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“YOU ONLY SEE WHAT YOU KNOW”
GOETHE

SOCCERLOGIC

We find valuable insights in match data that enable football coaches make smarter decisions on how to improve performance

ABOUT

Vast amount of performance data are now available for all major football competitions.
It’s a game-changer! Many valuable insights on how teams play are hidden in this data.
Such precious informations can enrich match analysis with traditional methods, and enable coaches to make smarter decisions on how to improve performance.

However, to find these precious insights is not easy: analytic methods must be used, such as machine learning algorithms, and visualisation. Nobody has more experience than Soccerlogic in doing this. We pioneered data-driven analytics in football!  And we can help you fully exploit your own match data, as well as that provided by Opta, STATS, and Wyscout.

Soccerlogic have helped many football coaches discover those precious insights that drive successful performance. And can help you too improve performance by finding such insights  in your data.  Get an edge on the competion by contacting us at info@soccerlogic.com or by filling the form at the end.

Soccerlogic has the knowledge and experience to help you get the most from match data!

Sport Intelligence

Soccerlogic was founded by Gianni Pischedda in 2003.  It was the result of his passion for football, and of his many years experience of Business Intelligence (BI). He had discovered that business data-mining tools could be adapted to analyse match data of any team sports more effectively than any other software.  In practice, the performance of team and players could be studied to an unprecedented level of detail, easily and quickly – something not possible before. Realising that this process could enable coaches to make smarter decision on how to improve performance, he named it Football Intelligence.

Since pioneering this modern approach to the analysis of football, Soccerlogic has gained world leading experience of helping football clubs improve performance by exploiting match data.  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.

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OUR THINKING

You only see what you know.” Goethe

Video analysis and coaches’ knowledge/intuition is no longer enough to analyse the game and improve performance.
Of course, spending millions on better players can help.  Can you afford it? There is an alternative.
Make the most of the data!

Thanks to advances in technology, a lot of data is available on teams/players’ activity on the pitch.  And there are software which can quickly analyse it to find many valuable insights on performance.  Such insights will enable coaches to better understand the technical and tactical performance of teams/players, and thus make smarter decisions on how to improve it.

Computers driven by powerful machine-learning algorithms must be used for finding such precious insights.  Football is a complex game, and when it comes to analysing data, big-data, computers have an edge on humans. However, the knowledge and experience of coaches/analysts is crucial in driving this proceess of discovery, and translating these insights into actions that will lead to performance improvement in play.

That computers should play a leading role in helping football clubs improve performance was the key concept underpinning Soccerlogic’s Football Intelligence.  An intuition born out of its founder 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 focusing on understanding how the deep learning algorithms that drive AI can provide more and better ‘intelligence’ for improving performance in sports.   It is something all coaches should be keen to explore, and that we are eager to share with them.

 

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

 

How Soccerlogic can help you

Soccerlogic can help coaches/analysts find valuable insights on the performance of teams/playerst that will enable smarter decisions on how to improve performance and get an edge on rivals.  Some of these are:

  • Identifying significant changes in performance metrics during the season
  • Success Analysis – identifying tactics that drive successful performance
  • Highlighting key stats – save time, focus on what matters!
  • Knowing the strong and weak points of your team and opposition
  • Quickly verifying whether your observations and intuitions are evidence based
  • Monitoring performance (yours and opposition) during a match in near real-time
  • Fast results – more time to understand, find solutions and implement them in training

 

We can help analysts find key insights that will enrich the tactical and technical knowledge of a team.
We enable coaches to make smarter decisions on how to improve performance, and gain a comptetive advantage.

Why choose Soccerlogic?

Soccerlogic pioneered the application of data mining/science in football, and over the years has gained unrivalled experience of using this technology to find valuable insights from match data.

  • We are qualified: have higher education qualifications in computing and statistics
  • We have the skills: verifiable experience of working as data miners/scientist.
  • We have the know-how: we have been analysing football for over 15 years – much longer than anyone else!
  • We understand the data: we have been analysing Opta match data for years using data mining tools
  • We have a methodology: a unique, succesfull method to help clubs quickly benefit from data mining/science
  • We use certified software : what banks and other financial institutions employ – you can trust our results!

No other company has the experience and know-how to help you make the most of your data!

BLOG

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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!
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Possession chains and passing sequences

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

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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 ((www.stratagem.com), I have been doing some work on it.
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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 segments, and look at changes in activity (ball touches) between one time interval and the next,

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Mohamed Salah at Roma and Liverpool

Te shot performance of M Salah at Roma an 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.
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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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Gianni Pischedda

After university, a passion for computers drove Gianni to follow a career in IT. His interest in Expert System (an early development of Artificial Intelligence) meant that he was quick to appreciate the potential of the first commercial tools based on this technology. These data-mining tools – the first to use machine learning algorithms – could analyse large business databases very quickly, and discover much valuable information on the performance of a company.

After many years experience of using them to analyse business data, his passion for football led him to experiment with match data. And when he realised that these could be as effective in analysing performance in sports as in business, he started Soccerlogic to promote his analysis system to leading football clubs.

Gianni studied at Middlesex Polytechnic, and at Lancaster University, where he was awarded MA degrees in Numerical Analysis & Computing, and Systems Engineering.

 

 

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