Which team creates the best shots of the Eredivisie?

The secret behind Feyenoord’s successful campaign? Creating high quality shots. The reason VVV and RKC did not live up to the expectations of the predictive models? Too many low quality shots. This post will use shot location to capture a challenging part of performance: differences in shot quality. And yes, some teams create better chances than others…


Strike zones

Last week’s post has identified four different strike zones on a football pitch. These zones have been chosen so that Zone 1 identifies near-certain goals: shots with conversion rates of over 80%. Shots from Zone 1 are rare (< 1%), but nevertheless have a huge impact. Zones 2 to 4 all contain over 25% of shots, but with sharply diminishing success rates. Shots from Zone 2 are considered high quality shots, and roughly 1 of 4 shots results in a goal. From Zone 3 this number is 1 of 13 and from Zone 4 just 1 in 30. For convenience, we could say that shots from Zone 1 are worth three shots from Zone 2, which are worth three shots from Zone 3, which in turn are worth three shots from Zone 4.

Pitch zones

Using these zones allows us to study the basic fallacy of our beloved shot metric, Total Shots Ratio (TSR). Remember, TSR is a simple, but very successful metric, that uses the fraction of shots that teams take in their matches. TSR has shown to correlate very well with the amount of points that teams obtain and it has proven its usefulness in identifying teams that experience lucky or unlucky streaks.


All shots are equal, or not?

The main concern with TSR, however, is that all shots are treated equal. As simple as the TSR model is, shots from 40 yards out are counted the same as one yard tap-ins. Over the long run, most of the differences between shots will even out, but only if we assume that shot quality is evenly balanced out between teams. But is that really the case? Don’t certain teams create better chances than others? If so, we could better understand why certain teams did not live up to the expectations by the TSR model, while others have seemingly over performed.

The build-up of this post will be to look at all Eredivisie teams, and identify where they took most of their shots. Let’s get started with the raw numbers. I’ve excluded penalties for this analysis.

Zone 1 Zone 2 Zone 3 Zone 4
ADO 2 118 101 159
Ajax 3 192 161 186
AZ 4 161 126 160
Feyenoord 6 206 152 159
Groningen 2 157 93 174
Heerenveen 3 154 148 144
Heracles 3 141 138 176
NAC 3 118 82 131
N.E.C. 1 171 118 164
PEC Zwolle 1 133 99 165
PSV 8 225 172 213
RKC 4 100 122 135
Roda 4 137 89 110
Twente 4 181 134 152
Utrecht 3 178 118 153
Vitesse 2 172 109 146
VVV 2 120 112 147
Willem II 2 122 87 152

Thanks to my friend Benjamin Pugsley, this table format has now been improved a lot, and you can even sort the columns yourself! But from an analytics view, this data is not really accessible, is it? Let’s go through a few numbers in detail and see what we can work out from there… PSV have dominated the shots department and have created the highest number of shots in each of the three zones. Other outliers are a remarkable high number of shots from Zone 2 by Feyenoord – that’s a good thing – and a remarkable low number of shots from that zone by RKC – that’s a bad thing. Roda tend to shy away from taking long shots, with only 110 attempts from Zone 4, but they tend to shy away from creating shots from any zone, so, alas, not necessarily a good thing for them.  


Clearly, this table needs relativity. Teams like Roda may do well by avoiding futile shots (Zone 4) at goal, but they hardly create any quality attempts (Zone 2) either.

Zone 2 Zone 3 Zone 4
ADO 0.31 0.27 0.42
Ajax 0.35 0.3 0.34
AZ 0.36 0.28 0.35
Feyenoord 0.39 0.29 0.3
Groningen 0.37 0.22 0.41
Heerenveen 0.34 0.33 0.32
Heracles 0.31 0.3 0.38
NAC 0.35 0.25 0.39
N.E.C. 0.38 0.26 0.36
PEC Zwolle 0.33 0.25 0.41
PSV 0.36 0.28 0.34
RKC 0.28 0.34 0.37
Roda 0.4 0.26 0.32
Twente 0.38 0.28 0.32
Utrecht 0.39 0.26 0.34
Vitesse 0.4 0.25 0.34
VVV 0.31 0.29 0.39
Willem II 0.34 0.24 0.42

This is basically the same information, but presented in a slightly different way. PSV stood out in the previous table, because they had the highest amount of shots in each zone, but the spread across the zones is not remarkable. RKC stand out as a team with big trouble creating quality shots (Zone 2), while Feyenoord, Vitesse, Utrecht and Twente succeeded in creating a high proportion of shots from Zone 2.

Willem II, PEC Zwolle, ADO and Groningen take over 40% of shots from Zone 4, where teams on average need around 30 shots for a goal, while Feyenoord, Heerenveen, Roda and Twente limit themselves to less than 33% of shots from Zone 4.



We can repeat this trick for shots conceded, to try and identify teams that give up high quality chances and teams that give up mainly low quality chances. Here’s a similar table to the one above, but this time for the defensive side of things.

Zone 2 Zone 3 Zone 4
ADO 0.41 0.3 0.29
Ajax 0.33 0.31 0.36
AZ 0.31 0.29 0.39
Feyenoord 0.36 0.25 0.38
Groningen 0.31 0.24 0.44
Heerenveen 0.45 0.23 0.31
Heracles 0.38 0.31 0.3
NAC 0.36 0.25 0.38
N.E.C. 0.37 0.28 0.36
PEC Zwolle 0.38 0.29 0.33
PSV 0.33 0.28 0.38
RKC 0.4 0.24 0.35
Roda 0.36 0.28 0.35
Twente 0.32 0.23 0.45
Utrecht 0.32 0.26 0.41
Vitesse 0.34 0.29 0.36
VVV 0.41 0.27 0.31
Willem II 0.35 0.31 0.33

Painful news for Heerenveen, who give up a record high 45% of shots from Zone 2, followed at some distance by ADO and VVV at 41% and RKC at 40%. Better numbers in that regard for AZ and Groningen, who lead a bunch of teams with just over 30% of shots from Zone 2.
Remeber, you can sort the table yourself by clicking on the header.

Twente and Groningen perform well in terms of forcing their opponents into low quality chances (Zone 4), while ADO, Heracles, Heerenveen and VVV could do a lot better in that regard.


In the end

Lots of numbers, but don’t let that scare you away. We’ll wrap the concept of shot quality differences up in a later post, where we’ll fuse a lot of this concepts to make things simpler.

Using shot locations and league wide conversion from our well defined zones, we can see which teams did well in terms of creating shots from quality positions, while preventing their opponents from doing so. At the very least, it seems there are relevant differences between teams in terms of shot quality, which in itself is bad news for models based on TSR. And for the nearby future, this type of detailed analysis can help us to slowly build towards a better synthesis of analysis and tactics…

Leave a Reply