It all started with Moneyball, the 2011 film detailing how general manager Billy Beane used analytics to vastly improve the fortunes of his Oakland A’s. And while the film doesn’t come with a happy ending—the A’s are eliminated on their way to the World Series—it helped reignite the fire for professional sport associations to leverage the massive amount of data they possess. Bottom line? It’s a game-changer. Here’s why.
According to Forbes, a number of high-profile soccer clubs, such as Premier League’s Arsenal, are now spending big on analytics. One key investment for the team was a set of eight video cameras installed around their stadium, which track 10 data points per second, per player for a total of 1.4 million points per game. All this data is analyzed using a combination of both automated tools and manual coding to uncover patterns that coaches and players might otherwise miss.
For example, Arsenal can now closely examine “off the ball” events, which cover anything players do when they aren’t touching the ball. By fine-tuning their movement and positioning on the field, it’s possible to improve the team as a whole, as opposed to more single-minded efforts that come from focusing on the ball carrier alone.
Professional sports teams are collecting data from wearable devices worn by players to help prevent injury. As reported by Geekwire, the Seattle Sounders football club uses a combination of GPS trackers, heart rate monitors, and pre-game fatigue measuring tools to predict the likelihood of injury.
If, for example, a player is more tired than usual and also engages in more high-intensity runs than average, they may be at risk of a hamstring or other soft tissue muscle injury. While the governing bodies of many sports still don’t allow these devices during official games, they’re a critical part of keeping players and teams healthy both before and after a tough match.
So what can companies learn from the increasing use of analytics in sport? There are two key takeaways. First, it’s often the metrics you don’t see that matter most; while it’s critical to understand outliers, such as high-performing or low-effort employees, better insight about the “average” performers within your workforce—those “off the ball”—are critical to long-term success. What’s more, predictive analytics tools can stave off project fatigue and decreased efficiency if the supporting analytics platform records, analyzes, and then visualizes trends that put ROI at risk.
Professional sports teams are scoring big with analytics; companies need to follow suit and move up to the major leagues of Big Data.