It’s the flavor of the moment, whether it’s used in conjunction with politics, business or sports, and given the growing ease with which organizations and people can collect data, it looks as if big data is here to stay.
And when the BBC Technology section runs an article on how data analytics is influencing football, you know it’s a hot, hot topic.
In part one of this series looking at data-driven analysis in football, we discussed the growing popularity and importance of statistics to football scouts, which extends to how football clubs run themselves as organizations and businesses.
A key player in the stats arena that we looked at was Manchester City, so it’s no surprise that the BBC article just cited starts with City as a club to look at: They, after all, employ 10 full-time data analysts just for the first team (and this was the picture, at the time of writing, almost six months ago), and club captain Vincent Kompany has realized the value of in-depth analysis, such that he’s reportedly started meeting with his fellow defenders and the data analysts to discuss their findings.
We started off our last piece looking at the role that pre-match preparation played in Simon Mignolet’s exciting penalty save from Stoke City’s Jonathan Walters on the goalkeeper’s debut for Liverpool—the importance of data analysis and the simple of collection of statistics did the job there, and will continue to do this job.
We will now discuss the coach’s role and use of statistics in part two of our four-part series on Business of Soccer, in which we’ll look at how big data and related technologies and trends have influenced and augmented the beautiful game. Parts three and four will look at the sports scientists and, finally, the fans.
Photo courtesy of The Telegraph.
Let’s start with a fascinating Sports Illustrated article from Jen Chang, who talks about the use of performance analytics by Premier League club Everton and how it influenced ex-manager David Moyes’ preparation work.
And there are major repercussions on the tactics side of the game. Steve Brown, Everton’s First Team Performance Analyst, performs this exact role, where he analyzes information provided by Prozone (more on the data providers later) to develop game plans. Where are opposing full-backs usually positioned? What positional traits do opposing wingers exhibit? How can Everton prepare their team shape to take advantage of any habitual practices of next week’s opponent? As Brown says in the article, American forward Landon Donovan was often eager to solicit more information from Everton’s analysts during his time on loan at Goodison Park.
We can thus see the importance of opposition scouting in terms of tactical approach and how teams can prepare their own players to negate formations and systems, as well as take advantage of any possible habitual holes that are magnified. Add this tactical and positional information provided by data analytics onto detailed observations and reports prepared by specialist opposition scouts (such as this quite brilliant analysis done by former Chelsea scout Andre Villas-Boas via the Telegraph), and it could make for a comprehensive picture and extensive preparation.
The implications of this method quite naturally also extend and have applications beyond opposition scouting. By studying a club’s own players, managers can get a feel for how they can better train and mold them into all-rounded stars with fewer glaring holes in their games—and this not only means they can do tactical and positional work, but also fitness work.
We’ll look more in depth at the science of sports fitness in part three of this series (particularly a high-profile example at Liverpool), but we’ll also refer to one of many interesting applications of GPS technology: to track player movement, position and fitness.
Arsenal, with their aesthetically pleasing attacking movement, self-sufficient financial structure and new world-class stadium, are known for their modern approach to the game, and their use of GPS to monitor their own players won’t come as a surprise, and in the case of midfield starlet Jack Wilshere, according to a Guardian report, it was this technology that persuaded him to miss the 2011 Euro U21 tournament.
So all is well and good with regards to data analytics and statistical analysis employed by football clubs, but where does all of this information come from?
Well, there are a number of big players in the sports analytics scene, and Prozone and Opta are the two biggest names around, mostly because their scope and coverage extend far beyond just a single team.
To that end, Prozone has struck up a number of high-profile partnerships with the likes of Arsenal, Manchester United, Manchester City, Stoke City, Fulham and Wigan Athletic, and this self-styled performance analysis firm provides the information that helps the team preparation process of many other clubs around the world.
In the US, where as we covered last time Major League Soccer have been pioneers in the technological and analytical front, both DC United and Chicago Fire have struck up agreements with Prozone to provide technical and tactical analysis, while the US Soccer Federation itself also employs such data to aid its national team and referees association. Their work also helps the German Football Association, who does a similar thing for the German national football team.
Opta, whose succinct Tweets from a variety of accounts looking at different leagues complement a viewer watching football on TV, are probably as famous among fans for their one-word conclusions as they are among clubs with their information, but it is interesting that they seem to be more of a statistical analysis firm as opposed to “performance” per se.
What do we mean by this? This OptaPro blog will shine more light onto what exactly Opta does with its data. Opta is much more of an independent data provider, in that its information is gathered and supplied in a more third-party role, looking at league-wide trends and analysis, as the blog entry does for Premier League goal-scorers.
Opta is, as well, the official media partner of the Premier League, the Football League and the Scottish Premier and Football Leagues, and its focus is much more on the fan engagement level—official Premier League partners such as Barclays and EA Sports will be able to access use live Opta data, while other popular sites like EPLIndex.com and Squawka are built entirely on data provided by Opta.
But it is another kind of analytics project that Opta has done recently that really captures the imagination and the potential of such analysis.
Opta’s project with adidas on “The Engine,” in which a mathematical equation-based algorithm has searched out specific types of box-to-box, stamina-heavy players and will continue to do so over the course of the season. This collaboration looks on the surface to be an ambitious feature aimed at fans interested in player analysis and comparison, but in reality there could be big implications on the world of football scouting and coaching.
Will there be a day that third-party data analysts—not in-house analysts at clubs—take over all the information analysis functions of football clubs, much like generic call-centers and hardware manufacturers support different companies in the same facility?
Could Prozone come up with a standard set of coaching manuals and training regimes, based on their vast databases of performance-related data, that they could then sell onto clubs, academies and leagues as best practices as a “performance consultancy”?
Could Opta unearth players using specially designed algorithms to recommend to clubs as players they should be looking at?
How would clubs be able to turn down such offerings if both fans and they themselves knew that they are the organizations that have access to the widest range of data and as such should be the most reliable in their recommendations?
As we ponder the future roles of data providers like Prozone and Opta, we should also keep an eye on the present, where sports firms like adidas are expanding quickly and aggressively into the coaching analytics field.
We discussed above adidas’ “The Engine” project; in 2013, its miCoach Elite system will be implemented across MLS to provide real-time data available to both coaches and fans, who will be able to track performance levels to the minutest detail (if they wish) while the match is going on.
In part two of this four-part series on the proliferation of data-driven analysis in football, we’ve looked at the role data is now playing in the coaching arena. Most of the analysis is done pre- and post-match to prepare and debrief players and managers on what to do next, but when real-time data becomes widely available, everyone comes under heavier attention, and the pressure to perform becomes higher than ever.
As we look ahead to part three on sports scientists, there is already plenty of food for thought related to how all this information—and all the players in this field—can have ramifications for the beautiful game in the future.
This piece first appeared on BusinessofSoccer.com, where I cover business and marketing strategy, globalization and technology in football.
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