When I left school to start a professional football career, I understood very little about data – I did keep a note of the goals I scored, the assists I made and, most likely, the keepie-ups I could perform, but that was about it.
Fast forward 15 years and there is not much of my day that is not spent thinking about or applying data and insight to solve performance improvement challenges. But now the performance I am trying to improve is focused on retail execution rather than football.
I have come to realize that data is everywhere and there is huge value in harnessing and using it. Taking a data-driven approach to understand what has just happened on store sales and profitability in the hope that we can define what might happen in the future in order to drive the best performance.
To bring data to life, I am always looking for examples of best use. Given my passions, it is no surprise that I have found an increasing number of these in football as clubs make data and insight a key pillar of their performance strategy.
How football clubs use data to improve performance
There are a host of outstanding examples in recent years where football clubs have combined the data collected with their smart analytics teams and tools to gain a competitive advantage, both on and off the pitch, to acquire the right players, improve their performance, prevent and manage injury and make better commercial decisions.
When Brendan Rodgers was manager of Celtic Football Club, he was alerted to Jack Lyons, a Twitter user who had been breaking down the tactics of Rodgers’ Celtic teams based on a wide range of publicly available data. Rodgers was so impressed that he hired Lyons to join Celtic as a Performance Analyst. When Rodgers left Celtic for Leicester City, Lyons was part of the backroom team that departed with him. Lyons’ impact is clear for all to see, with Leicester City star James Maddison calling him out for special praise in elevating his game and helping him gain his first England cap.
And it is not just the billionaire-owned clubs in the EPL exploiting this opportunity. In 2019, Dundee United hired Ashwin Raman, a 17-year-old data analyst, from India. Not surprisingly, Raman had never been to Tannadice, Dundee United’s home, but from his remote location he spent hours poring over enormous amounts of player data and video footage, enabling him to formulate reports on social media that caught the club’s attention. They promptly offered him a permanent job within their analytics team.
The data-driven insight behind the perfect goal
These examples change the overall footballing system at a club, but there are many exploring specific tactical weaknesses and opportunities to exploit, sometimes in the hope they can influence a split second in a game.
When Liverpool’s Philippe Coutinho scored a wonder free-kick against Brighton & Hove Albion in 2017 by firing his shot underneath the jumping defensive wall, his manager, Jürgen Klopp, credited the club’s analysts for pointing out the opportunity. As fans, we direct our praise and plaudits to Coutinho for what was flawless execution, but there was no doubt that it was the data-driven insight from the analytics team that enabled this goal to happen. No standing ovation for the analysts yet, but maybe in time!
As capability grows, so do the platforms and tools to support. These tools are increasingly being used to help in the most costly and, arguably, stressful job for the football management team – player acquisition. iScout, a player data platform, offers a “cost-effective and comprehensive service, combining data analytics with live scouting of players, free from bias”. The Manager might ask his recruitment team for a midfield player who can tackle, cover the pitch and keep possession well. The analysts then review the statistics of ‘average kilometers covered per game’ or ‘average number of successful passes’ before adding more on player age, injuries, suspensions…etc. This enables the recruitment team to create effective shortlists of players on which to focus scouting efforts. Far more cost-effective than casting physical scouting assets far and wide.
Data analytics is key to successful retail execution
So, despite my career change, it seems that my job is not that far removed from modern football after all. If you do not up your game when it comes to grocery data analytics, you risk falling behind those competitors who do. And by quite a lot too – McKinsey Global Insight estimates that retailers who exploit grocery data analytics at scale across their organizations could increase their operating margins by more than 60% and every day at Retail Insight we are focused on that. If the football clubs can see what we are doing with data there then I might still get that call up.
I better clean my boots.