Thursday, October 29, 2009

Season Preview: Jason Clark

By some metrics, Jason Clark was the Hoyas’ best offensive player in conference play last year.

He led the team in eFG% [= (FGM + .5*3PM)/FGA] in conference play and was second only to Greg Monroe in TS% [= Pts/(2*[FGA + (.44*FTA)])]. He was the team’s best 3-point shooter. He was the team’s best rebounder from the guard spot, and again only Monroe was truly a better rebounder.

Of course, Clark wasn’t the Hoyas’ best offensive player. Actually, he really wasn't all that close to the top, probably sliding in at #5 spot in a short rotation. The reason was simple: turnovers.

As noted above, Clark was great at putting the ball in the hoop when he actually got a shot off.

The problem is that nearly 30% of the time Clark ended a Hoya possession, he never took a shot - he was turning the ball over. Every time Clark shoots the ball, the Hoyas score an average of 1.4 points, which is fantastic. But once you factor in the turnovers, Clark was a sub-par offensive player.

Clark is an extreme, but he’s no more an extreme on the Hoyas than the Hoyas are in college basketball. Since Thompson has been at Georgetown, the team has generally been very efficient at scoring when they actually shoot, and fairly poor at taking care of the ball:

Conference Play       
Year TO Rate Rank TO/game TS% Rank Off. Eff.
2004-05 22 11 13.8 56 2 105
2005-06 19 9 11.5 56 3 110
2006-07 22 14 13.4 60 1 115
2007-08 21 14 13.5 58 3 110
2008-09 23 14 15.0 54 7 101

This is not a surprise, of course.

The Hoyas work the shot clock, looking for a high percentage opportunity. Those extra passes and dribbles mean extra chances for turnovers. There are a significant number of attempts at backdoors and other cuts; those types of plays often result in either an extraordinarily high percentage shot - a layup or dunk - or a turnover. Additionally, the offense requires that all players handle and pass; there’s no doubt that some players are more turnover-prone than others (we're also looking at you, Mr. Vaughn). In other offenses the coaches may find a way to shield those players from having the ball too often.

The benefit to Georgetown’s approach, of course, is better shot selection than most teams. When working effectively, it generates a tremendous amount of easy shots and uncontested lay-ups. There are few ill-advised or forced shots.

In general, the Hoyas’ excellent True Shooting % has overcome the team’s difficulty with turnovers. But last year, two things happened on this front. The team did not make as many shots (and from my observation, did not get nearly as many easy shots). And the turnover rate increased as well as pace, leading to an increase of almost 1.5 turnovers per game.

This may not seem like much. But given the Hoyas’ efficiency at scoring, the benefit gained from reducing turnovers is more significant than most. Lowering the team turnover rate to 20% from 23% would yield an extra two offensive shot attempts per game, not including any put-backs. Provided that the team would take those extra shots at their normal accuracy, that yields an extra 2.5-3.0 ppg. Given the number of careless and stupid turnovers observed (painfully), there is no reason to think that a reduction of turnovers by one to two a game could only come at the expense of the team taking worse shots.

Georgetown was outscored in conference play 66 to 67 - 1 point! Would their record have been 7-11 if the average score was 69-67 instead? Looking at it another way, the Hoyas lost three games by three points or less: Cincinnati, at Syracuse and at St. John’s. With those extra points, that’s a 10-8 record and an NCAA bid without improving upon any other aspect of their game.

With Jessie Sapp graduated and Vee Sanford a freshman, more ball handling opportunities will fall to Clark this year. He was on the floor for just 44% of conference minutes last year and used only 18% of possessions once there. Both of those are likely to increase.

That means even more focus upon Clark’s ball-handling and decision-making than last year.

Another year of struggling to hold onto the ball, and much of the Hoyas’ season could replay like the Duke game, when Clark’s otherwise fine play was marred by a disastrous turnover when filling in at point for Chris Wright. But if Clark can solve his turnover problem, he may be one of the most efficient guards in the Big East. If the Hoyas as a whole can solve their turnover problem, they will return to being one of the best offenses in the country.

