The Wages of Wins Journal

Boston or LA?

December 17, 2009 · Leave a Comment

With 30% of the regular season complete, the Boston Celtics lead the Eastern Conference with a 10.3 efficiency differential (offensive efficiency minus defensive efficiency).  And the LA Lakers lead the Western Conference with an 8.3 mark.  Although it’s still early, such numbers suggest that for the 12th time in NBA history the Celtics and Lakers will meet in the NBA Finals. 

Again, it’s early.  But if these numbers hold up people will be asking the following until next summer: Who is better, Boston or LA?

The Celtic Argument

Let’s start with a look at the Boston Celtics after 24 games.  Table One reports each player’s Wins Produced and WP48 [Wins Produced per 48 minutes] this season, as well as what Boston could have expected given what these players did last season.  As one can see, given what these players did last season Boston should be on pace to win 72 games this year.  After 24 games, though, the pace is only 66.4 victories.

Table One: The Boston Celtics after 24 games in 2009-10

When we look at the performance of the individual players we see that Rasheed Wallace, Ray Allen, and Eddie House have declined the most.  What do these players have in common?  All three are on the wrong side of 30 years of age.  And that illustrates the problem facing the Celtics. Six of the Celtics are more than 30 years of age and these players have played 60% of the team’s minutes. And of these six, only Paul Pierce is offering more this season (relative to last season).

Although basketball players may like to think they age like fine wine, the general pattern is that players age like milk.  So as the season progresses, the Celtics might slip some more.  At this point in time, though, the Celtics are a very good team.  And this is because of the performance of Rajon Rondo, Kevin Garnett, Pierce, Kendrick Perkins, Ray Allen, and Shelden Williams. These six players are on pace to produce nearly 68 wins this year.

There are two surprises on this list.  First, Shelden Williams has been very productive and should (but may not) make fans of the Celtics forget about Glenn Davis.  The other surprise is Rasheed Wallace, who is really not offering much at all. Once again, given his age this shouldn’t be a surprise. 

The Lakers Argument

Okay, the Celtics are good, but not quite as good as their past numbers suggest.  The story of the Lakers is the opposite.

Table Two: The LA Lakers after 24 games in 2009-10

As Table Two illustrates, what the Lakers did last season suggests that this team should only be on pace to win 52 games this year.  When we look at production this season, though, the Lakers are on pace to win 63 games. 

Both of these numbers are deflated because of the early season injury to Pau Gasol.  In projecting wins I am taking the easy way out.  Projections are simply what has happened across 24 games multiplied by 82/24.  So for Gasol, his projected minutes are only 1,596 (which essentially assumes Gasol will keep missing eleven out of each 24 game segment). Currently, though, Gasol is averaging 36 minutes per game.  At this pace, Gasol will play about 2,550 minutes this season.  Given what he did last season [WP48 of 0.256], projections based on last year’s number would increase by 5.5 wins (so the Lakers should have expected about 57 wins). 

After 13 games, though, Gasol has posted a 0.465 WP48.  Such a mark bests – by a wide margin – anything Gasol has done in his career.  And it also tops anything anyone did last season.  If Gasol can keep this up, the Lakers can expect to win about 72 games this season.

But can Gasol maintain this pace?  Again, he has never produced at this level before.  When we look at the individual numbers we see that Gasol is posting career highs with respect to free throw percentage and rebounds.  As noted in the past, rebounding tends to be very consistent across time.  So one wonders if Gasol will keep grabbing 16.9 rebounds per 48 minutes (his previous high was 13.1 in 2006-07). 

If this happens, Gasol and the Lakers will probably finish with a better record than the Celtics.  And the subsequent home-court advantage – assuming the playoffs hold to form – will give the Lakers an advantage in the NBA Finals. 

Then Again…

But if Gasol slips, then the Celtics will have the advantage.  Then again, if the aged Celtics keep aging, maybe the Lakers will be better.  Of course, Kobe is both aged and hurt.  So maybe Boston will still finish with the best record.

Okay, here is what we know. Right now, the season numbers favor the Celtics.  But there is evidence that the Lakers are better right now and could finish with better season numbers.

And all of this ignores the other teams in the NBA. I still believe it’s possible that the Cleveland Cavaliers can come back (although I recognize the distinct possibility that won’t happen).  And the Atlanta Hawks and Josh Smith continue to be amazing (9.0 efficiency differential).

In sum, it’s still early (have I said this?).  But if you are looking at the Celtics and Lakers, we can clearly see that the Celtics are better.  Or is it the Lakers?  Or… how ‘bout that Pau Gasol?

- DJ

The WoW Journal Comments Policy

Our research on the NBA was summarized HERE.

The Technical Notes at wagesofwins.com provides substantially more information on the published research behind Wins Produced and Win Score

Wins Produced, Win Score, and PAWSmin are also discussed in the following posts:

Simple Models of Player Performance

Wins Produced vs. Win Score

What Wins Produced Says and What It Does Not Say

Introducing PAWSmin — and a Defense of Box Score Statistics

Finally, A Guide to Evaluating Models contains useful hints on how to interpret and evaluate statistical models.

→ Leave a CommentCategories: Basketball Stories

Pointing Fingers at the Miami Heat

December 16, 2009 · 19 Comments

The Miami Heat began the season with a three game winning streak.  After losing a game, the Heat won another three in a row.  Since that 6-1 start, though, the team has only won six of seventeen games.  After one of their latest losses – a 28 point defeat at the hands of the Memphis Grizzlies – the Heat began searching for answers. (HT True Hoop)

“I didn’t say a word. I let the guys talk. Sometimes, as a leader, you have to listen,” (Dwyane) Wade said of a postgame powwow led by veterans Jermaine O’Neal and Udonis Haslem. “I won’t say what any guy said. Just know that there was communication back and forth.”

Haslem insisted that there was no finger-pointing or animosity, although there was plenty of blame to share for the disappointing play at home. Instead, Haslem’s message was on all-inclusive accountability.

Sunday was for soul-searching.

“It’s not just about one person or two people,” Haslem said. “It’s on all of us. We definitely have to dig deep and find out what type of team we are.

“We need to get that chip back on our shoulder we had earlier.”

The words of Haslem suggest that if the Heat simply change their attitude, or try just a bit harder, the Heat will become a winning team.  Furthermore, this is a team issue.  Blame cannot be assigned to any one player or person. The numbers, though, seem to tell a different story. 

Pointing at the Supporting Cast

Last year Miami was led by Dwyane Wade.  Of the team’s 43 wins, about 22 were linked to the productivity of Wade.  This means that without Wade, the Heat were not a very good team.

