David Silva


David Silva’s nasty looking ankle injury is a demoralizing loss for Manchester City.  Although City will not have the Spaniard down the stretch of their Premiership title pursuit, world football (and City) fans will take some consolation in the fact that the injury is not as severe as it initially appeared.  While reviewing his season, Silva’s excellence across a number of passing statistical categories is striking.  It brought to mind a challenge I received from Matt Tomaszewicz  aka The Shin Guardian to try and derive an over-arching metric from a few ubiquitious passing statistics: number of passes, pass completion %, key passes.  The following is a (flawed) attempt to both quantify David Silva’s passing impact and meet Matt’s challenge.

Passing Impact

Who is the most impactful passer?  The obvious answer is someone whose passes create goals (assist).  But assists are so infrequent that really we are looking for passers that create goal scoring opportunities (key passes).  Of course, it would also be ideal to have the data for passes that create passes for goal scoring opportunities (secondary key passes), but that data is not publicly available.  Also, as has been pointed out by Colin Trainor (and others), being able to assess the quality of the shots the key passes create is very informative, and is notably absent from the key pass metric.  Nevertheless, key passes is what we have.  Below is the list of the top total key passers in the EPL this season.

 total kp

This seems a pretty good list.  Generally, these are names we associate with being impactful passers.  But what about efficiency?  Who is creating the most key passes per pass attempted?

pass per key pass

Ok, so this list is quite different than the first.  But look at the low passing % of some of these players, like Anichebe and Vydra.  We have to take incomplete passes into account as well.

KP incomplete

This is probably the best measure of key pass efficiency.  I included two versions of the same metric because while  I prefer KP/Incomplete %, some might prefer to visualize it the other way around.  It should be noted that turnovers or dispossessions are not included in this analysis.  Also absent?  Pass usage rate.  It is one thing for Kevin Mirallas to be incredibly efficient at creating goal scoring opportunities, but as an attacker how often does he see the ball relative to other players?  (Note: pass usage rate = player passes attempted / team passes attempted.)  This is the same list of the most efficient EPL key passers, but now with their pass usage rate.


So how do we combine the two metrics (efficiency and volume)?  I decided to measure each player’s total passing impact relative to an average EPL field player (non-GK).

David Silva impact


In David Silva’s case, his passing impact while on the field for Manchester City is equivalent to almost five average EPL players.  If we exclude defenders and compared Silva to just midfielders and forwards his passing impact would still be equivalent to approximately 3.5 average midfielders or forwards.  In short, Silva’s passing impact is equivalent to almost an entire midfield of an average EPL team.  Here is the list of the top 10 players.



There are obviously a lot of flaws in this analysis, chief amongst them the reliance on key passes as a primary indicator of passing impact.  Therefore, it is no coincidence that a majority of this list are creative attacking midfielders.  Then again, if one were to create a “goal impact” rating, that list would primarily be populated by strikers.  No matter the statistical inputs, it is self-evident that David Silva is having an exceptional season and City, despite having the number two player on the list in Nasri, will no doubt miss his passing genius.

  • Kurt Leimbach

    Really cool article, I enjoyed your process here, especially looking at incompletes per KP. One thing that irked me a bit this weekend as to how these records are kept is that I was looking at the StatsZone for the Milan / Roma game, and Opta gave Totti an assist for Pjanic’s goal (and presumably would have given him a key pass had the shot gone off target). The problem here is that Pjanic completed THREE dribbles to get into the danger area and get a shot off. The pass that Totti made was about 20 yards outside the box. Doesn’t it seem a little flawed that the stat was awarded as such? I wonder if there is any way to also look at the ease with which a shot was created by a key pass? (One time shot / # of defenders beaten prior to shooting etc.)

    • http://tempofreesoccer.blogspot.com Alex Olshansky

      Thanks for the comment. I do agree that key passes can sometimes be misleading as the player shooting sometimes does the majority of the work (in your example) or sometimes the real “key” pass is the preceding one (“secondary key pass”). That said, I think in a large enough sample those sorts of irregularities iron themselves out. There are probably ways of adjusting for types of key passes and I expect those adjustments to come with time.

  • James

    Hi Alex

    Excellent article I really like your line of thinking on this one. I just wanted to get my head round KP/Incomplete figure you have produced and the interpretation of it. Taking Mirallas as an example and his KP/Incomplete (48.1%) so for every incomplete pass 48% of them are Key passes??

    I think I know what your getting at I just wanted to clear it up in my mind so I can visualise it better.