Basketball Prospectus: Unfiltered Everything Else is Fluff.

November 6, 2012

Hoops List: Week 1

Filed under: Uncategorized — Bradford Doolittle @ 7:26 pm

I spent the last couple of days revamping the sub-structure on which the Hoops List are compiled, so while I don’t have any pithy comments for each team, I do have my first set of in-season rankings. I’ve changed my methodology from past seasons but rather than point out what is different, I’ll quickly walk through the steps by which these numbers are compiled.

1. I start by compiling each team’s in-season POW, which is a not-so-clever abbreviation for a power rating. These are the numbers that have been included in each of the first four editions of Pro Basketball Prospectus. The metric is meant to capture the “true talent” level of each team, as expressed by the probability that the team will win the championship. POW isn’t a magic bullet, but I’ve found that in most years, it has just the tiniest bit of advantage over point differential in terms of correlating with postseason success. I hadn’t messed with the metric much over the last three years, but I made a couple of slight modifications for this season:

First, I tweaked the way I measure strength of schedule. In my schedule simulator, each team is assigned a probability for winning each game based on team strength (as calculated by a blend of point differential and preseason projection), home court advantage and effects caused by game clustering (back-to-backs, etc.) Now, I am calculating schedule strength as an average of these probabilities. Theoretically, this should give me a more accurate portrait of which teams have played the more difficult slates.

The other components of POW are the same. I start with Pythagorean winning percentage, blend that with an adjusted winning percentage based on home-road success and then factor in the strength of schedule. The results are expressed as wins per 82 games, so a POW of 54.2 means a team has a true talent level of roughly a 54-28 team.

2. The second change I’ve made is that I decided to start giving extra weight to recent performance. My prior research didn’t suggest this was necessary, as long as a team’s roster remained largely stable. However, the change doesn’t harm accuracy either, and will do a better job of evaluating teams that have made a major transaction or suffered a significant, long-term injury to a star player.

3. At this juncture, I’ve got an in-season POW baseline. Next I factor in my NBAPET preseason projection. This is also a new procedure. Before, I only considered in-season results. The preseason projections are gradually phased out as the season progresses and disappear altogether by April 17.

4. My projection-adjusted POW is then fed into my simulation engine. The baseline probabilities for future games are based on current SCHOENE projections. So if a team makes a move or suffers an injury, then this will be reflected in the games yet to be played. Games already played are hard-coded, with the actual winners getting credit for those wins. The remainder of the schedule is played out 1,000 times, generating a new projected win total. This, finally, is the number by which teams are ranked in the Hoops List which, I swear, will normally appear on Monday afternoons. Also, running the sims gives revised playoff and championship odds, which I note.

Ordinarily, the rankings will be presented with 100-200 word snippets of analysis for each team, though as mentioned I’m forgoing that this week. The intent is to provide a weekly snapshot of the league. Also, the rankings provide a kind of narrative for each team’s season when read on a week-by-week basis. I find that handy.

NOTE: Numbers through Nov. 6

1. Miami Heat (3-1)
POW: 60.8; LAST WEEK: 61.2
SIMS: 100.0% playoffs; 49.3% conf; 30.6% title
ORTG: 120.9 (1); DRTG: 115.2 (30)

2. San Antonio Spurs (4-0)
POW: 57.9; LAST WEEK: 56.7
SIMS: 100.0% playoffs; 22.9% conf; 12.1% title
ORTG: 110.6 (8); DRTG: 100.0 (5)

3. Denver Nuggets (0-3)
POW: 56.4; LAST WEEK: 59.2
SIMS: 100.0% playoffs; 27.7% conf; 16.7% title
ORTG: 101.4 (23); DRTG: 110.4 (23)

4. Minnesota Timberwolves (2-1)
POW: 54.8; LAST WEEK: 54.5
SIMS: 100.0% playoffs; 14.0% conf; 6.1% title
ORTG: 106.5 (12); DRTG: 105.0 (14)

5. L.A. Lakers (1-3)
POW: 54.2; LAST WEEK: 58.2
SIMS: 99.9% playoffs; 22.1% conf; 12.8% title
ORTG: 111.4 (6); DRTG: 111.2 (25)

6. New York Knicks (3-0)
POW: 52.3; LAST WEEK: 49.9
SIMS: 100.0% playoffs; 11.9% conf; 4.4% title
ORTG: 120.2 (2); DRTG: 98.0 (2)

7. Atlanta Hawks (1-1)
POW: 50.9; LAST WEEK: 51.5
SIMS: 99.7% playoffs; 15.8% conf; 6.7% title
ORTG: 112.1 (5); DRTG: 111.0 (24)

