No Middle Class In Major League Soccer Could Be A Problem

Major League Soccer players might go on strike soon over the lack of free agency. This has to do with An MLS being a “single entity,” meaning that:

“[I]nvestors… purchased equity in MLS itself rather than any team. MLS did almost everything for its clubs. It assigned players to MLS clubs, protected intellectual property rights and negotiated broadcasting deals.”

However, individual teams are acting more, well, individually, especially since the Designated Player rules came into affect in 2007 (aka the “Beckham rule”).

(A Designated Player is someone a team can pay over the salary cap/budget slot. The team just has to pay the high salary out of its own pocket. This allowed the LA Galaxy to sign and pay David Beckham for $6.5 million/year in 2007 while the median salary that season was just $50,400.)

At the same time, the player acquisition system is murky in the MLS. It has detailed rules, but then throws them out when it comes to a national team star (Clint Dempsey or Jermaine Jones, for example) or an aging foreign superstar (more recently, Kaka and David Villa). It’s created a league where player salaries are artificially suppressed (like the NBA and NFL) until they aren’t. I’m not saying this is a bad strategy for the league to take, but it’s creating a breaking point for the vast majority of players who are receiving less than average salary.

One of the more interesting parts of MLS finances is that the players union has been publishing the salaries of all of its players since 2007. We can see how they’ve been distributed since Mr. Beckham graced us with his right foot and perfect cheekbones.

Distribution of MLS Salaries from 2007-2014You can see that there isn’t much middle ground between the star players and the rank-and-file. The disparity is even more glaring when looking at how far from the mean each player is. The horizontal axis below is standard deviation.

Distribution of MLS Salaries from 2007-2014 (Standard Deviation)Mr. Beckham earned 16 standard deviations more from the average salary from 2007-2009. Looking at the count of players through the lens of standard deviation…Count of MLS Salaries from 2007-2014… dang. Zooming in on most of the league, within one standard deviation of the average salary…Count of MLS Salaries from 2007-2014, One Standard Deviation… dang. The majority are below the mean (0.0 standard deviation).

How does this affect a single team? Looking at the aforementioned LA Galaxy, the former home of Becks and Landon Donovan (both since retired, Donovan finishing up last fall), you see the designated player in effect. There’s hardly any “upper middle class.” You either top out around $250-300,000 (if you’re lucky) or you’re a millionaire.Distribution of LA Galaxy Salaries from 2007-2014

This is an interesting point in MLS history and American soccer. The MLS has never been stronger, soccer’s popularity in America is growing, but it’s still not close to the same level as the three major sports. The MLS central office’s experiment to grow the league slowly as a single entity has worked, but its growing revenue and focus on stars is creating a lot pressure from the players who make up most of the roster. What will they do?

(MLS salary file and R code here on GitHub.)

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College Of Wooster Basketball Is Atlanta Hawks Good

The College of Wooster’s football is pretty good. Their men’s basketball team, on the other hand, is really good. Like, Atlanta Hawks good.

Since the 2006-07 season, my alma mater has made the NCAA Division III tournament (like the big NCAA tournament, but with amateur players) the last eight years. They’ve made it to the Final Four twice, and they lost in the championship game in 2011.

Year Tournament Result
2007 Final Four
2008 First Round
2009 Second Round
2010 Third Round
2011 Runner Up
2012 Sweet Sixteen
2013 Third Round
2014 Second Round

The Fighting Scots have been beasting their Division III conference – the North Coast Athletic Conference (NCAC) – for years now. Look at their conference winning percentage since the 2006-07 season:

NCAC Conference 2007-2014

In fact, they have the most wins in the 2000s for a Division III school, 387 from 2000-2014. How have they done it? Their coach, Steve Moore, who has been leading the team for 27 years (!), has his team score – a lot. Here’s how Wooster ranks versus the average offensive output in NCAC play. (Note: I started at 2006-07 because thats when the site d3hoops had easily accessible conference statistics. Data is through Friday, January 30.)

NCAC Conference Points Scored 2006-2014

The last three years, the Fighting Scots the highest scoring seasons out of the last full seven in the NCAC (just looking at conference play here). They have 7 of the top 15 conference scoring seasons under their belt.

How’s their defense? Well, not as good as their offense, but slightly better than average. In this case, being below zero is a good thing.

NCAC Conference Points Allowed 2006-2014

Their worst defensive seasons since 2006-07 have actually been the most recent. As they’ve ramped up the scoring, they’ve allowed more points. This hasn’t backfired yet, and they’ve been cruising in the NCAC for decades now.

(Note: R code for scraping d3hoops and making the plots is here.)

