.

But I will give a tip-of-the-cap to D. Butler for leading all players in net points produced.

HD BOX SCORE

West Virginia vs GU
01/22/09 7:00 at Verizon Center
Final score: West Virginia 75, GU 58

West Virginia Min +/- Pts 2PM-A 3PM-A FTM-A FGA A Stl TO Blk OR DR PF
Butler, Da'Sean 37:52 +16 27/72 7- 9 4- 9 1- 1 18/60 0/18 0/66 4/65 0/34 2/33 6/36 2
Ebanks, Devin 33:32 + 7 9/57 4- 8 0- 1 1- 2 9/53 0/20 1/57 4/58 1/27 3/31 4/28 2
Ruoff, Alex 37:11 +18 10/73 2- 3 1- 7 3- 4 10/57 9/26 2/65 1/64 0/34 0/30 1/34 1
Bryant, Darryl 26:41 + 5 13/46 2- 5 3- 5 0- 0 10/42 2/14 0/44 4/45 0/26 0/23 5/19 4
Smith, Wellington 25:48 +14 10/47 5- 8 0- 1 0- 0 9/40 2/14 1/47 1/45 3/24 2/21 2/29 4
Thoroughman, Cam 06:16 + 7 0/15 0- 0 0- 0 0- 0 0/ 8 0/ 5 0/10 0/ 9 0/ 6 0/ 4 1/ 8 3
Jones, Kevin 15:04 +13 4/38 1- 3 0- 0 2- 2 3/24 0/13 2/30 1/29 1/12 1/12 0/11 2
Flowers, John 17:36 + 5 2/27 1- 3 0- 0 0- 1 3/26 1/10 0/31 1/30 0/12 4/16 4/20 4
TOTALS 40:00 75 22-39 8-23 7-10 62 14/30 6/70 16/69 5/35 14/33 25/37 22
. 0.564 0.348 0.700 0.467 0.086 0.232 0.143 0.424 0.676

GU Min +/- Pts 2PM-A 3PM-A FTM-A FGA A Stl TO Blk OR DR PF
Summers, DaJuan 36:29 -17 12/52 3- 7 1- 7 3- 6 14/48 1/14 0/64 2/65 1/38 1/35 2/30 0
Wright, Chris 30:03 -11 13/45 5- 6 0- 2 3- 5 8/34 0/11 1/49 3/51 0/27 0/21 3/25 4
Monroe, Greg 36:15 - 9 11/54 4-10 0- 0 3- 6 10/48 4/15 2/62 4/62 2/37 4/35 4/34 3
Freeman, Austin 34:17 -25 9/44 1- 4 0- 2 7- 8 6/44 0/14 5/62 1/61 0/38 1/35 2/29 3
Sapp, Jessie 21:12 - 1 3/29 0- 0 1- 2 0- 0 2/27 2/10 0/35 0/34 0/20 1/17 1/19 3
Mescheriakov, Nikita 01:24 - 1 0/ 3 0- 0 0- 0 0- 0 0/ 7 0/ 1 0/ 3 0/ 4 0/ 2 0/ 7 0/ 0 0
Clark, Jason 23:44 -21 4/33 2- 4 0- 2 0- 0 6/31 0/ 8 1/43 5/45 0/25 0/27 3/19 1
Vaughn, Julian 03:45 - 8 0/ 4 0- 1 0- 0 0- 0 1/ 3 1/ 1 0/ 7 3/ 8 0/ 2 1/ 2 0/ 0 1
Sims, Henry 02:38 + 1 2/ 4 1- 1 0- 0 0- 0 1/ 3 0/ 1 0/ 3 1/ 3 0/ 1 1/ 1 1/ 3 0
Wattad, Omar 10:13 + 7 4/22 2- 2 0- 1 0- 0 3/10 0/ 5 0/17 0/17 0/ 5 0/ 5 0/11 1
TOTALS 40:00 58 18-35 2-16 16-25 51 8/20 9/69 19/70 3/39 12/37 19/33 16
. 0.514 0.125 0.640 0.400 0.130 0.271 0.077 0.324 0.576


Efficiency: West Virginia 1.087, GU 0.829
eFG%: West Virginia 0.548, GU 0.412
Substitutions: West Virginia 27, GU 27

2-pt Shot Selection:
Dunks: West Virginia 5-5, GU 0-0
Layups/Tips: West Virginia 11-18, GU 15-26
Jumpers: West Virginia 6-16, GU 3-9

Fast break pts: West Virginia 6 (0.088), GU 2 (0.048)
Seconds per off. poss: West Virginia 18.7, GU 15.7

Saturday, November 22, 2008

Recap: Georgetown 81, Drexel 53

The Drexel Dragons were no match for the Hoyas today at the Verizon Center, succumbing to efficient shooting in the 1st half and a strong defensive effort all game.

Let's run the numbers:

TEMPO-FREE BOX SCORE

. Home Visitor
. Georgetown DREXEL
. 1st Half 2nd Half Total 1st Half 2nd Half Total
Pace 32 37 69

Effic. 127.8 105.3 115.9 76.1 75.6 75.8

eFG% 67.3 50.0 58.5 38.6 25.8 31.1
TO% 18.3 13.5 15.7 33.5 16.2 24.3
OR% 20.0 12.5 15.4 26.7 26.9 26.8
FT Rate 26.9 55.6 41.5 36.4 48.4 43.4

Assist Rate 68.8 58.3 64.3 57.1 66.7 61.5
Block Rate 14.3 9.5 11.4 0.0 0.0 0.0
Steal Rate 21.3 16.2 18.6 3.0 8.1 5.7

2FG% 76.5 60.0 68.8 28.6 9.5 17.1
3FG% 33.3 25.0 28.6 37.5 40.0 38.9
FT% 100.0 80.0 86.4 100.0 80.0 87.0

I've bolded and highlighted key numbers from the tempo-free box:
  • Just a solid defensive effort by the Hoyas, across both halves.
  • Georgetown took good care of the ball today, while Drexel was exceptionally generous in the 1st half.
  • Georgetown was very efficient shooting from the floor in the 1st half, by shooting 12 layups or tip-ins and making 11. Drexel had a miserable 2nd half shooting the ball from 2-pt range (2-8 on layups didn't help, but 0-11 on 2-pt jumpers was the killer).
  • After 2 games, it looks like rebounding will be a big issue for the Hoyas. They've been outrebounded twice now, by teams that are unarguably inferior athletically.