8. L.A. Clippers (2-2)
POW: 50.5; LAST WEEK: 52.2
SIMS: 97.1% playoffs; 5.5% conf; 2.1% title
ORTG: 110.0 (9); DRTG: 107.9 (19)

9. Oklahoma City Thunder (1-2)
POW: 48.4; LAST WEEK: 50.0
SIMS: 89.4% playoffs; 3.7% conf; 1.6% title
ORTG: 105.4 (15); DRTG: 104.3 (13)

10. Boston Celtics (1-2)
POW: 48.4; LAST WEEK: 49.9
SIMS: 98.3% playoffs; 8.8% conf; 2.5% title
ORTG: 103.6 (20); DRTG: 111.3 (26)

11. Memphis Grizzlies (2-1)
POW: 47.6; LAST WEEK: 46.4
SIMS: 83.6% playoffs; 2.2% conf; 0.8% title
ORTG: 105.4 (16); DRTG: 101.9 (10)

12. Chicago Bulls (2-1)
POW: 47.5; LAST WEEK: 47.6
SIMS: 96.7% playoffs; 5.6% conf; 1.5% title
ORTG: 104.9 (18); DRTG: 94.8 (1)

13. Utah Jazz (1-3)
POW: 46.4; LAST WEEK: 47.3
SIMS: 75.5% playoffs; 1.4% conf; 0.4% title
ORTG: 106.6 (11); DRTG: 107.2 (18)

14. Philadelphia 76ers (1-2)
POW: 45.7; LAST WEEK: 47.7
SIMS: 91.4% playoffs; 4.4% conf; 1.0% title
ORTG: 95.9 (28); DRTG: 106.8 (17)

15. Indiana Pacers (2-2)
POW: 45.0; LAST WEEK: 45.2
SIMS: 87.8% playoffs; 1.7% conf; 0.2% title
ORTG: 96.7 (27); DRTG: 100.2 (7)

16. Dallas Mavericks (3-1)
POW: 45.0; LAST WEEK: 42.7
SIMS: 53.8% playoffs; 0.6% conf; 0.2% title
ORTG: 117.3 (4); DRTG: 106.7 (16)

17. Brooklyn Nets (1-1)
POW: 43.8; LAST WEEK: 44.8
SIMS: 76.9% playoffs; 2.4% conf; 0.4% title
ORTG: 111.1 (7); DRTG: 113.2 (28)

18. Toronto Raptors (1-2)
POW: 40.0; LAST WEEK: 40.7
SIMS: 27.8% playoffs; 0.2% conf; 0.0% title
ORTG: 105.8 (13); DRTG: 102.2 (11)

19. Milwaukee Bucks (2-0)
POW: 39.4; LAST WEEK: 37.3
SIMS: 21.3% playoffs; 0.0% conf; 0.0% title
ORTG: 107.5 (10); DRTG: 100.1 (6)

20. New Orleans Hornets (2-1)
POW: 36.2; LAST WEEK: 35.1
SIMS: 0.6% playoffs; 0.0% conf; 0.0% title
ORTG: 102.3 (22); DRTG: 100.4 (8)

21. Cleveland Cavaliers (2-2)
POW: 30.5; LAST WEEK: 29.5
SIMS: 0.1% playoffs; 0.0% conf; 0.0% title
ORTG: 104.9 (17); DRTG: 109.0 (20)

22. Golden State Warriors (2-2)
POW: 30.2; LAST WEEK: 28.3
SIMS: 0.0% playoffs; 0.0% conf; 0.0% title
ORTG: 103.8 (19); DRTG: 105.4 (15)

23. Sacramento Kings (1-3)
POW: 29.0; LAST WEEK: 29.3
SIMS: 0.0% playoffs; 0.0% conf; 0.0% title
ORTG: 93.3 (30); DRTG: 99.5 (4)

24. Portland Trail Blazers (2-2)
POW: 28.9; LAST WEEK: 26.9
SIMS: 0.0% playoffs; 0.0% conf; 0.0% title
ORTG: 105.5 (14); DRTG: 110.1 (22)

25. Orlando Magic (2-0)
POW: 26.0; LAST WEEK: 23.7
SIMS: 0.0% playoffs; 0.0% conf; 0.0% title
ORTG: 117.7 (3); DRTG: 99.3 (3)

26. Detroit Pistons (0-3)
POW: 26.0; LAST WEEK: 27.7
SIMS: 0.0% playoffs; 0.0% conf; 0.0% title
ORTG: 97.4 (26); DRTG: 112.5 (27)

27. Houston Rockets (2-1)
POW: 24.9; LAST WEEK: 22.8
SIMS: 0.0% playoffs; 0.0% conf; 0.0% title
ORTG: 103.5 (21); DRTG: 101.4 (9)

