We don’t know if you liked that one, so let’s get straight to the heart of the story; analytics can indeed contribute to the success of a sports team. Those of you who have seen the movie ‘Moneyball’ already knew this, of course. This story about Oakland A’s general manager Billy Beane using analytics to form a winning team suddenly made analytics sexy, and not just due to Brad Pitt’s presence.
But analytics can do more than help team coaches draft the best available players. It can also be of considerable help in maximizing ticket sales and in increasing fan loyalty. Take, for instance, the Major League Soccer, representing 19 top league soccer clubs in the United States and Canada. They have managed to win fans with an extremely focused personalized marketing program.
From filling seats to defining team tactics
Why not add a basketball example, more specifically Orlando Magic? This 20th-largest team, in terms of market opportunities, has managed to become one of the top revenue earners in the NBA. Their secret? They have studied the resale ticket market intensely using SAS analytics in order to price tickets better, and to better predict which season ticket holders are likely to defect in order to lure them back. Oh, and meanwhile they have also started using analytics to assist the coaches in putting together the best lineup. Just like Oakland A, indeed.
Another team that uses analytics in their game tactics is Bayern Munich. On an MIT Sloan sports analytics conference earlier this year it was revealed that Bayern managed to beat AS Roma partly because of analytics: historic data showed that opponent AS Roma played at its best with star player Francesco Totti behind two strikers. So they needed just three defenders, allowing more freedom to the offensive force. Bayern coach Pep Guardiola is very interested in such data to define his tactics, Bayern’s analytics head Michael Niemeyer added.
Practice makes perfect
But these successes don’t come easy. Behind every one of these stories is a story of hard work, focused energy and lots of communication. Thomas Davenport, an analytics expert with a broad expertise in sports analytics, has come up with a set of common denominators that can be considered key to the success of using analytics in sports. It’s about getting internal and external data and combining them to provide new insights.
But it’s also about gaining internal and external support, from top management and from the huge fan base that sometimes includes some very avid analyzers of sports data. This final observation led the English soccer team Manchester City to release their player performance data for analysis by their fans. An initiative that has delighted thousands of fans. And after all: delighting your fans, isn’t that what it’s all about?