Soccer Analytics

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Photo by Markus Spiske on

Modern technology has enabled us to store a large number of data easily and read them at any time very fast. Therefore, the stored information can be used to compute statistics and probabilities for any possible scenario. Betting agencies are using the data to define the odds for bets and sports journalists to communicate the teams’ and players’ statistical information.

Even more, today’s technology can be used to record a large number of data in brief intervals of time. In soccer, it is possible to record the position  of each and all players numerous times within a second. The result of such recording is a humongous collection of numbers.

Data Mining (also known as  Data Science or Big Data Science) is a term used to describe a discipline which works with these collections of numbers and, by the use of various methods, attempts to discover hidden patterns and order in the collection. Many simple and  sophisticated patterns  have been discovered through such mining of the data. Professional teams have created their own data mining teams hoping to find ways to get even the slightest advantage over their competitors.

The application of Data Mining in soccer has come to be known as Soccer Analytics.

The series of lectures in this category attempts to educate players about the development and the current status of soccer analytics: how it rose to prominence, how valuable it might be, what benefits have been derived, and where the trends seem to lead.