What businesses can learn from the way sports franchises use big data to improve performance

In companies such as Amazon and Google, data analytics is a foundation of the enterprise. However, for most organisations, the use of big data has been limited to a few tests or to narrow slices of the business. According to a recent report from McKinsey, very few have achieved “big impact through big data.”

In sport, things are quite different. You can’t watch any sport (be it football, cricket, basketball, tennis or even snooker) without seeing hundreds of statistics pop up on the screen, being quoted by commentators and rapidly analysed. And that’s just for entertainment.  

Behind the scenes, as made famous by films like Moneyball, data is a core component of the team’s dynamic. Collecting and analysing data in the right way can help a team achieve a competitive advantage which is, unsurprisingly, essential in the incredibly competitive world of sport. In professional sport, rather like business, winning is everything. 

Data analytics in the world’s biggest sport

Football provides a great example of data being pushed to the limit. In training, in just ten minutes, ten players with three balls can produce over 7m data points.

Being able to rapidly and accurately analyse data can enable managers to understand which combinations and players are yielding the most effective results. Statistics such as total metres run throughout a game; the number of sprints made; passes completed; and tackles made all affect a manager’s decision; influence a player’s salary; and will help inform a successful training strategy. What’s more, data analytics can help corporate sponsors determine which football clubs and players they will back.

Read more about sport:

• 5 ways big data won the America’s Cup for Ainslie and Oracle Team USA
• Glasgow 2014 Commonwealth Games: Where tech meet sport
• 5 digital trends that will change the way you run your business

Football is also leading the way in integrating big data analytics to capture more insights and react in real time. For example, FC Bayern Munich uses sensors to map players’ movements, instantly analysing millions of sets of data points to help evaluate patterns of play, and improve performance.

Field vision

Data growth has been accelerated through the use of social networks, mobile devices and internet-connected items – an ever-increasing availability of data. By 2020, there will be an estimated 2.5bn connections between people on personal and business social networks worldwide. 

Sport organisations have leapt at the opportunities created by advances in big data analytics, network infrastructure, sensors and connectivity technologies. From retail and banking, to manufacturing and sport, organisations that are able to digitise and collect data from devices, equipment, employees and customers will be able to thrive in this new order – the networked economy.

The business of sport has led the way in recognising the need and opportunity to take key learnings from data to improve optimal performance and ultimately deliver results. As we continue to watch games – the Premier League, the World Cup, the Six Nations, the Super Bowl – we should remember to ask ourselves if we’re on the same data playing field as them, or if we’ve still got a way to go.

Darren Roos is COO at SAP EMEA.

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