28. Phoenix Suns (1-3)
POW: 23.4; LAST WEEK: 24.5
SIMS: 0.0% playoffs; 0.0% conf; 0.0% title
ORTG: 98.1 (25); DRTG: 110.0 (21)

29. Washington Wizards (0-2)
POW: 22.1; LAST WEEK: 22.7
SIMS: 0.0% playoffs; 0.0% conf; 0.0% title
ORTG: 95.8 (29); DRTG: 103.1 (12)

30. Charlotte Bobcats (1-1)
POW: 17.5; LAST WEEK: 16.6
SIMS: 0.0% playoffs; 0.0% conf; 0.0% title
ORTG: 100.8 (24); DRTG: 114.7 (29)

November 2, 2012

Making the Point About Projections and Predictions

Filed under: Uncategorized — Kevin Pelton @ 5:05 pm

In the few weeks since Pro Basketball Prospectus 2012-13 (and the results of the SCHOENE Projection System) were released to the world, I’ve hammered home the difference between projections and predictions quite a bit, but I’m going to do so again because I think it’s an important distinction.

The other day on TrueHoop, Kevin Arnovitz discussed the popularity of the Denver Nuggets in a back-and-forth with Beckley Mason.

Aside from the stylistic appeal, where does this collective love for Denver come from? Is it a sincere belief the Nuggets have the necessary tools to mount a guerrilla war in the West and take down the likes of the Thunder or the Lakers or just a desire to see a verdict rendered once and for all that Carmelo Anthony is a bad guy?

I also wonder if the post-Melo Nuggets haven’t become a symbol for those who were repelled by the Anthony saga two years ago. In the era of the superteam, romantics want the Nuggets to prove that a team of non-superstars can compete for an NBA title through sheer effort, athleticism and creativity. A lot of basketball junkies want to live in a world where the 2004 Pistons aren’t a historical outlier and Anthony is the fool. The Nuggets represent their best hope.

Now, I don’t think Kevin was specifically referencing the optimistic statistical projections for the Nuggets (ours and John Hollinger‘s), but having the two points so close together reinforces the danger in conflating “the numbers” and our opinions based on them. I’d hate to have anyone think that the reason SCHOENE puts Denver atop the West has anything to do with liking the idea of an elite starless team.

As Kevin has pointed out via Nate Silver‘s new book The Signal and the Noise, the numbers never speak for themselves. And it would be disingenuous for me to argue that SCHOENE or any other projection system is completely objective. There are subjective assessments of how basketball works inherently built into the system. At the same time, the projection for the Nuggets–or any other team–has nothing to do with what I think of their players, the team or the narrative. The projections are individually compiled in an unbiased manner, and I do think it’s important for readers to trust that what they see from SCHOENE is strictly where the numbers lead, and if that occasionally leads to some LOLs it’s a small price to pay.

Naturally, this reflects the ongoing discussion about Silver’s more important projections for what’s going to happen next Tuesday. It’s perfectly fair to criticize his method, if you understand it. But simply demeaning Silver (who, it’s worth noting, hired the Basketball Prospectus staff in his old baseball life) because he’s an admitted liberal who happens to have the Democratic candidate more likely to win is silly and demeaning to his work. And I happen to think that’s easier to explain when the numbers and the opinions are explicitly kept separate.

You can contact Kevin at Follow him on Twitter at @kpelton.

October 30, 2012

The “Dumbest” 2013 Projections You’ll Ever See

Filed under: Uncategorized — Neil Paine @ 3:06 pm

With the 2012-13 NBA season tipping off tonight, I figured I should probably put up some kind of projections. A lot of smart people spend a lot of time and energy working on things like this (see our own SCHOENE system), but I wanted to create a set of projections that are as “dumb” as possible while still generating reasonable results (a la Tangotiger’s Marcel projection system). So consider these the baseline that any credible projection system must beat, because only the bare minimum of information has gone into them:

