Power Ranking Averages - Wk 31-32

Another double week for MLS with both 31-32 done. 11 out of 15 sites published rankings, which do not include the midweek games.

As always, if you know of a site I have not used please let me know in the comments and I’ll look into adding it to the list for next year!

Sites Used

• Jeff Sagarin
• Five Thirty Eight (Proj. points)
• Who Scored
• ESPN
• Massey
• Sonny Moore Rankings
• MLS
• Sports Club Stats (Seas. finish avg)
• Broadway Sports
• 3rd Degree
• Freeborg Power Index
• MLS Fantasy Boss
• Club and Country
• US Soccer Players (monthly)
• Coach and Crew (monthly) - Drop notice, no rankings for 5 weeks

You may notice the inclusion of ‘analytic’ sites; they serve to function as a ‘control group’ to the rest which are based on personal opinions. There are also sites included that some will argue are ‘prediction rankings’ - but that also is a form of Power Ranking is (see the quote at the top) since it uses algorithms to calculate a team’s likely final position.

Bias for or against certain teams are sometimes an unfortunate feature of power rankings. It can be based on their analytic formula, or the raters preference. In some cases the bias can become extreme - If you feel a site got the ratings wrong for your team I invite you to contact them regarding it.

I will typically only remove sites for two reasons.

1. Duplicating / copying ratings from another source on the list.
2. Failure to update for 6 consecutive weeks. Previous ratings will not be removed, but new ones may or may not be added. I will still periodically check them to see if they have resumed.

All the averages use the Olympic method (I.E. Truncated Mean value) of dropping the highest and lowest scores, and then averaging the rest to reduce bias.

The full spreadsheeet is here.

• Highest Standard Deviation: Vancouver Whitecaps 4.99
• Lowest Standard Deviation: New England Revolution 0.4
• Biggest Rise: New York City FC, Vancouver Whitecaps up 4
• Biggest Fall: D.C. United down 8

Site Bias

All sites are going to have bias, whether conscious (blogs) or due to analytic calculation (based on past performance). This section lets you see the extent that sites are biased for/against teams. Negative totals (-) are bias FOR, positive numbers (+) are bias AGAINST.