The notion that Carmelo Anthony is not Denver’s most productive player has been noted in this forum in the past.  And this past year this story has remained the same.  Anthony finished the 2009-10 season with a 0.112 WP48 [Wins Produced per 48 minutes] and 6.1 Wins Produced.  Of the eight players who played at least 1,000 minutes for the Nuggets this past season, five players – Chris Andersen, Chauncey Billups, Nene Hilario, Kenyon Martin, and Ty Lawson – posted higher WP48 marks.  And Hilario, Billups, Andersen, and Martin produced more wins.

With these number in mind, consider the following first few paragraphs from a story published by Mark Kizla in the Denver Post today:

After carrying an NBA franchise and the basketball dreams of a city on his shoulders for seven long years, Nuggets forward Carmelo Anthony is beginning to show the strain.

How much more of this can Melo take?

In a 117-106 loss to Utah that put the Nuggets on the brink of elimination from the playoffs, Denver looked like the same frustrating franchise it has been for most of Anthony’s career.

If Melo can’t do it, nobody can.

“I’m trying, I’m trying to beat them. I’m trying to do everything I can in my power to beat the Jazz,” Anthony said Sunday. “But, at the end of the day, I need some help. I’m not sitting here pointing fingers or nothing. As a unit, we’ve got to do this together. I can’t do this by myself.”

This article suggests that Melo has been carrying Denver throughout his career.  And again, I think the numbers suggest otherwise.

However, in this particular post-season, Anthony might have a point.  Here is how Win Score per 48 minutes [WS48 or the simplified version of WP48] has changed for each of the regular rotation players on the Nuggets as we moved from the regular season to the post-season [following numbers are playoff WS48 minus regular season WS48]:

• Carmelo Anthony: +3.3
• Arron Afflalo: +2.8
• J.R. Smith: +1.1
• Kenyon Martin: -0.8
• Nene Hilario: -3.3
• Chauncey Billups: -4.2
• Ty Lawson: -5.9
• Chris Andersen: -6.1

Most players tend to see productivity decline in the playoffs.  This is because players are playing better opponents and the pace of the game tends to slow.  Melo, though, is playing better and the Nuggets are still losing.  This tends to support the argument that Denver’s success is really not about Melo.  His supporting cast is really the key to this team’s success.  And even with Melo playing much better, Denver is still losing because the primary producers of wins on this team are just not playing well.

And why is this important?  I picked Denver in the TrueHoop challenge.  This was the hardest series to call, and I essentially was guessing.  After Utah lost Andrei Kirilenko I felt very good about my choice.  But then the key players on the Nuggets stopped producing. Consequently my drive to repeat is being threatened.  One would think that this alone would inspire Denver’s players to try harder.  I sense, though, that my plight is not being considered.

Let me close by noting that fans of Utah – a group that surrounds me in Cedar City – are very happy.  Repeating the above analysis for Utah reveals that the happiness I see is primarily due to the play of Paul Millsap [6.2 increase in WS48] and Deron Williams [3.1 increase in WS48].  If these two players keep playing well – and the aforementioned Denver players keep struggling – I might continue to be the only person in Utah who is not enjoying the NBA playoffs. 

- 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.

It will be a few more days before I complete my analysis of the 2009-10 regular season.  That analysis will include updating the Wins Produced model with the 2009-10 team data and evaluating each player’s productivity.  So the numbers I have right now will change a bit (not very much, though).  Given the numbers I have right now, though,  I can say that Aaron Brooks posted a 0.037 WP48 [Wins Produced per 48 minutes] this past season.  And in 2008-09, his WP48 was -0.004.  So yes, Brooks improved.  But not much. And he would not be the Most Improved Player for the 2009-10 season if Wins Produced was the metric of choice.

For the media, though, Wins Produced is not the tool used to evaluate the players.  The story announcing that Brooks had won this award noted the primary metric the media uses to measure player performance: His (Brooks) scoring average went up 8.4 points from 2008-09, the highest increase of any qualifying player.

