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Chris Fry

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W. Basketball. Georgetown Drops a Close One to Dayton

The Georgetown University women's basketball squad dropped a tough 62-59 decision to the University of Dayton Flyers (2-1) Friday evening in GU's first game of the BTI Classic hosted by Purdue University. Georgetown trailed through the first half, but solid defense in the second kept the team in the game until the final play. With the loss, the Hoyas drop to 1-2 on the season. GU will have two more games this weekend as part of the three-game tournament.

Swimming & Diving. Women's 200 Free Relay Breaks School Record at Patriot Invitational

Georgetown University advanced 10 swimmers to tonight's finals and the 200 freestyle relay team broke the school record after the first day of competition at the Patriot Invitational. The quartet of Lindsay Vickroy, Amy Ballanfant, Megan Harvey and Laura Alito swam a 1:36.95 to set the new GU mark.

M. Basketball. No. 19 Georgetown Visits Savannah State on Saturday in Non-League Matchup

The 19th-ranked Georgetown University men's basketball team returns to action on Saturday, Nov. 21, visiting Savannah State for a non-league game at Tiger Arena in Georgia. The game will tip off at 1 p.m. Fans interested in listening to the Hoya broadcast of the game, on AM 570 with Rich Chvotkin calling the action, can visit the Georgetown Athletics website - www.guhoyas.com - and click on the "Listen" link posted on the men's basketball team schedule.

W. Volleyball. Vanessa Dorismond Named to BIG EAST Volleyball Second Team

WASHINGTON - Junior middle blocker Vanessa Dorismond (Raleigh, N.C./Raleigh Charter) was named to the BIG EAST Volleyball second team, when honors were announced during the BIG EAST Championship banquet on Thursday evening in Louisville, Ky. Dorismond led the Hoyas in kills with 346, while hitting .286 in 30 matches this season. She was among the conference leaders in both of those categories.

Football. Georgetown Football Closes out 2009 Season on Saturday Against Fordham

WASHINGTON - The Georgetown University football team will close out the 2009 regular season this Saturday November, 21 as they play host to Fordham on senior day. Kickoff is scheduled for 1 p.m. at Multi-Sport Field on the campus of Georgetown University.

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scout.com

Big Class For Mizzou

Mizzou's run to a Big XII Tourney Title and the NCAA's Elite Eight in 2009 was huge. Equally important, was replicating that success on the recruiting trail.

Miller Living The High Life

A decision to change his surroundings combined with a blend of size and skill has helped 2011 star Quincy Miller ascend the charts.

Mitchell To The Big 12

Tony Mitchell decided he wanted to end his recruitment during the early period. The No. 8 small forward in the 2010 class is headed to the Big 12.

Ezekoye Taking Visits

Scout.com contacted 2010 prospect Ndubisi “Bisi” Ezekoye from Kennedy High School in Silver Spring, MD. The versatile athlete has finished his season and has begun to take the many visits he has planned.

Kendrick Makes A Move

Jelan Kendrick switched it up. Originally he was planning to wait until the spring, now he's off the board.

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hoyaprospectus.blogspot.com

Season Preview: Greg Monroe

Greg Monroe was the Hoyas' best player last year, and one of the very best in the country.

He led the team with a 57.6% eFG% and a 61.2% TS%. He hauled in 8.8% of the offensive rebounds, a figure topped only by Julian Vaughn in his limited minutes, and 16.7% of the rebounds on the defensive end, first on the team by a wide margin. He led the team in Stl% and had an excellent Block% as well (though Vaughn and Sims were both ahead of him in that in their limited minutes). He was second on the team in Assist Rate, though well behind Chris Wright.

There are really only two criticisms of Monroe:

He's not an outside shooter - while he showed nice touch at times from the high post and hit 70% of his free throws, he only took 6 3-pointers all year.
He turned the ball over a lot. While not as often as Jason Clark, he still turned the ball over on 23.8% of Hoya possessions he ended in conference, which was even more than Chris Wright did.

The question, then, is what Greg Monroe can do to perform better in what will likely be his final season wearing the Blue and Gray?

For an example of what he might be, I thought I'd look at the two final seasons on the Hilltop for the recent players he most resembles: Jeff Green and Roy Hibbert.

Of the two, Monroe more resembles Green, without the outside shot.

