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We help coaches discover valuable insights in match data –
to improve performance and win games






Soccerlogic analyses match data using modern techniques of computer analysis to discover many fresh and valuable insights that can help coaches improve performance. Such precious information will enrich their analysis of the game and enable smarter decisions making on how to select the best players and tactics to win games. Traditional methods of analysing football, like by video or match stats, cannot find such information.  

Soccerlogic is a game changer.  It can discover useful insights in all kinds of performance data, such as match events files (Opta, STATS), GPS tracking, fitness, etc. Such knowledge will enable coaches to get an edge on other teams, win games and competitions

Soccerlogic also provides coaches with a sophisticated tool of visual analysis of match data.  This can show graphically the position of  the players and the movement of the ball betwen them at any time during the match.  Used together with the insights gained from the data-driven computer analysis, such visualizations enable coaches to fully exploit match data for competitive advantage.


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


The Soccerlogic advantage


Soccerlogic’s statistical computer analysis (using machine-learning algorithms) can find patterns and trends in many matches.  Such information will enrich a coach’s knowledge of how his team plays and help him discover its weak and strong pointsct . He will gain much valuable information to enable smarter decisions on how to improve performance.

Some of the unique benefits Soccerlogic provides to coaches are:

  • Match stats aand conditional (in context) stats. Soccerlogic computes performance stats not only by match but by as many contexts (or conditions) a coach may wish to analyse.  Examples of such contexts are: Home vs. Away, 1st vs. 2nd half; before/after a goal, substitution, a yellow/red card, a change of tactics, and so on.  Conditional stats are more valuable because they focus on performance in specific contexts of a match, therefore they give a  coach the flexibility and power to evauate (and compare) performance not only between whole matches but in any particul context, time segments of choice.


  • Humans were not created to analyse data, computers were. The computer analysis of these stats quickly identifies and report significant changes in performance in all specified contexts. The process is automatic (of course), and frees coaches and their assistants from the need to spend much time analysing match data.  Moreover the results are available minutes after the match ends, giving coaching staffs the means to quickly evaluate performance, and start plannig training work to improve it.

Soccerlogic = quick analysis + more useful stats/metrics + more time to study and use these to improve perfromance


  • Success Analysis – Soccerlogic’s computer analysis can discover what drives a team’s winning (or losing) performance by relating match outcome to it .  Such analysis highlights what your team does better and worse than the opposition in a match or many of them.  If there is a pattern that explains good or bad performance it will find it!  These precious insights will help you make smarter decisions on how to improve performance.
  • Know your opposition as well as your team – Soccerlogic can enrich ​your ​scouting by a data-driven analysis of your rivals’ latest matches done in the same way as yours. This will gather a wealth of insights on how they play: their tactics, their strong and weak points.  This will complement your scouting reports with unique and valuable information even they themselves may be not aware of.  You can also see how their performance compares with yours in any aspect of the play (contexts) you wish to investigate.  Such  valuable information will help you select the best team and tactics to win the match.
  • Help in decision making.  Are you faced with a difficult decision?  Do you need to quickly verify if your gut feelings are objectively sound?  Soccerlogic’s data-driven analysis can help you make the right decision.  Has that player’s performance declined? Does the team play better with player X or with player Y in the starting lineup?  Has that new tactic been more or less successful than the previous one? These are just a few examples of how Soccerlogic helps a coach​ ​make those crucial decisions that can improve performance​.​
  • Get more from fitness or GPS tracking data or any data you have or may want to use to monitor performanceSoccerlogic will crunch it with its sophisticated analysis tools and squeeze any useful insights that can help you in deciding how to improve performance.
  • Help in making the most of new technology or latest regulation –  FIFA’s recent ruling that coaches can view match analysis results in real-time is a game-changer.  Soccerlogic can do that for you.  You’ll get an immediate insight on what is happening on he pitch, and can act quickly to make the changes required to improve performance.

There is more! Please ask for details or a demo at

Sports Intelligence

Gianni Pischedda founded Soccerlogic in 2003 (six years after starting on the project) with the aim of providing coaches with tools and know-how to make sense of the large amounts of data on performance increasingly made available to them. The information gained in this way would provide them many fresh and valuable insights to improve performance.

Before such a move, Gianni had already been providing data analysis tools and services to business companies for many years and gained much experience (8 yrs) in this new and innovative technology. Starting in the early ‘90s, in fact, he had been a pioneer in the emerging field of computer data analysis, which was crucial for businesses which wanted to become more competitive. The Soccerlogic project was the result of his intuition that such powerful tools of analysis could also help improve performance in football.   ‘Football Intelligence’* was born!

Since pioneering this data-driven approach to the analysis of football Soccerlogic has gained world leading experience of helping coaches make the most of match data for improved performance.  It has worked with many clubs around the world:  in football/soccer, AFL (Australian football) and Cricket.  Soccerlogic has also undertaken research projects in Rugby, Ice Hockey, Tennis and Basketball.


* The terms ‘Football Intelligence” and “Sports Intelligence’” were terms coined by Gianni from “Business Intelligence” which at the time (late ’90s) was the name given to the advanced techniques of data-driven analysis being widely adopted by business  for competitive advantage.



Does scoring at the end of the first half gives an advantage?

…  Only in the Champion league such goals appear to give a small advantage, but only for away teams.  In contrast, there is a small but significant gain for home ones in the Top 5.  But, the overall picture shows that goals in the last 5 minutes do not affect outcomes, and when they do, the result is more often negative than positive.


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….”

How good is xG at predicting match 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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