MLS payrolls: a mixed bag of escalating costs

Not even his $6.5M salary can create

a team payroll disparity within MLS

Much of this past MLS offseason was spent worrying about a potential strike or lockout due to the league and the players union not being able to come to a quick agreement on a new collective bargaining agreement (CBA). Most of the owner's concerns centered around player salaries and policies that would enable them to rise at a faster rate. Along with that concern was one of team competitiveness - we have seen how a lack of any spending cap in the EPL and La Liga has led to a pay-to-win philosophy.

This leads to two fundamental questions that I will answer with statistics.

1. Did the league see an increase in team payroll disparity during the last CBA?
2. Did the league see an overall increase in team payrolls during the last CBA?

Background

MLS and its players union signed a CBA that covered the 2005 through 2009 seasons. It included salary caps, limited player movement, a no strike clause, and a variety of other regulations for the league and its players. Prior to the 2007 season, the league announced the Designated Player rule in a desire to attract talented, visible stars from around the world while providing minimal impact to a team's salary cap. A few teams have taken advantage of that rule, the most notable being David Beckham and his $6.5m salary.

Of note is the salary cap during the 2005-2009 seasons. It has ranged from $2.0M in 2005 up to $2.3M in 2009. The cap has always been a bit of a fungible figure. Seven of the 12 teams ran payroll higher than the cap in 2006, with 12 of the 15 running higher than the cap in 2009. I am sure that MLS has some creative accounting rules that show the teams are under the cap, but it is not clear to me how this is done. The reality is that the clubs are spending a good bit more than the cap, and reality is what I am interested in.

At first blush, there seems to be a good bit of disparity in team expenditures that has grown over the life of the last CBA. Figure 1 shows how much each team has spent as a multiple of the league average for each season.

Figure 1: MLS team payroll, 2005-2009, as a function

of the average team payroll for each year (click to enlarge).

Statistics will tell us whether or not the disparities we see starting in 2006 are real, and whether or not there has been general upward movement in league salaries over the five years of the CBA.

The Prerequisite: Normality

The pre-requisite for many of the frequently used parametric statistical analyses (t-tests, test for equal variances, etc.) is that the data being analyzed be normally distributed. This is because the tests being performed on the data use concepts based upon the Central Limit Theorem to test two sample populations. Thus, normality is a prerequisite and the team payroll data must be checked for this property before beginning any analysis.

An interesting phenomena is observed when each year's distribution of team payrolls is checked for normality. The 2005 and 2006 seasons both test to be normal. That is to say, when a normality test is performed on the data we find a p-value greater that 0.05, which indicates a low risk of accepting the data is normal when it might actually be non-normal. See the Figure 2 as an example of what a "successful" normality test looks like.

Figure 2: Descriptive statistics for 2005 MLS team payroll.

(click to enlarge)

However, once the designated player was introduced in 2007, team payrolls for each season went to a non-normal distribution. That is to say, the p-value for normality tests of the 2007-2009 seasons is much less than 0.05, indicating that we would be at high risk of drawing the incorrect conclusion if a normal distribution were assumed. See the Figure 3 as an example of what such non-normal distributions look like.

Figure 3: Descriptive statistics for 2009 MLS team payroll.

(click to enlarge)

These results have very important implications for the types of tests used to answer the two fundamental questions posed at the beginning of this post. There are now two options:

1. Use a transformation method, like Box-Cox, to transform the 2007-2009 data to make it normal. This makes determining the absolute effects difficult due to the presence of the transformation function.
2. Use a non-parametric statistical test on the original data. Non-parametric tests are far more forgiving of the original data, but end up requiring a far greater spread in two sample data sets to show a statistically significant difference when compared to similar parametric tests.

In this case, I have chosen to pursue course (2) for my study. I am more concerned with testing whether there are differences, as well as easily determining how large a gap there is for tests that show a statistically significant one. Avoiding transforming data via (1) is a huge benefit in this case, especially since the statistics I am interested in don't benefit a whole lot from using parametric tests.

Has team payroll disparity increased?