He played 76% of available minutes last season, which is 4 minutes more per game than Hibbert ever managed.
His rebounding stats look like Green's, not like Hibbert's.
He's a better shot-blocker than Green, though he's not nearly in Hibbert's class in that category.
He's a superlative thief of the basketball, with a steal rate double Green's but still closer to Green than Hibbert.
His turnover rate resembles Green's, and not Hibbert's. This confirms what we saw on the court, that stylistically Monroe is playing Green's role as a facilitator of the offense and not Hibbert's role of possession-ender.
He commits fouls at about Green's rate, though he draws them more at Hibbert's rate, a difference probably largely explainable by his taking more shots inside.
One other difference - Monroe's role in the offense, while still heavy, was more akin to Hibbert's junior year than it was to Green. Green was a high-use player from his freshman year, and slightly increased that his sophomore and junior levels.

The general topic of %Poss usage and player efficiency was discussed at length in the Freeman preview, and I won't repeat that here, but it's worth noting that between his sophomore and junior years while Green's %Poss remained fairly constant, his ORating saw a big increase, from a slightly above-average 102.7 to an excellent 114.4. This increase doesn't seem to be driven by any major changes in his player profile - he had roughly the same rebounding rates, assist rate, turnover rate (actually slightly more), steal rate and other stats, but was driven almost exclusively by major improvements in his shooting accuracy across the line:

from 62% to 78% on FTA
from 50% to 56% on 2FGA
from 32% to 38% on 3FGA

The question is whether or not Monroe could expect those same kind of improvements in shooting accuracy. The answer to that is: not likely.

We can further break out the shot selection in a typical season for each:

.                        2FGA
Player/Year    Dunks    Layups  Jumpers     3FGA
Green, Jeff    22/22    60/87    49/119     32/84
2006-7                  0.690    0.412      0.381

Hibbert, Roy   15/15    82/136   46/88      2 /2
2007-8                  0.603    0.523      1.000

Monroe, Greg   21/21    78/133   25/61      2 /6
2008-9                  0.586    0.410      0.333

Here we see the biggest problem with Monroe's usage - while his rate stats look like those of a Green-style facilitator, his shot selection betrays that he also served as a Hibbert-as-a-senior-style post presence.

Even if he improves his post moves and his jumper to Hibbert's level, that's still only 8-10 additional made buckets in a season based on last year's shot totals. That's definitely useful, but not the sort of change that by itself would have a major impact on the Hoyas' fortunes in 2009-10. Noticeable improvements will almost certainly not result from changes in his personal profile, but instead will be the result of the supporting cast around him being better, particularly the emergence of another post scoring threat.

[N.B. - I'm not trying to claim Greg won't better develop as an NBA prospect, or that he won't have additional skills, just that it's unlikely his level of offensive efficiency will significantly improve.]

MORE ON FREE THROWS
One of the things Monroe got a bad rap for last season was an inability to hit clutch free throws. My impression is that rap largely results from the Cincinnati game, where the Bearcats hit all 6 of their free throws in overtime and Monroe missed 3 of 4 from the line, giving the Bearcats their margin of victory.

As I noted when I wrote about free throw defense after the season, the Hoyas were lucky from a free throw luck-oriented perspective to simply make it to overtime in the first place, as the Bearcats had a below-average shooting night from the line. While Monroe made a convenient scapegoat, it's not realistic to expect him to make all of his free throws. The one game where you could fairly criticize Monroe for having a poor free throw shooting night that seriously hurt his team was the loss at Notre Dame. That game, he hit only 3 of his 7 free throws, whereas he'd have made 5 on an average night. Keep this game in mind for a minute.

The Hoyas themselves were actually pretty consistent from the line. There were two games where they made as many as 3 more free throws than you would have expected (Drexel and Seton Hall), and none where they made three fewer than you'd expect. Without more complete data, it's difficult to say for sure, but this suggests Georgetown would have won more games had opponents' free throw shooting not been unusually inconsistent. This includes both St. John's games. This is straight-up luck, pure and simple.

As I did for Hoya opponents, I also did a comparison to see which teams, if any, fouled Hoyas that were good free throw shooters and those that were worse free throw shooters. This comparison wasn't very instructive, because every Hoya who had 25 FTA on the year shot at least 70% from the line. Clark was the only Hoya who shot over 80%, which held back the Hoyas' overall team FT%, but there wasn't a single player who averaged >1 FTA/game who was bad from the line.