INDIVIDUAL NET POINTS STATS

Georgetown Off Poss Individ Def Individ
Player Poss Used ORtg Pts Prod Poss DRtg Pts Allow Net Pts

Summers, DaJuan 43 10.5 107.1 11.3 45 75.8 6.8 +4.5
Wright, Chris 52 10.8 119.3 12.9 51 62.3 6.4 +6.5
Monroe, Greg 54 12.8 172.7 22.1 56 61.3 6.9 +15.2
Freeman, Austin 36 7.8 194.9 15.1 37 69.4 5.1 +10.0
Sapp, Jessie 41 5.1 103.0 5.2 40 47.2 3.8 +1.5
Mescheriakov, Nikita 20 5.0 19.2 1.0 19 88.2 3.4 -2.4
Jansen, Bryon 4 0.0 - 0.0 4 0.0 0.0 +0.0
Clark, Jason 44 6.1 112.4 6.8 47 83.1 7.8 -1.0
Sims, Henry 35 5.9 29.1 1.7 35 77.3 5.4 -3.7
Wattad, Omar 26 6.8 52.2 3.5 26 77.2 4.0 -0.5
TOTALS 71 70.6 112.8 79.6 72 73.6 49.5 +30.1

DREXEL Off Poss Individ Def Individ
Player Poss Used ORtg Pts Prod Poss DRtg Pts Allow Net Pts

Rodgers, Scott 63 11.5 84.7 9.8 63 119.4 15.0 -5.3
Colds. Gerald 35 11.4 82.7 9.5 34 141.6 9.6 -0.2
Harris, Jamie 66 10.9 105.0 11.4 65 120.7 15.7 -4.3
Neisler, Evan 33 10.9 28.2 3.1 33 123.2 8.1 -5.0
Tribbett, Kenny 16 2.0 0.0 0.0 14 168.8 4.7 -4.7
Hawthorne, Tramayne 45 7.8 120.5 9.4 43 77.3 6.7 +2.8
Spencer, Leon 32 8.6 27.0 2.3 33 115.7 7.6 -5.3
Formbor, Yannick 13 2.1 16.0 0.3 13 103.3 2.7 -2.3
Phillip, Kevin 15 2.3 35.9 0.8 15 39.1 1.2 -0.3
Givens, Samme 42 4.0 138.4 5.5 42 89.3 7.5 -2.0
TOTALS 72 71.6 72.8 52.1 71 114.1 82.3 -30.2
Comments:
  • Anyone know where Julian Vaughn was today? Edited to add: The crack staff over at Hoya Hoops got the story:
    Coach said that Vaughn had a minor leg injury above the Achilles and below the calf (he couldn’t remember the medical term or which leg) but he said it wasn’t serious. He said Vaughn suffered the injury before the Jacksonville game but played through it and you could notice him limping a bit in that game. Vaughn hasn’t practiced since then but Coach didn’t seem like it was anything major.
  • Greg Monroe is slipping (he had a Off. Rtg. of 174 last game).
  • Chris Wright didn't miss a FT today.
  • Austin Freeman recovered nicely from his 1-10 shooting performance against Jacksonville with a 4-4 2FG, 2-3 3FG game today. I'm going to go ahead and chalk up last game's problems to the obvious leg cramps he was having.
  • Henry Sims and Nikita Mescheriakov continued to struggle offensively with a bit more burn than last game. Meshcharakou (alternative spelling!) missed on two 3FGAs today - he'll need to start making those to stay in the rotation. Sims was 0-3 on 3FGAs today - he'll need to stop taking those, but he'll likely stay in the rotation either way.
  • Again in this game, Sapp lead the team with his defensive play (5 steals!). I'd suggest that he's doing a great job leading the team right now, by deferring on offense to players who need to get touches as they grow into the offense (Wright & Monroe, especially), but still bringing maximum effort on the other end.
  • Player of the game is . . . Greg Monroe. He used about 5 more possessions than last game on offense with virtually no drop in efficiency, while playing a better defensive game (3 steals, 3 blocks, 6 def. rebounds). His most important stat is probably his 4 assists, second today behind Wright (7).

HD BOX SCORE

DREXEL vs Georgetown
11/22/08 1:00 at
Final score: Georgetown 81, DREXEL 53

DREXEL Min +/- Pts 2PM-A 3PM-A FTM-A FGA A Stl TO Blk OR DR PF
Rodgers, Scott 35:14 -29 13/45 3- 8 1- 2 4- 4 10/49 0/ 7 0/63 3/63 0/28 0/39 2/22 4
Colds. Gerald 18:21 -23 11/25 1- 5 2- 5 3- 3 10/24 0/ 3 0/34 2/35 0/16 0/18 0/13 3
Harris, Jamie 36:15 -29 12/49 1- 3 2- 3 4- 4 6/48 2/ 9 0/65 5/66 0/32 3/37 3/25 3
Neisler, Evan 18:40 -23 3/18 0- 6 0- 0 3- 4 6/27 0/ 4 0/33 3/33 0/16 1/23 2/13 3
Tribbett, Kenny 09:10 -18 0/ 6 0- 1 0- 0 0- 0 1/10 0/ 1 0/14 1/16 0/11 0/ 9 0/ 4 1
Hawthorne, Tramayne 25:07 - 1 10/38 1- 2 2- 8 2- 2 10/31 2/ 6 2/43 0/45 0/17 1/23 2/18 1
Spencer, Leon 18:24 -11 1/29 0- 4 0- 0 1- 2 4/23 0/ 7 1/33 4/32 0/12 2/17 2/ 7 3
Formbor, Yannick 08:03 - 6 0/ 7 0- 1 0- 0 0- 0 1/ 9 1/ 2 0/13 1/13 0/ 5 0/ 7 0/ 3 1
Phillip, Kevin 08:31 + 5 0/13 0- 3 0- 0 0- 0 3/16 0/ 4 0/15 0/15 0/ 7 1/12 4/13 1
Givens, Samme 22:15 - 5 3/35 0- 2 0- 0 3- 4 2/28 3/ 9 1/42 0/42 0/16 2/20 2/17 1
TOTALS 40:00 53 6-35 7-18 20-23 53 8/13 4/71 19/72 0/32 11/41 22/26 21
. 0.171 0.389 0.870 0.615 0.056 0.264 0.000 0.268 0.846

