Monthly Archives: July 2011

Getting Freaky with Sports Economics

Posted on by
1

That's not a football!

Just as a shout out our esteemed General Manager of the Wages of Wins Network – Dr. David Berri – was asked to comment on several sports related economics issues over at the Freakonomics blog and you should check it out if you haven’t already

With the NFL Lockout Just About Over, a Sports Economist Weighs In

Dave was asked to answer a few questions about sports. I’ll give you the question and the short answer and you can check out the full article to read Dave’s full answers.

  1.  Will the lockout impact consumer demand? No.
  2. How does this deal impact the returns to owners and players? The owners get a better deal. The veterans get a better deal. Those with rookie contracts get fleeced.
  3. What will free agency look like once the deal is ratified? Free agency is going be chaotic and messy.
Hope you guys enjoy the article and make sure to leave feedback at the Freakonomics blog if you like what Dave wrote!

Get a great player and win! The NHL vs. the NBA

Posted on by
2

Dre Alvarez (@nerdnumbers) is a Co-Editor for the Wages of Wins Network and is also in charge of handling the stats data. He’s a long time fan of Colorado Sports, depending on the weather. He’s an even bigger fan of the stats, data and all things nerdy.

Lessons in being a GM

Today I’ll be giving a lesson in how to be a GM in not one, but two sports. The NBA and NHL both have their ideas about how to improve a team. I’ll address the notion that an NBA team needs a superstar to contend and the theory that an NHL team needs a top goalie.

You Need a Star to Contend in the NBA

In the NBA everyone knows to be a contender your team needs a star. This thinking is actually quite accurate. I’ll define a star as a top 25 player in the NBA using the Wins Produced metric. As a GM if you knew all the stats of last season could you find a star? Let’s take a look at the top 25 stars of this season with their last season rank and numbers for perspective.

Team 2011 Rank 2011 WP 2010 Rank 2010 WP
Kevin Love 1 25.3 22 12.1
Dwight Howard 2 24.3 2 22.3
LeBron James 3 22.6 1 27.2
Chris Paul 4 20.8 24 11.5
Dwyane Wade 5 18.1 7 17.8
Pau Gasol 6 17.0 12 15.4
Zach Randolph 7 16.8 17 14.3
Blake Griffin 8 15.5    N/A N/A 
Steve Nash 9 14.5 13 15.4
Kris Humphries 10 14.3 141 3.4
Kevin Garnett 11 14.2 28 10.1
Al Horford 12 14.2 21 12.7
Paul Pierce 13 13.8 52 8
Lamar Odom 14 13.6 14 14.6
Kevin Durant 15 13.5 3 19.7
Landry Fields 16 13.3    N/A N/A 
Rajon Rondo 17 13.2 8 17
Jason Kidd 18 13.1 4 19.6
Tim Duncan 19 13.0 10 16.2
Andre Iguodala 20 12.8 15 14.4
Tyson Chandler 21 12.2 178 2.3
Derrick Rose 22 12.0 78 5.7
Manu Ginobili 23 11.7 20 13.4
Russell Westbrook 24 11.6 43 8.7
Kobe Bryant 25 11.6 32 9.9

Table 1: 2011 Top 25 NBA Players using Wins Produced and their 2010 numbers.

Taking a look at these numbers here’s some strategies I’d offer to NBA GMs to acquire a star.

Strategy 1) Have and Keep a Top 25 Player

Good Players Stay Good

  • Success rate in 2011 for top 25 player: 15/25

Yup, if you have a great player you should keep them. They’ll probably be great next season. Only seven returning players on our list weren’t in the top 25 last season and only LeBron actually left his team for another. Not only do the top players stay at the top, their play seems to stay pretty consistent. Most of the players on this list stayed within 5 Wins Produced of last year’s totals.

Strategy 2) Have a Former Top 25 Player that had some injury problems and hope they get better

Out of Street Clothes and back at the top.