Seed	Eastern Conference	Avg W	Avg L	WPct
1	Miami Heat		56.2	25.8	0.686
2	New York Knicks		49.7	32.3	0.606
3	Chicago Bulls		47.7	34.3	0.581
4	Atlanta Hawks		47.7	34.3	0.581
5	Indiana Pacers		46.0	36.0	0.561
6	Boston Celtics		46.0	36.0	0.560
7	Brooklyn Nets		40.9	41.1	0.499
8	Milwaukee Bucks		40.5	41.5	0.494
9	Orlando Magic		40.2	41.8	0.490
10	Philadelphia 76ers	39.9	42.1	0.487
11	Toronto Raptors		37.1	44.9	0.452
12	Detroit Pistons		31.7	50.3	0.386
13	Washington Wizards	31.0	51.0	0.378
14	Cleveland Cavaliers	28.3	53.7	0.345
15	Charlotte Bobcats	21.0	61.0	0.256
Seed	Western Conference	Avg W	Avg L	WPct
1	San Antonio Spurs	54.1	27.9	0.659
2	Los Angeles Lakers	50.0	32.0	0.609
3	Oklahoma City Thunder	49.8	32.2	0.608
4	Los Angeles Clippers	48.9	33.1	0.596
5	Denver Nuggets		46.4	35.6	0.566
6	Memphis Grizzlies	45.4	36.6	0.554
7	Minnesota Timberwolves	41.7	40.3	0.509
8	Houston Rockets		39.6	42.4	0.482
9	Utah Jazz		38.9	43.1	0.474
10	Dallas Mavericks	38.6	43.4	0.471
11	Portland Trail Blazers	36.6	45.4	0.446
12	Phoenix Suns		35.6	46.4	0.434
13	New Orleans Hornets	35.1	46.9	0.429
14	Golden State Warriors	35.0	47.0	0.427
15	Sacramento Kings	30.6	51.4	0.373


Fact Checking Daryl Morey

Filed under: Uncategorized — Kevin Pelton @ 2:33 pm

One of the wonders of the modern political process is that, within hours of debates or speeches at the conventions, the presidential candidates’ claims can be thoroughly checked for objective accuracy. In that spirit, I thought something Houston Rockets GM Daryl Morey said during Monday’s press conference introducing James Harden deserved further research.

“I actually can’t come up with any examples of a player of his caliber and age getting traded at the time he was traded – it really has never happened,” Morey said when asked whether he was surprised Harden was available.

Just how unique is that? I set my parameters at players who were 23 or younger at the time they changed teams (Harden reached that age in August) and had posted at least 10+ WARP in a season (Harden had 11.3 last year). Here’s the list I came up with from the last three decades-plus:

  • Chris Webber, Golden State to Washington (13.0 WARP, age 21)
  • Stephon Marbury, Minnesota to New Jersey (13.7 WARP, age 22)
  • Tracy McGrady, Toronto to Orlando (10.4 WARP, age 21)
  • Elton Brand, Chicago to L.A. Clippers (9.8 WARP, age 22)

Of those four players, McGrady left via free agency under a system long since discarded. Marbury and Webber demanded trades, leaving just one example–the Bulls with Brand–of a team choosing to deal a player with established 10+ WARP track record (Brand had 10.7 as a rookie, before dipping slightly below that number in his final year in Chicago). So we’re certainly talking about something rare, and without precedent in the last decade, though I’d still grade Morey’s comment an exaggeration.

Since the trade, I’ve been surprised by how much more I seem to value Harden than the public at large. I liked Morey’s answer when asked why he felt Harden could be a first option: “I’ve watched him play.” That was a joke, sort of, but Morey continued by saying, “He played well in so many different environments. Obviously playing with Kevin (Durant) and Russell (Westbrook) he played well, but if you really studied the film, and I’d like to think our scouting staff is as diligent as any in the league – I think we are – when he had to carry the load with those guys off the floor he excelled. When there was just one of them on the floor he excelled. Really, frankly, in all environments.”

It’s worth keeping in mind that Harden was a top-three pick before ever playing with Durant and Westbrook. He led the Pac-10 in usage rate as a sophomore at Arizona State before declaring, and did so with above-average efficiency. As Bradford Doolittle pointed out in his analysis of the Rockets going forward, Harden was actually more effective last season with Durant on the bench (and presumably Westbrook, given Scott Brooks‘ tendency to rest both stars at the same time), pushing his usage rate to the stratosphere while increasing his True Shooting Percentage from .641 to .686, resulting in a jump from 16.6 points per 40 minutes to 34.7.

The counter to that stat is that Harden was playing against reserves. Ethan Sherwood Strauss raised a good question (I know, shocking): are second-unit defenders actually worse? The evidence suggests the drop-off is larger at the other end of the floor. Daniel Myers has studied the relationship between regularized adjusted plus-minus and minutes per game and found it much stronger on offense than defense. As in baseball, it appears that replacement level (and reserve level) is much higher on defense than offense.

Now, this does suggest Harden got a bit of a break at the defensive end going against backups, and I have argued that part of his poor NBA Finals performance was due to the extra energy he had to expend defending LeBron James. But I don’t suspect we’re talking about a big effect, and remember that Harden was much more valuable without the stars. If in reality his value to the Rockets is reflected by his overall performance in Oklahoma City, I’m pretty sure Morey would take that.