Georgetown Min +/- Pts 2PM-A 3PM-A FTM-A FGA A Stl TO Blk OR DR PF
Summers, DaJuan 25:18 +16 10/54 2- 3 0- 4 6- 6 7/28 2/15 2/45 1/43 0/22 0/13 4/24 5
Wright, Chris 29:49 +22 11/57 4- 8 1- 2 0- 0 10/39 7/15 2/51 1/52 0/24 0/21 5/28 1
Monroe, Greg 30:30 +36 20/76 7- 9 0- 0 6- 6 9/42 4/21 3/56 1/54 3/25 2/14 6/28 2
Freeman, Austin 21:01 +31 16/53 4- 4 2- 3 2- 3 7/29 3/15 0/37 1/36 0/22 2/ 8 3/25 2
Sapp, Jessie 23:31 +23 8/49 1- 1 2- 2 0- 0 3/31 2/15 5/40 3/41 1/18 0/13 2/22 2
Mescheriakov, Nikita 09:39 + 1 1/17 0- 1 0- 2 1- 2 3/16 0/ 5 0/19 1/20 0/ 5 0/12 1/ 8 2
Jansen, Bryon 01:52 + 0 0/ 0 0- 0 0- 0 0- 0 0/ 4 0/ 0 0/ 4 0/ 4 0/ 2 0/ 4 0/ 4 0
Clark, Jason 24:47 + 5 9/46 2- 2 1- 4 2- 2 6/31 0/11 1/47 1/44 0/23 0/19 3/27 1
Sims, Henry 18:31 + 3 2/29 1- 2 0- 3 0- 0 5/25 0/ 8 0/35 1/35 0/20 0/17 2/22 2
Wattad, Omar 15:02 + 3 4/24 1- 2 0- 1 2- 3 3/20 0/ 7 0/26 2/26 0/14 0/14 2/17 2
TOTALS 40:00 81 22-32 6-21 19-22 53 18/28 13/72 12/71 4/35 4/26 30/41 19
. 0.688 0.286 0.864 0.643 0.181 0.169 0.114 0.154 0.732

Efficiency: Georgetown 1.141, DREXEL 0.736
eFG%: Georgetown 0.585, DREXEL 0.311
Substitutions: Georgetown 29, DREXEL 28

2-pt Shot Selection:
Dunks: Georgetown 3-3, DREXEL 0-2
Layups/Tips: Georgetown 16-20, DREXEL 3-11
Jumpers: Georgetown 3-9, DREXEL 3-22

Monday, November 17, 2008

Recap: Georgetown 71, Jacksonville 62

And so begins another season of Georgetown basketball, with a closer-than-you'd-like win over a pesky Jacksonville Dolphins team.

Let's run the numbers.

TEMPO-FREE BOX SCORE

. Home Visitor
. Georgetown Jacksonville
. 1st Half 2nd Half Total 1st Half 2nd Half Total
Pace 39 30 69

Effic. 94.7 110.0 101.5 64.0 119.7 88.7

eFG% 51.6 35.7 45.2 29.7 45.5 37.7
TO% 20.5 9.7 15.7 25.6 9.7 18.6
OR% 26.3 21.4 24.2 30.8 50.0 39.6
FT Rate 35.5 104.8 63.5 28.1 30.3 29.2

Assist Rate 57.1 42.9 52.4 33.3 14.3 21.7
Block Rate 19.0 8.3 13.3 0.0 0.0 0.0
Steal Rate 17.9 6.5 12.9 12.8 3.2 8.6

2FG% 58.8 50.0 55.2 38.1 50.0 44.4
3FG% 28.6 11.1 21.7 9.1 22.2 15.0
FT% 45.5 86.4 72.7 66.7 70.0 68.4

Comments:
  • The 69 possessions from tonight's game is quite a bit faster than last year's team average (62.1). A sign of things to come? Not so fast, my friend; last season's game against Jacksonville had a total of . . . 69 possessions.
  • Much like last year's game, the Hoyas jumped out to a comfortable 1st half lead with good offense and excellent defense. This time, the Dolphins actually out-played G'town in the 2nd half to keep the game close.
  • For all of the moaning about FT shooting in the 1st half (C. Wright shot 1-6 FTs during the first half), the team ended the game with a perfectly acceptable 73 %FT.
  • The OReb% allowed, especially in the 2nd half, was not good. Over the years, it is becoming apparent that JTIII is willing to give up offensive rebounds for the sake of keeping eFG% down. Unfortunately, J'ville shot better in the 2nd half while getting fully half of their own missed shots.
  • That 13.3% block rate is comparable to last year's average thanks to G. Monroe and J. Vaughn, but the big men will need to watch their fouls until H. Sims is able to play more minutes.


INDIVIDUAL NET POINTS STATS

Georgetown Off Poss Individ Def Individ
Player Poss Used ORtg Pts Prod Poss DRtg Pts Allow Net Pts
Summers, DaJuan 46 10.1 112.0 11.3 46 103.8 9.5 +1.8
Wright, Chris 63 10.9 118.3 12.9 62 93.1 11.5 +1.4
Monroe, Greg 51 7.4 173.8 12.9 50 90.7 9.1 +3.8
Freeman, Austin 57 15.7 54.1 8.5 56 87.6 9.8 -1.3
Sapp, Jessie 60 10.2 131.8 13.5 59 79.6 9.4 +4.1
Mescheriakov, Nikita 7 2.0 0.0 0.0 6 56.1 0.7 -0.7
Clark, Jason 23 3.3 135.2 4.4 23 100.0 4.6 -0.2
Vaughn, Julian 17 2.3 116.2 2.7 18 114.6 4.1 -1.4
Sims, Henry 4 0.0 - 0.0 4 60.0 0.5 -0.5
Wattad, Omar 22 6.8 24.6 1.7 21 80.9 3.4 -1.7
TOTALS 70 68.8 98.7 67.9 69 89.9 62.6 +5.3

