Investigating a soccer dataset in Python

Posted on by Kevin Foong

Using Python to analyse a dataset on Premier League soccer matches around the metrics of "possession" and "matches won", reveals some interesting findings. This is a previous assignment I did for my Udacity Nanodegree in Data Analysis.

In season 2015/2016 Leicester City won the league at starting odds of 5000-1.  Their possession stats (number of matches where they had more possession than the opposition) put them 3rd from bottom, but then we can deduce that perhaps they were also a lethal counter-attacking side.

In season 2013/2014 Southampton, a mid-tier team, led the table in possession but that didn't necessarily translate to matches won.

See my full investigation on Github in a Jupyter Notebook.

Tags: python, data


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