To be honest, I’m not sure if I’m a great fan of shot placement work or not.

It’s reasonable to assume that when a player is shooting he is aiming for the target, however more than 50% of non blocked shots miss the target.  This means that in the majority of cases the player isn’t successful in actually putting the ball where he intended.
With than in mind, I wondered what there is to gain in attempting to undertake meaningful analysis due to the apparent difficulty for players to have as much influence on the accuracy of their shooting as they would like.
However, I realised it would be useful to create a reference source for what actually happens a shot or header once it reaches the plane of the goal line.

It’s worth noting that at this stage I am looking at all shots and headers.  I wanted to have a large enough data sample so meaningful high level patterns would emerge.

Expectation

It would certainly be expected that a shot hit down the goalkeeper’s throat would be a relatively simple save to make for the keeper, whereas a shot arrowed right into any of the corners would be substantially more difficult to save.
But just how more likely is the latter shot to score than the former?
Presently I can’t put my finger on a source that will give me that answer, hence this point of reference article.
As an aside, in my opinion this was part of the reason why this site was created in the first place.  Up until now there just hadn’t been a stats based site that can deliver articulate articles and data in user-friendly formats.  Hopefully that will change.

Probability of a Shot being scored

Here is a front-on view of the goalmouth showing the percentage of shots that resulted in a goal.  The plane of the goal has been divided into zones according to where the ball did or would have crossed the plane of the goal line had it not been saved:

ScoreZones

We can see that a ball hit dead centre at low to medium height will result in a goal 12% – 13% of the time (1 shot in every 8).

At the other extreme, a shot that is set to nestle in the corners will result in a goal approx  50% – 60% of the time (1 shot in every 2).
For the shots in between, we can see that there is a definite pattern where the percentage success gradually increases the further that the ball is struck away from the centre of the goal.
It is also clear to see that shots struck towards the higher parts of the goal are scored at higher rates than those that keep low to the ground.

Cheat Sheet

I have changed the magnitude of the above graph to create an “easy to remember Cheat Sheet”:

Cheat

The scale has been modified so that the figures in the chart now reflect how likely a shot is to be scored compared to a shot that is hit dead central at mid / low height.

The rate in the centre of the goal is 1, whereas shots into the corners are scored 4 or 5 times as often.  Shots that the keepers have to scamper across the goals to cover are scored 3 times as often as those hit straight at them.

Who knows, perhaps some time in the future we may hear a knowing pundit inform their viewers how much more likely the shot they have just witnessed was to score than one hit straight down the middle……..

Significance

Not sure really, but the main aim was to create a point of reference that could be referred to in the future.

We know that players don’t miss the target on purpose, yet most shots fail to trouble the goalkeeper.  It would therefore be a tall order for managers or coaches to instruct players to deliberately shoot for the corners and there is certainly comfort for strikers (especially those short on confidence) to ensure that they hit the target.
I’d wager that the next time you watch a match on television you won’t have to wait too long until you hear the commentator extol the virtues of “making the keeper work”, ie whatever you do ensure that the shot is on target.

However, if the striker had known the relative successes of shots hit towards different areas of the goal, and indeed that the success factor can increase by as much as 5 fold, would his thought process be any different?

Well, we can but hope.

 

Article written by Colin Trainor.  Colin can be followed on Twitter here.

 

  • Jesse Cannon

    Intriguing investigation. What are the statistics for number of shots per each zone? I wonder if there is some correlation to brute force number of shots? Also related would be the tendency of right-footed free kick takers (within range to warrant a wall) to aim for the upper right corner of the goal mouth, almost regardless of foul/ball position.

    • Colin Trainor

      Jesse, the number of shots per zone increased the lower down the goal you go. There were 48 shots in the zone with the least number of shots (top left), and the zones all along the bottom had between 400 and 925 shots.

      A quick glance at my numbers shows that there doesn’t seem to be too much of a left or right side bias as to where the shots are aimed at.

      Thanks for the interest in the article.

  • Toshack

    Thanks Colin for an interesting piece!
    Something for the offensive coaches to use in training! (wondering if all PL teams do have a specialist offensive coach?)

    • Colin Trainor

      I’d be amazed if clubs aren’t using that type of info, or at least they certainly should be. Given the reward for those shots that are aimed for the corners I certainly think that it would be worth the risk to try to try to avoid hitting central low shots.

  • mike

    Does your data show if shot placement varies with shot location?

    As for the uses of this data, I suspect it would be useful in finding the strengths and weaknesses of goalkeepers. For example, I think last season, a lot of people were saying Hart was weak on shots faced low to his left. Be interesting to see how accurate people’s perceptions were, or if it was just confirmation bias.

    • Colin Trainor

      Mike, I haven’t yet looked at shot placement by location. I went for some simple analysis first off.

      In relation to your point re goalkeepers, I had thought of thought myself and had a quick look at it but I’m not sure there is enough data for each GK to reach meaningful conclusions. I might grab Hart’s saving information and tweet the image when I next get a chance, so if you follow me you can get a look at it then.