Jacksonville Off Poss Individ Def Individ
Player Poss Used ORtg Pts Prod Poss DRtg Pts Allow Net Pts
SMITH,Ben 53 15.2 86.7 13.2 54 97.5 10.5 +2.6
HARDY,Ayron 46 13.8 65.8 9.1 44 110.8 9.7 -0.7
JEFFERSON,Evan 24 4.3 74.6 3.2 22 98.0 4.3 -1.1
COLBERT,Lehmon 53 9.5 82.7 7.9 53 100.2 10.6 -2.8
ALLEN,Marcus 53 10.8 144.5 15.6 52 98.2 10.2 +5.3
COHN, Travis 24 1.4 66.0 1.0 25 116.5 5.8 -4.9
GILBERT,Brian 16 0.0 - 0.0 16 112.8 3.6 -3.6
EDWARDS,Chris 16 0.9 203.0 1.8 16 102.3 3.3 -1.5
BROOKS,Aric 20 6.6 36.2 2.4 25 76.6 3.8 -1.4
GALVIN,Tevin 24 1.4 205.3 2.9 25 85.6 4.3 -1.4
LUKASIAK,Szymon 12 5.8 115.4 6.7 12 111.8 2.7 +4.0
ALSTON,Will 4 0.0 - 0.0 6 102.1 1.2 -1.2
TOTALS 69 69.7 91.2 63.6 70 101.4 69.8 -6.2

Comments
  • Most of the Hoyas had good to excellent offensive games. Exceptions were A. Freeman, who made only 1-10 shots from the field, and O. Wattad, who missed all five of his 3FGAs. I'll let N. Mescheriakov slide, as he only played seven offensive possessions.
  • A big question coming into this season was who would take over the possessions used by R. Hibbert, J. Wallace and P. Ewing? Freeman certainly took a healthy share today (15.7/57 = 27.5%), and Wattad wasn't bashful either. Too bad they weren't very efficient with their possessions.
  • There was much grumbling in the chat room about why Wattad was playing so many minutes (or about 30% of all possessions), but a couple of the lucky few who could actually watch the game pointed out that his defense looked good. The numbers bear this out, as he and Jessie Sapp had the strongest defensive numbers of those with >10 defensive possessions played. Unfortunately, his defense couldn't make up for his poor shooting. Have we found a drop-in replacement for J. Rivers?
  • The player of the game is . . . Jessie Sapp, who just nosed out G. Monroe, playing his first game. Let me take a moment to point out just how efficient Monroe was in his ~50 possessions played: 6-8 2FG, 2-3 FT, 2 OReb (only player with more than 1), 1 A, 3 Bl. He flirted with foul trouble most of the 2nd half, but this is to be expected for a freshman center. He looks very good after 1 game.

HD BOX SCORE

Jacksonville vs Georgetown
11/17/08 7:30 at Verizon Center
Final score: Georgetown 71, Jacksonville 62

Jacksonville Min +/- Pts 2PM-A 3PM-A FTM-A FGA A Stl TO Blk OR DR PF
SMITH,Ben 30:46 - 9 17/45 5- 8 1- 6 4- 4 14/52 1/11 1/54 2/53 0/22 0/38 4/25 1
HARDY,Ayron 27:00 -13 7/36 3- 8 0- 1 1- 2 9/45 0/11 0/44 4/46 0/18 6/34 3/18 4
JEFFERSON,Evan 14:05 - 4 5/18 1- 2 1- 4 0- 0 6/24 0/ 4 0/22 0/24 0/14 0/19 1/11 2
COLBERT,Lehmon 29:19 - 5 7/48 2- 6 1- 4 0- 1 10/48 1/15 1/53 2/53 0/20 3/35 2/23 2
ALLEN,Marcus 29:52 - 7 14/46 6-11 0- 2 2- 2 13/51 1/12 2/52 1/53 0/20 6/36 3/21 3
COHN, Travis 15:09 - 1 0/28 0- 2 0- 0 0- 0 2/26 0/10 0/25 1/24 0/ 9 1/19 2/12 2
GILBERT,Brian 10:38 - 4 0/14 0- 0 0- 1 0- 0 1/19 0/ 5 0/16 0/16 0/ 7 0/15 0/ 8 0
EDWARDS,Chris 09:14 + 0 2/17 0- 0 0- 0 2- 2 0/15 1/ 6 0/16 0/16 0/ 5 0/12 0/ 7 1
BROOKS,Aric 11:47 - 4 3/15 1- 3 0- 1 1- 3 4/16 0/ 4 0/25 3/20 0/ 8 0/13 2/12 1
GALVIN,Tevin 12:02 + 4 2/27 1- 1 0- 1 0- 0 2/23 1/10 2/25 0/24 0/ 5 1/15 4/12 0
LUKASIAK,Szymon 08:09 + 3 5/16 1- 5 0- 0 3- 5 5/13 0/ 4 0/12 0/12 0/ 5 3/11 0/ 7 5
ALSTON,Will 01:59 - 5 0/ 0 0- 1 0- 0 0- 0 1/ 3 0/ 0 0/ 6 0/ 4 0/ 2 0/ 3 0/ 4 1
TOTALS 40:00 62 20-47 3-20 13-19 67 5/23 6/70 13/69 0/27 20/50 24/31 22
. 0.426 0.150 0.684 0.217 0.086 0.188 0.000 0.400 0.774