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How Slow Am I

A few things are certain in life: death, taxes, and finishing in the bottom half of running events. I’m really slow. I love to run, but it takes me a while to get from here to there and back to here. By the time I finish a local road race, the fastest runners have already had a chance to eat some bananas and shower salty kisses on their loved ones.

After taking a running hiatus last winter and most of the spring (knees, y’all), I’ve been hitting the pavement about once a week the last 4-5 months. On Thanksgiving morning, I “competed” in my first race since last fall’s 4 Bridges Half Marathon, the Gobble Jog at Marietta Square in Marietta, Georgia. It was a nice run that started at the Strand, made it’s way north up Cherokee, wound past some nice houses and a school, then back south down Church. It was unremarkable because of my finish, 916th place out of 1326, and my girlfriend and her sister, both of whom ran, waiting for me for about ten minutes.

I’ve tried to find the results of each race I’ve done since 2011 to show just how unremarkable my mediocre finishes are. I couldn’t find the results for two of the events, but I have eight: four half-marathons, one marathon, one 10k, a 15K-er, and a smidge-more-than-15K-er. First up, the results of each of these races by time and place.

Race Results

My times and places in these races are the large points. I’m not exactly the worst, but I am decidedly mediocre. Also interesting, the shorter races (the 10k Gobble Jog and the half marathons), barring Olde Rope and Red Top (the blue and teal colors, both tough trail events), have little variation in their times, up to a certain point. The full marathon times, however, climb slowly and steadily.

To better show my mediocrity no matter the distance, below is a chart that compares my finishes using percentiles from 2011-2014. I’ve also showed how I compare to my fellow racers aged 50 and older.

percentile finish

Well, I wish I could say I finished better than those AARP members, especially in 2012. I really owned 30% of those old farts in 2011 and 2013-14. (One race in 2013, the 4 Bridges Half Marathon, didn’t have age data as part of their results, so that’s why it’s missing from Ages 50+.) I will say, though, that my performances have improved since I really started running in earnest a few years ago. That I’m still only better than a third of participants is neither here nor there. I’ve been enjoying my time getting back into it and traipsing through the mean streets of Hillsboro Village and Sylvan Park.

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Legislative Effectiveness, Part II: The South

This is a second post about legislative effectiveness. The first post is here.

After looking at the difference in legislative effectiveness between the majority and minority parties using new research from the book The Lawmakers, this is a more in-depth analysis of their data for the region of the country that I live in and call home: the South. (The researchers themselves examine the role of Southern Democrats.)

In this analysis, I want to see, using their legislative effectiveness scores (LES):

  1. If the effectiveness of Southern representatives have increased with the growth in Southern population (Southern states should have gained House members)
  2. Where in the South the effectiveness has increased or decreased

To get the regions, I used the US Census Bureau’s designation of regions and divisions. The Census has a loose definition of the South. Most egregiously, in my opinion, is that they not only include Delaware, the District of Columbia, and Maryland in the South, but also smush it in with Georgia, Florida, and the Carolinas within the same sub-division, the “South Atlantic.” I can handle DC & Maryland being considered Southern only because of the Mason-Dixon line , but Delaware? Well, they were a slave state, so… Delaware, I thought I knew you (as a corporate tax haven)? Southern by the grace of God enslaving people.

Still, I need to split up the Census’ South Atlantic division, if only because it has eight states, while the other two southern divisions only have four each. It will make for easier comparing between the divisions. Delaware, DC, and Maryland will be paired with Virginia and West Virginia as “Middle South Atlantic,” while Georgia, Florida, and the Carolinas will be “East South Atlantic.” The rest of the Census divisions are here. (My head is still spinning about Delaware, so I don’t have the energy to scoff at Texas and Oklahoma being Southern, especially the Okies. ANYWAY.)

Test 1: Southern Effectiveness Growth 

To test if Southern effectiveness has increased, we first have to see if the number of members in the South has increased. I am assuming Southern membership will have grown because of the region’s population growth. (On a side note, the West should probably increase, too.)

Southern House Membership

Southern and Western membership in the House has been steadily increasing, while the Northeast and Midwest have been declining. This isn’t too surprising. But what about effectiveness?

Effectiveness by Region

This gets more interesting. Despite more Southern members, the average effectiveness of Southerners didn’t jump until the Republicans took over the House again in 2011. At the same time, Northeastern reps’ effectiveness jumped when the Dems took over in 2007 and then plummeted when Boehner and company got their mojo back.

Test 1 Result: Southern effectiveness didn’t actually increase until the Republicans took over the House after the 2010 midterm election. This seems to reflect the South as the heart of the Republican party, especially considering that Southern Democrats were losing effectiveness in the 70s and 80s.