  • Success rate in 2011 for top 25 player: 4/25

NBA players — when they recover from injury — can revert to form, and if you had a formerly great player they can get back there. Kevin Garnett, Paul Pierce, Kobe Bryant and Chris Paul fall in this category. In the last three years each of these players has been a top 25 player in the league. Last year hindered their performance (it still didn’t keep Paul out of the top 25 though!) but this year they returned with a vengeance.

Strategy 4) Have a talented young player mature into a star

Young and improving.

  • Success rate in 2011 for top 25 player: 3/25

Young players improve. If you’ve got a talented player that’s been improving next year they make finally jump into the top level. Derrick Rose, Kevin Love and Russel Westbrook all saw a marked improvement this season and for the most part saw a jump in team performance. (2 out of 3 aint bad)

Strategy 4) Get a top Rookie

Can you imagine it?

  • Success Rate in 2011 for top 25 player: 2/25
The rate of a top rookie showing up is less than one a year (Dave’s looked over this) This year Landry Fields and Blake Griffin managed to play amazing and help keep their teams respectable. Of course there were 60 players in the draft and most years not even one of them is a top player so this strategy is risky at best.

Strategy 5) Get a Top 25 Player

South Beach wins!

  • Success rate in 2011 for top 25 player: 1/25

This is a great strategy but good luck getting teams to give up their stars. Only LeBron James falls in this category. Turns out Miami’s decision to get him worked out well. The 76ers are rumored to be shopping Andre Iguodala. Other GMs should take note.

Strategy 6) Find a former top 25 player that has recovered from injuries.

<img class=”size-medium wp-image-4360″ title=”

  • Success rate in 2011 for top 25 player: 1/25

Tyson Chandler in 2008 was ranked 17th with 14.1 Wins Produced. In 2009 he got injured and has been bounced around since. This year he returned to form and helped the Mavericks win a finals. A risky move, but it can work.

Strategy 7) Get an above average player that has been played limited minutes and hope they reach the next level

Do Women and Clothes make the NBA player?

  • Success rate in 2011 for top 25 player: 1/25

I wouldn’t rank this as a great strategy but sometimes teams have good players that have been cast as “role players” and are given limited minutes. It’s not the biggest stretch to assume if they play well in limited minutes, they might play well with starter minutes. You might also get extremely lucky and the player will play amazingly.

General Notes

The idea that these players are needed for success in the NBA is very accurate. A case in point is every team that made it to the 2nd round of the playoffs last season had at least one. The hard part is getting one of these players. Only Miami, New Jersey and Dallas were able to grab one in the last offseason and we can see the fates of two of those franchises turned around immediately. The problem is that there are over 500 players in the NBA. and with only a small handful of great players, it’s simply not possible for most teams to hope of getting them. This gets even harder when we notice multiple teams (Boston, Dallas, Los Angeles, Miami, Oklahoma City and San Antonio) grabbing more than one. In short, when your GM tells you they’re going after a star to contend next season you should be happy. Just don’t be optimistic that they’ll actually get one.

You need a top Goalie to Contend in the NHL

Recently we reviewed the great work of Stacey Brook and Dave Berri about NHL goalies. Here are the important lessons from this study.

  • NHL goalies are for the most part the same. The difference between a great goalie and an average goalie is small. And even the best goalies aren’t huge difference makers. The best goalie will earn you around an extra five wins and the worst may cost you around three.
  • Goalies are inconsistent year to year.

If your GM is spending the offseason in the front office doing their best to acquire last year’s top goalie, I wouldn’t be that thrilled. For fun though let’s redo our NBA exercise and ask our GM in 2011 to acquire a top 10 goalie based on the 2010 season using the Wins Above Average (WAA) metric (save% and shots on goal in terms of wins).

Player 2011 Rank 2011 WAA 2010 Rank 2010 WAA
Tim Thomas 1 4.75 19 0.67
Jonas Hiller 2 2.74 10 2.01
Ondrej Pavelec 3 2.36 66 -1.07
Pekka Rinne 4 2.10 38 -0.04
Henrik Lundqvist 5 1.99 6 3.11
Roberto Luongo 6 1.88 21 0.45
Marc-Andre Fleury 7 1.80 73 -1.66
Tomas Vokoun 8 1.71 2 4.26
Carey Price 9 1.59 26 0.21
Cam Ward 10 1.57 15 0.93

Table 2: 2011 top 10 NHL goalies with 2010 numbers.

