From being something only sporting nerds cared about, sports analytics is poised to become a business all on its own. ITW Core’s Devanshu Bhatt explores how the eco system has evolved and what lies in store.
Nowadays, it is hard to escape talk of Expected Goals or xG in footballing circles. However, football is far from the only sport where analytics have become mainstream. In fact, in markets such as the US, statistics have been a feature since the Moneyball days of 2002. Despite its global status, football is one of the last sports to the party. However, its global status has also enabled analytics and statistics to rapidly become widespread in the sport. So much so that the USD 889.4 million industry is set to grow 3.87x to USD 3440 million in 2028.
It could be conceived that the overuse of numbers might be off putting to fans however, the advantage of the internet age is that even this aspect of sport has found its niche. And its popularity is evidenced by the fact that the world’s most popular sports title, FIFA also has an xG statistic in its game now. Not just that – every club has specialized teams that utilize data to make decisions on the pitch and during player recruitment. Companies like Opta, Statsbomb and Enetpulse have occupied the space opened up by clubs and football analysts’ demand for reliable data and models. This can be likened to the effects of new technology in any other industry, signalling that the business of sport is seeing its own little paradigm shift with analytics at the heart of it.
Very notably, big cloud computing services like Amazon Web Services and Oracle Cloud have also partnered with the Bundesliga and the Premier League respectively to provide them with data for their viewers. This is notable for two primary reasons. AWS and Oracle already offer a host of cloud computing services on their platform and these partnerships are elaborate ways for them to find their way into the sports sponsorship market. The added advantage of this is that even the market is enriched through their expertise. Secondly, while raw numbers can be fun for a niche group, in order to appeal to the masses, they need to be packaged as such. This means they have to be presented in a fun, interesting and easily digestible manner so that it has universal appeal – even to those not fortunate enough to acquire a PhD in Statistical Analytics in Football. This might even mean including the more frivolous statistics like which player hit the highest top speed in 2021.
While I use the example of football here, such a revolution is occurring across the sports universe. ESPN cricinfo has introduced concepts like Smart Stats where common statistics like wickets and runs are contextualized to give a better picture of the game. In F1, through the use of data, the aforementioned AWS has helped fans visualize the rigours of racing by highlighting the speeds and forces that the drivers undergo in addition to how difficult a particular overtake is. However, this is not all. The crown jewel of their F1 association is their assistance in developing the design for the next generation of cars that are poised to make racing recapture its excitement.
Analytics is prevalent in every sport – from monitoring heartrates to managing workload to pre-empting injuries, certain fundamentals are common across the board. From the revolutionary to the frivolous, analytics has become the one of the pegs upon which sports performance and business stands. Who knew hours on the computer can actually help people get better at sports?