October 26, 2012

BP’s Nuggets Projection Goes National

Filed under: Uncategorized — Kevin Pelton @ 1:38 am

People have taken note of SCHOENE’s projection that the Denver Nuggets will be one of the top teams in the Western Conference, as seen in Pro Basketball Prospectus 2012-13 and ESPN the Magazine‘s NBA Preview edition–including TNT’s broadcast team of Kevin Harlan and Reggie Miller, which discussed the projection during Thursday’s broadcast of the Nuggets-Clippers preseason game. Check it out, courtesy @blazersedge:

The folks at the local Boys & Girls Club will be disappointed Reggie is so dismissive of my playing career.

You can contact Kevin at Follow him on Twitter at @kpelton.

October 15, 2012

Nothing except everything’s changed in five years

Filed under: Uncategorized — John Gasaway @ 12:24 am

Basketball Prospectus made its debut five years ago this week. My motivation in partnering with Ken Pomeroy on the college side of the new venture was simply to create a site that I’d like to visit as a reader, one that would give me trustworthy information and analysis on college basketball.

And in October 2007, there wasn’t a site like that. There were plenty of great college basketball writers, and there were many sites that covered their own beloved team with some of the same tools that Ken and I hoped to throw at all of Division I. But there was no site that could address why Florida had just won back-to-back national championships, or whether Derrick Rose or Michael Beasley would turn out to be the better freshman, or how good Kansas could be without Julian Wright, and do so in a way that would live up to the blurb Portland head coach Eric Reveno would one day give one of our books: It’s not just some guy’s opinion.

Coincidentally I had dinner with Ken last night. He was out East for a friend’s wedding, and we took the opportunity to make the Village Grille in Waldwick, New Jersey, the temporary tempo-free epicenter of the world while the patrons around us watched the Giants vs. the 49ers. Ken and I agreed a lot has changed in five years. Most notably, the amount of trustworthy information and analysis that’s available on college hoops has increased exponentially. As a reader I’ve never been happier.

Also if you’d told me five years ago that John Calipari would be contributing the Foreword for our book (on sale soon) or that Prospectus would be loaning out staffers to advise coaches who keep appearing in the national championship game, I would have been pleased.

But this is no time to be complacent, and 2012 is not my idea of utopia. Not when the RPI still sits contentedly at the same old corner, and national writers intone solemnly that Chrishawn Hopkins‘ dismissal from the program is “a significant blow” to Butler. Apparently five years is not sufficient for the task at hand.

So happy birthday, Prospectus. Happy birthday, and get to work.

Twitter: @JohnGasaway. Contact: here.

October 11, 2012

Considering the Offensive Rebound Tradeoff

Filed under: Uncategorized — Kevin Pelton @ 4:27 pm

The second week of training camp seems like as good a time as any to discuss offensive rebounding strategies. This week, ESPN Insider began rolling out John Hollinger‘s season previews. In his discussion of the Boston Celtics, Hollinger pointed out that the Celtics’ offensive rebounding rate in 2011-12 was the lowest in league history, and by a fairly substantial margin. Boston is at the leading edge of a lengthy trend toward teams sacrificing second chances in favor of getting back defensively.

TrueHoop’s Henry Abbott noticed, and wondered if teams aren’t better off following Boston’s lead and entirely abandoning the offensive glass. At Wages of Wins, Dave Berri responded by pointing out that there is little relationship between offensive rebounding and Defensive Rating.

Today came layer two of the analysis, as blogger Mystic looked at a more refined measure of offensive rebounding strategy and found that teams that pay less attention to the offensive glass tend to be better both on defense and overall. I think this latest study gets us about 75 percent of the way there.

Using the ratio of offensive rebound percentage to defensive rebound percentage, adjusted for league average, is a much better way to study the issue because it gets at the fundamental decision of whether to crash the boards or not. For example, the Chicago Bulls are one counterpoint to the “get back” argument because they combine one of the league’s highest offensive rebound percentages with its best defense. However, the Bulls are generating most of those second chances with their bigs while everyone else gets back on D. Chicago just happens to rebound particularly well, and they don’t appear among the leaders in offense/defense rebounding ratio.

The limitation of the study Mystic did is that it only looks at correlation, not causation. We don’t know whether getting back makes teams better, or better teams tend to play more conservatively and defensive-minded because they don’t need to take as many risks. To try to really isolate the causation, I looked at year-to-year changes in offense/defense rebounding ratio as well as team performance. I also limited the study to 2004-05 to the present to consider only the way the game is being played since the rules re-interpretations that opened up the floor for offenses.

