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Germany has emerged as the World Cup champion, beating out Argentina in extra time on Sunday in a match that had over 20 million TV viewers in England alone. It seems the entire world has caught football fever; Germany’s historic trouncing of Brazil in last Tuesday’s World Cup game, for example, was the most-socialized event of all time. At ground zero, the flood of data coming from spectators in Brazil has been unparalleled, causing big brands like ESPN to scramble to adjust social media in real-time and comb through waves of incoming posts, photos, and videos for relevant information.


In a similar fashion months earlier, Team Germany was combing through its own set of data - not from fans, but from its own tracking and analyzing of players’ practice stats to find ways to improve like never before.

 

There’s no question that strong coaching and other factors have contributed to Germany’s near sweep of the football series (7-0-1), brushing past Portugal with ease, tying Ghana, and knocking out the USA before beating Algeria and France. Still, Germany’s careful review of data from 2,000 “events” in games and practices - every kick, pass, steal, and goal - deserves recognition. Some are even calling data “Germany’s 12th man” at the World Cup. The 2014 FIFA World Cup Brazil Statistics show Germany at the top of many team and individual statistics categories.

 

The team has been using emerging tools such as goal-line and ball-tracking technology that can measure the tendencies of players in various situations. Video analytics using keywords to detect and return specific audio and visual events from game video allows the German team to retrieve video of relevant scenes and create a highlight reel for each win.

 

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To get an even finer look at players’ actions, Germany’s TSG Hoffenheim is placing sensors in shin guards, clothing, and even the ball itself to collect more than 60 million positional records per match, including speed averages, ball possession, and other player tendencies. Those records are then streamed, analyzed, and stored using SAP HANA, the in-memory data platform for real-time analytics, and used to build customized training applications that target the strengths and weaknesses of each player. Through data, the team has created the most efficient training plan, reduced the risk of injury, and ultimately boosted game performance.

 

[Did You Know: The latest Intel Xeon E7 v2 processors deliver a 2x improvement in scan speed per core, without rewriting any of the SAP HANA code.]

 

The use of analytics in sports and businesses is growing fast. MLS reported in early 2013 how teams, like my hometown Seattle Sounders, are using big data to improve fan experience and build stronger teams. And with Seattle boasting the best record in MLS at the mid-point of the 2014 season, I’m happy they chose to be on the leading edge of this trend.


And it’s not just the teams that are looking to emerging technology to improve. World Cup refs are embracing goal-line sensor technology along with precise video recording and ball-tracking systems. Of course, don’t expect that to clear up coaches concerns over referee choices or commentators wondering if the USA was robbed of a World Cup win again this year. Then again, I’m not above a bit of home-team speculation during a heated match either. (We’ll get ‘em next time, Dempsey!)

 

Here at Intel, we’re committed to helping IT organizations, sports-centric or otherwise, embrace and deploy advanced analytics, whether you’re just getting started or working to optimize your existing solution. If you’re looking to win big in the enterprise, the Intel IT Center Essential Series on Big Data has more insights on big data trends along with detailed research and planning tools to tackle analytics projects.