This year – as Table One illustrates – the Heat are once again led by Wade.  And after Wade, Miami – once again — doesn’t have much.  The Heat are currently on pace to win about 40 games this year (the team’s efficiency differential is -0.7). 

Table One: The Miami Heat after 24 games in 2009-10

Of these 40 wins, about 26 of these projected wins can be linked to players not nicknamed Flash.  About four of these wins can be linked to the play of Dorell Wright.  Last year, Wright only played 73 minutes.  So his production (which is quite similar per 48 minutes to what he did in 2007-08) is somewhat surprising.  In fact, Wright and Wade are the only players to surpass the WP48 [Wins Produced per 48 minutes] mark of 0.200 (twice the average mark).  And only Udonis Haslem and Quentin Richardson (of those who have played 100 minutes) surpass the average mark.  Yes, much of this roster is below average.

One player who comes close to average – although still falls short – is Jermaine O’Neal.  And like the play of Wright, this is also somewhat surprising. Last year O’Neal posted a -0.037 WP48.  This year he’s still below average, but his ability to approach the average mark – something he hasn’t done since 2006-07 — is worth about four additional wins to the Heat across an entire season (or about six more wins than this team could have expected O’Neal to produce). 

Without the play of Wright and O’Neal the Heat would not be as close to the 0.500 mark. So clearly one can point a finger at whoever assembled Wade’s supporting cast.  But one can also point the finger of accusation at Wade. 

Pointing at Flash

In 2008-09, Wade posted a WP48 [Wins Produced per 48 minutes] mark in excess of 0.300.  This season, Wade’s WP48 is 0.207.   In other words, last year Wade’s productivity went beyond what we see from Kobe Bryant [WP48 of 0.244 in 2008-09).  This season, Wade’s production lags behind Kobe.  And for the Heat to be a team that goes well beyond 41 wins (at least, more than one or two games beyond), Flash really has to do more than Kobe.

This year, though, that’s not happening.  And the big reason why Flash has dimmed is Wade’s shooting efficiency.  Last season Wade posted a 51.6% adjusted field goal percentage.  This season this mark has fallen to 44.8%.  If Wade could return to the level of efficiency seen last year – and the same happened with respect to assists (which are also a bit down) – the Heat would see the team’s projected wins rise by about nine.   

One should note, though, that even if Wade returned to form – and Wright and O’Neal kept doing what we have seen thus far –the Heat would probably fall short of 50 victories. And that mark is not quite what Miami envisioned when it started 6-1. 

The problem for Miami is that this start was a bit of an illusion.  As Dean Oliver noted in Basketball on Paper, there is a 90% chance that a team that ultimately wins 30% of its games – or about 25 games – will win three in a row at some point in an NBA season.  So when the Heat – a team that will probably win 50% of its games – started with a three game winning streak (and followed it with another three game winning streak after a loss); the expectations for the Heat shouldn’t have changed immediately.  At least, we shouldn’t be surprised that Miami has fallen short of the promise of these early streaks.

Pointing All the Fingers

At the end of the day, Miami doesn’t have much beyond Wade.  So a finger of blame needs to be pointed at the person (or persons) who assembled this roster.  And as noted, a second finger can be pointed at Wade himself. The Heat would not be one of the top teams in the league if Wade reverted to form.  But they could be a bigger threat to surpass the mark of an average team and perhaps come closer to 50 wins.

Unfortunately for Miami, “approaching 50 wins” is probably the ceiling for this team; and struggling to stay above .500 is closer to reality.  One suspects that this will not be enough for Miami to keep Wade when the season ends.  And if Wade does depart, we can expect the finger of blame to be frequently pointed next summer in Miami.

- DJ

The WoW Journal Comments Policy

Our research on the NBA was summarized HERE.

The Technical Notes at wagesofwins.com provides substantially more information on the published research behind Wins Produced and Win Score

Wins Produced, Win Score, and PAWSmin are also discussed in the following posts:

Simple Models of Player Performance

Wins Produced vs. Win Score

What Wins Produced Says and What It Does Not Say

Introducing PAWSmin — and a Defense of Box Score Statistics

Finally, A Guide to Evaluating Models contains useful hints on how to interpret and evaluate statistical models.

→ 19 CommentsCategories: Basketball Stories

How Much Has Phoenix Improved and Is Amare An All-Star?

December 14, 2009 · 44 Comments

If the NBA playoffs began today the Phoenix Suns would currently have the 4th seed – and home-court advantage in the first round — in the Western Conference.  The Cleveland Cavaliers – in the Eastern Conference – also hold the 4th seed.  Why is this comparison important?

Last year the Cavaliers were the best team in the NBA (at least, in the regular season) and the Phoenix Suns missed the NBA playoffs.  This past summer the Suns sent Shaquille O’Neal to the Cleveland Cavaliers.  And after one-quarter of the 2009-10 season, it appears that Shaq’s departure has made the Suns better and caused the Cavaliers to decline.

Shaq’s impact on the Cavs was discussed last week (and it ain’t a pretty picture).  Today we are going to examine the surprising Suns.

Are the Suns Rising?

The Suns have won 16 of their first 24 games.  Such a record, though, is somewhat deceiving.  When we turn to efficiency differential (offensive efficiency minus defensive efficiency) we see a mark (after Saturday’s games) of 2.85.  This mark ranks 7th in the West, just ahead of the Utah Jazz (2.70) and the Houston Rockets (2.15).  So a focus on efficiency differential reveals that the Suns are not far from slipping into the 9th spot (and out of the playoffs). 

A differential of 2.85 is consistent with a team that wins 48 games across an 82 game season.  Last season the Suns posted a differential of 1.95, a mark consistent with a 46 win team (the number of wins the team had last season).  So the Suns have not really improved much relative to last year.

Not much, though, is still something.  And something has happened without Shaq.  When we look at Wins Produced – reported in Table One — we can see where the improvement has come from. 

Table One: The Phoenix Suns after 24 games in 2009-10

Table One reports what each player has done for the Suns this season.  It also reports each player’s expected production, given what the player did last year.  A quick glance at the numbers reveals that the two players who have improved the most are Steve Nash and Channing Frye.

A different picture emerges, though, if we consider what Nash and Frye did two years ago.   If Nash and Frye were repeating what they did in 2007-08, each player’s production would be as follows:

Steve Nash [2oo7-08 production]: 0.276 WP48, 15.7 Projected Wins

Channing Frye [2007-08 production]: 0.043 WP48, 2.3 Projected Wins

Team Wins Produced [with Nash and Frye from 2007-08]: 46.1

Again, the team is currently on pace to win 48 games.  So the story in Phoenix is simply that Nash and Frye have reverted to what we saw in 2007-08. 