To answer this first question, I turn to a comparison of the 2009 and 2005 team payroll data. Using this data means I am looking at the bookends of the last CBA. I did this, rather than analyzing each of the five years of the CBA, as it is reasonable to suspect that any change in the distribution of team payrolls will be gradual from year-to-year. Thus, to see any potential difference one must look at the beginning and the end of the CBA, which is what the owners and players really cared about anyways when they were negotiating the new CBA.

To do this, I performed a test for equal variances between the 2005 and 2009 seasons' team payrolls. Performing such an analysis can identify whether the variation in team payrolls between the two seasons is statistically different. If this were so, and if the 2009 variance was higher than 2005, we could conclude that the gap between "rich" and "poor" clubs' expenditures on player payroll was widening. As the 2009 data is non-normal, I used a specific subset of the test for equal variances, Levene's test, to make this evaluation. If the Levene's test comes out with a p-value of 0.05 or lower, we can reject the null hypothesis that variances are equal and safely assume that they are different. Figure 4 displays the results of such a test.

Figure 4: Test for equal variance results,

2005 vs. 2009 MLS team payroll.

(click to enlarge)

The first conclusion that can be drawn from the analysis is that we cannot reject the null hypothesis (p-value from Levene's test = 0.219), thus we cannot declare that there has been a statistically significant increase in the spread in MLS team payrolls throughout the last CBA. We must accept the null hypothesis: there is no difference in the variation in team payroll between 2005 and 2009.

The second conclusion is that this test demonstrates the danger of not performing the initial check for normality. If I hadn't known that the data was non-normal, I might have used the results from the F-test, and it's p-value of 0.00 would have led me to conclude that there was a difference in payroll variation between 2005 and 2009. This would have been the wrong conclusion.

The third conclusion is that not even David Beckham's 6.5M+ salary and the resultant $10M LA Galaxy payroll (the star on the far right of the Levene's test box plots) can generate such a disparity. One might be able to rationalize excluding Beckham's salary from the analysis, or at least cutting it down to the $3M range, as it is more than double the next closest DP salary. This would only close the gap in 2009 salaries, raising the p-value even more and making any test for equal variances more difficult to reject.

Has the average team payroll increased from 2005, and if so by how much?

Now that we know that the variability in team payroll has not increased, it is time to determine whether or not average team payroll has increased from 2005 to 2009 and by how much. To answer these two questions, I used the Mann-Whitney two sample test for non-parametric data. In this case, the null hypothesis is that there is no difference between the two seasons while the alternative hypothesis is that 2009 team expenditures were greater than 2005. Figure 5 shows the results of the test.

Figure 5: Results from Mann-Whitney

test, 2009-2005 team payroll

The results from the test return a p-value of 0.0018, which means we conclude that there is a difference between the 2009 and 2005 season payrolls. The test also gives an estimate for the difference - $746k. Thus, we can conclude that the average team's payroll has increased by $746k over the five year CBA.

General conclusions and new questions

Through statistical analysis, we can see that the gap in team payroll has not grown over the last three years, but the average team payroll expense has increased by almost three quarters of a million dollars. For a league concerned about financial stability and a modest $2.3M salary cap, this had to be part of the reason for the concern in negotiating a new CBA. Teams are spending far more money in 2009 than in 2005, regardless of the good intentions of the CBA.

This analysis leads to a whole new set of questions. Two of which that come to mind are:

1. How much of this increase is due to normal competitive pressures year-over-year in a pro league vs. the unique salary impacts of the DP?
2. Like the EPL and La Liga, can the difference in finishing position year-to-year in the league be partly explained by team expenditures?

I will address these questions in future blog posts.

Sources of Data

Note: I will keep this post archived in the "Key Blog Posts" section of the column to the right for quick reference by users. The latest revisions to the post will be marked via italicized, red text. I will add content as posts require.

General Economic Data

Inflation rate data is taken direction from the US Bureau of Labor Statistics CPI data. Unless otherwise noted in a specific post, annual changes are used to bring past economic data into current day dollars.

MLS Data

MLS player salary data for 2007, 2008, and 2009 is taken from the MLS Player's Union website. Player salary data for 2006 is taken from the Washington Post. I have been unable to find 2005 player salary data, and thus have used Grant Wahl's compilation of team payroll's located here. Strangely enough, Sports Illustrated did post the 2004 player salary data here.

