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Week 9 - Meta Power Rankings

04/30/2013 11:46 AM | 107ist Admin (Administrator)

—by Mike Coleman

Tuesday is one of my favorite days of the week as far as soccer goes. It’s the day when most of the power rankings are released (for those of you who are unfamiliar, Power Rankings are where ‘experts’ look at the 19 MLS teams and rank them based on their current performance and future potential – these rankings are, of course,  100% subjective).

Another one of my favorite things is futzing with data in Excel. I’m not a statistician by any measure, but I love manipulating data and trying to figure out any relationships that might exist (yes, I know, that sounds terribly exciting).

In any case, back to soccer . . .

I read about 5 different power rankings, and have always wondered how they compare. So this week I built myself an excel spreadsheet where I take power rankings from 5 different sources (MLS.com, Bleacher Report, Sports Nation, Soccer By Ives, and The Oregonian) and figure out what the average ranking was, how much (on average) the teams moved from one week to the next as well as the standard deviation in the ranks and movement. Finally, I thought the results of the past 5 matches would be an interesting indicator of a teams "power" (although it would be a trailing indicator at best, and doesn't account for who the opponents were during that time e.g. there is no "strength of schedule" component)

I’m not sure if anyone else cares about this, but I thought I’d share it here this week. If folks dig it, I’ll happily keep doing it. I’m also looking to go back and input the data for the first 8 weeks so I can chart the change in power rankings over the season.

So, without further blathering here are your meta power rankings for Week 9:


Nothing to surprising here, but what’s interesting is what happens when you look at the last point totals from the past 5 matches:

 

 

 

 

 

 It would seem near the top and bottom the last 5 games are pretty well reflected. Houston is ranked a bit higher than their past 5 matches would suggest. The real surprise is San Jose who, despite only earning 3 points in the past 5 matches (which is tied for 2nd worst in the league) is ranked middle of the pack. One can only assume that the ‘experts’ feel like the 3 points are not indicative of their potential.

 

 

 

 The next thing I looked at was movement. The Union were this week’s biggest losers – their 2-0 loss to New England cost them an average of 3.4 spots in the Power Rankings. On the opposite side of the spectrum Columbus picked up a whopping 3.6 points by virtue of their 3-0 defeat of D.C. United (one could question if beating the consensus worst team in the league warranted such a big leap). D.C. United, Colorado, and Chivas all  held pretty steady week after week, and our beloved Timbers picked up the 2nd highest number of spots (2.8) with their defeat of Sporting Kansas City (it would be hard for me to argue that they should have picked up more spots as that would put them above Montreal, their lone defeat, LA, and Dallas).

The last thing I looked at were the standard deviation of both the movement and rankings. Like I said, I’m not statistician, but I believe that standard deviation (which basically provides an indication of how much variation there is in a set of numbers) offers interesting insight into what the ‘experts’ all agree on and where there is a lack of alignment.

 

With a standard deviation of 0 the ‘experts’ all agree that D.C. United is the worst team in MLS – every single one of them ranked them 19. On the other end of the spectrum there is considerably less agreement on New York (1.82) and Philadelphia (1.92). In the case of New York the rankings are almost uniformly spread from 7th (Soccer By Ives and the Oregonian) to 11th (Bleacher Report). For Philadelphia the main outlier is The Oregonian where they ranked 15th (compared to 10th, two at 11th , and 12th) – clearly GCA has no love for the Union. It’s also important to note that the teams at the top are generally agreed on by the ‘experts’ (as is the placement of Vancouver).

 

 

 Looking at the deviation in movement – clearly the biggest outlier by a pretty significant margin is New York. In two rankings they gained a whopping 4 spots, in two rankings they gained 2 spots, and in one ranking, Bleacher Report, they actually lost 2 spots, falling from 9th to 11th  (for the sake of completeness I will note that they were actually tied for 11th).

 

 

 

What does all this mean, I have no idea. Like I said, I just like to geek out with numbers. I’m sure some of my conclusions aren’t necessarily that insightful (or even correct). If you have a suggestion on how to improve this exercise, let me know.

For those who want to see the information for themselves, you can find my spreadsheet here on google docs.


Comments

  • 08/08/2016 9:05 PM | 107ist Admin (Administrator)
    Anthony says:
    Tuesday, April 30, 2013 at 11:18 pm

    Interesting stuff! I too like to geek out on numbers, though I rarely actually compile said numbers myself. Good work here, I think it could be neat to see these as often as you want to do them. Keep it Up is my vote.
    Link  •  Reply
  • 08/08/2016 9:05 PM | 107ist Admin (Administrator)
    Max says:
    Wednesday, May 1, 2013 at 12:31 am

    By no means am I asking you specifically to do this, due I would live to see someone break down our passing/shots/possession etc. to the rest of the league in the same format. See if extra passing means more success ie. higher in the table and other stuff. But I do like this a lot, and would love to read this every week!
    Link  •  Reply
  • 08/08/2016 9:06 PM | 107ist Admin (Administrator)
    Mike Coleman says:
    Wednesday, May 1, 2013 at 8:24 am

    Thanks for the extra sources.
    I actually used Sporting News, but for whatever reason called tem Sports Nation, and Goals.Com is actually just a reprint of Sporting News.
    I’ll add in the others for Week 10.
    Link  •  Reply
  • 08/08/2016 9:06 PM | 107ist Admin (Administrator)
    Scott T says:
    Wednesday, May 1, 2013 at 8:16 am

    Great stuff here! For a strength of schedule, you could take an average of the ranking for the opponent and use that as a multiplier. Example: a #2 team plays a #16 team and wins. The win would count as 1 x 3 (third lowest ranking opponent). There are other solutions as well of course. Basically, the multiplier is going to be low for low ranked team and will be high for top teams (i.e. a #1 ranked team has a multiplier of 19).

    Other good stats to see compared would be margin of win (sort of a goal differential) and number of shots on goal (shows who’s attacking team and who’s a defensive team). The time wasting is endless here! Ha!

    Thanks for your work here! See ya all on our Pitch Thursday night. Let the weekend begin with green smoke billowing from the Army!
    Link  •  Reply
  • 08/08/2016 9:07 PM | 107ist Admin (Administrator)
    Mike Coleman says:
    Wednesday, May 1, 2013 at 8:27 am

    Thanks for the suggestions.

    While I agree that average power ranking of a team could proxy strength of schedule, that would require me to know who each time played the past 5 weeks plus I’d also want to figure out what the “home field advantage” effect was. And, honestly, I’m not sure I have *that* much free time :)

    But I do concur there is an endless amount of time wasting possibilities here – thanks for reading.
    Link  •  Reply
  • 08/08/2016 9:07 PM | 107ist Admin (Administrator)
    CaptRK says:
    Wednesday, May 1, 2013 at 12:51 pm

    Interesting read and good stats. Thanks for sharing.
    Link  •  Reply


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