
Performance based winning: the data behind Kevin De Bruyne
A touch of genius or the hand of God: a question for those of us old enough to recall the 1986 World Cup in Mexico. Isn’t sport all about that thin line between winning and losing? As it turns out, the sports industries have been absolute frontrunners in crunching data to boost performance.
You don’t need to have a crush on Brad Pitt to have seen Moneyball, a witty film based on a true story. In the early 2000s, a has-been coach lifts up a baseball team, the Oakland A’s, whose players are noble unknowns and the occasional wash-up. The real team star isn’t out there on the pitch, nor is he on the bench. It’s a data analyst, crunching the numbers and stats behind his desk. Soon, other sports followed in baseball’s first steps. A mindset switch was inevitable. Today, the professionalism of individual professional sportspeople as well as pro teams is reflected by their commitment to science-based performance optimisation.
In his bestseller ‘Atomic Habits’, author James Clear tells the story behind the so-called ‘marginal gains’, the mantra of the famous British Sky cycling team. When Dave Brailsford became the head of British Cycling in 2003, cycling across the channel hardly was worth mentioning. But Brailsford had this strategy of focusing on tiny improvements adding up to big impact, a bit like compound interest. The team even started rubbing alcohol on tires for a better grip. In 2008, Great-Britain would win 60% of all cylcing gold medals at the 2008 Olympic Games in Beijing. That same year, Bradley Wiggings won the Tour de France. In a Sky shirt, of course.
Moneyball revisited
Entire service and product markets have emerged out of this data revolution. For example, the daily jogger casually checks the automatically uploaded data from her Fitbit to the Strava platform. Video-analysis, heat maps, power metres, sensors for ski boots, wrist watches that calculate the distance to the green – to help you perfect your golf swing – they are all well within reach of everyone who wants to work on personal improvement. Not to mention the piles of data and the growing abilities of machine learning to dig up useful insights out of them.
While the numbers vary from report to report, it is certain that the global sports analytics market has already passed the USD 1 billion post. And all forecasts agree that exponential growth is still to be expected, and some say annual growth rates of more than 20% are realistic. The future looks bright, as a vibrant startup ecosystem is rising on one hand of the spectrum, while big tech players such as SAP and Oracle are also very present.
Data hasn't just revolutionised sports on the pitch, but also around it. When Opta became the British Premier League’s, the best viewed soccer league in the world, official data supplier, it also set in motion a whole new range of content. Live content on twitter and other social media or broadcasts but also an eternal flow of sports articles analysing soccer players on virtually any parameter you can think of. Today many pro leagues have a deal with Opta, since it boosts fan engagement on many levels.
Who’s the coach?
But data rules elsewhere, too. The 2018 World Cup was nicknamed the ‘data tournament’. The Brazilian squad, starring Neymar and other soccer virtuosos, had live game data from gps-trackers beamed to Rio de Janeiro, analysed in real time and sent back to the coaches on the bench for strategic follow-up. Result: they lost to the Belgian team in the quarter finals. When asked about this in a 2020 interview, Red Devils coach Roberto Martinez had a rather quirky answer in store: “Maybe we read the data better than they did”.
While everybody is counting down for the next soccer world championships to kick off in November of this year in Qatar, the battle has already begun, and the game is being played in spreadsheets and visualisation tools. The Belgian Red Devils now have a cell of three full-time performance analysts on their staff. They use drones during training sessions. Data and simulations of opponents help select the right footage for a video analysis, which in turn helps compose the tactical game plan and prepare players for their specific role during a game.
But who decides where Eden Hazard plays – centre behind the strikers or coming from the left wing? Is Kevin De Bruyne more dangerous as a false no. 9 or operating from the midfield? When do you bring Batshuayi for Lukaku? The data has some things to say about that. But it’s always the coach who decides. And in desperate need, he could always tap into the wisdom of the crowd, as hundreds of thousands of fans have their opinion ready, watching tv at home or doodling their tactical plan on a beermat in a bar.
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