A numbers game? How data science is changing football scouting | OneFootball

Football clubs are turning to data and analytics to improve the way they recruit players. And small businesses are stepping into the big leagues to give these clubs the specialist support they need.

Just five minutes after coming on as a substitute against Paris Saint-Germain in France's Ligue 1 in October 2024, Pape Diong scored his first goal for RC Strasbourg. His team lost the match, but the 18-year-old's goal was a victory for one small Prague-based start-up. Eyeball, which specialises in video and data, had identified the Senegalese midfielder as a rare talent and recommended him to scouts at Strasbourg's owner BlueCo.

Strasbourg isn't alone. A growing number of leading football clubs are using Eyeball to add scientific rigour to the way they recruit players. “We have video and data on a quarter of a million players in 33 countries,” explains the company's director David Hicks. “Many clubs are trying to find the talent no one has spotted yet – but you can’t do that without data.”

Eyes on the prize

Eyeball is one of the small and medium-sized enterprises (SMEs) identified in new research by FedEx and the Financial Times as a Champion of Business – an SME that's encouraging excellence, innovation and entrepreneurship in football. It has quickly filled a gap in the market.

As Hicks says, clubs are desperate to identify young players who they can develop into first-team stars or players they can sell on for a profit. Eyeball supplied video cameras to thousands of clubs, including many amateur teams, to film youth games. Its artificial intelligence (AI) technology analyses the videos to assess each player’s contribution, which provides the clubs with feedback they can use for coaching. Not only that: professional teams can then use Eyeball’s database to identify promising young players.

Shipping all the equipment to so many clubs represents a significant supply chain challenge. It’s a reminder that SMEs working in football often have to prove they can cope with complexity; that might mean using third parties such as logistics providers to execute on practical issues with the same efficiency as larger companies.

Exploiting data to spot talent was a technique popularised in Moneyball, the 2003 book and 2011 film that told the true story of how a baseball manager used sports analytics to identify undervalued talent and create a cut-price squad.

“The Moneyball idea isn’t really about performance," says Ian Graham, a former director of research at Liverpool FC. "It’s about performance per unit of money spent.” Player recruitment and wages account for about 90% of professional clubs’ turnover, says Graham: “You make the difference by spending that money more wisely.”

In 2023, Graham founded Ludonautics to advise sports organisations on how to turn statistical analysis into a winning advantage. Also on the FedEx/FT Champions of Business list, Ludonautics helps clubs use data to work out, for instance, the extent to which a player can increase their chances of scoring or of not conceding. It can also predict outcomes such as whether this would increase the club's chances of achieving promotion, avoiding relegation or qualifying for international competitions. That helps the club to establish the potential return on their investment in a particular player.

“We start to answer the question of whether a player offers good value for money,” says Graham. “You might want the player as a coach or a fan, but what about their financial impact?”

Combining data and judgement is a balancing act

Most clubs use data analytics alongside the judgements of scouts and coaches. That's because it’s relatively simple to collect data such as pass completion or successful defensive positioning, but much harder to analyse a player’s leadership capabilities or professionalism. A centre-back who has lost some of their pace, for instance, might be a crucial influence in the dressing room. And data is backwards-looking: young players develop very rapidly – and sometimes for the worse.

But analytics are a way for clubs to cut through the noise. “We’re advisers, not the final decision-makers,” says Graham. “We give clubs a tool to make an informed decision.” It's a balance between the efficiency of the data analytics and the human instinct of experienced coaches.

David Hicks agrees. Clubs often use Eyeball's data to put together a shortlist of players to watch at a particular tournament, he says, so that scouts don't have to go to endless matches in the hope of spotting an unknown talent. “Data is just data,” says Hicks. “It’s up to the club how they interpret it – they can click on our videos to watch the player for themselves.”

Getting it right means doing the groundwork

There’s no point investing in data analytics unless the club is prepared to commit to it. For that, they need to do two things: invest in in-house data facilities so the club can work with the advice and analysis it receives, and build cultural acceptance of the science throughout the organisation.

“We always recommend that clubs have their own data teams,” says Graham. “You need to be able to ingest and store and organise the data, and to translate that data into insights and reports that inform your work.”

According to Hicks, managers who are under pressure to produce short-term results might be reluctant to pick the young players that the data has suggested the club buys. “It’s a bit of a cliché, but will the manager give young players a chance?” says Hicks. “Does the club have a good academy, or B team or partner clubs, where players can develop?”

What's next: Predicting stardom from age 12

The influence of data on football and other sports continues to grow as technology and innovation accelerate. Hicks says that advances include DNA analysis that can help clubs to predict the top speed of their players, and cognitive testing that measures players’ decision-making speed. And AI is helping Eyeball to evaluate all of its analysis so far to identify which of its recommendations succeeded and which failed – and why.

“We will soon be sitting on the largest database of youth footballers in the world,” says Hicks. “The holy grail will be the ability to look at 12-year-old players and predict with a degree of accuracy which ones will make it.”