It’s important to emphasize.  Frye from two years ago was still below average (and a bit better than what we are seeing this year).  He just wasn’t as bad as he was in 2008-09.

All-Star Amare?

When we look at the leader in Wins Produced, we don’t see Channing Frye.  And we don’t see fellow big man Amare Stoudemire until we get past Nash, Jason Richardson, Grant Hill, and Jared Dudley.  Yet it’s Stoudemire  — with the help of David Spade – who is campaigning to start the 2010 All-Star game. 

Once upon a time it made sense for Stoudemire to think about the All-Star game.   In 2004-05, Stoudemire produced 12.9 wins with a 0.214 WP48 [Wins Produced per 48 minutes].  After missing much of 2005-06 with injury, Stoudemire came back to produced 12. 1 wins in 2005-06 [with a 0.217 WP48]. And then in 2007-08, he posted a 0.251 WP48 and produced 14.0 wins. 

Last year, though, Stoudemire’s WP48 dropped off considerably.  Many people blamed the addition of Shaq or perhaps a change in the team’s offensive philosophy.  This year, though, Shaq is in Cleveland. And the team’s offense is supposed to be a return to what we saw before Terry Porter became coach.  Despite these changes, though, Amare’s production is hardly at an All-Star level.  So what’s happened?

Table Two: Evaluating Amare

Table Two reports the box score statistics for Amare.  Relative to what we saw prior to last year, Amare is offering fewer rebounds and blocked shots.  These changes, though, don’t explain the entire gap.  Another issue is the number of shots Amare is taking.  More specifically, Amare is simply taking fewer shots than he did in the past.  And because he’s an efficient scorer, this reduction in shot attempts is reducing his overall production.

Unfortunately for Stoudemire, both Nash (59.6% adjusted field goal percentage) and Richardson (56.8% adjusted field goal percentage) are currently more efficient scorers.  So it’s not clear that giving more shots to Stoudemire (55.8% adjusted field goal percentage) is such a good idea.  Still, it does appear Stoudemire’s drop off in shot attempts – coupled with a decline in rebounds and blocked shots – explains why Stoudemire is no longer that productive.

So here’s what we’ve learned.  In spite of their impressive record, Phoenix is not dramatically improved over what we saw last year.  What improvement we have seen can be linked to Nash and Frye reverting to form.  And Stoudemire – who really wants to be an All-Star – is simply not as productive as he was in the past. 

Can any of this be linked to the departure of Shaq?  I really don’t think so.  Although Shaq bears some responsibility for what’s happened in Cleveland, the small improvement we see in Phoenix – and it is rather small – is really not about  Shaq departing.

- DJ

The WoW Journal Comments Policy

Our research on the NBA was summarized HERE.

The Technical Notes at wagesofwins.com provides substantially more information on the published research behind Wins Produced and Win Score

Wins Produced, Win Score, and PAWSmin are also discussed in the following posts:

Simple Models of Player Performance

Wins Produced vs. Win Score

What Wins Produced Says and What It Does Not Say

Introducing PAWSmin — and a Defense of Box Score Statistics

Finally, A Guide to Evaluating Models contains useful hints on how to interpret and evaluate statistical models.

→ 44 CommentsCategories: Basketball Stories

New York Times Magazine and the Ninth Annual Year in Ideas

December 13, 2009 · 1 Comment

In today’s issue of The New York Times Magazine is The Ninth Annual Year in Ideas.  If one looks under the heading “Sports” one sees a brief discussion of a paper Rob Simmons and I published in the Journal of Sports Economics.  Our paper presents evidence that black and white quarterbacks are not compensated the same. More on this topic is offered in our next book “Stumbling on Wins” (which ships to book stores in two months and should be available in March).

→ 1 CommentCategories: Football Stories

Is Age Finishing Shaq?

December 10, 2009 · 30 Comments

There is one certainty in sports.  For every athlete, a day will come when a player’s production declines.  The decline doesn’t always happen in a consistent pattern (i.e. ups and downs are still possible at an advanced age).  And significant drop-offs don’t happen at the same age for every player.  All we know is that someday, every athlete stops helping.*

To illustrated, consider the WP48 [Wins Produced per 48 minutes] marks Kareem Abdul-Jabbar posted after the age of 30.

30: 0.394

31: 0.348

32: 0.340

33: 0.274

34: 0.206

35: 0.182

36: 0.143

37: 0.225

38: 0.145

39: 0.115

40: 0.045

41: -0.056

An average player posts a WP48 of 0.100.  Kareem was three times the average player prior to 33 years of age.  He was still twice the average player before age 35.  At the age of 36 his WP48 numbers were still above average, but clearly Kareem was no longer outstanding.

But then at age 37, Kareem was suddenly twice the average again. This spike, though, was temporary. His performance at age 38 looked quite similar to what we saw at age 36. And at age 39 he was just barely above average.  In his last season – at age 41 – Kareem’s performance dipped into the negative range.  Yes, one of the greatest centers to play the game was suddenly reduced to Spencer Hawes (Hawes posted a -0.021 WP48 last season) once he passed 40 years of age. 

Now let’s consider the WP48 numbers of Shaquille O’Neal after the age of 30.

30: 0.321

31: 0.287

32: 0.292

33: 0.220

34: 0.106

35: 0.116

36: 0.167

Like Kareem, Shaq entered his 30s as a player producing at a rate well beyond what we see from an average player.  By his mid-30s, though, Shaq was no longer the same player.  Yes, he was still above average.  But the 20-something Shaq that dominated the NBA had vanished.

Although Shaq has clearly declined, the Cleveland Cavaliers still took a chance on acquiring his services.  This chance was motivated by the age and health-status of Ben Wallace.  Last season Big Ben posted a 0.159 WP48.  But his health limited his availability in the regular season and his production in the playoffs. 

So this past summer, Wallace was sent to the Phoenix Suns for Shaq.  It was suspected that Big Ben would retire.  But after being released by Phoenix, Big Ben signed with the Pistons and is now leading Detroit in Wins Produced.

Meanwhile, the Cavaliers decided to take a chance on Shaq.  Yes, it’s likely that people in Cleveland knew that “someday” O’Neal would stop helping.  But it was hoped that “someday” would happen after the 2009-10 season (and after a championship parade in Cleveland).

Unfortunately, there’s evidence that “someday” is happening in Cleveland. 

Table One: The Cleveland Cavaliers after 22 games in 2009-10

Table One reports the Wins Produced of the Cleveland Cavaliers after 22 games.  In addition, it reports what we could have expected from this team had player performance not changed from what we saw last season.  With respect to most players, the assumption of constant performance doesn’t lead us too far astray.  There are, though, two notable exceptions. 

