Big Data in Sports

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Friday, July 21st, 2017
Kim Chang-min

Before the emergence of the 4th Industrial Revolution, big data didn’t have the capability to analyze dozens of terabytes of data. However, A.I, one of the main drivers of the 4th Industrial Revolution, has contributed to “upgrading” big data. As a result, big data is being utilized for many industries, even sports. In the movie Money Ball, a movie about the Oakland Athletics in the 2000s, Brad Pitt, who plays Billy Beane, improves the team by selecting players based on data. This is the first use of big data in sports. With the improvement of big data, the method of analyzing the data also evolved, and other sports applied big data as well.

The biggest use of big data is to improve the game. In 2014, Germany won the World Cup, the biggest event for soccer fans. While all of the 32 teams competing for the World Cup had video analysis, Germany had a hidden weapon, a specially built data-based program, SAP Match Insights, which analyzed the individual players’ and the overall team’s performance. Video data was captured from 8 on-field cameras and crunched into thousands of data points per second. This enabled coaches to analyze performance metrics, such as player speed, position and possession time. The program did not only collect and analyze the vast amount of data from its own or opposing teams but also changed the data into a visual with the custom-made app so that all the players, coaches, and directors could see it whenever they wanted. The improvement of the German soccer team proves the advantage of the program.

For the German national team, one of their key targets ahead of the World Cup was to improve their passing speed. With the help of SAP’s Match Insights technology, the team cut their average possession time from 3.4 seconds in 2010 down to 1.1 second in 2014. "With the help [of SAP], we came up with an app that allows us to send short clips of analysis to individual players or groups of players from different parts of the team. Every player gets a couple of examples of him doing things well and badly straight after the game. They can look at it on their own time and also check their performance data. The players appreciate that sort of feedback,” said Oliver Bierhoff, German national team general manager.

In Korea, Gang-Won FC, a soccer team in K-league, is the only team using big data. Gang-Won FC made a contract with Big 52 to apply Big SASS (Big data Soccer Analysis Strategy System). Big SASS consists of 4 kinds of programs, JPD-57, J-Shoot, JST, and JDM. Unlike SAP Match’s Insight, which provides data on individual players, Big SASS provides comprehensive data about the team, and makes recommendations on the team’s plays. With this system, Gang-Won FC won the K-league Challenge (the second Division) and was promoted to the K- League Classic.

Another use of big data is to engage with the spectators. Wimbledon, the US Open, and the Australian Open needed a way to engage the fans. Also, the coaches and players had to collect data of their opponents. They chose to collaborate with IBM Technology, which in 2012, made IBM Slam Tracker. This platform was invented to show the in-game situation by analyzing data from players with IBM’s own technology. This platform identified each players’ patterns and style by analyzing the data from the previous 8 years. The National Football League used big data to help players, fans, and teams alike.

The NFL announced their contract with tech firm Zebra to install RFID data sensors in players’ shoulder pads and in all of the NFL’s stadiums. The chips collect detailed location data on each player and each players’ personal data, such as player acceleration and speed. The data would be made available to fans and teams, though not during game play. Like other sports depending on data, the data will help coaches make better decisions. They will also, in the future, be able to use the data on an individual player to determine if he is improving. However, that is not the only benefit of big data in the NFL. The stats of each player will be updated and offered to fans as a way to qualify and market the game.

Finally, injuries are one of the biggest worries to players and fans. Many players lost the chance to get medals even before the tournament or game started because of injuries. However, big data can help to prevent injury by monitoring the condition of every player. In fact, big data was used by several Olympic teams around the world. Kitman Labs has collaborated with several Olympic teams to prevent sports injuries by using big data and analytics. The system that Kitman Labs invented and uses allows team performance directors, coaches and trainers to understand how athletes are responding physically and mentally to the stresses endured during training and exercise. Any signs of negative response will make the staff adjust an athlete’s training and recovery program to avoid injury. Kitman Labs CEO Stephen Smith says: “This new technology is able to prevent injuries through data and analytics.”

Like Gang-Won FC, who weren’t afraid about being different, Korea should be more courageous and welcome big data in sports. Big data will qualify the games. And qualified games will bring in a larger audience, and companies will be tempted to sponsor the teams in the sports. As I mentioned in the article: Sports Industry In Korea, Part II this will help to activate the economy, so that the sports industry will be in a virtuous cycle. Korea should take seriously the impact of big data on sports.

Kim Chang-min (Daejeon Daeshin High School)

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