Soccer Statistically

I recently found a blog that looks at soccer in a much different way than most are used to; while the majority of soccer blogs deal with specific teams or tactics, Soccer Statistically analyzes statistics from soccer matches and proposes potential application to match play. This blog provides an alternative way to study the sport and serves as a resource for those looking for innovative ways to look at soccer statistics.

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Soccer Statistically is run by college sophomore Ford Bohrmann, an Economics major at Haverford College. Bohrmann plays forward for the Haverford College soccer team and is a Manchester City fan, which explains why a lot of the data he analyzes comes from Manchester City matches.

Soccer Statistically has analyzed nearly everything, ranging from when goals are more likely to be scored and the influence of momentum in a game to prevalence of transfer rumors on Twitter and the relative strength of European leagues.

With a few exceptions, the posts follow a general format that is very easy to follow. Bohrmann gives a little background on whatever issue he is analyzing and gives a hypotheses as to the outcome. Next, he explains what data he is using and how he broke it down to analyze it. He then gives the results, usually using some kind of graph or visual aid. Finally, he draws a conclusion, applying his results to the game or explaining how his results fit in with soccer theory.

A great example is his in-depth look at the effects on possession in a post titled, “Possession Analysis: A Closer Look.” In a previous post, Bohrmann had revealed that in the MLS, teams that possessed the ball more did not necessarily tend to win more games. Others had also found similar results and after reading a few other blogs, Bohrmann decided to look at possession more specifically within a game to see how it effects goal scoring. To do this, he took specific Premier League games and graphed how many of the last 25 passes were made by each of the teams.  In his own words,

As the game progresses and passes are made, I found the difference in passes in the last 25 passes between the two clubs. For example, the home team could have completed 15 of the last 25 passes, while the away club completed the other 10. This would give us a difference in passes of +10, as the home club completed 10 more passes than the away club.

His hypothesis was that even though possession time did not lead to winning the game, it WOULD impact scoring. Specifically that a team is more likely to score when it has made the majority of the past 25 passes, or controlled the recent possession.

And it worked.

Bohrmann’s data showed that while there were certainly exceptions (be it from counter attacks, etc), there was a general trend that the team who possessed more of the previous 25 passes was more likely to score. He shared graphs for 5 of the matches he analyzed (I included one below). He also went back and analyzed the games looking at the previous 50 passes and found similar results.

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So what does this mean? Possession matters. While overall possession percentages of a game can be misleading, possession is critical in the short term for teams to score goals. This seems pretty obvious, but it can be a useful concept for smaller teams who are struggling with possession. If it is difficult to control the overall pace of the game, focus then on stringing together short series of passes and capitalizing on that possession.

My goal here was to give you a simple taste of what Soccer Statistically is like. It is a great blog that puts a new and innovative spin on how we look at the game. If you are looking for an in depth analysis of players’ abilities, recent trades, news on league results or that kind of stuff, this may not be the blog for you. However, if you are looking for an occasional supplement to your soccer fix or want to rethink how you look at soccer stats, I highly encourage you to check out Soccer Statistically.

Soccer Statistically posts about once per month, which makes a lot of sense, given the time and effort that go into the data analysis behind each post. Currently, the dates from the posts on the first page make it seem as if the posts are much more infrequent than that, but this is misleading because Bohrmann was travelling over the summer and unable to blog. Beginning in July, he seems to have returned to his ~once/month schedule.

Additionally, Bohrmann is on Twitter (@SoccerStatistic) and has a Facebook page called “Soccer Statistically.”


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