Backdrafting

A question came up on BigSoccer about how many players taken in the supplemntal draft wound up being signed for their team, which got me wanting to clear up something I had done when I started loking at the draft figures for 2012. Namely, who, from 2011, was still playing for their team in 2012, and how much playing time were they seeing?

From what I was able to track down, it looks like 25 out of 54 players saw action in 2012. The first 11 players taken saw significant playing time. Those guys were :

Omar Salgado
Darlington Nagbe
Perry Kitchen
Zarek Valentin
Zac MacMath
A. J. Soares
Kofi Sarkodie
Michael Nanchoff
Jalil Anibaba
C. J. Sapong
Will Bruin
After that it became kind of a crapshoot, with not a lot of correlation between position picked in 2011 and playing time from 2012. Here's what the graph looked like.

For those players who saw playing time, the average amount of minutes played was 1,528, almost exactly a half season, but you can see from the graph this bounces around a bit. Some guys played a lot, and some guys played almost none.

Of course this doesnt take into accoun players who are "projects" and never anticipated to start immediatly, or players who left the league for greener pastures, or left due to injury, but it seems to make a bit of sense that picks #1 - 10 will tend to stick around while players taken later on will have a broader range of success.

Consistent Inconsitency

So I noticed one or two weird things creep into my spreadsheet when calculating rankings this round, and it's because of the way the formula does the fading averaging over five games when five games have not yet been played. In this sense, Houston, having only won one game, cruises a little unfairly on that, while on the other end Seattle's single loss has then unfairly punished as they're behind even Colorado, who have lost two. I won't get into details, but rest assured, this should be sorted out once every team is at five games. Well, maybe a little detail. Basically, the normal rating formula is calculated using 1A + 0.4B + 0.3C + 0.2D + 0.1E. With only one game played, Seattle has 1 loss/1 game played = 1. With two games played, Colorado has 1 + 0.4 = 1.4 losses / 2 games played = 0.7. So Seattles one loss looks bigger than Colorado's 2 losses. It's not presented here, but Seattles calculated rating is -0.333 while Colorado's is 0.231, which is -0.333 * 0.7. Note that it works out like this only because all the losses have been by one goal...

At any rate, here's how the tables look this iteration

LA still at the top, Candian teams climbing, with Seattle and Chicago in the basement. Too early to tell anything, obviously, but it's shaping up to be a wild March I think.

Upside down in Canada, eh?

Well that wasn't all that enjoyable. Two more give away goals and a mountain to climb in the second half on oen of the worst playing surfaces I've ever seen. Still, it's tough to win on the road in MLS, and 3 points from two away games isn't all that bad going into the homeopener next week.

Bieler looks like a great pickup, and I've got to think Zusi will be seeing some offers down the road. Convey and Feilhaber need to get it together though, they're just not getting it done like Kei and Roger were.

Here's the player ratings for the game. Teams actually weren't very far apart at all, and if you look only at the stats, SKC really controlled a lot of the match, especially in the second half. Just couldn't find a way to breakdown Toronto once they had a two goal cushion. Back line cohesion seems to be a problem as well. I've seen so many times now where half the back line would step up while the other half would be a step or two late in keeping a man onsides. I'm not saying we're playing an offside trap neccessarily, but the high pressure and high back line seems to be giving up a lot of space in behind the defenders, and if they're not communicating, better teams can really punish us.

 So kudos to Robert Earnshaw and TFC for the win. Hopefully, Toronto's last of the season.

MEANINGLESS UNFRIENDLIES

So I hesitate to throw my hat into the ring in Week 1 with some power rankings since they're totally unrelated to the Week 0 ones from a bit ago, but I decided, for consitencies sake, I'd try to get in the habbit of doing this every week.

The reason I hesitate is that these ratings really don't get off the ground every team has played five game (they use a five game running average in the formula), so the numbers start off really meaningless and get better as the season goes on. But hell, even if the math is silly, let's just go for it.



