Big Data and Sports: A Winning Strategy

Big Data and Sports: A Winning Strategy

by Richard G. Twilley

When the final two teams face off soon for the NBA finals, one thing that probably won’t get a lot of attention amid all the hoopla is the role Big Data likely played for the organizations.  

But the NBA and other professional sports organizations are very much like traditional businesses: They are always seeking ways to improve the bottom line, get ahead of the competition, and offer value to their customers and stakeholders. And, increasingly, Big Data is crucial to achieving success.  

Business leaders — whether they are from more traditional organizations or sports organizations — can learn from one another when it comes to using Big Data. Let’s take a look at some of the beneficial ways sports organizations are employing Big Data. We’ll start with basketball, in honor of the ongoing NBA playoffs:  

Basketball: Many pro teams — about half in the NBA —are using a system called SportVU to track player movement on the court. The system’s six cameras in the arena rafters record the action and give team management a breakdown of speed, distance, player separation and ball possession data. The Toronto Raptors, for instance, are using the data they’ve accumulated on 140,000 plays to assess what players have done and what they should have been doing on the play, based on player tendencies and coaching expectations.  

Baseball: You’ve probably heard about “Moneyball,” the book and movie that tell the story of how the Oakland Athletics used a statistics-based approach to assemble a successful team. Well, Big Data use extends beyond “Moneyball.” Thanks to a network called MLB Advanced Media and a complementary system called PITCHf/x, 20 terabytes of media and statistical content can be compiled on a single game night. The systems record video on everything that happens in a game, generating statistics on batting averages, strikes, fouls, and home runs, as well as photos that measure the speed and trajectory of each ball.  

Auto racing: The organizations that field Formula One teams take advantage of telemetry systems by the McLaren Group that collect data that car sensors generate during test and practice sessions and races. The teams are then able to analyze the data to make immediate adjustments on the course.  

Olympics: Besides measuring athlete performance, Big Data can also aid game-day atmosphere and security. During Olympics in London last year, the city used a real-time situational awareness system that ran data from sensors on door locks, point-of-sale systems, and other sources inside and outside of the stadium to give officials a picture of any unusual activity in real time.  

Just like at traditional businesses, Big Data use in sports continues to evolve to bring organizations the greatest benefits. In what ways can you emulate sports organizations’ Big Data use to benefit your organization? What are some ways sports organizations learn from traditional businesses in using Big Data?