Why analytics and ingenuity only add to football’s romance
This past weekend, one of the top voted posts on the popular subreddit /r/soccer featured a single sentence headline that read, “Lyon, who have spent €19.8m on new players in last four years, go 1st and seven points clear of PSG, who’ve spent €453m.” (That lead has since shrunk back to four points after PSG beat Evian 4-2).
Why was this post so popular? Had the poster omitted information related to their relative spending, chances are few would care. It’s the enormous gulf in spending that piques our interest; not only is Lyon outperforming PSG, they’re doing so on a fraction of the cost. Their success on a limited budget makes them, in modern terms, the perfect underdog. It’s part of what makes football–and sport–both unpredictable and enjoyable.
Lyon of course are famous for their youth development policy developed under club owner and chairman Jean-Michel Aulas. It won them seven straight French championships between 2001 and 2008, and was featured in Simon Kuper and Stefan Szymanski’s popular book Soccernomics. Though in recent years Lyon has struggled to match their former glory, this season the team is making a remarkable run in part with the help of 23 year old wunderkind and Lyon youth product Alexandre Lacazette. Lyon’s success comes down to a proven method and an ability to identify and develop world class talent. It has given the team a major competitive edge without putting the club in financial peril.
Though it’s not known how or whether Lyon uses data in their youth system, clubs that use analytics in order to pay less money for better value in the transfer market are essentially attempting to do the same thing–find a way to win at the football that doesn’t start and end with a giant transfer kitty. These clubs won’t be limited by their ability to spend; they’re trying to use data analysis to find new and innovative ways to beat a very closed system.
However, much of the football-loving public public doesn’t see it this way.
For them, analytics represents the cynical infusion of economics into sport. The use of data to aid decision-making in football involves is the forced transformation of the qualitative into the qualitative–it reduces the magic of football to a bottom line, an accountant’s calculation. Analytics is about finding efficiencies to ensure that every dollar of club spending is accounted for, rather than the glory of the game played out in 90 minutes on a football pitch. It is fundamentally opposed to the inherent romance of sport.
Perhaps this perception, which I believe confuses the modernity of the tools analysts use for the art of analysis itself, is the result of a failure of storytelling. After all, we know that something as dry as using data to derive value in sport can be transformed into a compelling narrative, otherwise Moneyball–the book and the film–would not have enjoyed popular success. Yet we can’t entirely blame this failure on the media; the proprietary nature of analytics work in football means there may be countless Moneyball-esque tales of underdogs climbing the table that have not and perhaps never will see the light of day.
Even so, I think it would help if we viewed club stats analysts first and foremost as competitors alongside players, managers, coaching staff etc. There is a reason why teams often recruit immensely talented statisticians for a fraction of the salary they might get in the business world–club analysts are driven first by a love of football and a strong desire to win, not just in the short-term, but again and again, season after season. Their will to succeed means they aren’t satisfied with the same old hoary cliches about grit, heart and “chucking it in the mixer”. They won’t accept the Sky Sports transfer window logic about the need to break the bank every January. They don’t just want to beat their rivals not just this year, but over the next five or ten years. In other words, if you want to know who the real footballing competitors are, skip the mercenary athletes in the locker room and instead find the 22 year old statistics graduate on an internship who has turned his back on a lucrative private sector career in order to tease something potentially groundbreaking out of raw datasets.
This image of course runs almost comically counter to our ideas of the sport, in which talented players hustle and brilliant managers tinker. The idea we might make room in this image for some backroom-dwelling, Excel-using nerd is almost heretical.
And yet the problem with football–and sports in general–is it can get stale. Super Sunday, Jim White chasing landing helicopters, the Big Transfer Rumour, 4-2-3-1, double digit transfer fees, Chelsea Man United Arsenal Man City, year after year after year. Analytics is one of the last areas of football where destiny and money are not one and the same, where ingenuity and a sense of discovery still have currency. Though the methods are modern, the passion of the analysts involved, whether working for clubs or sharing information in public, is as old as football. Perhaps our increasingly cynical view of a game driven by money rather than sport might be improved if we dared to look at it with fresh eyes. We might better see that the analysts, in pushing teams to play beyond their means, are on our side.