This perspective tends to support my view that there’s a trade-off between offense and defense when it comes to hitting the glass. There’s a positive correlation between the change in offensive rebounding and the change in Offensive Rating (+.125) and a negative correlation with the change in Defensive Rating (-.141), indicating that as teams hit the offensive glass more from one season to the next, they get better on offense and worse on defense. Even though the correlation with Defensive Rating is slightly higher, the overall relationship to change in winning percentage is ever so slightly positive. The bigger takeaway is that it’s almost zero. The r^2 figure suggests that about 0.1% of the difference in a team’s record from one season to the next is attributable to the change in their offense/defense rebounding ratio.

The same trends hold up when we look at the extremes. The teams that increased their offense/defense rebounding ratio the most had better offenses and worse defenses and were marginally better; teams that paid less attention to the offensive glass had worse offenses and better defenses and identical winning percentages on aggregate.

The one surprise of the study was that it appears personnel may have more to do with offense/defense rebounding ratio than coaching strategy. The teams that increased their offensive rebounding the most generally added dominant rebounders like Zach Randolph (2009-10 Memphis Grizzlies) and Greg Oden (2008-09 Portland Trail Blazers). The 2009-10 San Antonio Spurs are the ultimate example. For years, they had eschewed offensive rebounding under defensive-minded Gregg Popovich, but the addition of DeJuan Blair made them much more likely to come up with second chances. The Spurs scored a little more, defended a little worse and were essentially the same team.

Ultimately, I don’t think there’s one right or wrong answer about crashing the glass. The best strategy for each team depends on personnel and style, and any number of approaches can be successful.

You can contact Kevin at Follow him on Twitter at @kpelton.

August 27, 2012

Hornets247 Podcast

Filed under: Uncategorized — Bradford Doolittle @ 7:32 pm

Last week, I took time out from our annual hermitage — during which the Pro Basketball Prospectus annual is produced — to do a little podcasting. I got together — in a virtual sense — with Michael McNamara and Ryan Schwan from Hornets247com for their weekly hoops chat. We had a nice conversation about the future of the New Orleans franchise, Ryan Anderson, Austin Rivers, win projections and a lot more. Check it out.

August 14, 2012

Since Reputable People Are Using These

Filed under: Uncategorized — Drew Cannon @ 7:12 pm

Since my recent historical (2002-present) recruiting class rankings have been used a little bit around the Internet, but I’ve never actually written much about them, I thought I should remedy that. I give teams credit for signing players by fitting each player’s ranking to a curve that spits out 10 points for the #1 player, seven points for the #10 player, five points for the #25 player, three points for the #50 player, and one point for the #100 player. If you sign someone and they never play (Enes Kanter, J.R. Smith), you get half credit. Anybody unranked is generally ignored, although sometimes there are exceptions, as in the case of Jarnell Stokes (who I give a ranking of 18.5). All rankings are Dave Telep’s.