Sunday, October 25, 2009

Season Preview: Austin Freeman

Edited: [10-26, 10pm] Crap. Well, apparently it's preseason for the bloggers, too.

I had a typo in one of my spreadsheet formulas, which was screwing up the possession usage data in the Georgetown players' skill curves. I've corrected the figures and accompanying text - the story has changed a bit now, especially as it relates to Austin Freeman and the other returning players, so if you've already read this article, you might want to re-read the last section.


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For better or for worse, the media, the fans and even the Georgetown Athletic Department have embraced the notion that this season's Hoya team will be led by it's three McDonald's All-Americans: Greg Monroe (soph), Chris Wright (junior) and Austin Freeman (junior).

These are the only three returning players that we credit with positive net points (created more points than they allowed) from last season, so it seems natural that they would become the core of the team.

A trio of players leading the team is not new. During the JTIII era, there have been typically three players who use ≥22% of available possessions each season. If all players shared the ball equally, we'd expect a possession usage of 20%, so in effect the offense is usually dominated by three guys.
.       Player         %Poss    %Min    ORat
2004-5  Bowman          24.2    82.7    112.4
.       Green           23.8    84.0    111.5
.       Hibbert         25.3    39.3     89.2
.       Cook            20.3    80.1    102.3

2005-6  Green           25.4    80.7    102.7
.       Hibbert         25.6    59.6    120.9
.       Bowman          24.6    70.7    101.0
.       Cook            18.1    76.8    113.0

2006-7  Green           24.9    83.0    114.4
.       Hibbert         22.8    65.7    130.8
.       Summers         22.0    65.7    101.8
.       Wallace         18.9    80.2    119.7

2007-8  Hibbert         25.9    66.0    120.5
.       Summers         23.8    67.5    104.0
.       Sapp            22.7    66.4    105.5
.       Wright          21.9    42.4     97.7*
.       Freeman         18.1    63.9    115.9

2008-9  Summers         24.4    72.0    104.0
.       Monroe          22.9    76.0    110.9
.       Wright          21.3    81.5    107.2
.       Freeman         19.4    74.3    115.6

*Wright missed 18 games his freshman year, so his usage stats aren't easily compared to his teammates.

Usually, the next man in line for possessions is much more efficient offensively than at least one of his more aggressive teammates. Last season the "next man in line" was more efficient than all three players who were ahead of him.

That man was Austin Freeman. It's also worth noting that he was able to keep a high offensive rating despite having his 3FG shooting accuracy drop from 40% to 31% from his freshman to sophomore season. One could reasonably hope that he will be even more proficient this year.

There are two fundamental hurdles that he - and any player looking to step into a bigger role - must overcome. We'll call them inertia and marginalism. Each of these concepts is fundamental to a pair of questions we'll ask about Austin Freeman coming into this season:
  1. Can Austin Freeman increase the rate at which he uses possessions, to become a go-to offensive player rather than just a complementary one?
  2. Will there be a cost in his offensive efficiency if he does use more possessions?

Inertia

A couple of years ago, Ken Pomeroy posted an article on Basketball Prospectus noting that
[o]nce a player demonstrates himself to be a role player, it's unlikely he'll ever be a go-to guy and, therefore, a superstar. It's not quite a law in college basketball, but players who are not very involved in the offense tend to stay that way. Any major changes in a player's usage are usually the result of filling the hole left by a departing possession eater.
I found this point compelling, so much so that I wrote about this each of the past two pre-seasons, and here I am doing it again.

As an aside, an important point to keep in mind during this discussion is that we are discussing usage rate (a percentage), not possessions used (a counting stat). As players receive more minutes of playing time, their counting stats will naturally increase. But here we are concerned with how their rate statistics change, which should better indicate a change in behavior or ability.

