What Sports Can Teach Us About Using Analytics

Lessons from the data-obsessed world of sports


It says a lot about sports analytics that one of its key proponents, Billy Beane, should be played by Brad Pitt in a movie about his work, a man with the big screen star factor you might not naturally associate with number crunching. Sport’s data revolution has been heavily romanticized, not least because of the truly inspirational achievements it has made possible. Numbers saw the Oakland As to go on a fairytale run, it has discovered otherwise unheralded talent, and it has underpinned much of Bill Belichick’s success with the Patriots, despite his claims to the contrary.

But sport is not a detached entity void of connection with the real world. It is, after all, a business, an industry in which astute decision making and financial nouse are every bit as important as passion and flair. The world of business can look to sport as an example. Sport has largely allowed data to influence top to bottom working practices, in an industry where results are heavily scrutinized not just by shareholders, but by millions of emotionally invested fans the world over. Here, we’ll look at how sport is leading the way in terms of managerial buy-in, research and development practices, and the ownership of personal data.


There are a number of pioneering figures in sports (and, more specifically, sports analytics), but to get a real picture of managerial buy-in in sport, its best to look at those that have been slow to change. In February this year, the New York Times ran a piece that centered on Arsenal’s Arsene Wenger and his commitment to data. Not famed for his willingness to change his approach on the pitch, the Frenchman is relatively progressive off of it. Even one of the Premier League’s oldest, most famously staunch managers has been open to the use of data for some time, his scholarly attitude making it impossible for him to ignore the evident benefits. When it was made clear exactly what the manager could avoid with data - as opposed to sweeping statements about wholesale change - he gave the green light to a $4 million purchase of data company StatDNA.

At the Sports Analytics Innovation Summit, I spoke to data professionals from clubs like West Ham, Aston Villa, Newcastle United, and Everton FC. When discussing data programs with the representatives, a general theme of managerial buy-in ran through the talks. The topic was essentially that of digital transformation in sports coaching. The more data-sceptical old guard is slowly but surely leaving the industry, making space for the young, innovative, data-savvy managers to step in and move the game forward. Business can learn from soccer’s experience; giving managers clear, actionable incentives to invest in data analytics - both financially and mentally - is far more effective than talk of revolutionary change.


In November last year, entrepreneur Valery Bollier stood up in front of an audience at a conference and told them that Riyad Mahrez, the almost unheard of Leicester City midfielder, would have a huge valuation by the end of the season. With no background in football and a self-professed tennis fan, Bollier’s claim was a bold one to say the least. He even went as far as to say that, at the time, Mahrez was the best midfielder in Europe, not just in England, predicting that the talented Algerian would be snapped up by a bigger club come the end of the season. Leicester City went on to win the Premier League, with a great deal of help from their technically gifted wide man, who deservingly won the PFA Player of the Year award. Mahrez wasn’t bought by a bigger club, but Leicester had uncovered a gem.

Soccer is a good example of a sport that uses data to uncover otherwise unknown opportunities. Businesses can operate in a not all that dissimilar way. Rather than having teams research areas of potential growth and report back to management at length, analytics departments can run the numbers and provide insight in half the time, with machine learning only set to speed up the process. It’s inconceivable that Mahrez was found by accident, a £425,000 slice of immensely good fortune - the numbers would have supported Leicester’s scouts in their assessment, and the value of their asset now lies at around £25.5 million.


Another topic that came up repeatedly in my conversations with sports analytics professionals was the extent to which athletes actually care about their personal data. The answer, naturally, was that the interest varies - some are competitively obsessed with improving specific metrics, where others want to see outcomes rather than spreadsheets. The latter is the important group. Across sports, from athletes to coaches, data is only useful or interesting when it has a clear outcome. If a physio can predict, with confidence, that an athlete’s current training level has a high chance of seeing them injured, that’s a persuasive and actionable piece of information to bring to the coaches. Similarly, if a member of the analytics team notices that, statistically, long balls lead to fewer goals for their side, they can make the tacticians aware of their findings.

One area in which businesses often struggle is getting their employees to take ownership of the data that affects their work. Sport is particularly effective at this, because each department within a club or organization will be very clear on how data can help them do their work because the results are tangible. Couple this with a clear view of how any given team’s work affects the club or organization as a whole, and data in sports has a clear path to acceptance. Business can follow sport’s lead by ensuring that each team is aware of how data can tangibly improve their work. This makes it far easier for actionable, though out insight to be collated and brought to management. 


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