Before getting to Shaq, let’s talk about Zydrunas Ilgauskas.  Last year, Ilgauskas posted a 0.093 WP48 [a mark very close to average]. This season – at the age of 34 – Ilgauskas is posting a -0.051 WP48.  Yes, Ilgauskas is now a 41 year-old Kareem.  Consequently, Ilgauskas is on pace to produce 5.5 fewer wins than what his performance last year would suggest.

For much of his career, Ilgauskas has been an above average (i.e. WP48 in excess of 0.100) but not outstanding performer (i.e. WP48 less than 0.200).  As noted above, though, Shaq has often been amazing.  And even as age has taken its toll, he has still maintained an above average WP48 mark.

At least, until the 2009-10 season began.  Shaq’s WP48 mark this season has only been 0.017.  So at the age of 37, Shaq is a bit worse than the 40-year old Kareem. 

Again, the impact of age is not constant.  So it’s possible Shaq – and Ilgauskas – will bounce back.  But if they don’t, the Cavaliers are simply not going to be what I envisioned before the season started. 

As Table One notes, had everyone maintained what we saw last year, the Cavs would currently be on pace to win 69.3 wins.  Such a record would make the Cavs a clear contender to win a title (which is what I suggested before the season started).  The declines we see with respect to Shaq and Ilgauskas, though, takes 10 wins off of the Cavs projected totals. And that clearly drops the Cavs behind the Celtics and Lakers.

Let me close with two observations.  First – as Table Two suggests – the problems for O’Neal and Ilgauskas are primarily related to shooting efficiency.  Most other numbers for these players haven’t changed from last year.  But shooting efficiency from the field – and for Shaq, also from the line – has declined for both players. And consequently, overall productivity has declined considerably.

Table Two: Shaquille O’Neal and Zydrunas Ilgauskas

Secondly, some people might remember that I have already commented on the Cavaliers troubles.  This first comment, though, came after just seven games (so the sample was even smaller than what we have today).  And at that time, Shaq was playing better (although Ilgauskas was still very bad).  Since that time, though, Shaq has missed time due to injury.  Of course, injuries are part of the problem of age.  But if Shaq can recover and start producing at the level we saw last year, Cleveland can get better.  If not, a season of promise in Cleveland may end up a very big disappointment.

- DJ

* – we talk about age and performance in the NBA in more detail in our next book.

The WoW Journal Comments Policy

Our research on the NBA was summarized HERE.

The Technical Notes at wagesofwins.com provides substantially more information on the published research behind Wins Produced and Win Score

Wins Produced, Win Score, and PAWSmin are also discussed in the following posts:

Simple Models of Player Performance

Wins Produced vs. Win Score

What Wins Produced Says and What It Does Not Say

Introducing PAWSmin — and a Defense of Box Score Statistics

Finally, A Guide to Evaluating Models contains useful hints on how to interpret and evaluate statistical models.

→ 30 CommentsCategories: Basketball Stories

Melo for MVP?

December 9, 2009 · 18 Comments

Carmelo Anthony got off to a very fast start this season.  His performance across his first two games led Henry Abbott – of TrueHoop – to post the following: Carmelo Anthony’s trainer on his MVP-caliber client.  Abbott’s interview with Melo’s trainer explained how Anthony’s game has changed and why he was the league’s MVP (in the view of his trainer). 

The words MVP and Carmelo once again were heard when Melo scored 50 points – including two clinching free throws — against the New York Knicks towards the end of November.   After this game, Chauncey Billups – the starting point guard on the Denver Nuggets – noted the following: “‘Melo is one of the best players in the world. If you’ve got him going like that, then you’ve got to ride him.”

Anthony entered the league in 2003.  Across his first six seasons he has not exactly been part of the MVP conversations.  Last season he received no votes for the award.  And in 2007-08 he only received one 4th place vote – and this was his best career finish.

This season, though, seems different.  Melo currently leads the NBA in scoring.  And the Nuggets – as Table One reports – currently ranks 3rd in the NBA in efficiency differential (offensive efficiency minus defensive efficiency).  In fact, Denver is one of only three teams (after Boston and the LA Lakers) who are on pace to win 60 games this season. 

Table One: Efficiency Differentials after 25% of the 2009-10 Season

There are two factors that appear to dominate voting for the MVP award: Scoring and Team Wins.  Since Melo leads in scoring – and he plays for one of the league’s top teams – he must be part of the conversation. Right?

Well, maybe not.  For Melo to be MVP in 2009-10 he should – at the very least – be clearly better than LeBron James (the 2009 MVP).  We know Carmelo is scoring more points.   And as Table One reports, the Nuggets are doing better than the Cavaliers (a story for another day).  So in terms of scoring and team wins, Anthony is the better player.  But when we look at all the individual statistics – reported in Table Two – we see that King James is clearly doing more than Melo this season.

Table Two: Comparing LeBron James and Carmelo Anthony in 2009-10

The key differences can be seen with respect to shooting efficiency, rebounds, and assists.  When we turn to Wins Produced and WP48 [Wins Produced per 48 minutes] we can see the size of the difference.  As of the games played on December 8, LeBron has posted a 0.396 WP48 and is on pace to produce 25.4 wins.  Meanwhile, Melo is posting a 0.188 WP48 – and if this performance continues – will produce 10.4 wins by the time the season ends.  Yes, Anthony is above average.  But when we look at everything it’s clear that King James is still King (at least in a kingdom of James and Anthony).

Okay, what if we shift our focus to the Nuggets?  Denver currently is posting a 7.36 efficiency differential.  If this mark continues it will be the best the Nuggets have ever done as an NBA team.  So the Nuggets – who reached the conference finals last season – have clearly improved.  But can we attribute this change to Melo?

For an answer we turn to Table Three (wow, three tables in one post).

Table Three: The Denver Nuggets in 2009-10 After 22 Games

Table Three reports what Denver’s players have done this season.  It also reports what the Nuggets could have expected given what their players did in 2008-09.  As one can see, Denver has improved by about seven wins.   Most of this improvement can be tied to the play of Nene Hilario.  Although Hilario is scoring less (due to declines in shot attempts and shooting efficiency), he has improved with respect to rebounds, steals, assists, turnovers, and personal fouls.   And this means Hilario is on pace to produce about five more wins than his performance last year would suggest. 

Not only is Hilario the most improved on this team, he is currently leading the Nuggets in Wins Produced.  Second on the team – although just barely – is Chauncey Billups.  And that means, Melo – the player some think is the best player in the league (and the player Billups thinks is one of the best in the world) – is currently only third on the Nuggets in Wins Produced. 

So is Melo MVP?  If we define this award in terms of scoring and team wins, Anthony has a case.  But if we define this in terms of a player’s contribution to wins, Anthony isn’t even MVP on his own team.

