Germany’s Secret World Cup Weapon: Big Data

By Jack Rosenberger

A wing commander in the British Royal Air Force, Charles Reep has been credited with creating the first notational analysis system of soccer when, in 1950, he used a pencil and notebook to record the play between a pair of English soccer clubs. Today, Reep’s toolkit seems fairly quaint, especially when it’s compared to Match Insights, the enormous database developed by SAP and Germany’s soccer team, which won the 2014 World Cup earlier this week, defeating Argentina 1-0 in extra time.

The story of how the German Football Association and SAP developed and used Match Insights for Germany’s competitive advantage is both edifying and inspirational, whether or not you are a digital-ready CIO. While some details about the Match Insights database have been publicly disclosed by the German coaches and SAP executives in press interviews, the types of data gathered by Germany team, the extent of the data gathered, and some particulars of its strategic usage on and off the pitch remain closely guarded secrets.

All of the final 32 teams competing for the World Cup in Brazil had a dedicated performance and video analyst, but Germany appears to be the only one that had a specially built database to measure and analyze individual and team performance and strategies. Not only did the German team collect and analyze a vast amount of data on its own and opposing players, but it delivered the data in a visual and easily understandable manner to its players, trainers and coaches, via a custom-built app, so they could use it on their mobile phone or tablet, as one German coach said, “whenever and wherever they want.”

With a Little Help From Some Students

Developed with input from German national team general manager Oliver Bierhoff, Match Insights was launched in 2012 when a group of about 50 students at Deutsche Sporthochschule Koeln, a sports university in Cologne, started compiling information about the players and teams competing in the forthcoming World Cup and inputting it in the database. Some of the most important data that the sports students entered in Match Insights was video from eight on-field cameras that surround the pitch, which the database views as a grid. Each German and opposing soccer player is assigned a unique identifier, enabling their movements to be tracked digitally, and the resulting data is used to measure key performance indicators, such as the number of touches, average possession time, and movement speeds.

Before Germany’s semi-final game against Brazil, German assistant coach Hansi Flick was asked about the team’s preparation for the match. Flick’s reply provided an insider’s view of Match Insights’ genesis and strategic utility. “The sports students in Cologne have been studying in great detail our opponent and put every play they’ve run, every newspaper article on them, and everything about them out there under the microscope and made all that data available to us,” Flick told reporters. “We’ve got this enormous database to draw upon and, together with our scouts, we’re able to take a close look at our opponent and make our plans for the match. It’s a project we’ve been working on intensively for the last two years. We’ve been able to cull some very high-quality information from all the data from the students. It’s very much helped us prepare.”

Germany’s preparation paid off handsomely, as it proceeded to defeat Brazil by a score of 7-1, a result that is partially due to Match Insights, which some commentators have described as Germany’s 12th man on the pitch.

One of the German team’s key strategic aims before the World Cup was to improve the speed of its passing. Thanks in part to Match Insights, Germany was able to cut its average possession time from 3.4 seconds in 2010 to 1.1 second in 2014. This striking improvement in possession time enabled the German players to better implement their aggressive, fast-paced style of play that, at the end of the World Cup, left them the only undefeated team.

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