Success and completed passes in the final 3rd and beyond

Bolton-Manchester City (2-3) – EPL Season 2011-2012

Continuing my graphic analysis of the Bolton-Man City match (#MCFC data), in this blog I am going to look at completed passes (CP) in the final third.  Passes in this area of the pitch provide a good indicator of a team attacking performance, and have been found to be highly correlated with goals scored (see Ravi Ramineni*).  A discovery confirmed by  this particular match, as we shall see.  Digging deeper, however, we discover some interesting facts about the importance of CPs in the final 5th, and the relative strengths of Milner and Silva.

The graphic below show the position of completed passes (CP) made by Bolton (red) and Man City (blue), together with their count for each team.   Man City made a significantly greater number of CPs in the Final third than the Trotters, 92 vs. 65, and scored more goals.

Fig.1 – Completed Passes (CP) in the Final third

Final third ball touches

A quick analysis of this image reveals that both teams are more dangerous when attacking from the Left (they manage to make more passes from those areas): 57L|35R Man City vs. 36L|29R Bolton.

We can also notice that Man City is much more successful in getting beyond the penalty line (last 17% of the pitch), with 27 CPs vs. Bolton’s 6.  This fact is fact highlighted Fig.2, which shows completed passes in this area for both Bolton (red) and Man City (blue).

Another interesting fact is revealed in this image if we show who made these passes for Man City. It turns out that the names of Milner and Silva appear most frequently, and in both sides of the penalty area.  Obviously these players are given the freedom to roam, and are the ones who with their passes are likely to create more goal scoring chances.

Fig.2 – Completed Passes (CPs) in the final 5th (penalty ‘zone’)

Fig. 2 CPs in penalty 'zone'.

Fig. 2 CPs in penalty ‘zone’.

However, looking at details of final third passes by all Man City players, we can see (Fig.3) that both Milner and Silva provide a greater danger when attacking on the left, where they make most of their successful passes.

Fig.3 – Completed passes in final third – all players

Final third bt by players

But, if we look at all passes made by Milner and Silva in the final 5th of the pitch (Fig. 4) , we cannot fail to notice that success (blue dots) depends on the side these were made. Milner makes the same number of passes from left and right, but is more successful from the left.  Silva, in contrast, makes more passes from the left, but has a 100% record when passing from the right.

So, while both were willing to have a go from either side of the pitch, we find that their success depends upon the side that the passes were made from.  Thus Mancini faces an interesting dilemna in future games: should he continue to give the players free rein to wander to both sides of the pitch, or tell Milner to stay more on the left, and Silva on the right, from where he enjoys 100% accuracy.”

Fig. 4 –  All passes in penalty ‘zone’ – Milner and Silva

Fig. 2 - MIlner and Silva, all passesIs this analysis valid for all matches played by Milner and Silva? What happens when either one is not playing?  Is their performance the same in matches drawn or lost?  This kind of (interactive) graphic analysis can answer these questions, and similar ones, rather quickly.  And as many matches can be analysed together, it provides a very effective way to analyse performance for both a team and individual players

PS The white line cross that appears in Fig. 2 and 4 was left by mistake. And laziness prevented us taking it out.  It is related, however, with what appears in these figures . See if you can work out what it represents.  There is a prize for the first correct answer.



About soccerlogic

Data analyst/miner of 23 years experience. Pretty sure I was first (1998) to apply Statistical Analysis and Machine Learning to study performance in soccer. I probably invented Soccer Analytics or, as I called it then, Football Intelligence. Haven't stop learning since, and experimenting new analysis that can help teams improve performance.
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