MLS
Introducing MLS xG-Elo: Matchday 4 Power Rankings
Check out the latest rankings to see which teams are on the rise and who is falling after Matchday 4.
If you follow Major League Soccer, you know the league standings don’t always tell the entirety of how teams perform, especially given the squirreliness of having Eastern and Western conferences and unbalanced schedules. Because soccer is relatively a low-scoring, and sometimes chaotic game, the better team sometimes loses to a lucky bounce or a moment of brilliance. On the flip side, looking only at underlying stats like Expected Goals (xG) ignores the fact that actually finishing your chances and putting the ball in the net is kind of the whole point of the game.
To get a picture of who is playing the good soccer, I put together a custom Power Ranking engine that blends the two together using a chess style Elo rating system.
Here is the methodology: Every time two teams play, their performance is graded on a 70/30 split. 70% of their grade comes from the score-line, and 30% comes from their share of the Expected Goals (xG) created during the match. The winner steals rating points from the loser, with a built-in weighting that adjusts for home-field advantage and gives a slight bonus for blowout wins.
One crucial thing to keep in mind when looking at these rankings: the slate does not wipe clean at the start of a new season. To make this model as accurate as possible, it has calculated the results of every single MLS match dating back to 2013. This means historical baggage matters. For example, a team like Sporting Kansas City is still being dragged down by their dismal run last year, while the reigning heavyweights started the 2026 season with a head start. You have to consistently play well over a long stretch to climb to the top.
I may tweak the 70/30 weightings or the home-field adjustments as the season progresses, but for now, this serves as a fun, somewhat mathematically grounded snapshot of which teams are truly trending up or down.
Take a look at the current standings below! (Note: Click the link below the image to view the live, interactive dashboard where you can click on any team to see a deep dive of their recent form!)
I’ll try to provide some more commentary and thoughts in the following weeks, but for now, it could be fun to have something new to argue about discuss.
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Nice work.
I will likely never build a model like this myself. However, it might make for a fun article to dig in depth to your calcs and decisionmaking process on why these weights are this and those weights are that, etc. Probably not the most popular article this website will ever host, but as an enthusiast site, I know there would be at least Some audience for it.
Thanks! I can try to suss it out a little more. I might want to make it a little dynamic and “faster” since in MLS, turnover happens, and carrying over last years results doesn’t really capture a teams quality; by the end of the year these numbers should look ‘better’ but I might play with it some, and would be happy to share more on the (honestly really simply) under the hood stuff.