Yes – and this is not a surprise – scoring is the story. By the way, here is what I said last fall when discussing what we should see from Houston in 2009-10:

Aaron Brooks – who may lead this team in scoring – will be considered one of the best point guards in the game.

Let me close by noting that the article announcing this award argued that Houston failed to prove the doubters wrong this season.  This argument rests on the observation that Houston failed to make the playoffs, as many expected.  But this argument misrepresents what was said about Houston when the season started. Before the season started it was expected that Houston was going to be a below average team.  I argued, though, that this team should win more than 40 games but struggle to make the playoffs (in other words, not be as bad as expected).  This is indeed what happened.  And as a consequence, Brooks got to collect some hardware. 

Okay, I need to get back to those Freakonomics questions.  This process is going slow since I am also watching the NFL draft (as I have noted in the past, this is the best day of the year for fans of the Lions).

- 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.

A quick note… we have many questions from Freakonomics to answer (would like to get these answered by tomorrow).  Plus this is the last day of classes at Southern Utah University.  So this post is going to be short (yet hopefully still interesting).

ilikeflowers – a frequent commentator in this forum – asked the following question last night: has there ever been a 0.400+ player who didn’t reach the finals in their career?

To answer this question we need a list of all players who posted a 0.400 WP48 [Wins Produced per 48 minutes] in a season.  Our data only goes back to 1977-78.   Plus, I am going to restrict the examination to all players who appeared in at least 41 games and played more than 30 minutes per contest.

Given these restrictions, here are the 14 players who made this mark (in alphabetical order):

• Charles Barkley
• Larry Bird
• Kevin Garnett
• LeBron James
• Magic Johnson
• Michael Jordan
• Shawn Marion
• Hakeem Olajuwon
• Shaquille O’Neal
• Chris Paul
• David Robinson
• Dennis Rodman
• Ben Wallace
• Bill Walton

From this list, only Chris Paul and Shawn Marion have failed to make it to the NBA Finals. 

Beyond that observation, one should note that only twelve teams have ever employed such a player (Boston, Chicago, Cleveland, Detroit, Houston, LA Lakers, Minnesota, New Orleans, Philadelphia, Phoenix, Portland, San Antonio).  And only Chicago, Detroit, LA Lakers, and San Antonio have had two players reach the 0.400 mark in their uniform.

At the midpoint of this season, though, Kevin Love of the Timberwolves was above the 0.400 mark.  Had Love maintained this production (he didn’t by the way), then Minnesota would have joined the list of teams that once employed two 0.400 players.  And of these teams that drew a pair, only Minnesota would have failed to reach the NBA Finals. 

This point is important because I saw a rumor (this was a few weeks ago and I don’t wish to find the link) that the T-Wolves are thinking of giving up on Love.  From their perspective, Al Jefferson is the better power forward. 

So this is one way your favorite team can get better this summer.  Give Minnesota something for Love.  Okay, that won’t work if your favorite team is the T-Wolves.  If that is the case… well, how about those Twins (or Vikings)?

- 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.

And we have a winner!!

The fourth contest in the Stumbling on Wins promotion was as follows:

There are four NBA playoff games on Sunday involving Orlando, Charlotte, Oklahoma City, LA Lakers, San Antonio, Dallas, Portland, and Phoenix.  Which player – in these games – will post the highest PAWS?  Please give a name and also your guess for the player’s PAWS in Sunday’s game.

To win this contest you had to guess both a player and his PAWS – or Position Adjusted Win Score.  There was come confusion last week on how PAWS is calculated.  So before I get to the winner, let me provide an example.

Dirk Nowitzki posted a 0.569 Win Score per minute on Sunday.  An average power forward would posts a 0.215 Win Score per minute, so Nowitzki’s Position Adjusted Win Score per minute would be 0.354 (0.569-0.215).  Since he played 40.4 minutes, his PAWS would be 14.3 (0.354*40.4).