Georgetown Min +/- Pts 2PM-A 3PM-A FTM-A FGA A Stl TO Blk OR DR PF
Summers, DaJuan 28:09 - 1 13/46 4- 5 0- 1 5- 6 6/31 1/ 9 1/46 2/46 1/33 0/19 4/36 3
Wright, Chris 35:56 + 8 16/66 2- 3 3- 5 3- 8 8/45 4/16 1/62 1/63 0/42 0/27 5/44 1
Monroe, Greg 28:16 +15 14/56 6- 8 0- 0 2- 3 8/36 1/10 0/50 1/51 3/28 2/23 5/35 4
Freeman, Austin 33:00 + 5 7/56 0- 5 1- 5 4- 6 10/43 2/19 3/56 2/57 0/38 1/25 6/41 3
Sapp, Jessie 33:45 +14 13/61 2- 3 1- 4 6- 6 7/42 3/14 2/59 2/60 0/40 1/28 5/44 1
Mescheriakov, Nikita 03:54 + 5 0/ 7 0- 1 0- 0 0- 0 1/ 5 0/ 2 0/ 6 1/ 7 0/ 8 0/ 3 0/ 7 1
Clark, Jason 12:25 - 1 4/23 1- 1 0- 1 2- 2 2/13 0/ 3 1/23 0/23 0/13 1/10 2/14 1
Vaughn, Julian 10:23 - 6 2/15 1- 1 0- 1 0- 0 2/13 0/ 4 1/18 0/17 2/16 1/ 8 0/12 1
Sims, Henry 02:23 + 3 0/ 5 0- 0 0- 1 0- 0 1/ 4 0/ 2 0/ 4 0/ 4 0/ 1 0/ 3 0/ 2 0
Wattad, Omar 11:49 + 3 2/20 0- 0 0- 5 2- 2 5/18 0/ 5 0/21 2/22 0/16 0/14 2/15 1
TOTALS 40:00 71 16-27 5-23 24-33 50 11/21 9/69 11/70 6/47 7/31 30/50 16
. 0.593 0.217 0.727 0.524 0.130 0.157 0.128 0.226 0.600


Efficiency: Georgetown 1.014, Jacksonville 0.899
eFG%: Georgetown 0.470, Jacksonville 0.366
Substitutions: Georgetown 30, Jacksonville 50

2-pt Shot Selection:
Dunks: Georgetown 3-3, Jacksonville 0-0
Layups/Tips: Georgetown 11-16, Jacksonville 11-24
Jumpers: Georgetown 2-8, Jacksonville 9-23

Saturday, October 25, 2008

Big East Growth Charts

About this time last year, I posted about possession usage, based upon an article by Ken Pomeroy about effective usage. Possession usage, or possession percentage (%Poss) is yet another in a litany of stats that you'll find here and other site run by fans with a predilection towards numbers and too much time on their hands. It is simply the ratio of possessions that a player ends divided by total possessions played. A player can end a possession by:
  1. scoring
  2. turnover
  3. missing a shot that is rebounded by the defense.
On a team that was truly democratic (socialist?), everyone would have a %Poss = 20%, meaning that team possessions were used equally. In the real world, %Poss for Big East basketball players typically ranges from 10 to 30%, with a median value around 18%*. In other words, the majority of players choose to use less than number of possessions you'd expect.
*Edited to add: Where did this come from? See the end of the article.

Why? Simply, because someone else on the court is using possessions at a disproptionately higher rate. There are a few reasons why this could be (here comes another list):
  1. the coach has instructed the team to allow certain player(s) to use more possessions
  2. certain player(s) have decided on their own that they should use more possessions
  3. the player in question thinks other player(s) should use more possessions
Whatever the reason, the logic of the 18% player is sound so long as he is giving away those possessions to someone more efficient (i.e. with a higher Off. Rating) than his own. However, when a player has a very high Off. Rating (e.g. Darrel Owens, Colin Falls) but uses significantly less than his allotted 20% of possessions, he may by hurting his team. Of course, the counter-argument can be made that by using more possessions, he'd become less efficient, but there would still be some marginal returns until this player's efficiency is comparable to his teammates - and yes, I've just lapsed into economic theory.

Ken Pomeroy's - remember Ken? we started out by talking about him - thesis is "role players don't usually become go-to guys from one year to the next, or at any point during their careers."

To prove his point, he provided a couple of nice charts, showing the change in %Poss from one year to the next, or one year to two years later. I'll reproduce them here (as always, click any image to enlarge).


There are 4 types of fitted lines on these charts.
  • The thick black line represents the best fit of the data (all 2005, 2006 and 2007 college players, I think).
  • The thick dark blue lines indicate the 50% prediction interval around the fit - that is, 50% of all players should be between these two lines. Another way to think of the lines is that 25% of all players will fall below the lower line, and 75% of players will fall below the upper line (and therefore 25% of players will be above the upper line).
  • The thin black lines are 95% prediction intervals - only 2.5% of all players should fall below the bottom line, or lie above the upper line.
  • Finally, there is the dashed line, which the is the 1:1 line. A player lying on this line would have no change in his %Poss from year 1 to year 2 (or 3).
There's actually a bit more information we can glean from these plots. For example, you'll notice that the 1:1 line is below the best fit line until %Poss ≈ 22.5% for year 2 vs. year 1. What this means is that, for players who used less than 22.5% of their possessions in a given year, more will increase their usage the following season than not. For the year 3 vs. year 1 plot, this point of intersection is ~23% - very similar.

This is not to say that all players will eventually become 22.5% possession users, but rather that this is the point where increasing possession usage becomes more difficult than not, likely due to increased competition with teammates for available possessions.


So, is there a point to all of this?

Since KenPom has %Poss data available back to 2005, I decided to plot all Big East players from the last 3 seasons (or 2 seasons) on his charts, to see if the Big East behaves as the rest of college basketball with respect to changes in usage.

Here's season 2 vs. season 1 (you'll need to click to expand to see things clearly):



A bit of explanation is in order (if there's one thing I want to be famous for, it's busy charts).
  • I've sized the markers by Season 1 %Min (% of available minutes played), so that end-of-bench players wouldn't swamp regular players on the scatter plot.
  • I've color-coded the markers by Season 2 Off. Rating. When I initially ran this analysis, I expected that the rate of increase from year 1 to year 2 would be strongly related to how well the player performed in the 2nd year, but this is obviously not the case - the color appears random.
  • I've also color-coded Georgetown players as gray rather than on the color scale, so they'd stand out. Nothing of exception with this group.
  • I've added tags identifying a few outliers.
  • Finally, I've added a horizontal and vertical line at 22.5%, indicating the point where more possessions become scarce.
The analysis by KenPom seems to apply very well to the Big East - the data almost entirely within the 95% prediction interval, and follows the trend line.

