Big Data: The Next Revolution of Sport

Big Data -- the aggregation and analysis of data to optimize performance -- is transforming modern society. Sport, which has always served as a reflection of society, is no exception. While calculations have been employed since the dawn of athletics, the latest innovations in data are poised to trigger a revolution.

A new experience for fans.

Big Data in sports affects two major groups: fans and teams. For the former, the use of Big Data has provided a new experience- one they are happy to soak up. Fans interact in real time with teams and players via Twitter feeds, Facebook accounts and email newsletters. A single franchise can attract multiple fan blogs and watchdog sites, updated constantly with the latest news and statistics from the team, and analyses of the players.

Many professional sports leagues understand their core fans' thirst for new statistics and have developed ways to distribute these analyses to an even wider audience. For example, the NBA's statistics site,, has already racked up over 20 million unique views. On this website, fans can find not only figures for points, assists and steals, but also, for example, Kevin Durant's career shooting percentage against the Milwaukee Bucks and the type of pass (chest, bounce, behind-the-back) he uses most often.

The NBA, like many other professional leagues, relies on innovative technology to track these statistics. At every NBA game, cameras positioned at various angles record and log the movement of the players and the ball.

In tennis, the 2014 French Open at Roland Garros saw the introduction of the IBM Slam Tracker. This technology aggregated and published a variety of statistics- from a competitor's point-by-point probability of winning the match to her opponent's popularity on social media at any given moment.

A revolution for the teams.

This influx of new data is a boon for professional sports organizations. Many teams now employ a data specialist who is responsible for interpreting advanced statistics. This process gained fame through Moneyball, a book by Michael Lewis, later adapted into a film starring Brad Pitt. Its story follows coach Billy Beane's Oakland Athletics baseball team- one of the first professional outfits to use advanced statistics to draft and acquire talent. The team's success in spite of a shoestring budget showed how stats-based player evaluation can help a team significantly improve its performance on the field.

During training and games, athletes are now equipped with sensors that monitor every aspect of their performance- from the heart rate and metabolism to reaction time. This data allows managers and technical staff to determine the factors that influence player performance and consequently, the performance of the team.

Already at work with Germany's World Cup winners.

Germany's national soccer team was one of the first of its kind to understand the value of aggregating and interpreting Big Data. Several months prior to this summer's World Cup, Die Nationalmannschaft used software to analyze players' biometric data and movement during training, along with comprehensive analyses of its opponents' play history and tactics.

Developed in partnership with German software company SAP, which specializes in software that helps streamline business operations, the Match Insights program was developed. This tool helped the German team optimize performance using cameras and biometric sensors worn by the players. The cameras analyzed individual movements, the trajectory of opponents, the way teams occupied space on the field and which tactics were best suited to each opponent. The sensors also tracked the distance each player covered in a match, player acceleration and deceleration, and heart rate in order to assess player fatigue and hence avoid preventable injuries.

According to head coach Joachim Loew, this analysis was instrumental in Germany's World Cup triumph. The pursuit of the ultimate prize started with the data analysis during the first training session and continued all the way through to the Final against Argentina in Rio de Janeiro. Throughout the process, data helped Germany optimize performance, enhance team chemistry, and avoid injuries.

"We already had the data, but we did not know how to use or aggregate them quickly and make them interesting," said Oliver Bierhoff, the German Football Association's technical director. "With this software, we have the opportunity to work individually with players, quickly and intelligently, and gather more sources in a single tool. Ultimately, it really improves the performance of players."

It's clear that Big Data can be beneficial for fans, players and organizations alike. Far from obscuring the natural beauty of sport, Big Data gives it a more professional savvy. Big Data will never fully account for Kevin Durant's athleticism and talent, nor explain precisely how Germany triumphed at the 2014 World Cup. However, a clean and comprehensive analysis of so many forms of data has helped grow the game while simultaneously adding detail. Put simply, sport is undergoing a data revolution, and everyone involved is delighted.