If anyone does know where to get 2005 player salary data, I would love to know where it is. This would help plug a key hole in pre-DP era player data.

I have compiled the 2006-2009 player salary data in to a Google Doc spreadsheet for public use.

All player and team payroll data is expressed in 2009 dollars unless otherwise noted.

To avoid issues in statistical analyses, I have coded all San Jose team data prior to 2006 as Houston Dynamo data. This will preserve the reality that Houston was not an expansion franchise, but rather an existing team that moved from the San Jose area. MLS insistence that the San Jose statistics not transfer to the Dynamo notwithstanding, the reality is that the team roster and ownership remained the same after the move.

Why Spanish players are on strike

Hope you enjoyed Messi's performance against

Arsenal. He's on strike next week.

The top two tiers of the Spanish football leagues will be on strike next week.

As it stands, there will be no soccer matches in Spain next weekend after the Spanish players' union, the AFE, Friday called a strike over unpaid wages that will halt games in the country's top four leagues between April 16 and April 19.

The AFE said that 85% of soccer players in Spain's top three divisions either get paid late or not at all. It also says that the Spanish Football Federation still owes the union €8 million ($10.7 million).

So why are players going unpaid or paid late? Here's one reason why.

The reality of the financial situation in Spanish football is that Barcelona and Real Madrid earn more than four times as much from the domestic TV deal alone as any other La Liga side and their turnover is more than six times as high.

Although they are among the wealthiest sporting franchises on the planet, the reality below them is disconcerting. Both clubs have used their weight to accumulate more of the domestic TV revenue to enable them become wealthier at the expense of the remainder of Spanish football.

What is the result of this pay disparity? Barcelona and Real Madrid have won the last 5 league titles, one of them will make it 6 straight this year, and 21 of the last 25 league titles (HT: myfootballfacts). It seems as if the EPL isn't the only league with a pay-to-win problem that's leading to financial problems.

Why Rafa is concerned

"Show me the money!"

Liverpool's six month bid to get a £110m investment from Rhône has apparently collapsed. And Rafael Benitez, Liverpool's manager, is not happy.

"If we don't have new investors it will be difficult to go one step further," the Liverpool manager said yesterday, disclosing that the collapse of the Rhône offer, when a deadline imposed by the fund management company expired at midnight on Monday, had shattered the optimism he had started to feel in recent months about the club's financial future. "For six months I was really optimistic, especially about this group, because they were one of the groups who were there," said the Spaniard, who is understood to have met with Rhône. "But they are not there now. The Rhône Group is not there."

While his unhappiness is understandable, what is the deeper reason for it?

Benitez's comments raise further questions about whether he will be around at Anfield to experience a new financial era. There certainly will be a new one of some description from July, by which time RBS will want to see £100m of the debt heaped upon the club by Hicks and Gillett paid back. Rhône's investment would have gone straight to the bank and RBS is unlikely to allow prevarications from Hicks and Gillett beyond July, by which time the current debts must be refinanced.

Hicks' and Gillett's ability to meet interest payments under the current arrangements will be tested to the extreme if Benitez fails to deliver them the £20m bonanza of Champions League football next season...

As I showed in my previous post, Soccernomics demonstrated why "money = table position" in the EPL. The ability to win is fueled by money that enables the teams to afford the best players. As an example, a loss of £20m represents the combined salaries of Fernando Torres, Steven Gerrard, and part of Dirk Kyut's salary. To put it another way, Liverpool's 32 players average £2.5m per year for a total payroll of £80m. Losing the Champions League income would represent a 25% drop in income for an already financially strapped team.

Going back to the underlying regression data in Soccernomics, we find that Liverpool spent about 2.68 times the league average on wages between 1998 and 2007. If they were maintaining similar expenditures this season, they can reasonably be expected to drop to 2.01 next season. Clubs that dropped this low in expenditures had an average finish of 9th in the Premier League. This may not be the case for Liverpool if they choose to go into further debt next season or finance part of it through a transfer fee for one of their key players, but such debt-fueled expenditures will be harder to swallow without Rhône's money.

