Building Marcel, Part 1 (Addendum): Expected Goals per Shot

One more stat, and a few notes on what statistics mean

In the concluding section of my first newsletter on projections, I studied how different statistics predict player goal scoring. The study found clear evidence that the classic advanced statistics of expected goals and expected goals assisted (or xG and xGA) provide better projections of future goal-scoring and assisting than goals and assists numbers themselves. But there was one finding that was perhaps less intuitive for analytics. As I went over it in my head and in a few discussions online, I realized there was a bit more to say here. So this is a short addendum to last week’s newsletter.

The most notable finding to me in that study was that a regressed, weighted average of shots has a significantly worse correlation with non-penalty goals in the following season than a regressed, weighted average of non-penalty goals does. That is, if you want to know how many goals a player is going to score in the next season, you would be better off basing your projection on how many goals they have scored in the past than how many shots they have taken. Despite all the randomness in goal-scoring, it still has more “signal” of future goal-scoring than a count of shots attempted does.

I also found that expected goals was a better predictor of future goal-scoring than goals were.¹

As I went over this finding on a recording of my podcast, the Double Pivot, I realized that this is probably a finding about expected goals per shot. If xG does “work” in this sense but shots does not, then it should follow that crucial information is contained in expected goals per shot. It is a player’s tendency to take higher- or lower-quality shots, and the ability of expected goals as a statistic to capture that tendency, which allows us to project goal-scoring using more advanced statistics.

But I had not run these correlation tests on xG per shot. So, today, I did that.

Here are the results.