Dave Laidig is back with the third part of his series looking at the use of statistics and numbers in soccer. For Part I, click here. For Part II, click here. So far, this series has focused on analyzing objective measures of

performance. In Part 1, we covered the Castrol Index and an adjusted

index that allows meaningful comparisons on overall contribution to

wins between positions. In Part 2, we used this information to

determine the potential impact of field players from different

positions on wins. However, in the business of soccer, resources are

limited. And one must get the maximum value for their investments in

players. Here, we review some of the financial aspects of obtaining

the performance levels discussed in earlier installments of this

series.

The theme for this part is return on investment: knowing what can be

obtained for a given price. And to get this analysis, I made some

assumptions. For example, I used the 2011 “guaranteed salary”

reported by the MLS Players’ Union, instead of base salaries. I

believe teams likely know which contract incentives will probably be

met. Thus, I treat the salaries guaranteed as of Sept. 2011 as

expected by teams, and use them for my salary analyses. Also, I treat

all guaranteed salaries above the designated player (DP) threshold as

DPs. I understand there is room for teams to buy-down salary cap

values using allocation money. But sticking to my dollars and cents

theme, I classify DPs based on actual expenditures, and not salary cap

rules.

With the background aside, we turn to the role of money on

performance. First, player salaries are poor predictors of team

success. Between 2007 and 2010, total team expenditures were not

significantly correlated to league points (.193). Considering

individual players, guaranteed salary was not correlated with Castrol

Index scores or adjusted index ratings (.166 and .172 respectively).

And if we ran the equations in Part 2, with salary replacing the

performance indices as a predictor of team points, there is no

significant relationship to league points and the model R-squared was

a paltry .27 (compared to .78 of a maximum possible 1.0 for the

adjusted index weighted by playing time). Further, I created an

effective average salary for each team (avg. salary weighted by

minutes), and that was not significantly related to points either.

These results inform us that more money does not lead to more wins in

MLS. In contrast, in the 2010 EPL season, team salary costs were

highly correlated (.85) with league points. As a rough indicator of

the value of large salaries, consider whether Designated Players (2011

salaries above $335,000) are more likely to be in the top 20% of

performers. There were 31 non-goalie DP salaries in 2011, and 11 of

these were in the top 20% of their position group. This is a

statistically significant result (Chi-square = 4.75, df 1), but the

size of the effect is modest in comparison to the wages. A randomly

selected DP has about a 35% chance of being a top performer, while the

rest of MLS players have a 19% chance of being a top performer. And

of course, one could sign several other players for the typical DP

salary. In MLS, one can obtain high quality player performance

without spending more than opponents. In short, there is room for

more efficient player spending.

But knowing there is room for improvement and actually improving are

two different things. A standard is needed to measure the value of

performance, and not just for DPs. As an initial step, the average

salary per adjusted index point is $31,228 for forwards, $23,425 for

midfielders, $17,849 for defenders, and $18,861 for goalkeepers. The

median salary per point is about $12,000 for the field positions;

which is interesting even though the average performance index and the

wages differ for each position. Also, the range of dollars per index

point is very wide. Indeed, the field players with the greatest value

(typically key starters on a minimum salary) are in the $4,200 per

point range; while the egregious examples can be over 600k or 800k per

point. And with such incredible variability, I use the median values

as the basis for calculating value.

In addition, I chose to examine a subset of the top players as well.

Some economists have suggested that performance at the top-end is

disproportionately rewarded; possibly due to the all-or-nothing nature

of sports. Thus, considering the top 20% of performers at each

position, we find their average salary per adjusted index point for

forwards are $84,175 (median $ 13,243), midfielders $40,689 (median $

14,880), defenders $17,339 (median $17,954), and goalkeepers $10,197

(median $ 7,728). When compared to the entire position groups, it

becomes evident that purchasing higher end talent is slightly more

expensive.

These data points are involved in creating wage standards for

performance levels. For example, the median wages per point

multiplied by the median points creates an “efficient salary” for a

50th percentile player. With the math, an efficient salary for a

mid-level forward would be $87,800 (7.48 * $11,738), a midfielder

would be $91,318 (7.44 * $12,274), and a defender would be $91,116

(7.71 * $11,818). These “efficient salaries” are slightly below the

median position salaries reported in Part 1.

Similarly, we can calculate an “efficient salary” for a top player

(80th percentile) using the median wages per point for the top 20% of

players. An efficient salary for a top-level forward would be

$107,665 (8.13 * 13,243), a midfielder would be $117,254 (7.88 *

14,880), and a defender would be $146,863 (8.18 *17,954). Using these

salaries, one can start to analysis the value of a player contract.

These standards represent what a performance increase alone would

justify, based on the current MLS market. Any expenditure beyond

these levels would require an additional justification.

And soccer is a business. Any salary or wage must be justified; but

increased performance is only one justification for a DP. Obviously,

anything else a player contributes to increased revenue would support

extra wages (beyond that supported by performance). And because fans

will buy Donovan jerseys over Franklin jerseys, the Galaxy are

justified in paying Donovan more, even if both contribute the same to

wins. Further, there are less tangible benefits as well. A DP may

attract better competition for friendlies, or lead to more TV

exposure. And other players may accept less for the chance to play

alongside a star player. All of which may affect the bottom line.

Consequently, a DP decision process should consider the value

justified by performance (rough estimate of performance * $ per point)

and projected revenue (additional jerseys and tickets) and as well as

the more speculative benefits.

And by using a quantitative method to account for the various buckets

of player value: teams may be able to make better business decisions

by recognizing where their purchase price is going (performance,

merchandising, or improving other players’ performance) and then

evaluate the success or failure of the results. Over time, one can

quantify the risk involved for each category and improve the market

efficiency of player acquisition.

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