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The new Premier League season has landed to a chorus of cheers/groans, depending on your outlook, and with it the latest innovations in play.
Will it be £200 million signings like Neymar that make the difference this year? The ability of referees to retroactively punish blatant divers? Or Liverpool’s sleeves being sponsored by Tinder?
Although all of these will come to bear, no doubt, on the outcome of the league, there is a more subtle, digital revolution going on behind closed doors.
For one, we can save you an awful lot of time predicting a winner this year: it’s going to be Tottenham. Promise. And that’s not just because I’m a fan...
The latest data from 21st Club, a consultancy that advises football clubs about squad evaluation and the perfect players to transfer, suggests that the North London club are the most likely to be lifting a trophy next May. The firm’s methodology is based on analysis of thousands of data points and some bayesian AI algorithms thrown in for fun.
But can a sport that relies so much on the moment-to-moment - a missed pass here, a flash of skill there, the incredible unlikelihood of a perfectly-timed overhead kick - be demystified with a few dozen Excel spreadsheets?
This was the thinking behind the Seattle Sounders’ experiment over the past few seasons. The team’s sports science and performance manager, David Tenney, analysed reams of data obtained throughout the season and pre-season to find out when his players were being injured, and how they could train more effectively.
Now in every training sessions the Sounders’ stars wear a full-body monitor that collects information on their speed and distance run. Twice a week they receive a full-body scan to measure how their muscles are coping with the strain of the game.
All of this data feeds into an SQL Server database, where it is analysed by Tenney and his team - including Microsoft alumnus Ravi Ramineni and compsci guru Chat Kolarick.
Tenney stresses though that the data may not be robust enough to make concrete recommendations, though it is possible to at least measure player fitness and make suggestions based on that.
Closer to home, this approach has resulted in far more palpable success. The runaway success of the 2015-2016 season - little Leicester City - was largely down to the club being one of the Premier League’s data trailblazers.
According to Chris Mann of Prozone Sports - which supplies tech to 19 of the 20 current Premier League teams - Leicester has been using its products for more than a decade to keep tabs on player fitness and development.
Leicester picked up surprisingly few injuries among their big name talents like Jamie Vardy and Rihad Mahrez in their run to the cup, which meant manager Claudio Ranieri was free to pick a relatively unchanged 11 week in, week out and maintain their breakneck counter-attacking play style.
Of course, with so much vital data around football clubs now there’s the obvious question of security to worry about. Earlier this month Everton became the first club to comply with the EU’s General Data Protection Regulation (GPDR) that mandates them to protect private data, including playing and training data collected from their players.
Working alongside Netskope, Everton will allow all employees to see exactly what data is stored and shared in the cloud in the name of avoiding the risk of a hack.
Whether Wayne Rooney will be able to look through Romelu Lukaku’s old shooting drill stats, however, remains to be seen.
Back to Spurs, meanwhile, whose new stadium is going to boast some of the latest IT infrastructure to allow information from ticketing, merchandising and other consumer-facing services to be shared around the stadium securely.
This even extends to the crowning glory of the new White Hart Lane - a luxury cheese “experience” for corporate and premium ticket holders - in what Hewlett Packard’s managing director Mark Waters called “the most technologically advanced stadium in the game”.
So, whether it’s leading to their domination on the pitch or in the pie shop at half-time, clubs are embracing the implications of big data infrastructure to their success.