Test 2: Where In The South?

Within the South, we can see exactly where House membership has grown.

Number of Southern House Members by Census Division, 1973-2011


While the “West South Central” (the green line: Arkansas, Louisiana, Oklahoma, and Texas) has been increasing, my newly crowned division, the “East South Atlantic” (the purple line: Florida, Georgia, and the Carolinas), took off in the 1990s. The rest of the South, House memership-wise (and thusly population-wise), remains stagnant. But how does that transfer over to legislative effectiveness?

Average Effectiveness of Southern House Members by Census Division

The mid-1980s, like in the second chart in this post, weren’t good for the South. Their influence was dipping in all divisions. However, once we get into the 1990s, the divisions are, well, divided. States like Alabama, Kentucky, Mississippi, and Tennessee (the red line) can’t find traction. It wasn’t until the GOP takeover of Congress in 2011 do we see each Southern division’s effectiveness ratchet up.

Test 2 Result: In the 1990s and 2000s, the South Atlantic states (Southern states that touch the Atlantic Ocean) were much more effective. The differences in effectiveness were also more pronounced. The split between the divisions is starkest in the Congressional sessions starting in 2007 and 2009, both Democratic majorities, when the Mid-Atlantic states’ effectiveness shoots up and the other three divisions are at or near their nadir. When that tanned Ohioan became Speaker, those three shot up while the Mid-Atlantic came down, showing exactly which parts of the South are dominated by Republicans.

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Legislative Effectiveness, Part I: Pelosi vs. Boehner

Two political science professors, Craig Volden and Alan Wiseman, have come up with a way to measure the effectiveness of individual House representatives in their new book. They’ve created a “legislative effectiveness score” (LES) that compares each individual member’s legislative productivity during one two-year session relative to other members of that Congressional session. (Each two-year term has 450 points – equal to the number of members – available.) In their words:

“As concisely defined, legislative effectiveness is the proven ability to advance a member’s agenda items through the legislative process and into law.”

They try to show how successful a member of the House is able to move their bill through the committee process, onto the floor, have it pass, and eventually be signed into law. (Within each of these steps there are more finely grained indicators of effectiveness.) Effectiveness is only related to bills – not deal-making skills, constituent services, media appearances, or eating corn dogs at state fairs. “Significant” and “substantive” bills are weighted more than, say, a new name for a post office. They examined the 93rd through 112nd House sessions, which span from 1973-2012.

Volden and Wiseman look at a host of indicators for each member to try and find what criteria, if any, lead to more effectiveness: committee chairmanship, majority or minority party, women, African-American, and more. In addition to all the richness of variables they examine, I’m also interested in how different regions, the South especially, have fared in this research.

But before getting to regional differences, let’s get a sense of what the LES looks like in general. I took their data set and played around with it in R. Here’s a chart showing the effectiveness of the average majority and minority party member. Remember, there’s 450 points available – an average of 1 per member – for each Congress:


As you’d might expect, a representative in the majority party is going to be more effective than a minority party colleague. That doesn’t necessarily mean that an individual Democrat in, say, the 99th Congress (1985-1987) is more or less effective than a Republican, but as a whole, the lefty is more likely to push their bill through than the righty.


In the above chart, we see the LES score of each representative split up between majority and minority party members. The minority members  are concentrated near the bottom – joined by most of the majority, by the way – while the most effective members are almost always in the majority. And guess who is the most effective lawmaker based on their data? Why, it’s controversial New York Democrat Charlie Rangel, who was chairman of the House Ways and Means Committee from 2007-2010 until he had to step down from the committee because of ethics violations. Despite being 84 and “disgraced” (in the eyes of some), he was reelected a couple weeks ago.

Last but not least, let’s look at a couple of lightning rods, House Majority Leader John Boehner and House Minority Leader Nancy Pelosi.


Speaker Boehner, using Volden and Wiseman’s calculation, is the much more effective legislator. He was a committee chair during the Bush presidency when the Republicans held the House. Pelosi never held a committee chair (she was on Appropriations and the senior Democrat on the Intelligence committee), just party leadership positions. This isn’t to say she wasn’t “effective,” just that the tangible data points used don’t translate well for her. Her prodigious fundraising for other Democrats isn’t incorporated.

Stay tuned for my look at the South through the lens of legislative effectiveness later this week.

(Code and data here on Github. Warning, the code is still a work in progress.)

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Map Quest: Nashville Residential Building Permits

Strap on your tool belt, we’re talkin’ ’bout building permits! Specifically, we’re dipping our toes into the building of new homes in Nashville, Tennessee, where we mourn the loss of former resident Swizzle Stick to the Big Apple. Bye, Tay-Tay!

