The case for Return V Expected

I started the blog in May this year by, for want of a better term, throwing up the data I had. I knew that if I didn’t start the blog then, prior to the Championship starting, it just wasn’t going to happen.

Part of the raison d’etre for the blog was to find a method for ranking attacking performances – the old nugget that not all scores are equal therefore two players scoring 0-4 each did not necessarily have the same impact. That method was “Return V Expected”

I didn’t push this return during the year as (a) I hadn’t really explained how it was constructed and (b) obvious deficiencies in the process presented themselves as the season progressed.

I hope my last post shows the basic math behind the principle whilst I have updated the database to account for some of the glaring weakness. Namely
–> Returns from 45s are now treated separately from frees
–> Shots in Sector 8 that go for goal are treated separately from those that go for a point.
–> There isn’t enough data on Penalties (12 charted in 2 years) and shots from sidelines (19 charted) to treat them separately. Penalties are treated like shots on goals whilst sideline balls are included in frees

Despite my initial reticence I still believe however that using “Return V Expected” is a better measure of a player (and teams) performance than the raw scoring return. Take the below examples from the 2012 Championship

Player Game Shots Scores Success Rate Return Vs Expected Ranking
Ben Brosnan Dublin V Wexford 8 4 50% 0.7501 62nd
Jamie Clarke Armagh V Tyrone 8 4 50% -0.0731 236th

Both players took 8 shots with both scoring 4 points. Conventional scoring/ranking would equate these as being comparable returns. However when we break down where their shots, and scores, came from we can see that Brosnan took his shots from much more difficult positions on the pitch. Clarke’s were much closer to goal – an average county player would be expected to get more of Clarke’s kicks than Brosnan’s

B Brosnan J Clarke
Inside 21m 1/1 4/7
21m – 45m 1/5 0/1
Outside 45m 2/2

Clarke didn’t have a bad day – in fact he basically had a bang on average day – Brosnan had a good day scoring 4 points from positions that average county players just would not score from. Traditional ranking/analytical methods wont show this.

Attached below are the Scatter charts, for frees & shots from play, for all returns charted in 2012. Given that we are comparing everything to the average they look as expected … the ‘line’ crosses the X axis (An average Return V Expected = 0) at approximately half the volume. These outcomes again strengthen my belief that using “Return V Expected” will better rank performances – the outliers especially tell us exceptionally good (or poor) performances.

The -3 on the left hand side of the ‘Frees’ graph was Ben Brosnan’s horror show from dead balls against Dublin (the same game outlined previously when his shooting from play was very strong!). He had 4 frees and a 45 but missed all 5. Three of the frees were from Sector 6 which is directly in front of the posts whilst the other free was inside the 21m line. Knowing the high success rate there is for frees Brosnan got hammered for missing relatively simple kicks.


2 Responses to “The case for Return V Expected”

  1. Rob Says:

    Great post and it does highlight the need to compare performances in some sort of context. There are a couple of things I would also consider though.

    Game Situation: Is scoring a point when your down by 10 the same as scoring when teams are level?

    Game Time: Similarly are scores more valuable at certain times in a match.

    Opposition Quality: I have done some work on this to suggest that opposition quality effects the performance indicator. You will probably find that shooting averages change if you compare them against opp of different quality.

  2. dontfoul Says:


    I couldn’t agree more with the general thrust of your post – what I have done to date is take the very lowest of the hanging fruit. There is huge scope for improvement.

    To the three specific variables raised

    Opposition: This is definitely a factor – it is a huge variable in the work of FootballOutsiders. I am doing a piece on the top performances for 2012 and if I had opposition adjustments then I have no doubt Keating’s performance for Cavan against Donegal would come out on top. The issue with doing this is volume. There are 25 games from 2012 but 7 of these games involved Donegal. There is a good baseline for them but I only have one game for the likes of Kildare … it is very hard to make a consistent opposition variable when there is 1 performance, at most, for the majority of teams. It is definitely on the radar but may take a while to build enough critical mass to be reliable. I could alternatively award levels to teams but that would bring a level of subjectivity into proceedings that I’m not comfortable with yet – will attempt to nail down objective variables first!

    Time & Game Situation: I think these are very highly correlated. Of the two I am more inclined to work on game situation. I’m not sure there will be any great difference in averages between shots in the 15th minute and the 55th however I would imagine that this will change when there is a point or two in the 2nd half (“game situation”). This one will take quite a bit of coding/analysis to correctly group the game situations however is eminently doable.

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