The ideal strategy

Just pick one, doesn't matter.

I don’t need multiple bullet points and examples to explain the ideal strategy here. It’s actually pretty simple.

  • If you’re an NHL team and you want a top 10 goalie: Have a goalie on your team. Play them. Hope they play like a top 10 goalie.

Yes, that is about the best strategy you can adopt.

One should also note — as Dave and Stacey noted in their paper — that performance of goalies seems to depend on the defense playing in front of the goalie (i.e. goalies depend on their teammates).  So maybe if your goalie isn’t playing well maybe you should take a closer look at your defense.

We repeat ourselves: Goalies are hard to predict.

Only three goalies in the top 10 from last season return to this year’s top 10. Even then it’s not that great. Lundqvist and Voukun both saw massive drops offs in performance. Hiller saw a slight increase. Tim Thomas, this season’s top goalie, was barely better than average last season. What’s more the number of terrible goalies from last season (Pavelec, Rinne and Fluery) that  are top ten matches the number of great goalies that returned top the top ten! In terms of making the right choice it’s next to impossible. Compare this with the NBA where a top player regardless of position is almost a lock.

Being able to predict a top goalie has not been shown to be easy. That isn’t to say a top goalie doesn’t help. Tim Thomas and the Bruins did win a Stanley cup and Thomas’ regular season help amounted to around ten points in the standings (the difference between 3rd place and 8th place in the Eastern Conference). But can the Bruins count on him leading them to greatness again next season? Should other teams pursue him like crazy and hope he throws a press conference saying he’s bringing his talents to their town? No. The best strategy might just be to put the same goalie back in net, even if they played badly last season, and hope they play like a top 10 goalie.

-Dre

Quick Takes: Southwest Division Draft Grades

Posted on by
9


Devin Dignam (of NBeh? “fame”) is the Toronto Raptors writer for the Wages of Wins Network. He’s also an avid enthusiast of the draft (helped by being a Raptors fan).  This post continues his comprehensive review of the 2011 draft. 

Reviewing the Draft

Today I am continuing  the Western Conference grades by taking a look at the Southwest Division teams. Previously I’ve looked at:

For those who are forgetful (thanks for the suggestion, mmotherwell), here are the average positional values for PAWS/40:

  • PG: 7.4
  • SG: 8.4
  • SF: 9.95
  • PF: 12.59
  • C: 12.32
  • All players: 10.17

Ranking all players by PAWS gives us a good idea of how well a player performed in their various leagues. A word of warning, though: NCAA PAWS/40 does not correlate perfectly to NBA success, and Euroleague PAWS/40 is even worse. For the most part, though, players with a PAWS of 12 or higher usually end up being good NBA players, and players with a PAWS of under 7.3 end up being below average players.

In order to come up with team grades, my method is as follows: I have a spreadsheet with all the draft prospects, all the draftees, their PAWS/40, and (thanks to Arturo) the expected values of each pick. I also recorded the change in salary and wins obtained through draft day trades involving veteran players. Based on these numbers, I came up with the value that each team stands to gain if PAWS/40 can perfectly predict NBA productivity. Of course, PAWS/40 can’t predict NBA productivity perfectly, so the values I came up with aren’t infallible; I had to offer some subjective alterations to the raw scores. I won’t pretend that my evaluations are perfect, but nevertheless, I much prefer my methods to the vast majority of draft evaluations, which rely almost exclusively on subjective elements.

On to the grades!

San Antonio Spurs: A

There were a lot of potential second round steals this year, but to me, the team that had no business getting what it got was the San Antonio Spurs. In exchange for George Hill- an average guard still on his rookie contract – the Spurs got Kawhi Leonard, who posted a PAWS/40 of 13.02, which was good enough for 4th amongst all drafted players. The really amazing part about the trade is that they still have a strong guard rotation (Parker, Ginobili), it shores up the Spurs’ weakest position (small forward), and takes minutes away from the unproductive Richard Jefferson. Now the Spurs can trot out a starting lineup of Parker, Giniobili, Leonard, DeJuan Blair, and Tim Duncan, and try for one last ring before Duncan retires.

