The Premier League returns today, marking the start of the 2022/23 season. Although football has been played professionally in England since the 1800s, the game today looks very different from its origins – largely due to the rise of data analysis technology.
But how important is data analysis to football? And how did it change the game? According to Paul Caldbeck, account director for data start-up Sportlight, “is the key word”.
“Most decisions are made with data to back them up,” says Caldbeck RATN.
Founded in 2015, Oxford-based Sportlight works with Premier League teams to provide data that informs strategic and business decisions.
Elite sports teams are increasingly turning to companies like Sportlight to gain a competitive edge or just to keep up with the pack.
The services include the use of LiDAR to track real-time player performance. That data is then analyzed using AI to determine the athletes’ ability and form, providing information on transfers and strategies for directors and managers.
Football clubs have, to some extent, been incorporating data into their decision-making for some time, but only recently has it become a necessity.
“The early clubs started playing with it 20/25 years ago, but in the last 10 years or so there’s been a whole Moneyball approach, and it’s much more public now,” says Caldbeck.
“Clubs have had access to key data for some time. That was better than having him there.”
But Caldbeck says modern innovations mean sports teams can measure “quick actions” and “really complex actions” that legacy technology struggles to capture.
The value of the industry rose dramatically in that time period. Figures Strategic Market Research put the global value of the sports analytics market at $2.1bn (£1.7bn), predicting it will grow to $16.5bn (£13.6bn) by 2030.
In June, Sportlight raised £4m in a funding round that included support from the owners of Southampton FC.
The sector is obviously highly regarded by professional sports organisations, but what kind of impact is it having on clubs?
“Coaches will make decisions on player purchases, squad rotation, and picking the final squad,” says Caldbeck. “Data has a big impact on that, we know there’s a lot more to the decision to sign a player or not.”
Caldbeck described how profitable clubs can determine transfers from the data, particularly for “certain club sizes”.
“A mid-tier team in the Premier League, it might be very profitable for them to bring players from the lower leagues or the smaller leagues overseas into the Premier League with a potential sale. [fees] in the future.”
By using data to determine the potential future value of a player who appears to be priced as a bargain, smaller clubs in the Premier League can look to maximize profits from buying low and selling high.
How data became a football game changer
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