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We find valuable insights in football data… to help coaches
make smarter decisions on how to improve performance






Many precious insights are hidden in the vast quantity of performance data now available to football (soccer) clubs.  Finding these can enrich the analysis of the game, and enable coaches to make smarter decisions on how to make a team more competitive. It’s a game changer!

Discovering such insights is not simple, and only data miners/scientist with knowledge of advanced analytic methods (machine learning algorithms) have the skills required.  At Soccerlogic we combine such skill with an in-depth knowledge of the game.  We pioneered Football Analytics, and over the years gained unrivalled experience in finding such precious information.

So, you can trust us to make the most of your data! We have helped many coaches drive performance improvement by finding fresh and valuable insights in any kind of performance data: match (Opta, STATS), GPS and fitness.  And we can help you too?  Find out how by contacting us via or filling the form at the end.

SoccerLogic is a very powerful Performance Analysis software package that will enable the coaching staff to both determine and improve the level of performance. Having worked with the product, the capabilities and extent of the analysis available is very impressive, allowing the coaching team to assess the interactions occurring within the game to an unprecedented level.”  Dan Bishop


How Soccerlogic can help you


Soccerlogic analyses performance data from many matches using advanced analytic techniques (including machine learning) and finds many hidden insights on how teams and players have performed.  Much of this precious information cannot be found in any other way. It will complement and enrich a coach understanding of the game, and help him make smarter decisions on how to improve performance.

This approach provides a number of benefits, such as:


  • In-depth, contextual analysis.  We will tell you how teams and players perform in-depth, objectively and accurately; broken down by as many contexts/conditions as you may wish: Home/Away, 1st vs 2nd half, before/after a goal, a substitutions or a yellow/red card, before/after a change of tactics (or formation), … any event during a match that you feel has been a game-changer.
  • We can keep track of these stats during a season and report any significant changes – those that have affected performance, and how. We won’t waste your time looking at lots of stats but focus on those that matter.  That’s how advanced data analysis gives you an edge.
  • Success Analysis – we will discover which tactics drive successful performance.  What you do well, better than the opposition when you win and what goes wrong when you lose.
  • Know how your opposition plays as well as your team.  Scouting reports from a few matches don’t give the full picture. We analyse your next rival’s matches in the same fashion we do for yours and identify vital insights on how they play. We also compare their performance with yours.  This analysis discovers much useful information to complement your traditional scouting reports, allowing you to select your best team and tactics.
  • Help to decide. Are you faced with a difficult decision and unsure what to do?  Has that player’s performance declined? Has that new tactic been more or less successful than the one you employed before? Our data-driven analyse will provide the answer.
  • We can give you more than what GPS data provides. We will crunch this data and stats with our sophisticated analysis tools and squeeze every bit of useful insight from it.
  • Are you making the most of new technology that can help you improve performance?  For example, FIFA’s new ruling that allows clubs analyse matches in real-time. We can monitor the performance of your team and opposition during the game and provide information that will help you make smarter decisions during the match – whom to substitute, how your tactics are working, etc.



There is more, and you can ask for details at

Sport Intelligence

After working for many years as Business Intelligence (BI) consultant, Gianni Pischedda started Soccerlogic in 2003.  It was the result of his passion for football, and his discovery that analytics software developed for business could also analyse match data very effectively.  This meant that he could provide coaches with many fresh and valuable insights on how to improve performance.
Football Intelligence was born!

Since pioneering this modern approach to the analysis of sports data, Soccerlogic has gained world leading experience of helping coaches improve performance. It has undertaken many projects around the world, delivering performance improvements for football/soccer, AFL (Australian football) and Cricket. Soccerlogic has also carried out succesful application research of its novel method to Rugby, Ice Hockey, Tennis and Basketball.