The 50 most impressive recruiting classes of the 2002-12 era:
1. 2006 North Carolina (#3 Brandan Wright, #5 Ty Lawson, #7 Wayne Ellington, #36 Deon Thompson, #55 Alex Stepheson, #79 Will Graves – 32.60 points), top ACC
2. 2011 Kentucky (#1 Anthony Davis, #4 Michael (Kidd-?)Gilchrist, #8 Marquis Teague, #19 Kyle Wiltjer – 31.42 points), top SEC, top 4-man class
3. 2009 Kentucky (#2 John Wall, #3 DeMarcus Cousins, #17 Daniel Orton, #37 Eric Bledsoe, #46 Jon Hood – 31.09 points)
4. 2002 Duke (#8 Shelden Williams, #12 Shavlik Randolph, #13 J.J. Redick, #29 Sean Dockery, #31 Michael Thompson – 29.58 points)
5. 2012 Kentucky (#1 Nerlens Noel, #13 Alex Poythress, #15 Archie Goodwin, #40 Willie Cauley – 26.40 points)
6. 2010 Kentucky (#6 Brandon Knight, #8 Terrence Jones, #28 Doron Lamb, #67 Stacey Poole, half credit for #3 Enes Kanter – 26.30 points)
7. 2012 UCLA (#2 Shabazz Muhammad, #5 Kyle Anderson, #26 Tony Parker, #41 Jordan Adams – 25.83 points), top Pac-12
8. 2006 Ohio State (#1 Greg Oden, #13 Daequan Cook, #28 Mike Conley, #31 David Lighty – 25.67 points), top Big Ten
9. 2008 UCLA (#4 Jrue Holiday, #23 J’mison Morgan, #31 Jerime Andersen, #39 Malcolm Lee, #42 Drew Gordon – 25.36 points)
10. 2011 Duke (#3 Austin Rivers, #29 Michael Gbinije, #35 Marshall Plumlee, #38 Quinn Cook, #41 Alex Murphy – 24.93 points)
11. 2005 Kansas (#8 Julian Wright, #15 Brandon Rush, #19 Mario Chalmers, #22 Micah Downs – 24.61 points), top Big 12
12. 2005 Duke (#1 Josh McRoberts, #18 Greg Paulus, #36 Eric Boateng, #55 Marty Pocius, #88 Jamal Boykin – 23.78 points)
13. 2012 Arizona (#4 Kaleb Tarczewski, #9 Grant Jerrett, #16 Brandon Ashley, #65 Gabe York – 23.74 points)
14. 2002 North Carolina (#3 Raymond Felton, #7 Rashad McCants, #10 Sean May – 23.28 points), top 3-man class
15. 2006 Texas (#2 Kevin Durant, #19 Damion James, #29 D.J. Augustin, #80 Matt Hill, #86 Dexter Pittman – 22.39 points)
16. 2006 Duke (#15 Gerald Henderson, #18 Lance Thomas, #20 Jon Scheyer, #38 Brian Zoubek – 21.46 points)
17. 2009 North Carolina (#4 John Henson, #33 Dexter Strickland, #53 Leslie McDonald, #55 David Wear, #56 Travis Wear – 20.73 points)
18. 2010 North Carolina (#1 Harrison Barnes, #16 Reggie Bullock, #29 Kendall Marshall – 20.71 points)
19. 2004 Texas (#12 LaMarcus Aldridge, #17 Daniel Gibson, #26 Mike Williams, #53 Dion Dowell – 20.32 points), top 2004
20. 2004 Kentucky (#8 Randolph Morris, #13 Joe Crawford, #15 Rajon Rondo – 20.06 points)
21. 2007 Kansas State (#2 Michael Beasley, #7 Bill Walker, #50 Dominique Sutton – 19.78 points), top 2007
22. 2005 North Carolina (#7 Tyler Hansbrough, #24 Danny Green, #41 Bobby Frasor, #52 Marcus Ginyard – 19.17 points)
23. 2010 Memphis (#12 Will Barton, #20 Jelan Kendrick, #23 Joe Jackson, #75 Tarik Black – 19.17 points), top C-USA, top mid-major
24. 2009 Villanova (#9 Mouphtaou Yarou, #22 Dominic Cheek, #26 Maalik Wayns, #82 Isaiah Armwood – 18.89 points), top Big East
25. 2005 Oklahoma State (#23 Byron Eaton, #46 Roderick Flemings, #81 Kenneth Cooper, #94 Terrel Harris, half credit for #2 Gerald Green and #14 Keith Brumbaugh – 18.88 points)
26. 2006 Connecticut (#23 Stanley Robinson, #35 Curtis Kelly, #39 Hasheem Thabeet, #43 Jerome Dyson, #62 Doug Wiggins – 18.86 points)
27. 2002 Villanova (#5 Jason Fraser, #37 Randy Foye, #41 Curtis Sumpter, #49 Allan Ray – 18.66 points)
28. 2009 Texas (#5 Avery Bradley, #14 Jordan Hamilton, #47 Shawn Williams – 17.60 points)
29. 2009 Kansas (#6 Xavier Henry, #24 Thomas Robinson, #29 Elijah Johnson – 17.56 points)
30. 2006 Washington (#4 Spencer Hawes, #16 Quincy Pondexter, #52 Adrian Oliver – 17.30 points)
31. 2004 Kansas (#28 Sasha Kaun, #32 Russell Robinson, #45 Alex Galindo, #59 C.J. Giles, #62 Darnell Jackson – 17.15 points)
32. 2007 Syracuse (#8 Donte Greene, #21 Jonny Flynn, #58 Rick Jackson, #75 Scoop Jardine – 17.02 points)
33. 2004 Indiana (#14 D.J. White, #47 Robert Vaden, #72 A.J. Ratliff, #78 James Hardy, half credit for #5 Josh Smith – 16.98 points)
34. 2010 Ohio State (#4 Jared Sullinger, #24 Deshaun Thomas, #64 Jordan Sibert, #97 Aaron Craft – 16.74 points)
35. 2007 Florida (#10 Nick Calathes, #32 Chandler Parsons, #45 Jai Lucas, #68 Alex Tyus – 16.66 points)
36. 2003 Kansas (#4 David Padgett, #21 J.R. Giddens, #59 Omar Wilkes – 16.28 points), top 2003
37. 2008 Ohio State (#3 B.J. Mullens, #14 William Buford, half credit for #64 Terrelle Pryor – 16.18 points)
38. 2009 Duke (#12 Ryan Kelly, #18 Mason Plumlee, #40 Andre Dawkins – 16.16 points)
39. 2002 Arizona (#19 Hassan Adams, #21 Chris Rodgers, #26 Andre Iguodala – 16.08 points)
40. 2006 Louisville (#24 Earl Clark, #25 Derrick Caracter, #44 Jerry Smith, #64 Edgar Sosa – 15.74 points)
41. 2005 Mississippi State (#32 Jamont Gordon, #38 Vernon Goodridge, #49 Reginald Delk, half credit for #3 Monta Ellis – 15.62 points)
42. 2007 Purdue (#27 E’Twaun Moore, #29 Scott Martin, #47 JaJuan Johnson, #51 Robbie Hummel – 15.56 points)
43. 2003 LSU (#14 Brandon Bass, #27 Regis Koundjia, #34 Tack Minor – 15.36 points)
44. 2007 Duke (#6 Kyle Singler, #26 Nolan Smith, #56 Taylor King – 15.34 points)
45. 2009 Georgia Tech (#1 Derrick Favors, #36 Mfon Udofia, #90 Kammeon Holsey – 15.23 points)
46. 2011 Arizona (#15 Josiah Turner, #22 Nick Johnson, #61 Angelo Chol, #94 Sidiki Johnson – 15.02 points)
47. 2011 St. John’s (#25 Dom Pointer, #39 Moe Harkless, #64 D’Angelo Harrison, #99 Amir Garrett, half credit for #32 JaKarr Sampson and #77 Norvel Pelle – 15.00 points)
48. 2003 Syracuse (#24 Demetris Nichols, #25 Darryl Watkins, #41 Terrence Roberts, #90 Louis McCroskey – 14.99 points)
49. 2012 Baylor (#3 Isaiah Austin, #36 Ricardo Gathers, #63 L.J. Rose – 14.99 points)
50. 2003 Michigan State (#5 Shannon Brown, #28 Brandon Cotton, #65 Drew Naymick – 14.93 points)

