Soccer Analytics: MLS and Premier League Comparison

In the previous entry in this series we discussed the relationship between team performance (points in the standings) and a ratio of expected goals for to expected goals against. We also showed the impact of the team’s salary on their performance. Note that we did this all for the US MLS soccer league. Here’s what we saw from 2022:

MLS 2022 season results: Impact of npxG ratio and team salary on points

This shows a strong relationship between points (the teams on the left side of the chart were the highest ranked) and the xG Ratio. But there doesn’t appear to be any correlation between the team salaries and performance. This could mean a lot of different things, but the well-known relationship in the English Premier League between salary and performance seems to be absent in the MLS. So I wondered, what would this graph look like for the teams in the Premier League during 2022? Would we see the same trends or something different? So here goes:

Premier League 2021-2022 season results: Impact of npxG ratio and team salary on points

A few things are obvious from this comparison.

  1. The premier league teams are paid WAY more than MLS. We knew that this was likely to be the case, but this is an order of magnitude higher! Perhaps Manchester United is reflecting Ronaldo’s salary in that big outlier!
  2. In the Premier League, it is clear that there is a strong direct correlation between team salary and performance. This is very unlike what we saw in the MLS. I can think of a few reasons… first, the MLS has a kind of salary cap that I have read prevents them from using salary as effectively as the European leagues. Second, the Premier League has relegation, where teams that end at the bottom of the league (sorry, Norwich City) get relegated to the second tier league while the top performers in the second league get pulled up. This is likely to have major effects on the salary. There are likely many more reasons.
  3. Note how smoothly the xG Ratio descends down the point scale compared to the MLS. In the MLS chart, we saw a general trend with some outliers, but it is very clear that the xG ratio correlates strongly with performance in the Premier League.

Why is this interesting?

Well, what we see here are two measures that are easy to collect which are nice proxies for team performance. In the Premier League, we know that increasing team salary tends to lead to improved performance. We also know in both leagues that increasing the number of expected goals by focusing on creating more quality shots (instead of concentrating on only perfect shots) and reducing your opponent’s number of quality shots leads to better performance. This is important, because of the chance involved in converting a shot (about 1 out of 10 shots are converted). Expected Goals gives teams a good measure to try to optimize.

LINKS to Other Soccer Analytics Entries

  1. Soccer Analytics Series Intro
  2. MLS and Premier League Comparison
  3. Home and Away Luck Metric
  4. Does Counterpressing Work? Evidence.
  5. Evaluation of Outcomes using the Luck Metric
  6. More Analysis using the Luck Metric
  7. Soccer Analytics in Practice – Youth Soccer Example
  8. xG and Luck update on recent MLS season

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