Nashville’s real estate market has been on fire the last few years, and there’s much discussion in the local media about how the rising sales prices and rents are affecting the growing population. Looking at building permit data, specifically permits for new residences (not demolitions or rehabs, which would be interesting to see) would… permit me… to accomplish a few things:

  1. Use Nashville’s public data web site
  2. See if information on building permits coincides with the fastest growing Nashville neighborhoods
  3. Broaden my R knowledge by trying to make a map.

I’ve been getting pretty good at making charts in R, but whenever I’d see some egghead make an awesome map, I’d get envious. Learning that R demi-god Hadley Wickham has co-developed a package within R to make maps, using ggmap (the package) and Nashville data was a no brainer.

Without further ado, here’s where building permits for new residences have been distributed in Nashville. The lighter the blue, the more permits in that area.


If you’re familiar with neighborhoods in Nashville, most new residences seem to be in East Nashville and southwest of downtown. Let’s focus in closer to downtown.


Now we can really see the density of building permits for new residences in East Nashville, as well as the Hillsboro/12South (south of downtown) and Sylvan Park/West Nashville areas. This isn’t too surprising. We could look at these last two places, but let’s take one more zoomed in look at yuppie/hipster central, East Nashville.


Everyone is trying to build as close to Five Points as possible (without going west of Gallatin Pike).

The locations of new residential building permits show where homeowners and investors are remaking Nashville’s housing supply. It doesn’t explain the consequences of this building – the gentrification, huge rents, and traffic (to name a few) – but it does confirm that people trying to live in the city are trying to move to the same three or four areas.

(Code and data located here.)

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Frank Wren’s Firing: Looking At The Braves Through A New (To Me) Metric

While the Major League Baseball playoffs have been amazing so far, the Atlanta Braves’ 2014 season is mercifully over. After a quick start to the season (17-7), they finished three games under .500 and 17 games back from the division leader.

Oh, boy, was Atlanta’s offense terrible. They scored the second fewest runs in the majors and struck out the fourth most. It was painful to watch BJ Upton swing and miss so much. (His brother, Justin, only struck out two fewer times than BJ, although Justin can connect when he actually hits the ball.)

The general manager Frank Wren, the hand-picked successor of John Schuerholz, took the fall. (Schuerholz is considered the brains, along with manager Bobby Cox, of the Braves’ 1990s success.) He was fired after seven years on the job by… John Schuerholz. Who chose Frank Wren’s replacement, John Hart, a friend of John Schuerholz? Mmm, John Schuerholz. But we’re not here to talk about John Schuerholz.

Wren just had too many bad signings and dead money during his tenure. His decisions have been chronicled in depth here by Braves blog Talking Chop, so I’ll just look at the bottom line: Money and Wins. How much value did Frank Wren wring out of Atlanta’s rising salary?

We’re going to look at it by seeing how much he paid per win by doing a simple calculation: team salary divided by wins. To put the Braves’ performance in more context, we’ll compare them with the 2014 National League playoff teams: Los Angeles, Pittsburgh, San Francisco, St. Louis, and Washington. We’ll start by looking from 1988 through 2014, as far back as USA Today’s salary database goes.

Salary Per Win, 1998-2014

Every team is paying more per win these days. The revenue explosion in baseball (mostly from TV money), plus a strong players union, sees to that. The Dodgers, always big spenders, have outdone themselves since 2012. Their division rivals, the Giants, have been trying to keep up, and have won two World Series’ recently in 2010 and 2012.

Although this is interesting, the statistic doesn’t “normalize” the value of the win. How do we go about comparing salary per win when salaries are constantly rising?

The method I have taken is to compare the salaries and wins according to how well the teams do versus a .500 club with the same salary. Basically, how does their salary/win ratio per season compare against a team with the same salary that won 81 games? By then finding the percent change of the 81-win ratio from the actual ratio, we’ll be able to compare a team’s success (success in this instance being salary/win) from year-to-year.

Salary/Win Ratio vs Wins

The above plot show how this new relationship works. As a team becomes better than 81 wins (a .500 winning percentage), the salary/win value increases versus the 81-win team.

Braves Value vs 500 team

Focusing on just the Braves, Wren was extracting a lot of value out of the team from 2009-2012. It was a strong improvement over the last five years of the Schuerholz era. One could even interpret Wren’s firing after this season as a bit harsh. However, the bad free agent signings, a listless team, and some tension in the front office led to Atlanta’s upper management pulling the plug.

(Note: Not sure if what I did is really “new.” Baseball stats are sliced and diced so often, it’s hard to know what is original and what isn’t. Code and data on Github here.)

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