What's of most interest to me are the two points in the upper left quadrant: James Holmes and Draelon Burns. These two players represent the exception to KenPom's rule, in that they made the leap from role players (%Poss = 18.7 & 19.5, respectively) to go-to players (27.5 & 28.4) in a year. Since I wasn't paying much attention to either team at the time (or now), I'll leave it to someone else to explain what happened in each case.


On to the two-year gap (season 3 vs. season 1):



Many fewer data points here (n=80 here; n=274 for the previous plot), but again the analysis by KenPom seems appropriate for the Big East.

The players of interest here include Daryll Hill, who fell from go-to to role player due to injuries, and three rising seniors: Anthony Mason, Levance Fields, and Georgetown's own Jessie Sapp. Only Mason has made the leap into true got-to status (17.1 to 23.0 to 26.9), but Jessie Sapp has made an extraordinary rise from pass-only to important cog (12.2 to 18.7 to 22.6). It will be interesting to watch these three to see if they can continue to absorb possessions.

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Edited 10-27-08, 10:00pm to add:

While playing with the data, one thing I did look at was the distribution of %Poss for Big East players. Here are the histograms for all players (n=611) from 2005-2008, and also for those with %Min > 40% (n=395). What's interesting is that majority of players who play less than 40% of available minutes also use less than 18% of available possessions (note that KenPom has his own filter of %Min > 10% on the data, so players with very little playing time [< 4 min / game] are already dropped from the data set).



I suspect that the subset of players with 10% < %Min < 40% group has a significant number of freshmen who are slowly being introduced to their coach's respective systems. I used the median value of the entire population in the discussion above, since many starters began their career in this role as bench / role players (e.g. Jessie Sapp).

I hadn't thought to plot %Poss vs. %Min before tonight, but the histograms above imply a relationship. Here it is:



The data points are both colored and sized by offensive rating, but there doesn't seem to be much trend in that variable. The slope of the line is ~0.085; in other words, an increase in %Min by 23% will increase %Poss by 2%, on average.

You've got to love D. Caracter's freshman season at Louisville.

Saturday, October 18, 2008

Individual Offensive & Defensive Ratings - 2007-8 Review

General comment about the edits - I realized soon after originally posting this article that the underlying numbers just didn't look right. Sure enough, I tracked down at least 2 mistakes in my math. I think I've got everything correct now, but I make no warranty. I reserve the right to continue to make mistakes, but I will do my best to avoid them.


Before I get started, I just want to point out that the player +/- stats page has been updated, and now includes all available games for the last 2 seasons.

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In my last few posts, I've be touting my new HD Box Score MakerTM, which uses game play-by-play data to extract a lot more info than a standard box score yields (all available HD boxes for the last 2 seasons now posted).

In my never-ending quest to keep you, my only reader, ahead of the curve when it comes to basketball knowledge, I thought I'd start a series of posts using the data generated by my HD Box Score MakerTM to learn a bit more about your Georgetown Hoyas.

To start, I thought I'd try to take on one of the questions that I raised at the end of my intro post to HD box scores:
2. Was J. Rivers really that great of a defender? I'll look at the team's offensive and defensive efficiencies with each player on or off the court, to see if I can learn a bit more about the defensive side of things.

Analogous to fielding defense in baseball, individual defense in basketball is not well-described by traditional basketball statistics. We can talk about team defensive stats (Def. Efficiency, DReb %, Def 2FG%, Def eFG%, Block %, etc.) with some confidence that we are able to describe what is actually taking place on the court, but the difficulty comes in attributing the individual defensive stops, rather than just taking a holistic view.

There are a few ways to tackle this problem:
  • Watch each game, and chart each defensive possession for who was responsible for stopping (or allowing) the defense from a score. This has been advocated by Dean Oliver, the father (mid-wife?) of advanced basketball statistics - but, as far as I know, simply isn't available for college basketball games.
  • Use the available box score data to estimate the number of stops each player makes, based on some rather large assumptions; one example of this metric is called Defensive Rating (also developed by Dean Oliver). This is similar to his Offensive Rating for individual players, which I, Ken Pomeroy and many others calculate, but uses less certain assumptions. Currently, I'm only aware of Henry Sugar at Cracked Sidewalks reporting Def. Ratings (example linked), although I'm sure there are others. I'll talk more about this stat below.
  • Use the available play-by-play data to estimate the importance of each player to total team defense. Your first thought might be that we could use the play-by-play data to determine actual defensive stops by player, but we can't. The play-by-play doesn't tell us who is guarding whom, so we'd be back to the same assumptions that Dean Oliver uses. However, there is a simple analytical tool that we now have available to us: we now know how many points each team scored when any player was on (or off) the court. That is to say, we can calculate a team's offensive and defensive efficiency (points per 100 possessions) as a function of whether any player is on the court, and thereby look at what impact each player has on team offensive or defense.

At this point, I will explain some basic terms as a refresher, and also cover what's new here. All of this is explained in much more detail at the web pages linked to the right under "Tempo-Free Stats 101." Feel free to skip ahead if this is all familiar.

Possession-based (tempo-free) statistics is a concept in basketball going back at least as far as Frank McGuire, and is useful for comparing players and teams who operate at different paces, or speeds of play. A possession ends either by a made basket (including some made FTs), a turnover or a defensive rebound - that's it, that's the list. Offensive rebounds don't create new possessions, only prolong the current one. If you use this definition, two teams will end up with either the same number (± 1) of possessions at the end of any game; since possessions go back-and-forth, it must be so. The equation for estimating total possessions per team per game is floating in various forms around the internet, but I will add to the clutter:

Possessions = FGA + 0.44 * FTA - OReb + TO

Since this formula is only an estimate of the actual number of possessions, I find that it is best to solve for each team, then take the average. Any team's (or player's) stats should be instantly comparable to any other with a per-possession system, since what is expressed is team (or player) efficiency rather than counting stats.

Offensive (and defensive) efficiency is a team statistic expressed in the units of points per 100 possessions (why per 100 possessions? so there aren't so many digits to the right of the decimal). This statistic is rather simple to calculate, once you've worked out how many possessions have been played with the equation above. Ken Pomeroy, one the populists of tempo-free stats, has an additional version of this stat, called adjusted off. (or def.) efficiency. Here, he attempts to weight points per possession based upon quality of opposition.