Let me close by noting the play of Ty Lawson.  Currently Lawson is posting a 0.189 WP48 and is on pace to 6.9 wins.   Such production surpasses what we see from Jonny Flynn, Brandon Jennings (yes, Jennings had dropped off quite a bit), and Jrue Holiday (all point guards taken before Lawson).  But all of this is also a story for another day.

- DJ

The WoW Journal Comments Policy

Our research on the NBA was summarized HERE.

The Technical Notes at wagesofwins.com provides substantially more information on the published research behind Wins Produced and Win Score

Wins Produced, Win Score, and PAWSmin are also discussed in the following posts:

Simple Models of Player Performance

Wins Produced vs. Win Score

What Wins Produced Says and What It Does Not Say

Introducing PAWSmin — and a Defense of Box Score Statistics

Finally, A Guide to Evaluating Models contains useful hints on how to interpret and evaluate statistical models.

→ 18 CommentsCategories: Basketball Stories

Big Ben Cannot Save Detroit from Ugh!

December 7, 2009 · 20 Comments

Soon after the 2009 free agent market opened the Detroit Pistons made a huge splash, giving $100 million to Ben Gordon and Charlie Villanueva.  At the time this deal was announced I – as a lifetime fan of this team (with a wonderful team banner on my office wall) – offered a quick response: Ugh!

To understand this response, let’s look at the career numbers for Gordon and Villanueva:

Gordon’s Wins Produced = 15.3

Gordon’s WP48 [Wins Produced per 48 minutes] = 0.059

Villanueva’s Wins Produced = 11.2

Villanueva’s WP48 = 0.074

An average player posts a 0.100 WP48, so both Gordon and Villanueva had career numbers that were below average.  Given such numbers, Detroit’s $100 million investment was unlikely to generate the return the Pistons envisioned.

Well, we are now 20 games into the Gordon-Villanueva era.  And the early returns – despite winning three of the last four games – are still “Ugh”.

Table One reports what the Pistons have done – with respect to Wins Produced and WP48 – after 20 games.

Table One: The Detroit Pistons After 20 Games in 2009-10

The Pistons’ efficiency differential (offensive efficiency minus defensive efficiency) is currently -2.0.  This mark – and the team’s Wins Produced – suggests the Pistons will win 36 games this season (assuming – incorrectly – that minutes played stay the same the rest of the year).  As Table One indicates, about 7.7 of these wins can be traced to the production of Gordon and Villanueva.  More importantly, Gordon’s WP48 is 0.084 while Villanueva’s WP48 stands at 0.073.  Yes, the $100 million players are still below average.

The good news is that Ben Wallace – after three years away from the Motor City – has returned.  And his productivity – after years of injuries – is quite impressive for a 35-year old player.  As Table One reports, Big Ben’s WP48 is currently 0.281 and his projected Wins Produced stands at 14.8. 

Here is what was reported when Wallace was signed for $1.3 million last August:

In Detroit, the Pistons plan on using Wallace as a backup to Kwame Brown. The Pistons were especially thin on their front line last season and still believe that Wallace can defend and rebound — albeit not at the same pace as his last stint with the Pistons.

Although it may have been the plan to have Wallace come off the bench, that’s not what happened.  Big Ben has started all twenty games, and his productivity – although not quite what he did last time he was in Detroit (0.332 WP48 in 2005-06) – is simply amazing for an old basketball player.

Again, this is not what the Pistons expected.  And if we subtract Wallace’s projected productivity from the rest of Detroit’s roster we see a collection of players that are only expected to produced 21.3 wins.  In sum, without Big Ben – a player who was not expected to play much or play this well — Detroit would be very bad.

Fans of the Pistons (not this fan, but perhaps other fans) might note that so far Tayshaun Prince and Richard Hamilton haven’t played much.  Last year, though, Hamilton was below average (WP48 of 0.052).  And although Prince was above average (WP48 of 0.122), he only produced 7.8 wins.  In sum, even with Prince and Hamilton the Pistons wouldn’t be that good.

Of course, in the Eastern Conference – where the list of truly good teams only includes Boston, Cleveland, Orlando, and Atlanta – “not that good” might still be good enough for the playoffs.   But for $100 million, the Pistons fans probably expect a team that can seriously contend in the East.  And the signings of Gordon and Villanueva – as expected – are probably not going to make that happen.  So for this Pistons fan, “Ugh!” is still the word.

- DJ

The WoW Journal Comments Policy

Our research on the NBA was summarized HERE.

The Technical Notes at wagesofwins.com provides substantially more information on the published research behind Wins Produced and Win Score

Wins Produced, Win Score, and PAWSmin are also discussed in the following posts:

Simple Models of Player Performance

Wins Produced vs. Win Score

What Wins Produced Says and What It Does Not Say

Introducing PAWSmin — and a Defense of Box Score Statistics

Finally, A Guide to Evaluating Models contains useful hints on how to interpret and evaluate statistical models.

→ 20 CommentsCategories: Basketball Stories

The Impact of Losing Greg Oden

December 6, 2009 · 18 Comments

My latest post for Huffington Post Sports is a comment on the latest injury suffered by Greg Oden. Here is how this column begins:

The most coveted player in the 2007 NBA draft was Greg Oden. The elation of the draft, though, has been followed by much disappointment. An injury cost Oden his entire rookie season. Last year he was only healthy enough to play 1,314 minutes across 61 games. So after two years, Oden hadn’t played much. And now, after just 21 games, he’s going to miss the entire 2009-10 season.

The fact that Oden hasn’t played is certainly disappointing. But a more important question is how much it matters that Oden isn’t going to play anymore this year. And that question depends upon how well Oden has performed.

Oden averages less than 24 minutes per game. So his per game statistics (i.e. point scored, rebounds, etc…) don’t look very impressive. When we turn to per-minute performance – or per-48 minutes performance – Oden’s impact is far more striking. Read the rest at Huffington Post Sports

The primary purpose of this post was to highlight how well Oden had played this season (to see how good Oden has been, please read the post).  Certainly it’s possible that the Blazers could overcome this loss.  But it seems fairly likely that Portland’s season is not going to go quite as well as I thought earlier this year

And I should add – as others have noted – the Blazers franchise seems cursed.  First it was Bill Walton (see Is it Teamwork? A History Lesson).  Then we see the story of Sam Bowie (see A Little Bit of Hindsight Bias: Reviewing the Drafting of Sam Bowie).  And now we have the story of Greg Oden.  Although all of this is just a coincidence, one suspects that any highly touted center drafted by the Trail Blazers in the future is going to be more than just a bit concerned about starting his career in Portland.