The Red's performance this year clearly demonstrates that salary expenditure is no sure way to great table position. It is purely an enabler - a condition of entry to succeeding in the hyper-competitive world of Premier League soccer.

As a fan of the MLS, I am wondering if a similar relationship exists in that league. A salary cap keeps team payroll disparities down, so there is greater parity in expenditures. The use of the designated player rule has introduced higher levels of spending in some clubs. I wonder if there is a growing disparity in club expenditures, and if so does any growing disparity contribute to a difference in team performance? In later posts I will try to answer such questions.

Why the MLS owners fought the players so hard

Note: This is a repost from March 8th, 2010 at my other blog, which is a mix of politics, economics, and containted a few soccer-related posts before this blog was created. I made this post in the middle of the MLS labor turmoil. I have reposted this here as it will provide the background for the first few posts I make of new analysis.

Figure 3.1 from Soccernomics, which shows a substantial

correlation between wage expenditure and where a team
finishes in England's top two soccer leagues.

I mentioned in a previous post that I am reading the book Soccernomics, which is chock full of statistics that clarify or challenge conventional sports wisdom. The authors do a very good job of not only comparing differences in soccer leagues, but also across other sports with a special emphasis on baseball given it's similarly lenient financial rules. One of the more interesting aspects of international soccer versus traditional US sports leagues is the financial and transaction rules governing the game.

Most US professional sports leagues are governed by some form of salary cap to prevent runaway spending by big market teams that translates to widening disparities in competitiveness. The most successful model of this behavior is the NFL salary cap and it's resultant goal of "league parity". Transactions between teams nearly always involve player trades, and are often executed as much for salary cap management as for overall team improvement. This is due to the fact that the teams are often required to assume the terms - both financial compensation and duration - of the contract. This model minimizes costs, and provides a predictable and somewhat stable source of revenue and cost for owners.

International soccer, governed by FIFA rules, is completely different. Largely, there are no salary caps - although that may change as an emerging soccer debt bubble may cause governing bodies like UEFA to place "break even" financial requirements on clubs. Teams are free to spend what they want, where they want. When it comes to transactions, player swaps do not take place. Rather, a "transfer" will take place where the club and player are paid a one time compensation for the transferring of rights from one club to another. Transfer fees can be huge, as speculation plays a big part when rival clubs are bidding for a player's talents. They can be the difference between profits and losses for clubs.

The authors of Soccernomics have found out some interesting things related to transfers and team payroll.

First, there is very little correlation between the money a team spends in the transfer market and their success in the league.

But much of this [transfer] money is wasted on the wrong transfers. In fact, the amount that almost any club spends on transfer fees bears little relation to where it finishes in the league. We studied the spending of forty English clubs between 1978 and 1997, and found that their outlay on transfers explained only 16 percent of their total variation in league position. By contrast, their spending on salaries explained a massive 92 percent of that variation.

What's interesting is that even given this data, clubs still go out and blow huge sums of money on transfers. Soccernomics goes into many reasons why transfers largely fail to improve a club and why clubs continue to pursue them, but I will save readers from me regurgitating all of Chapter 3 of the book. Rest assured - transfers present a bad ROI, and you need to read the book to get the full story why.

Second, there is a good bit of correlation between the money a team spends on annual total player payroll and their success in the league. The graph at the top of this post shows the author's regression results when studying payroll and club success. While there is a substantial correlation, the graph must be deconstructed to understand the true magnitude of the trends given that logarithmic functions had to be used to get the linear fit. If one is to look at what it takes to move from mid-table on average to the top 4 positions, we could examine points that correspond to 0 and 1 on the x-axis. Adjusting both the payroll data and the finishing position data by their logarithmic functions, one finds that a club must spend about 3 times more money than the league average to achieve an average finishing position 5 places higher than the average club. Given a table of 20 teams, that means one must spend 300% more than the average team to move up 25% of the table - diminishing returns indeed! Given that finishing in the top of the league effectively means promotion - either from the Championship to the Premier League or the Premier League to the Champions League - and ever growing revenue, there is huge pressure on team finances to compete for those top few spots.

