High schools attended by players on the Crossfire and Sounders Academy U15/U16 teams 2010-2014

Crossfire Academy

Using the rosters on the http://ussda.demosphere.com pages for the Crossfire Academy U15/U16 teams for the last 4 years and recorded data on the high school listed for each player.  In most cases the HS was listed on the USSDA team page.  When it wasn't, I did a google search.  In many cases a google search would come up with a local article mentioning them in a HS game (soccer or other sport).  High schools were categorized as Eastside (Redmond, Bellevue, Issaquah, Mercer Island), Seattle/Shoreline, South SeaTac (Tacoma, Auburn, Kent, etc), Everett/Snohomish Area and Other.  Very few players were in Other. High Schools in each category are at the bottom.

The figure shows the fraction from a high school in each region for players listed on the roster of the Crossfire Academy U15/16 team (all players listed) from 2010-2011 to 2013-2014.  Overall the fraction of players from Seattle and South SeaTac high schools declined during the 4 seasons with sudden drop of players attending Seattle area high schools in the 2013-2014 season.

Interestingly the Seattle high schools for the players is overwhelmingly private.  Seattle private high school attendance is approximately 20%, while 70% of the academy players attended a private high school.  Sample size is small however (7 players with 2 public and 5 private).  The private/public split of the players attending eastside high schools matches the approximate private HS attendance on the eastsite (ca 10%).  12% of players going to an eastside HS attended a private school.  Sample size was 25 players (22 public and 3 private).

Sounders Academy

Same plot except that I wasn't able to get HS (not listed on the USSDA website) but the home town is listed.  So this shows home town.

Sounders and Crossfire U15/16 Academies together

Raw numbers
Note that roster # on the USSDA team page in 2011-2012 was unusually high.

U15/U16 2010-11 2011-12 2012-13 2013-14 Eastside 6 5 3 11 Seattle/Shoreline 5 5 2 0 Everett-Snohomish 4 4 2 2 South SeaTac 7 8 3 3 Other 1 5 4 1 EWA 1 3 1 0 Alaska 0 0 0 1 Unknown 3 2 4 4 Total known 24 30 15 18 Total 27 32 19 22

Categorization of HSs

Eastside (private are *)
Redmond, Mercer Island, Issaquah, Sammamish, Eastlake, Bellevue, Skyline, International Community School, Eastside Catholic*, Bellevue Christian*

Seattle/Shoreline is HSs in the SYSA boundaries.
 Seattle (private are *)
HS: Nathan Hale, Ballard, Lakeside*, Seattle Prep*, Seattle Christian*
Shoreline
HS: Shorecrest

South SeaTac
HS: Todd Beamer, Auburn Riverside, Puyallup, Mount Rainier, Stadium, Decatur, Highline, Thomas Jefferson, Woodrow Wilson, Kentridge, Rodgers, Emerald Ridge, Tacoma Baptist*

Everett/Snohomish/North SeaTac
Inglemoor, Glacier Peak, Snohomish, Everett, Meadowdale, Woodinville, Monroe, Henry M. Jackson

More on the Relative Age Effect in the US Development program

"For everyone who has will be given more, and he will have an abundance. Whoever does not have, even what he has will be taken from him." Matthew 25:29

In my last post I looked at the birth months for a few of the Academy teams.  This shows that the age-cut is skewing the birth month distribution.  The Matthew Effect says that those players with an advantage, in this case being older for their age group, will advance faster in their skills due to the extra play time and coaching because they would be more likely to be the 'stars' being the eldest on the team.  What's interesting is that US players will mainly have been affected by a different cut-off during their U11-U14 years before they try-out for an academy team at U15/16.  Most US players would have been playing under a system with a August 1 cut-off for their U11-U14/15 years.   If the Matthew Effect is operating, we would expect to see an overabundance of August relative to July birth months on the Academy teams.  August boys were the eldest in their age group while July boys were the youngest---however they are basically the same age.  Now, keep in mind that July boys might have started formal soccer a year earlier (being born in July), so perhaps this extra year (at age 8-10) would offset the disadvantage of being the youngest.

For this analysis, I used all players on the US Development Academy teams whose citizenship was listed as USA.  No players who listed another country or dual citizenship were included.  The following shows the birth month for the U15/16 players born in 1996 (U16).  I left out the 1997's since my previous post suggested that their birth months is strongly skewed to the first quarter.  I also looked at the U17/18 players, broken out for birth year 1997 (U17) or 1998 (U18).

The following plot shows the result.  Y-axis is the frequency of the birth month.  The thin line is the median expected frequency.  It's wavy because the months don't have the same number of days.  The dashed lines are the 95% percentiles.  We see that there is an overabundance of quarter 1 boys, but look at the difference between July and August boys.  They are basically the same age, but July boys are much less frequent than you would expect and August boys are more frequent.   The strange birth month frequency for the U18's (birth year 1994) presumably shows the effect of college.  The boys born in 1994 in Jan-July would be in college while the 1994 Aug-Dec boys are high school seniors.

It matters when you are born: the Matthew Effect

One of the questions I'll be looking at with the strength ratings data for multiple ages is the effect of age on strength of a team. Basically, 'what is a year worth?' and how much can a team potentially gain by being stacked towards kids who are older within the age group.  Note, it is not that coaches are looking at birth month when selecting players.  They are selecting the best players. Age and skill/physical prowess/speed etc. are highly correlated in kids, so the best players will tend to be the oldest in the age-bracket.

This is related to a well-known effect called the Matthew Effect, which you'll be familiar with if you have read the book Outliers. Basically, the existence of age-cutoffs means that kids born towards the beginning of a cutoff have an advantage and are preferentially selected for elite junior teams. These early advantages then translate to an over-abundance of players with birth months near the cutoffs on the most elite teams. So in our Aug 1 cut-off system, kids born in fall are at an advantage and summer kids are at a disadvantage. If the cut-off is Jan 1, then 1st quarter kids have an advantage. Here is a nice blog on the Matthew Effect: The Matthew Effect: Talent ID and sports science application.

Do we see this in soccer? Definitely. The US National Development program is on a Jan 1 cut-off. Here's some pie plots of the birth quarters of the players on the Sounders Academy U16, Crossfire U15/16, and US National U-15 men's teams. For Crossfire, there were 4 players listed as DP. I did not include them as the stats indicated that these players didn't play any games (so presumably DP means 'did not play'). As you can see, there is a clear advantage to being born near the Jan 1 cut-off. Notice the almost complete absence of quarter 4 boys. (The Crossfire team did have a couple qtr 4 boys but they were all "DP").

Does this translate to an over-abundance of players with birth years in the first quarter on the National Team (U-23)? Well, there is an over-abundance of those players on the US National Team.

The Crossfire and Sounders teams are U15/16, which means that some U15s are on the team. Let's look at the distribution of birth year on the teams and the birth months of the U15s:

My next post looks at the birth month effect across all the US Soccer Development Academy teams and shows that we see the '4th quarter' deficit across all team, but we also see a 'May-June' deficit.  The latter would be consistent with an effect of the Aug 1 cut-off on players before they enter the USSDA program.  Another post looks at the birth month effect and the 'December deficit' in the 2012 Olympic rosters and Division I US college soccer players.
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Related work showing that even a 1-month average increase in the team's age has an effect on the team's performance:
Augst and Lames (2011) The relative age effect and success in German elite U-17 soccer teams
http://www.tandfonline.com/doi/abs/10.1080/02640414.2011.574719