Introducing the European Power Rankings

We are at an interesting phase of the season. Enough matches have been played to make reliable assumptions about the strength of the teams involved, yet most relevant outcomes in league football are still to be determined. But the last two weeks have brought a new challenge to light too, as the European Cup Competitions awoke from their annual winter sleep.

When Ajax plays Groningen, usual models can provide an estimate of the teams’ playing strength, be it by tradional methods like shot rates, more advanced stats like Expected Goals, or even by the new Composite Team Rating.



But Ajax played Legia, a team they hadn’t faced ever before. Legia played just three double-legged confontations with Dutch teams ever, with one of those going back to the early seventies, and the most recent match-up with a Dutch side was their clash with PSV in 2011.

So, comparing historical outcomes between Ajax and Legia doesn’t work. Comparing outcomes between Legia and teams that Ajax play regularly, or Polish teams that play Ajax isn’t going to work either. Now what?



Well, now math!

Without overcomplicating things (hopefully), I’ll explain the basics of a solution to tackle this problem. All of this leans heavily on an idea of Michael Caley (@MC_of_A), who came up with a tweet, and an ESPN article, on European Power Rankings, a few weeks ago.

The basic idea is that although Ajax and Legia didn’t meet before, and not one team played both Ajax and Legia this season, if we look at all matches played in European leagues and European club competition, there are still enough indirect links between the teams to get an estimate of their strength.

We’ll use a data set of all Europa League matches and Champions League matches, including qualifiers. To this set we add all matches played in leagues that have teams involved in European football this season. For the main EL and CL tournaments and the top-5 leagues, plus the Eredivisie, Russia and Turkey, we use ExpG numbers. For all other matches we use goals.



Next, a lineair regression is constructed to assess the influence of both teams on the match outcome, ExpG results if available, goals results if not. The regression assigns a coefficient to each team to reflect the team strength. Good teams are associated with a positive result in terms of ExpG / goals, bad teams with a negative result.

With the present abundance of European football, there are enough links between the teams to obtain decent rankings. Ajax may have played Team X that has played Team Y from league Z. Other teams from league Z have played Dutch teams, and other teams that have played Legia, etc etc. Without us having to dizzy ourselves by discovering all those links, the regression just shows us how to estimate the strength of each team.

The next graph shows you the top-20, with the number representing the coefficient that a particular team is assigned. For now, don’t pay too much attention to the exact numbers, as I still need to work this into something more satisfying than an uninterpretable regression coefficient. Just use it to get an indication of order and separation between teams.

Top 20 - bar chart - 03 maart 2015Looking at the top-20, we can see that this method passes the eyeball test. Bayern and Barcelona are shown as the strongest teams in Europe, while the chart is filled with the usual suspects of European club football. The top-20 is dominated by Germany, Spain and Portugal, while France and Italy are limited to a single top-20 side.

What about the world’s richest league? The EPL teams, apart from league leaders Chelsea, play an outside role in Europe’s elite, according to this model.


Ajax, PSV and Feyenoord

To find Ajax and Legia we have to scroll quite a bit further down, far away from the top-20, to the 191st and 172nd place. At the same stage, PSV (92nd) unsurprisingly lost heavily at Zenit (12th), who as the second highest ranked team in competition remain one of the favorites to win the Europa League, according to the European Power Rankings. Feyenoord (77th) was eliminated by Roma (32nd), who are rated significantly higher than the Rotterdam side.


Next week

Let’s finish with the rankings for next week’s ties.

(89th)               Everton           –           Dinamo Kiev              (51st)

(112th)             Dnipro            –           Ajax                            (191st)

(12th)               Zenit               –           Torino                         (44th)

(11th)               Wolfsburg       –           Inter                            (36th)

(13th)              Villareal          –           Sevilla                         (16th)

(23rd)               Napoli             –           Dinamo Moscow        (147th)

(49th)               Club Brugge   –           Besiktas                      (80th)

(47th)               Fiorentina       –           Roma                          (32nd)





8 thoughts on “Introducing the European Power Rankings

  1. insdieman

    FC Porto ahead of Real Madrid? Celta and Frankfurt ahead of Man City? Benfica ahead of Chelsea? Hoffenheim ahead of PSG? those kind of set off alarm bells to me. I don’t think this passes the eye test at all. I mean Benfica just finished last in one of the easier CL groups, it’s hard to imagine the same thing being more likely to happen to Chelsea

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  3. Pim

    Predictions were pretty accurate I must say. Villareal and Sevilla was wrong, but they were rated as 13 and 16. Also Fiorentina and Roma was wrong, but again 47 vs 32. Nevertheless you’re on to something here 🙂

  4. De Hete Pappie

    How is this any different or more reliable than UEFA’s own club rankings? Granted, if clubs clearly underperform (eg City, Galatasaray) it isn’t fully 100% predictive, but on the whole that list looks quite ‘right’.

  5. hello

    dortmund were terrible in the bundesliga this season, but they did quite okay in the bundesliga. since they won against arsenal in the CL and lost against a lot of teams in the bundesliga, does this push the ratings of the german teams?

  6. NB

    Is there any repository (a Github repo or something similar) where it’s possible to find data, calculations and the full ranking?

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