San Antonio Spurs' Larry O'Brien trophies

Will Tim Duncan win another one of these?

Dallas Mavericks: B

Dallas traded their picks (#26 and #57) away in order to obtain Rudy Fernandez. As far as value goes, Fernandez is a little bit more valuable than your typical #26…but there is always the potential to pick up a decent young player at #26. But I suppose Dallas is in a ‘win now’ mentality at the moment, and Fernandez is still only 26 years old, so this was an okay move. Fernandez was unhappy in Portland and had seen his productivity decline, so there is also a chance that the change of scenery will help him to perform even better than expected.

Calm down Dirk; it's just Rudy Fernandez

New Orleans Hornets: F

The Hornets had only one draft pick – #45 – and they sold it! While most second round picks don’t amount to much in the NBA, every now and then a team will strike it rich. And because you can’t make a shot you don’t take (please keep this info away from the Raptors), New Orleans gets an F.

Chris Paul with his hands on his head

"What is the owner thinking! Oh, wait a minute...who owns the Hornets again?"

Memphis Grizzlies: D

With their only pick – the #49 – the Grizzlies selected Kansas shooting guard Josh Selby. This is notable because Selby posted a PAWS/40 of 3.77 – the lowest of any NCAA player who was drafted. Not only that, but he posted the 12th smallest PAWS/40 of any NCAA prospect in this year’s database, just ahead of such notables as Trey Zeigler, Lamont Jones, and Mfon Udofia. In defense of the Grizzlies, most teams aren’t expected to pick a useful player so late in the draft anyways, and there is always a chance that Selby will play better than his past performance indicates. For this reason, I am giving the Grizzlies the lowest possible non-failing grade: D.

"Josh! Over here!"

Houston Rockets: C

Houston was involved in some draft day trades. They obtained the #20 and Johnny Flynn in exchange for the #23, #38 and Brad Miller. They then bought back the #38 from Minnesota, leaving them with the #14, #20, and #38 picks, as well as Johnny Flynn. At #14, the team selected Marcus Morris, a power forward who posted a PAWS/40 11.48 (18th). The player they obtained with the #20 was Donatas Motiejunas, a player who posted a PAWS/40 of 4.60 (75th – just ahead of Josh Selby). At #38, the team obtained Chandler Parsons, who posted a PAWS/40 of 10.32 (25th). Motiejunas was not a good pick, but Parsons and especially Morris look like they could become decent NBA players. Why am I being so hard on the Rockets if this is the case? Because of Johnny Flynn. While Brad Miller is no longer an above average player, doesn’t play very many minutes, and is overpaid, he is certainly better than Flynn, who is the 38th most overpaid player in the league. This more unfortunate Flynn effect drops Houston down to a C.

No, not that Flynn effect

-Devin

The Coach is Wrong!

Posted on by
24

Arturo Galletti is the Co-editor and Director of Analytics for the Wages of Wins Network. He is an Electrical Engineer with General Electric in the lovely isle of Puerto Rico, where he keeps his production lines running by day and night (and weekends) and works on sport analysis with his free time.

Talking Coaches Again

To quote Prof. Berri’s last post on the subject:

Readers of Stumbling on Wins would note that Bradbury’s results for baseball are quite similar to what we reported for the NBA. The study we review (which I co-authored with Mike Leeds, Eva Marikova Leeds, and Mike Mondello and published in the International Journal of Sport Finance) looked at 62 NBA coaches across thirty years of data. Across this sample, only 14 coaches were found to have a statistically significant and positive impact on player performance. So most NBA coaches – like most baseball managers — do not appear to make their players more productive.

We, as NBA fans, may hear a lot of noise about what a difference a great coach can make. I can even list some of the more commonly repeated refrains :

  • He’s a leader.
  • He’s a motivator.
  • He inspires his team.
  • He makes his team better.