Offensive rating (as mentioned above) was created by Dean Oliver in an attempt to better rate individual basketball players on offense. The calculation of this stat is not simple - I've had people ask me in the past for the equation, but it's actually a bunch of equations (see this book for details). In simple terms, it is the ratio of points produced (not scored) by any player, divided by possessions used (not played), with both of these terms estimated from normal box score data. It is a tempo-free statistic, since it is expressed in points per (100) possession. Since players should be credited for assists and offensive rebounds as well as actual points scored, this rating is just an estimate of actual player worth, but the underlying assumptions are well thought out (you'll have to trust me, or read the book).

Defensive rating is an attempt to estimate the contribution of each player to the team's defensive efficiency. It is calculated as team defensive efficiency, plus one-fifth of the difference between team defensive efficiency and individual player stops per 100 possessions played. Player individual stops are estimated from the number of blocks, steals and defensive rebounds each player has, plus some team stats. Since it is not a simple ratio, it is more like being graded on a curve, such as that it is limited to the range of 80% - 120% of team defensive efficiency. So, a player who literally refused to play defense (e.g. Donte Greene) could score no worse than 80% of his team's efficiency. I would describe this stat as a very rough estimate of actual defensive worth . . .

. . . which leads me back to the point of this post (there really is a point). Now that I have access to the play-by-play of most G'town games, can I use this to better estimate the defensive contribution of each player, on a possession-basis? If so, we could finally talk about the overall value of a player to his team, rather than just his offensive contribution. The play-by-play shows who was on the court at any point during the game, so we can assign partial credit to each player for how well the team plays at both ends while he's in the game; likewise, we can see if the team plays better or worse when he leaves. This is really just applying the concept of plus-minus and Net/40 (or Roland rate), but rather using possession info to speak in tempo-free terms, rather than per-minute.

To explain explicitly here, I've taken each player, and added up the points that G'town scored and allowed while he was on the court. and how many were scored and allowed when he was off the court. In each case, I also know how many offensive or defensive possessions he participated in, so I can divide each point total by respective possessions (times 100) to find the team's offensive of defensive efficiency while he was on or off the court. Then, I find the difference between on- and off-court efficiency (either off. or def.) and add that to the team's efficiency.

For example, to calculate Jessie Sapp's Net Offensive Efficiency:

Jessie Sapp played 1171 offensive possessions, and the Hoyas scored 1298 points while he was on the court.
[1298 / 1171 x 100 = 110.8 Off. Eff. on-court]

He sat for 561 offensive possessions, and the Hoyas scored 585 points while he sat.
[585 / 561 x 100 = 104.3 Off. Eff. off-court]

So Jessie Sapp's Net Off. Eff. is equal to:
(Off. Eff. on-court - Off. Eff. off-court) + Team Off. Eff. =
(110.8 - 104.3) + 108.7 = +6.5 + 108.7 = 115.2 pts/100 possessions


Before I jump into the defensive analysis, I first want to see if my idea that player-based on-court / off-court net efficiency correlates to individual player rating holds water. To do this, I'll take a look at each player's net offensive efficiency versus individual offensive rating for last season.

One last point before I go on, the individual player ratings here won't match exactly with what either Pomeroy or I post for season totals. Since I don't have play-by-play data for all games, I re-ran the player ratings using box score data only for games that also had p-b-p data [to see which games are missing, go to the player +/- page].

Let's take a look (as always, click any image to enlarge):




This seems to work quite well! Players in the upper right of the graph are the best offensive players by either metric, while players in the lower left are not carrying their weight. The red line is a linear fit to all the data (r = 0.81), excluding Bryon Janson, who just doesn't have enough playing time to generate meaningful stats. The slope of the line is about 0.55, significantly less than 1, which is actually to be expected. The Net Team Efficiency stat doesn't completely isolate a player from his teammates in the way that Off. Rating attempts to do; since there is variability player-to-player, the range of the Net. Team Eff. stat gets compressed - a bad offensive player surrounded by good players will look better than he is.

The strong correlation indicates that the two statistics are highly coupled (co-variant). Individual offensive rating is a fairly well-accepted statistic, and it seems to do a good job of measuring how important a player is to team efficiency. Of course, the converse should also be true - team offensive efficiency as a function of each player on or off the court is a good measure of individual offensive value.

Moreover, and here's where I may be stretching the statistics a bit, the scatter plot can tell us a bit more: if a player is above the line, he makes the team more efficient than expected based upon Off. Rating (i.e. the player is underrated by Oliver/Pomeroy/etc.) while if he is below the line, he is overrated. Keep in mind that there are considerable uncertainties for the data on both axes that are not shown or even calculated, because that would make my life a lot harder. But it looks like Jessie Sapp and Roy Hibbert were underrated offensively last season, while Patrick Ewing Jr. and Vernon Macklin were overrated.


Now, let's now take a look at the defensive side. The math as the same as presented above, just looking at defensive possessions now.




Things here are not so clear-cut as for offense. There is poor correlation between the two data sets (r = 0.11), so I've just thrown a 1:1 line onto the chart. Note that both axes have their scaling reversed (they get smaller as you head away from the origin), since a lower defensive rating or efficiency is better. Again, players in the upper right corner are the best defenders, those in the lower left are the worst.

One thing that I notice immediately is that the scaling for the two statistics is much closer to 1:1 than for offense. We already expect that Net Def. Rating should be compressed since we can't isolate individual players, only their effect on the team while on the court. But here, the Def. Rating stat shows about the same scaling meaning either a) there isn't as large a difference between a good and bad defensive player as there is for an offensive player, or b) the Def. Rating stat isn't able to isolate individual defensive skills.

To take this a bit further, we demonstrated above that the Net. Efficiency methodology for offense seems to work quite well in correlating to a "good" measure of offensive prowess, albeit on a somewhat compressed scale. Since the method is identical for defense and offense, there's no reason to expect Net Efficiency to stop working for defense. Therefore, it could be argued (I just did) that Net. Def. Eff. is a better measure than Def. Rating.