- DJ

The WoW Journal Comments Policy

Our research on the NBA was summarized HERE.

The Technical Notes at wagesofwins.com provides substantially more information on the published research behind Wins Produced and Win Score

Wins Produced, Win Score, and PAWSmin are also discussed in the following posts:

Simple Models of Player Performance

Wins Produced vs. Win Score

What Wins Produced Says and What It Does Not Say

Introducing PAWSmin — and a Defense of Box Score Statistics

Finally, A Guide to Evaluating Models contains useful hints on how to interpret and evaluate statistical models.

→ 18 CommentsCategories: Basketball Stories

The Inconsistent Quarterback Story Told Again in Less than 3,000 Words

December 6, 2009 · 22 Comments

The Wages of Wins discusses how performance can be measured in both the NBA and NFL.  The Wages of Wins Journal, though, almost exclusively focuses on the NBA.   Why isn’t performance in the NFL discussed more frequently?  The answer to this question can be illustrated by comparing the play of Jay Cutler and Kyle Orton. 

Cutler and Orton Defy the Pundits

The Chicago Bears finished the 2008 season with a 9-7 record, a mark that fell just short of qualifying for the playoffs.  In discussing Chicago’s problems, people tended to focus on the team’s quarterback.  As Table One reports, Kyle Orton – the Bears starting quarterback in 2008 — was ranked 25th (out of 32) quarterbacks in both the NFL’s QB Rating system and the Wages of Wins metrics (i.e. QB Score, Net Points, Wins Produced).

Table One: Final Quarterback Rankings for 2008

In the offseason it became clear that Jay Cutler – a player who ranked 7th in Net Points per Play (and Wins Produced per 100 plays or WP100) – was available.  So the Bears sent Kyle Orton – plus two first round draft picks and a third round pick – to the Broncos for Cutler.  Fans of the Bears rejoiced at this move.  And fans of the Denver Broncos became very, very angry.  In the pre-season the views of both groups of fans were confirmed.  The Bears finished the exhibition season with a 3-1 mark, while the Broncos – led by a less than impressive Orton – finished 1-3.  Many NFL pundits were heard expressing the conventional wisdom:  You simply don’t trade away a “franchise” quarterback. 

And then the real games were played.  As December begins, the Broncos are 7-4 while the Bears are 4-7.  When we look at each quarterback’s stats – reported in Table Two – we see that the 2008 result has been essentially reversed.  Orton now ranks 9th in the NFL in Wins Produced per 100 plays (Wins100) while Cutler is ranked 25th. 

Table Two: Week Twelve Quarterback Rankings in 2009

The reversal in the ranking of these two quarterbacks is hardly unique.  Nine of the quarterbacks ranked in the top 10 this year qualified for the rankings last year.  Of these nine, only four – Drew Brees, Peyton Manning, Philip Rivers, and Matt Schaub – were ranked in the top ten at the end of last year.  And we see the same story at the bottom of the rankings.  Seven of the players ranked in the bottom ten qualified for the rankings last year.  Of these, only two – JaMarcus Russell, and Derek Anderson – ranked in the bottom ten in 2008.

Despite such inconsistency, fans of the NFL – and apparently at least some decision-makers – can be impressed by a quarterback’s past numbers.  Consequently, the Bears can be tempted to give up three draft picks and a starting quarterback for an apparent “franchise” signal caller.  And the Chiefs can give up a second round pick and significant dollars for Matt Cassel (currently ranked 26th). 

The problem facing decision-makers in the NFL is the numbers – which are often cited – don’t tell us very much about the future performance of a quarterback.  A quarterback’s statistics depend on his teammates and the quality of his coaching.  Change the teammates and coaches and you often see the numbers change as well.  Unlike basketball – where player statistics are remarkably consistent from season to season – football numbers suffer from very significant interaction effects.  This means those numbers – which told us that Cassel and Cutler are “great” quarterbacks – may not tell us much about what these quarterbacks will do when these players change teams.

And it’s important to note that this isn’t just some numbers or some quarterbacks.  Less than 25% of a quarterback’s completion percentage and passing yards per attempt are explained by what the quarterback did with respect to these statistics last season.  Less than 10% of touchdowns per pass attempt this season are explained by last year; and when we turn to interceptions per attempt, explanatory power falls to less than 2% (these results come from an examination of 399 quarterbacks who played consecutive seasons from 1994 to 2007).  When we turn to measures such as QB Score, the NFL’s quarterback rating, or the numbers at FootballOutsiders.com, again we see inconsistency (explanatory power is less than 20%). 

Such results tell us that what we see from Cutler and Orton in 2008 and 2009 should not be surprising.  Predicting performance of quarterbacks in the NFL is simply very difficult (and this is not just the story I tell, but also the story told by Brian Burke at Advanced NFL Stats).

This is really a fascinating story.  But the story was essentially told in The Wages of Wins.  And I told it again during the 2006, 2007, and 2008 NFL season.   Consequently, this is what I said towards the end of my discussion of the final quarterback rankings in 2008: “…the measurement of performance in football really only tells one story.  The interaction effects in football cause the performance statistics to be inconsistent.  So the players we see perform well today are not necessarily going to perform well tomorrow.  Although I like telling that story, it’s really about all I ever say about the NFL. Consequently, this very long post … might be my last post on football.”

Looking at the NFL Draft Again

But now another aspect of this story has sparked some interest.  Rob Simmons and I recently wrote an academic article examining the relationship between where a quarterback is selected in the draft and how he performs in the NFL.  For many the results were surprising.  As Rob and I report, where a quarterback is taken in the draft is not related to how that quarterback performs in the NFL. 

Once again… it’s difficult to predict the future performance of NFL quarterbacks.  On draft day NFL decision-makers have an even more difficult challenge.  People in the NFL must project how well a quarterback will play in the NFL before he ever plays with — and against — NFL talent.  Now if predicting performance of actual NFL quarterbacks is hard, what should one expect to see when it comes to projecting performance of quarterbacks that are not in the NFL?

Well, here is what Rob and I found.

1.  We did find several factors that predict where a quarterback will get drafted.  Specifically, we find that taller, faster, and smarter (i.e. better Wonderlic scores) quarterbacks get drafted first. 

2. The factors that predict draft performance, though, don’t predict NFL performance. 

3. Given this result, we shouldn’t be surprised that where a quarterback is drafted doesn’t predict how well a quarterback will perform in the NFL.

