Ben White and Kevin De Bruyne used unique tactic in Arsenal and Man City contract talks

Arsenal defender Ben White signed a new four-year contract earlier this year (Image: Getty)

When Ben White’s Arsenal contract came up for renewal earlier this year, the defender’s representatives adopted an unusual approach. Rather than sitting around the negotiating table with club staff and arguing White’s case subjectively, they hired Analytics FC to conduct an objective analysis of the player’s worth.

In partnership with financial experts LCP, Analytics FC have created a platform called Transfer Lab, a data hub that is largely used by clubs for recruitment. Transfer Lab’s algorithm was able to provide a comprehensive report on White’s ability, his importance to Arsenal, and which other teams he might fit into.

Central to Transfer Lab’s algorithm is a metric called goal difference added (GDA). It assigns a positive or negative value to each action during a football match, of which Analytics FC’s Alex Stewart predicts there are between 3-4,000. The data evidences how valuable a player is to a team, and how likely they are to contribute, positively or negatively, to certain achievements.

A report provided to White’s representatives showed that of all the players in the top five European leagues, the former Brighton player is in the top 10 per cent for progressive forward passes and for passing accuracy. His data profile matched the tactical systems of top European clubs including AC Milan, Barcelona, Bayern Munich and Manchester City. An age profile showed that White could continue playing as an excellent Premier League right-back until his early 30s, by which point he might revert into a central position to prolong his career.

“Each player’s pass, dribble, tackle, interception, contact at a set piece, etc, we can assign a value to that which tells us whether their team is more likely to score a goal, or more likely to concede a goal. The former is a positive, the latter is a negative. It means we can look at a whole variety of different analytics in one measure,” Stewart tells Express Sport of goal difference added.

Ben White’s Transfer Lab profile graphic (Image: Transfer Lab)

“We can compare players in lots of ways, but we also have an underlying number that says: this player contributes a lot, this player not quite so much.”

White has excelled for Arsenal at both centre-back and right-back. In the past two seasons, he has displayed excellent versatility on the right of a back four, capable of bursting down the right wing or by tucking inside as effectively an additional centre-back to provide a solid base and prevent counter-attacks. It is a system adopted by Arsenal, Man City and many other successful clubs and proves that, should White ever become available on the transfer market, he would be in high demand.

“If you can show that by removing a player, it demonstrably shows the unlikelihood of a team achieving certain benchmarks, those benchmarks are tied to financial rewards and you can therefore say, ‘well look, by taking this player out of the team you reduce your Champions League qualification’,” Stewart adds.

“We can then bring in salary information and that’s where it gets quite crunchy for the negotiations because what you’re then able to do is say, ‘if you took Ben White out of the team and replaced him with an average Premier League right back, how would that affect Arsenal’s chances of winning the title, getting into the Champions League’, and so on.”

Arsenal were fortunate that White wished to commit his long-term future to the club. He signed a new four-year contract that will take him to roughly the time at which Analytics FC predicts he may begin to decline in the role he currently plays.

White is not the only player to commission data for contract negotiations. Kevin De Bruyne did so when he found himself without an agent – although aided by lawyers – in 2021. The Belgian midfielder commissioned a report from Analytics FC which helped him negotiate a contract reportedly worth in the region of £83m.

At the time, De Bruyne was considered among the best midfielders in the world and City were very keen to keep him. But the data was able to provide objective evidence of his importance and how much City ought to pay him. The use of data, Stewart argues, has made negotiations fairer as it gives a clear picture of the player’s ability and their worth.

Stewart says: “One thing about basic performance data is that it establishes a level of trust. Say it’s a centre-back – and I’m not talking about White specifically here – and they’re very, very good at passing, and they’re very bad at heading. The club will look at our report and say, ‘yeah that’s reasonable’.”

Bart Huby, head of analytics at LCP, adds: “You want to be in a position where the club can’t really argue with what you’re saying. You don’t want them to sit there critiquing the report.”