Top five by teams currently outside the BCS conferences:
1. 2010 Memphis (#23 above)
2. 2008 Memphis (#5 Tyreke Evans, #55 Wesley Witherspoon, #63 Angel Garcia, #89 Matt Simpkins – 14.22 points)
3. 2005 Memphis (#25 Shawne Williams, #42 Antonio Anderson, #51 Chris Douglas-Roberts, #85 Robert Dozier – 12.85 points)
4. 2007 Memphis (#5 Derrick Rose, #43 Jeff Robinson – 11.53 points)
5. 2012 UNLV (#7 Anthony Bennett, #47 Katin Reinhardt – 10.75 points)

July 24, 2012

The Best Teams Since 1992 (Now Adjusted for League Quality!)

Filed under: Uncategorized — Neil Paine @ 9:53 am

In this ESPN article, I looked at how each Dream Team stacked up next to each other talent-wise in an absolute sense, estimating league quality by looking at how age-adjusted Advanced Statistical Plus/Minus (ASPM) for the same cohorts of players changed from year-to-year. Relative to the 2008 season (which represented the average league quality over the 1992-2012 period), here’s how difficult each NBA season was:

Year	Avg Plyr Δ	Plyr Rel to 08	Tm Rel to 08
1992	 n/a		 0.3		 1.4
1993	 0.0		 0.3		 1.6
1994	-0.1		 0.2		 1.2
1995	-0.2		 0.1		 0.3
1996	-0.1		 0.0		-0.1
1997	-0.1		-0.1		-0.6
1998	 0.0		-0.1		-0.5
1999	 0.1		 0.0		 0.1
2000	 0.1		 0.1		 0.5
2001	-0.2		-0.1		-0.4
2002	 0.0		-0.1		-0.3
2003	-0.1		-0.2		-0.9
2004	 0.1		-0.1		-0.5
2005	-0.1		-0.2		-1.1
2006	 0.0		-0.2		-0.9
2007	 0.1		-0.1		-0.3
2008	 0.1		 0.0		 0.0
2009	 0.0		 0.0		-0.1
2010	 0.1		 0.1		 0.6
2011	 0.1		 0.2		 1.2
2012	 0.0		 0.2		 1.1

And here’s that in graphical form (in this case, relative to 1992):

NBA Talent

In a nutshell, expansion and dilution (plus the decline and retirement of numerous Hall of Famers in the late 90s/early 00s) dragged the league’s talent level down to its low point in 2004-05, when it was as easy to put up ASPM numbers as it has ever been over the 1992-2012 period. However, NBA talent has gradually climbed back since, reaching essentially the same difficulty level as the league had in 1992.

Anyway, using those numbers we can adjust team ASPM ratings (which are basically schedule-adjusted efficiency differentials) for the quality of the league to arrive at absolute team ratings relative to the 2008 season. Here are the best (regular-season) teams from 1992-2012 after that adjustment:


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