You only see what you know“, Goethe

Video analysis and coaches’ intuition have been the mainstay football analysis for a long time.  But in recent years a lot of data has become available on what happens on the pitch and in training.  Powerful software has also been developed to crunch this data and discover many insights on performance that could not be known before.  This fresh information can enable coaches to better understand the technical and tactical performance of teams and players, and make smarter decisions on how to improve it.

That computers should play a leading role in helping coaches make sense of data  is the key concept underpinning Soccerlogic’s Football Intelligence. Such intuition came to its founder after many years experience of using data-mining software to drive performance gains in business.

This was back in 2003, when artificial intelligence (AI) only got a mention in academic papers and science fiction books. How times have changed!  Computer technology has evolved, and a faster rate than anyone had anticipated.  Artificial intelligence is now a practical reality, and its many applications bringing benefits to all areas of human enterprise.

This unpredictable development has not escaped our attention, nor have its implication for football and team sports in general. For a few years now Soccerlogic has been studying how the deep-learning algorithms that drive AI can provide coaches more and better ‘intelligence’ to improve performance.  That will certainly come in the near future.  Meanwhile coaches can count on Soccerlogic to continue to stay ahead in the game of exploiting existing data mining/science technologies to provide them with those insights that enable smarter decisions on how to improve performance, and gain an edge on the competition.

“People don’t know what they want (or can get – Ed.) until you show it to them.” Steve Jobs

WHY choose Soccerlogic ?

We pioneered the analysis of football with advanced data mining tools, and over the years have gained unrivalled experience of using them to find valuable insights in match data.

  • We have the educational qualifications: higher degrees in computing and statistics
  • We have the skills: verifiable experience of using advanced analytical tools  in business and sports
  • We have the specific know-how: over 15 years of analysing football data – much longer than anyone else!
  • We are familiar with the data: we have been analysing match data (Opta and others) for years
  • We have a methodology: a unique, proven method to help clubs quickly benefit from data mining/science
  • We have the right tools: we use certified software – what banks and other financial organizations trust
  • We won’t make you wait long to get the first results: few days, a week at most



 We have the tools, the know-how and experience to help you make the most of your data!



Analytics first, sport second

… Of course, anyone involved professionally in Performance Analysis of any sport has to ‘know’ the sport.  But this deep knowledge that Dean advocates is no longer of primary importance if one has an analytics role in a club.  Analytics is about analysing data, lots of data (big data?); hence the primary skill required for this task is knowledge and experience of advanced analytic techniques and tools.  Without this knowledge and experience is not possible for anyone to analyse data efficiently and effectively.  Any data!

Possession chains and passing sequences

“A major objective of football analysis should be that of identifying event chains; that is to find out the outcome of a chain of single events. For example, if a team scores, it is useful to know what chain of events preceded the goal. For instance, this could be after five successive short passes, or after a defensive player lost the ball to the opposition forward player who shot immediately….”

Is xG any good at predicting game outcomes?

One can’t afford to ignore Expected Goals (xG) now that Match of the Day are giving the metric such a huge profile. I’m not a massive fan of xG, but I thought it was worth further investigation and so, thanks to data from StrataData ((, I have been doing some work on it.

Finding changes in tactics and their impact on a match

… To discovery tactical changes, we try finding significant changes in performance by the two teams in the many binary contexts of the game; for example between 1st & 2nd half, before/after a goal conceded/scored, before/after substitutions, etc. We also split the match in ten time intervals, and look at changes in activity (ball touches) between a time interval and the next,

Mohamed Salah at Roma and Liverpool

The shot performance of M Salah at Roma and Livepool is compared in this post. The objective is to find any statistically significant (p<0.05), and non significant (but revealing) changes in performance.

Balls and Runs – an attempt to Cricket analytics

“I am taking a rest from football, and since the battle for the Ashes  is on (England – Summer 2013), I have turned my attention to cricket.  Australia’s bowlers have been criticised by their lack of success, especially in the 2nd Test at Lords.  So here is my attempt at an analysis of their performance, as well as that of the England’s …”


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