How data is revolutionising football

Data and sport have never been the most natural of bedfellows. The battle lines have been very clearly drawn by traditional culture – the data geeks wear horn-rimmed glasses, spend most of their day in the science lab or in front of a computer and cannot find the words to ask the cute girl-next-door to prom. The jocks on the other hand are brash, muscular party-animals and thus by extension date the prom queen. In no circumstances do these social groups meet, interact or (gasp!) work together. 

Football 2017, however, is steadily crushing traditional perspective. Never the most open of sport to change, football has steadily adopted to the data revolution. Data geeks are increasingly the bedrock of traditional football institutions with analytics giving a whole new perspective to the centuries old beautiful game. As fans, we are fast learning that things like corner kicks have no cause to quicken the pulse (the conversion on them is ridiculous), players like Lionel Messi, while gamechangers, are still less important than the weakest link and while having possession can be paramount, it does not necessarily translate to more goals scored. 

Data in sport has been embraced by pop culture since Billy Bean's baseball team Oakland Athletic's used analytics to beat an unfair game. Beane's exploits, captured in the wonderfully detailed Moneyball, had always been a data lover's gem, but it only catapulted into prominence when Brad Pitt played him in a 2011 movie of the same name. Ever since, it has become more culturally accepted to be a data geek and still like sport. 

In football, the data brigade is led by a company called Opta. Founded in 1996, Opta began collecting new kinds of information from English Premier League games. They were largely ignored by clubs as a gimmick for more than a decade of their existence, but ironically also gained prominence around the turn of the noughties. For the first time, clubs began to show interest in metrics. They were now interested to find out how much each player runs during a game, how many tackles each defender makes, and even which two players pass most often to each other. The results have been eye-opening and now data tells us far more about a player than we ever knew before. 

Football is already taking notice and adapting. Coaching revolutionaries like Pep Guardiola has, for instance, completely given up on corner kicks because the data tells him that making pass at that point is more valuable and has a higher chance of conversion. There are other insightful conclusions as well that contradict often with what individuals perceive – a good example is how data tells us that Mesut Ozil runs more every game than Alexis Sanchez, which most fleeting observers would think absurd. The numbers, ultimately, do not lie. 

Football hasn't had its Billy Bean moment yet, but it has at least adopted from a world of no data to one of big data. The challenges are many, and the adoption into the game itself has been slow. But the feeling is that football's big data revolution is just around the corner. And then someone like Billy Beane will come around and change the sport forever. 

The writer is a sport lover currently working in technology.