Actually nothing too terrible there just yet... But like I said, this is all but meaningless, just based on one game and has no relation to what happened last season or evaluating overall team strength. Give me a few weeks and we might be able to hammer out something a bit better.

Until then?

Courage.

SKC-Union Player Ratings

So soon? So soon.

I'd say I'd add some major thoughts to this post, but I only really have three. The first is, for the first 20 minutes, SKC looked awful, unorganized, and uncommunicative. Coming out of preseason maybe I shouldn't be that worried, but Philadelphia should have had at least one or two more goals in the first thirty minutes, and that would have put the game out of reach. We came out looking like Toronto. We can't look like Toronto.

The second thought was that I was glad to see the response, especially the second half adjustments.

The third was, I thought Nagamura had a helluva game, even if it didn't show up in the stats.

That said, these are stats based player ratings, and given that, there's one clear Man of the Match. Here's how the numbers worked out. Same system as last year.

No surprise there. Man of the match to Zusi, who notched a goal and assist. Rosell also with a great game, and hard to say anything bad about LeToux. Philly fans will be thrilled to have him back.

So hats off to Mr. Zusi, who has probably sealed a spot on the USMNT roster if he can keep up putting up games like that.

Week 0 Power Rankings

We're baaaaaaack.

Technically, we were never gone. But still.

So, to do the most meaningless of meaningless things, I opted to do one final spreadshet iteration before retiring the 2012 version and starting up a new 2013 one. I ran the power ranking system through the playoffs to determine a final final set of power rankings to use as the starting point for this season. Well, that's not entirely true, this season will actually start with everyone at 0, since I think there's enough parity in MLS to dictate that past season results are no indicator of next season performance. I've even posted about it! But that's under the bridge.

Here's how the numbers worked out :

San Jose	1
Kansas City	2
DC	3
New York	4
LA	5
Houston	6
Seattle	7
Chicago	8
Salt Lake City	9
Columbus	10
Colorado	11
Vancouver	12
Dallas	13
Montreal	14
New England	15
Philadelphia	16
Chivas	17
Portland	18
Toronto	19

Maybe it's blasphemy to not put LA at #1 and Houston at #2 due to their postseason performance, but I simply weighted each post season game as another match. Perhaps I should have given more weighting to each round, but this seemed like the best way to do it. I think I'll be making a few tweeks to the system this year, but otherwise, it should be more or less the same. Stay tuned!

MLS : More like Germany, less like England?

So awhile ago I did a look at the season over season correlation in MLS and the PRemiership and found that there's much less correlation in MLS than there is in England. i.e. Good teams in the Premiership tend to stay good, and bad teams tend to stay bad, and there's not much surprise in where teams are going to end up. Conversely, in MLS, each season tends to be a new season and it's much harder to predict where a team will finish based on how they performed last season. I thought maybe that I should take a look at some of the other leagues and ee how they stood up and the first one I looked at was the Bundesliga. I was a little surprised to see that there's actually less correlation in the Bundesliga than there is in MLS. The highest correlation there was in the 2008-2009 season, with an R value of 0.65, but the last two seasons have been highly variable, with correlation values of 0.08. The average correlation over 5 seasons was 0.30 while the R^2 value was 0.087, lower than even MLS.

In looking at the numbers, this actually seems to have been an artifact of typically dominant teams like Schalke, Stuttgary, Weder Bremen and Wolfsburg all doing poorly in 2010-2011 and then doing well again in 2011-2012. I'm not sure there's that much to read out of it and sort of wonder if looking at a wider set of data would come to a different result, but I do think now that the German system seems to foster more pairty than the English system and seems to be comparable to MLS, while still able to create competetive teams that do well in European competition.

Here's the chart.

Some day I'll do a good side by side comparison of each of the worlds major leagues, but for now, it seems like MLS is trending more like the Bundesliga than the Premiership in terms of team parity, and I think that's a good thing.