Greg Monroe and Chris Wright appear naturally predisposed toward using possessions - Wright has used ~22% of available possessions each of the first two seasons, and Monroe was using more than 23% last year. This was a good thing last season, as both were more efficient than the team overall, especially when looking at performance versus Top 100 opponents. In fact, they were the second and third best option on offense in those games. The most efficient offensive player, whether you look at vs. Top 100 teams, conference games or even all games, was Austin Freeman.

Can we expect that Freeman will use significantly more possessions this year? First, let's see if we learned anything from his freshman to sophomore growth.

From the table above, we see that the Hoyas went into last year with only one possession-eater lost (Hibbert) and three returning (Summers, Sapp and Wright). So possessions were available, but there wasn't a wholesale change at the top.

To understand the year-to-year change in possession usage a typical Big East player experiences, we can take a look at all Big East players from 2005-2008 and fit a line through their possession usage rates from one year to the next. I've attached a figure from last year's article - you'll need to go back and read that post to understand all of what's going on in it, but for now all we care about is the solid black line that is fitted to the circles (click on the figure to enlarge).




The typical Big East player will increase his usage from one year to the next, so long as he used less than 22% of possessions in the previous year. Players who used more than 22% of possessions the previous season tend to use less. Moreover, we can use that fitted black line to actually estimate how many more possessions a player would be expected to use the next season.

Austin Freeman went into last season having used 18.1% of possessions as a freshman. Based on historical Big East growth rates, we expected him - on average - to use 18.9% of possessions as a sophomore. He actually exceeded that by a bit (19.4%). So it looks like Freeman is fairly well-described by our little model, or perhaps we're being a bit conservative.

This season, the Hoyas again have lost one possession eater (Summers) and return two (Wright and Monroe), so we'd expect about the same change or increase in usage from the returning players.

If we apply the model towards next season, we'd only expect Freeman to use 20.0% of available possessions, which would frankly be a bit disappointing in light of his offensive ability. Let's take this a bit further. Because we are über-geeks here, we can actually predict what his usage rates would be under favorable (75th percentile) and extraordinary (95th percentile) conditions, just as Pomeroy did.
.                       Year 2
Year 1: 19.5%         Expectation
.  Average               20.0
75th percentile          22.0
95th percentile          25.5
Assuming the model is good for Freeman, an increased usage to the magical 22% rate - both the seeming natural usage rate for players and the top tier for players in the Georgetown offense - has about a 1 in 4 chance of happening this season. It's tempting to say that he'll likely take more than 20% of possessions, since he used more than predicted last year (or to say that there is better than a 1 in 4 chance he'll get to 22%), but I'm a bit hesitant to draw this conclusion from one data point (his change from freshman to sophomore year).


Marginalism

Throughout the above discussion, we were only concerned with the percentage of possessions Austin Freeman might use this year, with the hope that he might increase his usage rate more than expected. The assumption is that a sharp increase in possession usage by Freeman would help the team because he is the team's most efficient scorer. Taking some of Summers' and Sapp's possessions and scoring on them at Freeman's rate will help the offense.

But if Freeman takes more possessions and shots, would he remain as efficient a scorer? As a player takes more and more possessions from his teammates, does his efficiency decrease, and by how much?

The law of marginal utility (i.e. "diminishing returns") should be familiar to anyone who's had to suffer through an economics class. Simply, as a resource is increasingly available or used, the utility of each quanta of the resource decreases. In plainer English, the more abundant an item, the less its value. Think crop prices, or water rates.

To my best knowledge, this idea of marginal return was first applied to basketball by Dean Oliver, who wondered if players were more offensively efficient when they used fewer possessions. He discusses this in his book Basketball on Paper, and, to this end, he looked at three NBA players: Jerry Stackhouse, Michael Jordan and Georgetown's very own Allen Iverson via what he calls "skill curves" (I've reproduced his plot here):




To my way of thinking, he's got the axes backwards (usage rate is the independent variable and therefore should be on the X-axis) but the conclusions from the data are still clear. I'll flip the axes to make my point, though (and ignore that red line for a moment):



As players increase their usage - the percentage of possessions they use - they become less efficient.