If you've not read Basketball on Paper, you should probably just skip over the next paragraph.

Digression: Before I go on, I should point out that I'm using a slightly modified version of D. Oliver's Defensive Rating calculation. His formula estimates defensive stops in two parts, and the second has a necessary assumption that he, himself, acknowledges to be poor with regards to position-specific uncredited stops. Since centers get a disproportionate number of stops by way of blocks, they tend to be overweighted by his formula (for reasons far too obscure to explain here). I've added a simple weighting factor, based on Steals/(Steals+Blocks) to correct this. For this data set, the effect of this correction ranges from -2.7% for Roy Hibbert to +2.3% for Jonathan Wallace and Chris Wright. (n.b. - The weighting factor is based on Oliver's own data).

Returning to the scatter plot, once again we can find over- and underrated players by using the fitted line.

Now, Tyler Crawford and Chris Wright are the most overrated defenders, while Jonathan Wallace (!), Roy Hibbert and Jessie Sapp are underrated. Of course, that only looks at the comparison between two poorly correlated stats; the real take-home message is that Hibbert, Sapp, DaJuan Summers and Patrick Ewing anchored last year's excellent defense, just as Hibbert, Wallace and Austin Freeman were the most effective on offense.

And to answer the question that started this whole thing - yes, Rivers was a good defender, but not extraordinarily so, and not as important as Hibbert, Ewing or Summers. In fact his stats are not obviously better than either Sapp's or Wallace's(!). I will speculate that Rivers was the best on-ball defender as a guard, but Wallace and Sapp were more sound within the defensive schemes used last year (I just made that up). And I'm not sure why Omar Wattad looks like Gene Smith on this plot, but I'll guess it's just the result of a small sample size (n = 58 def. possessions).


Finally, we can combine the offensive and defensive metrics on a single plot, to get a rank of the overall value of each player. Here, I'm simply taking the average of Off. Rating & Net. Off. Eff. for the y-axis, and the average of Def. Rating & Net. Def. Eff. for the x-axis. Here, I'm hoping that the averages of two measures of the same variable come closer to describing its true character than either measure on its own.





This plot is a bit more complicated, as I'm trying to convey a lot of information.

Again, you'll need to re-jigger yourself to the axes. Offense is on the left-axis, with up equaling better performance; defense is on the bottom axis, but still with reversed scaling, so that right equals better performance. Players in the upper right are most valuable, players in the lower left are least valuable; those closer to the upper left have more value on offense, those down and to the right have more value on defense. This last bit looks to be well correlated with expectation, as the two players best know for offense rather than defense (Wallace & Freeman) show up right about where you'd think.

The size of the names are now scaled by possessions played, so Omar Wattad's newly-discovered value as an all-world defender is now tempered by the fact that he rarely plays. DaJuan Summers somewhat swallows up Patrick Ewing because of this, but I think you can still make them out.

Finally, the series of diagonal lines (isopleths) on the chart mark show contours of total player value (i.e. the difference between off. and defensive worth). For example, Jessie Sapp's off. worth = 108.9 and his def. worth = 89.8, so you'd expect that he'd provide +19.1 (= 108.9 - 89.8) pts./100 poss. to the team. Meanwhile, Austin Freeman's off. worth = 115.4 and his def. worth = 95.8, so you'd expect that he'd provide +19.6 pts./100 poss. That is, Sapp and Freeman were essential equally valuable to last year's team on a per possession basis, although they did it in different ways. Because they are rated at equal value, they both lie on about the same position relative to the diagonal lines.

Moreover, if you had a team of players all equally efficient overall as Sapp and Freeman, you'd expect the overall difference in team Off. Eff. and Def. Eff. to be around +19 pts/100 poss. FWIW, last year, G'town's efficiency difference was +18.8 (raw, not adjusted), good enough for a #2 seed in the NCAA tournament.

Here's a summary table of off., def. and total player worth for all the players:
                      Off.      Def.    Total
Hibbert, Roy 122.3 90.2 32.1
Wallace, Jonathan 118.7 94.0 24.7
Freeman, Austin 115.4 95.8 19.6
Sapp, Jessie 108.9 89.8 19.1
Ewing, Patrick 106.1 90.5 15.6
Summers, DaJuan 105.6 90.6 15.0
Wattad, Omar 103.3 88.3 14.9
Wright, Chris 100.8 93.2 7.6
Crawford, Tyler 95.6 95.4 0.1
Rivers, Jeremiah 90.1 94.4 -4.3
Macklin, Vernon 94.4 100.0 -5.6

We will miss Roy Hibbert. On a team that was ranked 7th by Ken Pomeroy after the NCAA tournament, Mr. Hibbert was the best Hoya player on the court by a large margin.

Next comes the gang of five (+1), who were the other important contributors to the Hoya's success; in very rough order of importance: Wallace, then Freeman and Sapp, then Summers and Ewing. Wattad sneaks in right behind this group, despite his few possessions (who knows, maybe the whole point of this article was to find a new player to champion; after all, the last time went so well).

By my reckoning, the two soon-to-be-transfers were not helping much last season. In the end, Rivers' defense just couldn't make up for his offensive woes, while Macklin struggled at both ends of the court. I never gave much thought to Macklin's defense, but he was easily the worst defender on the team by my numbers. Does that seem right? Tyler Crawford struggled with his outside shooting last year (3-22 3FGs), and wasn't able to make up for it with great defense.

There's one returning player that I haven't mentioned - Chris Wright. He missed the majority of the season with a foot injury, and ended up with a little more than half of Macklin's total time played. After struggling early in the season, he seemed to have a breakthrough in the 2nd half against Derrick Rose and Memphis, only to go down 2 games later. And while he played in 5 post-season games after getting healthy (3 in the BET, 2 in the NCAA), I only have the Pitt game in the BET finals in this analysis, since I don't have p-b-p for the other 4 games. From looking at the box scores, 3 of the 4 games I'm missing (Villanova, UMBC, Davidson) were among his best.

What I'm saying is that I think Wright is being undervalued here, not because there's anything wrong with the analysis, but because his underlying data doesn't do him justice. I hope I'm right.