Different injuries have different impacts. In this article I am going to look at how historical injuries have affected teams from the perspective of expected goals. Given each squad member’s xG per 90, and the number of games they missed, what’s the total amount of xG that was sidelined in a season?

I call this metric EGMAYO: Expected Goals Missed due to the Absence of Your Offence. Here are the top 10 EPL seasons by EGMAYO:

Season	Team	EGMAYO
2014	Arsenal	26.9
2010	Arsenal	23.3
2013	Arsenal	22.9
2012	Manchester City	19.4
2014	Liverpool	17.7
2013	Manchester City	17.4
2014	Manchester City	17.2
2014	Newcastle United	15.0
2011	Manchester United	14.8
2012	Manchester United	14.2

This indicates it’s not necessarily overly dramatic to point out that Arsenal’s injuries have had a big impact. Their lowest EGMAYO season was 2012, scoring 7.1, against an overall EPL average since 2010 of 6.7. Man City were title runners-up in their worst EGMAYO season:

Season	Team	Player	Games	Chance Quality per 90	Chance Quality missed
2012	Manchester City	Jack Rodwell	18	0.36	6.42
2012	Manchester City	Sergio Agüero	7	0.45	3.18
2012	Manchester City	Micah Richards	22	0.12	2.67
2012	Manchester City	Maicon	16	0.15	2.43
2012	Manchester City	Mario Balotelli	4	0.53	2.12
2012	Manchester City	David Silva	3	0.23	0.69
2012	Manchester City	Aleksandar Kolarov	6	0.10	0.57
2012	Manchester City	Vincent Kompany	7	0.06	0.42
2012	Manchester City	Samir Nasri	2	0.16	0.32
2012	Manchester City	Javi García	3	0.09	0.28
2012	Manchester City	James Milner	2	0.12	0.23
2012	Manchester City	Pablo Zabaleta	1	0.08	0.08
2012	Manchester City	Joleon Lescott	2	0.02	0.03

Obviously it’d be far more interesting if we could better capture Vincent Kompany’s 7 game absence from City’s back line, or David Silva’s expected assists missed in his 3 games, but we’re not there yet, which brings me to:

Caveats

Sometimes my kids go up to a box of toys and just empty it onto the floor, play briefly with a couple of things, and then bog off to let mummy and daddy deal with it. Perhaps I haven’t made this abundantly clear, but this is very much my approach to football stats. I enjoy cutting data up, throwing it haphazardly on the floor, and seeing what it looks like, especially to other people. I intend to return to this later to clean up, but I’d like to make a few things clear:

• This metric takes no account of the squad members that come in and replace injured players. Obviously these replacements have their own output in terms of xG, which may even exceed the injured player. Ideally, we would capture all of this in a similar way to Chad Murphy’s model, or even in more detail to capture the strength of schedule faced during each injury.
• It takes no account of the importance of midfielders, defenders or goalkeepers. It’s only interested in the xG per 90 of a injured players, and therefore is weighted heavily in favour of strikers. I’m merely using it as one way to look beyond raw injury stats, I’m not saying it’s the final destination.
• The EGMAYO calculation uses the same season as the injury for xG per 90, so players injured early on, or starting the season injured, aren’t measured particularly accurately.

So, I know all that, don’t point it out – I’m working on it. I just want to get this up for discussion’s sake, because it adds more context to articles like this in the Telegraph today. Comments welcome here, or on Twitter.