However, it's not a smooth curve, but rather a sigmoidal fit (an S-curve), so that there is a big jump between efficient usage and inefficient usage. That notch varies from player to player, and Jordan's greatness shows up by where his notch is: he can produce a 120 offensive rating (1.2 pts. per poss. used) even while using more than 30% of available possessions.

There is a common criticism of Oliver's work, summarized recently by Kevin Pelton over at Basketball Prospectus:
Most past efforts [to understand efficiency vs. usage in the NBA] were tripped up by the problem of looking at usage on a game-by-game basis. Naturally, players will use more possessions on nights where they have a more favorable matchup, so it is not surprising that these studies actually found that players' efficiency rose as their usage increased.
More recently, Eli Witus expanded greatly upon this pioneering work by comparing high-usage and low-usage lineups for the 2007-8 NBA season, to find a relationship between player usage rates and efficiency without the confounding effect described by Pelton. I won't go into much detail here - the article may be a bit advanced for non-geeks - but the upshot was that he found that, if a player increases his usage rate by 1%, his efficiency will decrease by 1.25 points. This result is that red line added to the graph above. While it doesn't apply to Jordan, this new analysis actually shows good agreement with Oliver's work with "normal" NBA superstars.


This is all well and good, but is this information applicable to Austin Freeman, or the Hoyas more generally?

To find out, I compiled efficiency vs. usage stats for the past three seasons for Georgetown, much like Oliver did. I don't have the energy, and probably not the skills either, to redo Witus' work. Here, I simply compiled offensive rating vs. poss. usage rate for each player in each game, using my HD Box Score program, which should be more accurate than using the traditional box score calculations.

The data tends to be quite a bit more noisy than Oliver's plots, mainly because there aren't nearly as many games to sort through. Oliver looked at 2 NBA seasons (164 games), while I have data for 88 Georgetown games over the last three years. I've also used relatively narrow "bins" or ranges of possession usage to average - I'm using increments of 2.5% (e.g. averaging games with 15% - 17.5% poss. used). I've done this so each player's skill curve will have at least 8 points. I've included standard deviations for each bin to help indicate that noise - a point with no error bars is from a single game.

We'll start with Roy Hibbert and Jon Wallace, combining their junior and senior seasons. Here, Witus' expected decline rate is now indicated by the dashed gray line.



We don't see the notch - the big and sudden drop in efficiency at high usage rates - but there also aren't the extremely high usage rates that the NBA stars can reach. What we do see is that the decline looks very different for the two players.

Hibbert - a high usage player - was incredibly efficient at virtually every usage rate (and I have no idea why he has that drop when he used less than 10%), good for about a 130 Off. rating when using between 12% and 33% of possessions. His efficiency finally starts to drop at extremely high usage rates (>35%), but even this part of the curve is being drive by a single game (against Michigan, Nov. 2007).

Wallace - a low usage player - has a very different skill curve. There's a lot more noise in his data, which I believe is attributable to his high dependence on 3pt shooting. He also suffered from a much steeper drop in efficiency as he used a higher percentage of possessions. If we fit a line to his curve (not shown) we'd see that his expected offensive rating drops below 100 around 25% of possessions used. And since he was surrounded by other skilled offensive players, it makes intuitive sense that we'd not want him to use much more that 20% of possessions, which was his natural behavior.


Next up are Sapp and Summers, for whom I have the last three seasons. I've left the Witus line at the same location as for the Hibbert/Wallace plot, to allow for easy comparison.