And thus, we get to the rub of soccer in the United States. The MLS player's union and ownership is locked in a stalemate over the terms of the next collective bargaining agreement (CBA). Players are asking for fundamental changes to the way the league manages their contracts - they are asking for free agency, terms closer to the rest of the world's players when it comes to transfer terms, and for an eventual dissolution of the league's single entity structure so that players can sign contracts directly with teams. The league's ownership is steadfastly refusing these terms - and for good financial reasons. No one expects MLS to turn into the Premier League overnight, but the failure of the NASL looms large as the cautionary tale of what happens when US soccer leagues don't run a conservative financial house. Given the expectation of US sports franchise owners that they should run their team like a business and make a profit (an assumption Chapter 4 of Soccernomics ultimately destroys), the owners can look at results like those from the English leagues and see what the end game is - large sums of money, often spent irrationally, producing unpredictable results and destroying the financial health of the league's teams. Teams like the Seattle Sounders, with deep pocketed owners and fans who set the league record for attendance in the team's first season, would look to use that financial position to build a permanent place at the top of the league for themselves.

As a Libertarian, I can't say I agree with the owners' position. There's a legitimate point to be made for workers' rights and against the business collusion of a single entity. But as a growing soccer fan that wants the MLS to be a stable, long-term venture I also can't disagree with the owners' approach of limiting the financial commitment required of teams. They are doing the rational thing of following the statistics, and recognizing that the league can't support such an arrangement at this time.

An Introduction

Where the love affair began - Carnegie Mellon University

It was during my junior year of college, when taking a class in basic statistics for the Engineering and Public Policy half of my double major, that I fell in love with the representation of behavior and phenomena by numbers. First it was hypothesis tests that could actually tell if a difference was statistically significant or not. I don't know why it fascinated me so much, but I found such beauty in being able to prove with numbers whether I was seeing a real difference in two sample populations. It then moved on to the assumptions and requirements for statistically correct regression models. All of a sudden, Excel graphs and their regression functions were to be used only by those who didn't know better. It made me so happy that I took several more classes in statistics.

I started my career as a design engineer at Ford a few years later. I focused on my engineering career, dabbling in statistics occasionally during my masters degree. A lull five years into my engineering career led to an opportunity to complete Six Sigma Black Belt training and certification at Ford. Over the course of a year I completed five projects at Ford, realizing more than $5 million in hard and soft savings. I rediscovered my love for statistics. Statistics had allowed our project teams to see solutions that we wouldn't have otherwise seen. More importantly, I learned the key to statistics: they are useless unless you have enough of a foundational understanding of a topic to ask the right statistical questions.

And that's what has inspired this blog. I plan on approaching statistics as a tool to answer questions that I have already asked myself. I will not search for random patterns, but instead pose hypotheses based upon reasonable expected potential behavior and seek to prove or disprove those hypotheses via statistical analysis. I will not take the approach of the authors of Freakonomics, seeking random behavior in patterns of numbers for shock value. Rather, I will take the approach of the authors of Soccernomics - I will attempt to answer questions that have much emotion surrounding them but have had little data applied to them during the endless, heated debates.

(Quick sidebar: If you listen to one thing I say on this blog, it is this - READ SOCCERNOMICS. If you like soccer and/or statistics, you will love the book. It is chock full of real, data driven soccer knowledge that cuts through the "tribal knowledge" that turns out to just be tribal)

I may not always be right, but I will go where the numbers lead me. I will always try to give enough of the statistics theoretical background so that readers can understand the relative strengths and weaknesses of the analysis method used. Most of all, I will try to be clear in my presentation of my hypotheses prior to conducting any analysis. I may not be the most prolific blogger, but the posts I do make will be full of analysis that is statistically correct and way more useful than the statistics you find on ESPN's Soccernet.

I hope that you find this blog interesting. It is a passion of mine that I hope to communicate to you.

Winter Olympics 2010

The Vancouver 2010 Winter Games kicks off with the Opening Ceremony on February 12, 2010 and ends with the Closing Ceremony on February 28, 2010.

Watch all the games live.