But as Dave notes, this is not – for the most part – generally true. The simple truth is that NBA coaches are overvalued. Players are who they are and coaches don’t generally affect that.

With some notable exceptions, of course.

Given this glaring fact, how then can we objectively rate coaches? Is there any actual value in the function of coaching – and if there is, how do we capture it? I’ve struggled with these questions for some time**. As with most things in my life, the answer came to me in the form of a graph.

Not quite like this (Image courtesy of xkcd.com)

Coaches matter because they decide who plays

The graph in question contains every player season since 1978 for the National Basketball Association (all 14698 of them). Each point represents a player playing for one team for one season and shows their minutes played per game and their Wins Produced per 48 minutes played. It looks like so:


 In essence this is a graph of a player’s perceived value in the eyes of their coach (as represented by the minutes played per game) and their actual value (as represented by their actual productivity in WP48). The thing that jumps out very quickly is that while there is correlation between perceived and real value (see the R2 = 32%) that only accounts for 32% of the variation we see.

Did I lose you? Let me break it down for you. A player’s actual playing ability only accounts for less than a third of the variation we see in playing. What that means is that every time you scream at the television that the wrong guys are getting the playing time, there’s a good chance you are correct.

It hasn’t gotten better over time either.

This of course led me to a deeper examination of the data. What I found is that there are real differences on a year to year, team to team basis in that value versus playing time correlation. Teams and coaches simply do not play their best players; instead they play the players who they think are their best players.

That makes all the difference in the world.

So coaches do matter, but not in the ways that the media tries to sell us. It’s not about what book Phil gave Ron or the relationship Larry has with Allen. It’s not about the respect everyone has for Pop. It’s about who they put on the court.

Coaches control the minutes and everyone knows this. The surprising thing is that proper allocation of those minutes is actually a rare skill.

Really? I could have told you that.

The 2011 Coach of the Year: Doug Collins

Let’s take a look at how well NBA coaches did this season in terms of playing their best players. Which coaches should be rallying the troops when it really matters?

The highest correlation between talent and playing time was enjoyed by Doug Collins and the Philadelphia 76ers. By the numbers, Doug Collins got more out of his roster than any coach in the league – by a wide margin – and was thus an easy choice for 2011 Coach of the Year. A coaching top five of Collins, Thibodeau, Popovich, Spoelstra and Hollins is not bad. The bottom of that list doesn’t hold many surprises either.

Before anyone complains that Phil Jackson is left on the outside looking in, I’ll just say that historically he does very well. We’ll get to that in part 2!

-Arturo

**Editor’s Note: Arturo has actually wrestled with this issue before. Check the links below if you’re interested

Your NHL Goalie doesn’t matter (much)!

Posted on by
7

 Dave Berri is the General Manager of the Wages of Wins Network.  He is a Professor of Economics at Southern Utah University, where he teaches students by day and publishes papers on Sports Economics by night. What follows is a post from him and co-author of “The Wages of Wins” Stacey Brook.

Wait, it doesn't matter which of us plays?

Decision Makers and Goalies

Stacey Brook and I published “On the Evaluation of the “Most Important” Position in Professional Sports.” in the Journal of Sports Economics.  This article makes the following observations (readers of Stumbling on Wins should find much of this to be familiar):

  • Decision-makers in hockey primarily consider past save percentage — as opposed to a goalies past performance with respect to Goals Against Average (GAA) or wins — in evaluating goalies.  Because GAA and wins clearly depend upon teammates (since GAA depends on shots faced and wins… well, it is pretty clear goalies can’t win games by themselves), save percentage would seem to be a better measure of goalie performance.
  • Goalies, though, are very similar with respect to save precentage.  In the population we examined for our study of salaries the average save percentage was 90.6% with a standard deviation of 1.2%.
  • Not only are goalies quite similar with respect to performance, goalies also are quite inconsistent across time.  We found that only 6% of a goalies save percentage in the current season was explained by the goalies save percentage the previous season.
  • Because goalies are so inconsistent, a goalies current save percentage is completely unrelated to a goalies current salary.

