The analysis of match data using powerful techniques of machine (computer) learning – the same that drive artificial intelligence (AI) – can provide a coach and with many valuable insights on how to improve performance. These can be found only this way, not by video analysis, not from stats. They will enrich a coach analysis of the game and enable him to make smarter decisions on how to select the best players and tactics to win games.
This is the promise of Soccerlogic.
Soccerlogic is a game changer. It can discover useful insights in all types of data on performance available to coaches, such as match events files (Opta, STATS), GPS trackin, fitness, etc. They can then exploit this knowldege to get an edge on other teams, win games and competitions.
Powerful analysis combined with sophiticated graphics
Soccerlogic also provides a sophisticated tool for the visual analysis of this data. In particular, this allows coaches to easily visualise the position of players and the movement of the ball at any time during the match. Such visualizations, combined with the insights provided by the statistical analysis enable coaches to fully exploit performance data for competitive advantage.
Find out more, or ask for a demonstration by contacting email@example.com or filling the form which you’ll find at the end of this page.
“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
Soccerlogic employs powerful methods of computer analysis (including machine-learning algorithms) to search for patterns and trends in match data (many matches). The result is the discovery of much valuable information on performance that cannot be found by watching a match or video-analysis. This fresh information will enrich a coach understanding of performance and enable him to make smarter decisions to improve it.
Some of the unique benefits Soccerlogic provides to coaches are:
- In-depth, contextual performance metrics. Performance is evaluated broken down by as many contexts (or conditions) a coach may wish to analyse, such as: Home vs. Away, 1st vs. 2nd half; before/after a goal or substitution, a yellow/red card, before/after a change of tactics, and so on. These metrics are more useful than the standard match stats since they highlight (correlate) changes in performance (for better or worse) to specific situations and events in match.
Significant changes in such metrics are identified and reported, thus freeing coaches from spending hours analysing stats. These are also available minutes after a match ends. The coaching staffs can the quickly make an accurate evaluation of performance, and start plannig training work. Such is the advantage of Soccerlogic computer analysis of performance.
Soccerlogic = quick analysis + more useful stats/metrics + more time to study and use them
- Success Analysis – Soccerlogic discovers the metrics which drive winning (or losing) performance. It highlights what the team does better and worse than the opposition when it wins or loses. If there is a pattern that explains good or bad performance Soccerlogic will find it! These are precious insights to help a coach make smarter decisions on how to improve performance.
- Know your opposition as well as your team – Get more than scouting reports to understand how rival teams play. Soccerlogic can enrich scouting by analysing (as above) rivals’ latest matches, and gather a wealth of insights on how they play: their tactics, their strong and weak points, and so on. It can also compare their performance with your team to find major differences, positive or negative. That’s a lot of valuable information to help select the best team and tactics for 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 plays 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 you, the head coach, make many crucial decisions.
- Get more from fitness or GPS tracking data. In fact, from any data you have or may want to use to monitor performance. Soccerlogic will crunch it with its sophisticated analysis tools and squeeze any useful insights that can help you 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 give them to you. You’ll get an insight on how the team is playing, and can act quickly to make those changes required to improve performance.
There is more! Please ask for details or a demo at firstname.lastname@example.org
Gianni Pischedda founded Soccerlogic in 2003 with the aim to help coaches make sense of large amounts of data on performance. Thanks to advances in computer data analysis, unique and valuable insights could be found in such data. And these could help coaches make smarter decisions to improve performance.
Starting in the early ‘90s, Gianni had been a pioneer of applying such advanced data analysis to help businesses become more competitive. His intuition that such powerful analysis could also help improve performance in football led to the formation of Soccerlogic. Naturally, such idea only occurred to him because of his passion and knowledge of the beautiful game. 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 coined by Gianni from ‘Business Intelligence” which at the time (late ’90s) was used to indicate the new and advanced techniques of data analysis being increasingly adopted by business to exploit data for competitive advantage. Football/Sports Analytics is the term that is often used these days to describe such analysis.
… 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.
… 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!
“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….”
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.
… 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,
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.
“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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