This is how point #3 was described a few days ago:

… here is a sample of what we found.  After a quarterback has played five seasons in the NFL (minimum 500 career plays), here are the correlation coefficients between draft position and various career statistics:

Completion Percentage: -0.01

Passing Yards per Pass Attempt: -0.02

Touchdowns per Pass Attempt: -0.12

Interceptions per Pass Attempt: 0.00

QB Score per Play: -0.01

Net Points per Play: -0.02

Wins per Play: -0.02

QB Rating: -0.06

Directly below this data — and I mean, directly below this data – I wrote the following sentences:

Our data set runs from 1970 to 2007 (adjustments were made for how performance changed over time). We also looked at career performance after 2, 3, 4, 6, 7, and 8 years.  In addition, we also looked at what a player did in each year from 1 to 10.  And with each data set our story looks essentially the same.  The above stats are not really correlated with draft position.

We should note that although draft position and performance are not related – and our story is the same regardless of when we look at the relationship — draft position and salary are clearly correlated.  To illustrate, JaMarcus Russell has collected millions of dollars to play quarterback in the NFL.  But he clearly has not performed at a level consistent with all those dollars.  And a similar story can be told about David Carr, Ryan Leaf, Tim Couch, Joey Harrington, etc…  Quarterbacks who are drafted early clearly get paid more. They just don’t seem to perform any better.

Reacting to Some Reactions

There have been a few reactions to this result that I would like to address.  Here is a sample of what I have seen.

1. A problem with reading comprehension

Let me start with a response that suggests people don’t always read what’s being said. Despite the sentences I highlighted above, I have read statements like the following (this is comment #10 on Jason Lisk’s post at Pro-Football Reference.com from one of the bloggers that Steven Pinker cited):

The Berri choice to exclude QBs who didn’t play five years in the league is a pretty fundamental error to make.

Hmmm… pretty fundamental error?  Perhaps a more fundamental error is not reading a single paragraph that, once again, appeared directly beneath the results I posted. 

2.  Per-play vs. Aggregate Measures, Part One

Beyond the issue of reading comprehension skills is the objection some people have voiced to how we examined the correlation between draft position and NFL performance.  Rob and I focused on per play measures — such as completion percentage, yards per pass attempt, interceptions per pass attempt, touchdowns per pass attempt, NFL’s quarterback rating, QB Score per play, Wins Produced per play, and Net Points per play – in examining the link between draft position and NFL performance (again, at a host of different points in a quarterback’s career). 

People have argued, though, that it’s better to look at aggregate measures such as total touchdown passes or total yards.  Such examinations show a stronger correlation between draft position and performance (although not that strong).  And these examinations show that “better” quarterbacks – where “better” is defined in terms of total touchdowns or total yards – tend to be picked first (again, this is not a strong tendency).  Of course, one could define quarterbacks in terms of total interceptions thrown and show the opposite.  Quarterbacks chosen first in the draft throw more interceptions, and since interceptions are not good, this means quarterbacks taken first tend to be “worse”.

The results with respect to interceptions — and passing yards and touchdowns — are driven by the fact quarterbacks taken first tend to play more.  So by focusing on the aggregate measures one is really looking at the link between one decision (a team liked the quarterback on draft day) and another (the team decided it will play the quarterback it liked on draft day). 

The persistence of draft day evaluations in the NFL is reminiscent of a study by Colin Camerer and Roberto Weber offered in a 1999 article looking at the NBA draft.  The Camerer-Weber article looked at the factors that predicted minutes per game in the NBA.  What they found was that draft position could still predict playing time – even after performance was controlled for – years into a player’s career.  It wasn’t that performance didn’t predict playing time.  No, the important finding was that draft position – independent of NBA performance – predicted playing time.  Such results suggest that NBA teams had trouble ignoring sunk costs in making decisions.    

This is essentially what Jason Lisk reported (in a less sophisticated study) with respect to quarterbacks and the NFL draft.  Even after controlling for performance, Lisk reported that draft position predicted a quarterback’s playing time.

Such a story confirms the approach Rob and I took in our examination of quarterbacks and the NFL draft.  Aggregate numbers are biased because draft position is an independent predictor of playing time.  Therefore, one should focus on per-play metrics.

3. Per Play vs. Aggregate Measures, Part Two

One doesn’t need to consider the bias in playing time, though, to defend the choice of per play measures.   In evaluating players in sports we tend to focus on measures that consider how many opportunities given the player.  For example, in baseball we tend to look at batting average, on-base percentage, slugging percentage, OPS, ERA, etc…  In basketball we tend to focus on per-minute measures.  And in football, the basic quarterback rating measure is entirely defined in terms of performance per pass attempt.   

We tend to think quarterbacks are “better” when they have a higher completion percentage and throw fewer interceptions per pass attempt.  Draft position, though, doesn’t predict these measures (or any of the per play measures reported above).  But if teams were getting it “right” on draft day, shouldn’t the quarterbacks taken first have a higher completion percentage, or get more yards per pass attempt, or throw fewer interceptions per pass attempt, or produce more wins per play, etc…?

4. Draft Position and Never Playing

Steven Pinker had one more reaction to the construction of our study.  Pinker – in the New York Times – noted that lower drafted quarterbacks don’t “merit many plays”.  And this somehow establishes that teams are drafting correctly.  Again, though, this is using one evaluation to justify another.  We expect that NFL teams are going to discount players who were already discounted. 

For us to study the link between draft position and performance, we can only consider players who actually performed.  It’s possible that those quarterbacks who never performed were really bad quarterbacks.  But since they never played, we don’t know that (and Pinker also doesn’t know this).  What we do know is that for those quarterbacks who did play, draft position and performance aren’t related.   

Another way to think about this is to consider the careers of Kurt Warner and Tom Brady.  The numbers tell us that Warner and Brady are among the best quarterbacks of the past decade.  Yet both quarterbacks were passed over by teams on draft day (Warner was never selected and Brady was a 6th round draft choice). Are we to believe that Warner and Brady were the only quarterbacks passed over who could really play?  It seems likely that at least some of the quarterbacks who never played really could have contributed to an NFL team.  But once again, we will never know, since these quarterbacks never played.

And one should add once again… draft position and salary are clearly related.  Teams pay much more for a quarterback taken with one of the first ten slots in the draft.  But the evidence doesn’t indicate that these quarterbacks perform better than those taken later in the first round, second round, third round, etc…. 

5. Reacting to an Odd Interpretation of Our Results

All that being said, let me say what we are not saying.  Jason Lisk – in the blog post linked to above — notes that past NFL performance predicts future playing time.  Such a result is not surprising.  Past performance predicts future salaries in the NFL (hence Cassell gets a big payday after last season in the NFL).  How Lisk interpreted these results, though, was somewhat odd.  Here is what Lisk said towards the end of his post:

If you believe that the only reason Carson Palmer has played a lot more than Gibran Hamdan is because Palmer was drafted alot higher, then you can accept Gladwell’s position.