Goalie Inconsistency

As Stacey noted, we did not consider any hockey players in The Wages of Wins.  In a recent post at Team Sports Analysis, he sought to correct this omission by updating our goalie story.  Here is an overview of Stacey’s updated analysis of NHL goalies starting with his method:

  • Collect all goalie performances from the 1997-1998 season through the 2010-2011 season
  • Remove any goalies that started fewer than 8 (10%) of the games in a season
  • Grade goalies using the WAA metric – This is essentially a goalie’s save percentage compared to the shots faced and then measured in the impact of a goal on wins. (explanation at Hawkonomics – here).
  • Put all goalies into quantiles and assign a grade (top 20% = A, 2nd 20% = B, 3rd 20% = C, 4th 20% = D, bottom 20% = F) This is a similar metric as used in the Wages of  Wins for measuring NBA players, NFL Quarterbacks and MLB hitters.
  • Compare goalie grades season to season
Here are some of his findings
  • Martin Broduer has only kept a grade of A (top 20%) four times and has moved one grade five times and moved multiple grades three times. In short, Brodeur is not a rock in goal.
  • NHL goalies as a whole maintained their “grade” – stayed in the same quantile – 26% of the time, and moved either up or down one “grade” 34% of the time; thus about 40% of the time NHL goalies moved up or down more than one “grade”.
  • Looking back at The Wages of Wins results, it appears NHL goalies are about as consistent as NFL Quarterbacks, are less consistent than MLB batters and much less consistent than NBA players.

So the quintile approach confirms the story we have told before.  Goalies are rather inconsistent across time.  And again, they are also not very different from each other. A simple way to illustrate our point is the following. Look at the top five goalies from this last season in the NHL:

Season Rank Player Team WAA Save%
2011 1 Tim Thomas Boston Bruins 4.75 0.938
2011 2 Jonas Hiller Anaheim Ducks 2.74 0.924
2011 3 Ondrej Pavelec Atlanta Thrashers 2.36 0.914
2011 4 Pekka Rinne Nashville Predators 2.10 0.930
2011 5 Henrik Lundqvist New York Rangers 1.99 0.923

Table 1: Top Five NHL Goalies using WAA from the 2010-2011 Season(Full List Here)

Now take a quick check to see which of them was also a top goalie two season ago:

Season Rank Player Team WAA Save%
2010 1 Ryan Miller Buffalo Sabres 5.58 0.929
2010 2 Tomas Vokoun Florida Panthers 4.26 0.925
2010 3 Tuukka Rask Boston Bruins 3.75 0.931
2010 4 Jimmy Howard Detroit Redwings 3.56 0.924
2010 5 Evgeni Nabokov San Jose Sharks 3.45 0.922

Table 2: Top Five NHL Goalies using WAA from the 2009-2010 Season(Full List Here)

The Greatest Goalie Ever

Let me close with how we illustrated this last point in the Journal of Sports Economics.

After the 2008-2009 season, Brodeur had faced 25,126 shots and stopped 22,954; giving him a save percentage of 91.4%. An average goalie, though, would have posted a save percentage of 90.4%. In other words, an average goalie that faced 25,126 shots would have prevented 22,737.1 goals. Given the impact goals have on standing points, this 216.9 increase in goals allowed would have cost Brodeur’s employer (the New Jersey Devils) 66.9 standing points. In addition, because a win is worth two standing points, an average goalie facing Brodeur’s shots would have won 33.5 fewer games. After the 2008-2009 season, Brodeur had played 16 seasons in the NHL. So, an average goalie would have only produced about two fewer wins per season across Brodeur’s career.

To put that mark in perspective, at the conclusion of the 2008-2009 season, Brodeur had 557 career wins; a mark that led all goalies in the history of the NHL. An average goalie, though, would have won 523.5 games. Such a mark would currently rank second on the all-time win list.

This analysis illustrates the point we are making about the difference in goalies. One of the very best goalies in NHL history is simply not very different from an average goalie.When we couple this finding with the inconsistencies of goalies,we wonder then there are such large differences in the salaries goalies received. In other words, if there is very little difference in the performance of goalies, why would any team pay much more than the minimum salary to acquire a goalie?

- DJ