While Summers was a forward and Sapp a guard, the slopes of their efficiency curves are quite similar. They both shot about half of their shots from outside (Sapp: 428/811 3FGA/FGA = 52.8%, Summers: 411/838 = 49%) at about equal proficiency (Sapp: 34.5% 3FG, Summers: 35.1%) over their careers, so this may not be entirely surprising. Once again, we see no notch in their curves, but a decline in efficiency at increasing usage not as steep as for Wallace. Sapp, especially, showed a steady drop paralleling the Witus line, although he seems to have an upward notch at the 25% usage rate. I wonder if this is the effect Pelton discussed; Sapp - who I think was always under-appreciated for his basketball sense - may have been more adept at recognizing and exploiting a favorable matchup.

At even moderate usage (>15%), neither player showed an area of high efficiency (>120 off. rating), but Summers did post some very high off. ratings at the lowest usage bins (although those were highly variable). This is not to say that these were poor offensive players - a 120 off. rating is very good - but neither looked to be a consistently great offensive player, even when not required to carry the load.


Now that we've got some context, let's take a look at how Austin Freeman has performed over the last two seasons.



Freeman's curve is a bit harder to make sense of, as he's got that big drop in efficiency when using 17.5-20% of possessions. In a bit of a statistical fluke, most (7 of 9) of the games that make up this bin are from his freshman year, and that dip seems to be due to his freshman games (his two sophomore games in the bin are amongst the three best of the bin). More on year-to-year improvement below.

Ignoring that dip, we see that Freeman can be an elite offensive player when he's using less than ~22% of possessions, operating at the level of Hibbert and Wallace rather than Summers and Sapp. Also, it's apparent that Freeman does not do well when he takes on a higher load - above 22% of possessions used his off. rating drops below 100, i.e. to a mediocre level.

So here we are faced with a conundrum - Freeman has been anointed to be one of the big 3 players for the Hoyas this season, but his offensive game suffers greatly when he steps into the high usage (>22%) role.

I'll now add Wright and Monroe to Freeman's graph:



As you can see, Monroe also has the drop in his skill curve, although his looks to drop below a 100 off. rating somewhere around 27% of possessions used.

Chris Wright's curve is a complete mess. That huge drop at low usage rate is the average of two games against Pitt, including the 2008 BET when he put up 0 points created in 30 possessions played. But even ignoring that point, his skill curve just doesn't seem to obey the rules of efficiency vs. usage. I don't know if this is a result of the 18 games he missed during his freshman year or his inconsistent outside shooting, but I'll refrain from further comment until we get another season to add to the database.


Am I underselling Freeman's potential for this year?

There is one critical point that I've been ignoring here: year-to-year improvement. Unlike Oliver and Witus, we aren't discussing mature NBA players, but college kids who are still developing their skill sets and learning a complicated offensive scheme.

To address this, I've come up with a simplistic plot. I've taken all Big East players for the 2005-2008 seasons who played at least 10% of available minutes, and found the difference between their current and previous year's poss. usage and off. rating. For example, looking at Austin Freeman:
Season Poss % ORat 2007-8 18.1 115.9 2008-9 19.4 115.6 Diff. +1.3 -0.3
I've compiled all available player-seasons (n=274) in this graph:



The markers are color-coded by Year-2 offensive rating and sized by Year-2 percent minutes played. The fitted line (with the fit weighted by % min) is the black line, with the 75% and 95% prediction bands in blue and gray, respectively.

The evidence is not promising. That line has a negative slope, just as Witus saw for NBA players. Ours has a gentler slope, but still shows that a 1 percent increase in possession usage from one season to the next will cost an average Big East player about 0.78 points in off. rating.

All I can offer is that the correlation is extremely weak: the 1σ uncertainty of that slope is 0.73, which is to say that it is just barely significant. To put it another way, of the 274 player-seasons we're looking at here, 80 showed an improvement in offensive rating while increasing possession usage. Or take a look at Chris Wright, who improved his offensive rating 9.5 points (97.7 to 107.2) with a drop of only 0.6 points in usage (21.9 to 21.3).

Could inherent talent (using, e.g. RSCI ranking as a metric) help some players to improve offensively in spite of increased usage? That study will have to wait for another day.

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.