Kevin De Bruyne commissioned data when he signed a new Man City contract in 2021 (Image: Getty)

Around a dozen players have used the services of Analytics FC. Manchester City women’s player Alex Greenwood is among them. A separate report is being conducted for another women’s international footballer, who cannot be named due to the terms of the agreement.

It works for players seeking a fresh start, too. When Hector Bellerin found himself surplus to requirements under Mikel Arteta at Arsenal, he wanted to find the team that would provide him the best possible chance of playing for Spain at the 2022 World Cup.

Huby recalls: “Bellerin was an interesting case. His manager had spotted something I’d posted on LinkedIn about the Kevin De Bruyne case. He contacted me so I went to Analytics FC. He wanted to find a club that would give him the best chance of playing for Spain at the Qatar World Cup. It wasn’t about salary benchmarking, it was about playing for Spain.”

Bellerin joined Real Betis on loan but fitness issues prevented him from going to Qatar. “The report that Analytics FC did for him [involved researching] what kind of player gets into the Spanish national team,” Huby continues. “It found that to get into the Spanish national team, you generally need to be playing in Spain. Then what team in Spain would be the best tactical fit.”

Another player, who was playing in Serie A at the time, was able to show prospective buyers a report of his abnormal ability to win penalties. A type of Expected Assist metric was designed for the individual, who might have used it to counteract arguments that his open-play assist record was comparatively poorer to other players in his position.

Hector Bellerin wanted to know his best chance of playing for Spain at the 2022 World Cup (Image: Getty)

Football was relatively slow to the use of data. Across the Atlantic, American sports teams, particularly in baseball, had used numbers to their advantage. Billy Beane famously used a sabermetric approach to build his hugely successful Oakland Athletics team and kickstarted an era of moneyball. Football managers generally felt that, unlike American sports, their game was impossible to analyse using numbers.

That somewhat changed with the introduction of Prozone – a performance data analysis tool – to the Premier League in the late 1990s and early 2000s. Among Prozone’s staff was Michael Edwards, who worked at Portsmouth and later became Liverpool’s sporting director. Under Edwards’s guidance, Liverpool used data to underpin their performance and recruitment analysis and won a Premier League and Champions League.

It may therefore come as a surprise that players are only just realising how data can improve their own career prospects. Stewarts says players who commission Analytics FC are particularly “sophisticated” in their analysis of their own performance, and contrary to popular accusations, are not entirely driven by money. Many, like Bellerin, simply want to locate their best chance of success. In essence, it is maximising player power.

Will more players adopt the same approach as White, De Bruyne and Bellerin? “I hope so,” Stewart says. “Not just from a commercial sense [for Analytics FC] but because I think it’s a sensible thing to do. Why would you not want to know what your players are earning relative to their performance?

“A sportsperson’s career is short and pretty brutal – it seems only right that if there’s a huge amount of money swirling around that players get their fair share. That’s particularly acute in the women’s game, where we’ve seen a rise in serious injuries, some of which could be career-ending.”

Michael Edwards (left) was key to the analytics boom in Premier League football (Image: Getty)

In White’s case, his career can be mapped out by the data.

“The sensible thing for White to do is to not be a fully dynamic overlapping full-back, but the very smart passing full back that he is until his early 30s,” Stewart says. “At which point he can move back inside and play centre-back again and continue to operate at an elite level probably until he’s 35 or 36. That’s without any massive issues. I’m given to understand he’s extremely conscientious off the pitch and hugely professional in terms of how he looks after himself.”

The future of data in sport is intriguing. It is now widespread and there is a sense that believers outweigh the sceptics. Numbers are widely used in recruitment, performance analysis and now negotiations. Stewart and Huby both say that there is work to be done in injury data, particularly with a sharp rise in cases over the past 12 months, but they add that data protection laws could limit how numbers are used to understand injuries, their causes and the development of preventative measures.

It can only be a positive for players that they use it to enhance their own careers.