Although this mark is quite good, it only ranked second on Sunday.  The player who posted the highest PAWS was Gerald Wallace.   Wallace is primarily a small forward, but probably played some time at power forward on Sunday.  But even with some time spent at power forward, I still have Wallace posting a 16.2 PAWS. 

There were three people who guessed Wallace would post the highest PAWS.  Of these three, Mark – with a guess of 16.5 – came the closest.  So Mark wins an autographed copy of Stumbling on Wins!!

We will be having another contest soon.  When I figure out what that is I will post the contest. 

- DJ

The WoW Journal Comments Policy

The 2010 True Hoop Stat Geek Smackdown has begun.  In introducing this year’s line-up, Henry Abbott made the following statement: “….2009 champion David Berri is all over the Web promoting his book about the foolish mistakes of professional sports executives. I’ve had a few e-mails from NBA front-office people eager to see him get his comeuppance.”

Upon reading this words I thought… “are teams going to lose in the playoffs just to see me lose this contest?” 

Okay, seriously (or as serious as we get here)… here are a few thought on this reaction.  Much of what we say about human decision-making in Stumbling on Wins can be found elsewhere in the behavioral economics literature.  Much of the behavioral economics literature, though, is based on laboratory experiments.  And although such experiments reveal that people do not always behave rationally, subjects in experiments conducted by researchers like Dan Ariely (see Predictably Irrational) are anonymous.  So these subjects probably do not bear any ill-feelings towards Ariely or other researchers.

The criticism of experiments, though, is that real-life is not a laboratory. In the real world – so the story goes – people do a much better job of understanding costs and benefits.  And thus, in the real world, people should be rational.

As we note Stumbling on Wins, we are not sympathetic to this critique.  And what happens in sports serves as a very effective rebuttal.  What happens in the world of sports is extremely real to the decision-makers employed in this industry.  Furthermore, such decision-makers – relative to what we see elsewhere – are given an abundance of information and clear motivation to get the decisions right.  But as published study after published study indicates, this is not happening.  Hence the need for our book.

So we believe our book is an important contribution (okay, how about just “a contribution”?) to the behavioral economics literature.  However, there is a downside to research in sports.  The people we talk about are very real people. And naturally, when real people see their decisions questioned, some hostility results.

Oddly enough, though, many people in sports appear to agree with our basic conclusion (and I am not just referring to the sports executives I have personally talked with who seem quite happy with our research).  Sports teams are increasingly reaching out to statistical consultants.  Turning to such people is an admission that the traditional methods are not working.  In other words, teams are admitting that in the past, they were indeed stumbling on wins. 

As G.I. Joe would say, though, knowing is only half the battle.   Teams now know that statistical analysis is necessary.  But which analysis should be employed is the other half of the problem.  As I have noted in the past, some models teams have employed are not as helpful as advertised.

Of course, saying that means another group of people are rooting against me.  And I sense they are all likely to be made happy by the playoffs.  When it comes to analyzing teams, most analysts take the same approach.  The better teams have the highest efficiency differential (offensive efficiency minus defensive efficiency).  Homecourt advantage also helps.  With these two pieces of information, every person in the TrueHoop contest reached the same conclusion on six out of eight opening round series. The lone exceptions – Denver vs. Utah and Dallas and San Antonio – are series where differential and homecourt advantage tell a different story.  In these series, I think we all took an educated guess (with the emphasis on guessing). 

The winner of this contest will be the person who guesses on series like these the best. Yes, that could be me again.  But it seems unlikely. 

So if you are rooting against me, it seems likely that a bit of happiness will come into your life in the future.  But if you are an NBA executive ignoring statistical analysis, such brief periods of happiness are going to be followed by unhappiness.   In other words, a comeuppance is coming if you keep ignoring statistical evidence in making decisions.

- DJ

The WoW Journal Comments Policy