From the Oakland Athletics to Red Bull F1: How big data has helped sport teams win big
8 min read
15 August 2015
While calculations to improve performance have been employed since the advent of sport, the latest innovations in data are poised to trigger a revolution – as is seen by the latest batch of teams that have used big data in order to win.
Everyone probably knows the tale of the cash-strapped Oakland Athletics’ data-driven strategy to build a competitive baseball team. General manager Billy Beane and office assistant Paul DePodesta allowed measures of in-game activity to drive their decision-making and identify undervalued players.
This allowed the team to win almost two-thirds of its games in 2001, and nearly beat the New York Yankees in the 2001 Major League Baseball (MLB) playoffs.
This story has since been chronicled by the 2003 book by Michael Lewis entitled “Moneyball”, as well as in a 2011 movie starring Brad Pitt. Fast forward to today and you see all sorts of sports teams modelling the methods that had been employed by the A’s.
In fact, that businesses and sport teams alike will gain from a data-driven culture is a proven fact. Nobel laureate Daniel Kahneman revealed that intuition can be wrong if you ignore the data, and a recent MIT study highlighted how data-driven businesses and sport teams have a definite competitive edge.
The concept of using data analytics to boost success was once again showcased when Germany won the FIFA World Cup in 2014. Months prior to the event, the team used software to analyse players’ biometric data and movement during training, along with the analysis of its opponents’ play history and tactics.
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According to head coach Joachim Loew, this was instrumental to Germany’s victory. He suggested that through the use of big data they had optimised performance, enhanced team chemistry, and avoided injuries. This was done via cameras and biometric sensors worn by players, and allowed managers to track the distance each player covered in a match, acceleration and deceleration, as well as heart rate in order to assess fatigue.
Also take, for example, when Red Bull bought Ford’s Formula 1 team Jaguar Racing in 2004. In the five years it was controlled by Ford, its drivers had yet to win a single race. It now dominates Formula 1 racing, and won the double championship every year from 2010 to 2013.
According to Red Bull’s head of technical partnerships, Alan Peasland, some 100 gigabytes of data goes into winning a race. Each car is fitted with sensors which gather data about temperature, g-forces, spin, and then feed it back to the engineers.
Data also arrives at Red Bull’s UK HQ in “real time” – something CIO Matt Cadieux suggested no other team has the ability to do. This has reigned in some hefty benefits. In the final race of the 2012 season, Red Bull driver Sebastian Vettel nearly lost the championship after a crash with another car. The team decided against bringing him into the pit, instead keeping him on the track while engineers figured out whether the race could be salvaged. Vettel went on to finish in sixth place.
Another example comes from 2013, when Oracle Team USA made one of the greatest sporting comebacks of all time by using 300 sensors in much the same fashion. It was suggested that about 3,000 variables were running at ten times a second – all while sailing – from sensors that measured strain on the mast to angle sensors on the wing sail that monitored the effectiveness of each adjustment.
This just comes to show that teams and analytics providers have have come up with increasingly sophisticated ways of monitoring and capturing ever-growing volumes of data.
According to Business Diction’s Kevin Mulligan, the tactics employed in the Moneyball story yields an important lesson for SMEs as well. He said: “Sometimes the best ideas are born out of desperation. When the Oakland A’s started picking up random, undesirable players based on a single statistic, they were called crazy.
“No one thought it would work because it was an unorthodox strategy. The team’s financial situation may have pushed management toward an unorthodox strategy, but sometimes being unorthodox is your best option.”
Another team which is set to use big data as a way of punching above its weight is London-based football club Brentford. Having secured back-to-back promotions, which saw the team rise to the second best league in England, the owner has decided to employ tactics similar to the Oakland Athletics.
Led by entrepreneur and hedge fund manager Matthew Benham, Brentford has long dealt with a smaller than average budget and is hoping to leverage what has been done at Danish team FC Midtjylland – another team Benham is a sizable stakeholder in. So drastic is the change that widely-admired and successful manager Mark Warburton was disposed of, and a new mathematical structure for recruiting players introduced.
The next few years will prove key in determining whether Brentford’s gamble (Benham is a big poker player) pays off and allows the team to join the elite of the English Premier League – but it’s ambitious and trailblazing to say the least.
Something that made the A’s so great was management’s focus on its undervalued players. “Your industry standard for hiring might be someone with a bachelor’s degree in business management and three to five years of experience,” he said. “Or MBA candidates from a top ten school with ten years of experience. All of your competitors are investing serious money into salaries for these candidates, so obviously you have to do the same just to keep up. This can lead to an expensive war for talent.”
Essentially, when other MLB teams and critics called the A’s crazy, they built a winning team that was right for their financial situation. No one said it would work, and it did. What you may not realise is that investing in data and learning how to use it, no matter how small the change, might be transformative for your business – as is evident by the success witnessed by sports teams.