The bad news for 2009-10, though, is two players who the Hoyas will be looking for bigger contributions from were mediocre free throw shooters in 2009. Julian Vaughn shot 54.5% (12-22) and Henry Sims shot 58.8% (10-17). If Henry and Julian do play more minutes in 2009, Georgetown's free throw shooting may look more inconsistent than it was the previous season, simply because more non-good free throw shooters are getting shots.

And inconsistent free throw shooting can lead to some bad losses.

For the curious, here's how the Hoyas looked in each game last year in terms of offensive made free throws versus expected. Positive numbers mean the Hoyas made more free throws than their season-long average would lead you to expect, while negative numbers indicate fewer made free throws. As a reminder, the first column is calculated simply from the Hoyas' team FT%, while the second column is from the individual player FT%. The second column should be more accurate (but a lot more tedious to compute):

Opponent Team Players
Jacksonville -0.0 +0.4
Drexel +3.4 +3.3
Wichita St. +1.5 +1.7
Tennessee +0.3 +0.4
Maryland +0.7 +0.3
American +1.3 +1.4
Savannah St. +0.4 +0.4
Memphis +0.8 +1.3
Mt St Marys -2.3 -2.2
Fla Int'l +2.3 +1.7
UConn +2.6 +3.0
Pitt -0.3 -0.1
Notre Dame -3.0 -2.7
Providence -1.0 -0.7
Syracuse -0.3 -0.9
Duke -2.3 -2.9
West Va. -2.1 -1.9
Seton Hall +3.7 +3.7
Cincinnati +0.7 +0.9
Marquette -1.4 -1.3
Rutgers -2.3 -2.7
Cincinnati +0.3 +0.3
Syracuse -1.9 -2.1
South Fl. +0.3 +0.4
Marquette +0.1 +0.1
Louisville -1.5 -1.4
Villanova +1.1 +0.9
St. John's -2.1 -2.4
DePaul -1.4 -1.4
SJU (BET) +0.3 +0.7
Baylor +2.1 +1.9

Total 0.0 0.1

Each column should total 0 (less any rounding errors), which they do.

Finally, here are the cumulative numbers for Hoyas and opponents combined (again, see the original discussion of FT defense for the opponents' numbers). Positive numbers represent a Hoya luck advantage, negative ones Hoya bad luck.

Opponent Team Players Game Margin
Jacksonville +0.1 -0.2 +9
Drexel -1.1 -1.3 +28
Wichita St. +0.9 +0.8 +8
Tennessee -0.7 -0.2 -12
Maryland +0.8 +0.4 +27
American -0.2 +0.8 +24
Savannah St. +0.3 +1.0 +62
Memphis +0.2 +0.4 +9 (OT)
Mt St Marys -0.6 -0.8 +11
Fla Int'l +4.2 +2.5 +38
UConn +1.5 +1.9 +9
Pitt +1.1 +0.9 -16
Notre Dame -6.6 -5.5 -6
Providence +0.2 -0.7 +7
Syracuse +4.6 +3.2 +14
Duke -4.8 -5.0 -9
West Va. -2.1 -2.0 -18
Seton Hall +4.0 +4.2 -5
Cincinnati -0.5 +0.7 -8
Marquette -3.7 -3.9 -12
Rutgers -3.6 -3.8 +7
Cincinnati -0.2 +0.2 -4 (OT)
Syracuse -5.9 -5.9 -4 (OT)
South Fl. +5.1 +5.7 +25
Marquette +1.2 +0.4 -6
Louisville -1.0 -2.0 -18
Villanova +0.4 +0.7 +2
St. John's -6.1 -7.0 -3 (OT)
DePaul +0.3 +0.6 +8
SJU (BET) -4.9 -4.0 -5
Baylor +2.0 +2.3 -2

Total -15.1 -15.6

Those 4 bolded games?

Those are the Hoyas' only games of the year where free throw luck disparity played a role in the outcome of the game, and the all ended up on the Hoyas' bad side. If not for cruel fate, the Hoyas may have had two more quality road wins and avoided two bad losses. Better luck from the charity stripe alone could be the difference between another trip to the NIT and a return to the NCAA tournament in 2010.

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.

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:

Can Austin Freeman increase the rate at which he uses possessions, to become a go-to offensive player rather than just a complementary one?
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.