## The “obvious” stat that could spell life or death for the struggling football manager

Last week I wrote a little bit on Expected Goals. While not a new metric, it’s starting to come into vogue as more and more analysts demonstrate its predictive value.

The idea behind Expected Goals or ExpG is simple: it uses average conversion rates by shot type–whether by location, foot or head, distance etc.–to add another layer of analysis to raw shot data, like Total Shots Ratio.

There has been an outpouring of work in this subject over a short period of time, so it’s hard to keep track of every new development. My tentative opinion however based on the very early returns is that the truly “repeatable” element (that is the part of ExpGs which involves skill rather than random variation) is, as with shots, the volume of higher probability chances, rather than the actual ExpG to Actual Goal count which I think, like total team shot percentages, come to down to as yet unknown variables and skew a lot higher for the “best” teams.

Now as I’ve discovered over the years, whenever you write about what you think is clearly an exciting development, someone inevitably leaves a comment like this one:

“Wait. So youâ€™re telling me the team that creates more, high quality chances, will win?

BRILLIANT!”

(This is a real comment).

And this very real commenter has a point. What do football clubs do except to try to create as many high quality scoring chances in a game as they can with the players they can afford? What is the added value of this kind of statistical analysis?

Well, as Daniel Altman eloquently argued last week, it depends on just what exactly you’re looking to do with the data. If you’re a gambler, this kind of data can help improve your predictive model and put more money in your pocket. But what if you’re a manager?

Before I answer, I would urge you to take a quick look at Michael Caley’s Premier League table, which incorporates a host of data on Expected Goals for and against, shots from various areas of the pitch, etc, and reveals a fairly distinct correlation (this season at least) between the ratio of ExpGs for and against and place in the table.

Done? Good.