I certainly don’t recall Malcolm Gladwell saying that draft position was the “only” (this is Lisk’s word) predictor of future playing time.  What Gladwell argued – and what we argued – is that draft position couldn’t predict future performance.   At no point have I ever argued that NFL decision-makers don’t consider past performance in determining playing time or salaries.  In fact – as noted above – we have argued that NFL teams do consider past performance.  Unfortunately, past performance is a poor predictor of the future.  Hence, it’s not clear that the acquisitions of Cutler or Cassell will ever generate the returns envisioned when those players were acquired.

So we agree with Lisk when he argues that past performance predicts future performance.  Where we don’t agree is with the assertion that at some point we argued something else.

Another Study Confirming Our Story

Let me close with a comment left by fellow economist Kevin Quinn at Malcolm Gladwell’s blog (you have to go through a large number of comments to get to Quinn’s thoughts):

I am a sports economist and have investigated the predictability of eventual NFL performance by QBs based on the information available just before the draft. While my approach and methods differed somewhat from those employed by… Dave Berri, my results essentially confirm his findings.

Kevin co-authored a working paper that examined the NFL draft and came to – as Kevin notes – a very similar conclusion (across a smaller sample then Rob and I considered).  Again, this result –given what we see when we look at the consistency of performance in the NFL – is not surprising. 

And hopefully this extremely lengthy post answers all the reactions to the study Rob Simmons and I published (and yes, this post is less than 3,000 words – although not very far below this mark).

- DJ

The WoW Journal Comments Policy

For more on the Wages of Wins football metrics see

The New QB Score

Consistent Inconsistency in Football

Football Outsiders and QB Score

The Value of Player Statistics in the NFL

→ 22 CommentsCategories: Basketball Stories

Maybe It Is Time to Stop Blaming the Coach in Toronto

December 4, 2009 · 11 Comments

The Toronto Raptors lost to the Atlanta Hawks by 31 points on Wednesday night.

The loss gave the Raptors 13 defeats in their first 20 games.  The team’s efficiency differential – offensive efficiency (points scored per possession) minus defensive efficiency (points surrendered per possession) – of -5.9 suggests the Raptors are only going to win about 26 games in 2009-10.  In sum, the only NBA team in Canada isn’t very good.

After the Atlanta game, there were grumbles out of Toronto that the players are blaming the coach – Jay Triano — for their troubles.  (HT to TrueHoop).  Such grumbles are reminiscent of the story told a year ago in Toronto.  Last December, the Raptors decided to fire head coach Sam Mitchell (and replace him with Triano). The thinking at the time was that an 8-9 record was simply unacceptable.  And somehow if the players had a different coach, life in Toronto would be different.

At the time I expressed a great deal of skepticism regarding this perspective.  How players perform on the court determines the outcome of each game.   And coaches don’t appear to have much impact on the player’s performances.  Essentially, if you give a coach productive players a team will tend to win; and if a coach doesn’t have many productive players he gets to lead a loser.  The Raptors of last year didn’t have many productive players.  Consequently, we shouldn’t have been surprised that the Raptors only won 25 more games after Mitchell left the scene.

This past summer the Raptors seemed to get this message.  Toronto decided to keep Triano as head coach, while a number of new players were added.  Unfortunately – as the early results indicate — most of the new players haven’t helped.  Again, a differential of -5.9 suggests this team is going to struggle to reach 30 wins this year.

If we move from efficiency differential to Wins Produced, we can see where Toronto’s team makeover went wrong. 

Let’s start with the good news.  Chris Bosh – the team’s star – is on pace to produce 13.3 wins this season.  Jose Calderon – who led the Raptors in Wins Produced in 2008-09 – has struggled.  But Calderon is still on pace to produce 5.9 wins in 2009-10.

So Bosh and Calderon are on pace to produce 19.2 wins.  And the team is on pace to win about 26 games.  A bit of simple math reveals that everyone not named Bosh and Calderon must be on pace to produce only about seven wins.

The perception in Toronto is that everyone else is led by Hedo Turkoglu.  Toronto gave Turkoglu a $53 million contract this past summer.  Although Turkoglu was a sought after free agent last summer, he really has only been an average player across his career.  And he’s now 30 years of age (young for an economist, old for a basketball player).  Hence, we shouldn’t be surprised that he’s only on a pace to produce 2.9 wins this season.  His Wins Produced per 48 minutes [WP48] is 0.052, a mark that’s well below the average mark of 0.100 (and even if he was average, he wouldn’t be helping that much).  So the Raptors – as one could have expected — aren’t getting much return on this investment.

In addition to Turkoglu, the Raptors also held the 8th pick in the 2009 NBA draft (a reward for being so bad last season).  With this pick the Raptors selected DeMar DeRozan.  His draft position suggests DeRozan could be above-average.  His college numbers tell a very different story.  Of the 47 players taken out of college last year, DeRozan ranked 39th in PAWS40 [Position Adjusted Win Score per 40 minutes].  The early returns on DeRozan are consistent with this college numbers.  After 20 games, his WP48 stands at 0.013.  Again, that’s below average. 

Although DeRozan’s production is quite low, it’s well beyond what the Raptors are getting from Antoine Wright.  Last season Wright produced -2.4 wins.  This season he’s on pace to produced -5.0 wins.

Turkoglu, DeRozan, and Wright are not the only players the Raptors added.  Toronto also added Amir Johnson, Marco Belinelli, and Jarret Jack.  Of this trio, only Johnson was above average last season (WP48 of 0.145).  And of this trio, only Johnson is above average this season (WP48 of 0.169).

Of the players who have played 200 minutes this season, only Bosh, Calderon, and Johnson are above average.  Everyone else – and that includes Andrea Bargnani [WP48 of 0.043], Belinelli, DeRozan, Jack, Turkoglu, and Wright – are below average. 

Again, none of this should be surprising. The Raptors struggles are simply not about their coach.  This really is all about the players.  Toronto has assembled a roster of players with very few productive performers.  And these players can grumble about their coach all they want.   But until the Raptors employ better players, a better outcome is not likely to be seen.

- DJ

The WoW Journal Comments Policy

Our research on the NBA was summarized HERE.

The Technical Notes at wagesofwins.com provides substantially more information on the published research behind Wins Produced and Win Score

Wins Produced, Win Score, and PAWSmin are also discussed in the following posts:

Simple Models of Player Performance

Wins Produced vs. Win Score

What Wins Produced Says and What It Does Not Say

Introducing PAWSmin — and a Defense of Box Score Statistics

Finally, A Guide to Evaluating Models contains useful hints on how to interpret and evaluate statistical models.

→ 11 CommentsCategories: Basketball Stories