How Football Clubs Use Data to Sign Players

The Data Companies Helping Football Clubs to Find Players

Although the biggest clubs tend to have their own in-house data teams, other clubs make use of specialist companies which provide bespoke analytics to identify potential signings based on the needs of the club.

One such company is Twenty First Group, previously known as 21st Club. They have developed tools to calculate the link between a player’s performance and the team’s overall performance, producing a rating for each player in the team. Clubs can then use this rating to help determine whether a potential signing is likely to improve or weaken their own team.

Red Star Belgrade, the reigning champions of the Serbian SuperLiga, are one club that have made use of the scouting services offered by the Twenty First Group. In 2018, they were looking for a replacement for midfielder Guélor Kanga, who had left the club to join Sparta Prague. 

Working in London, the analysts at Twenty First Group searched their database for a suitable replacement. Red Star had given them a shortlist of names which had been suggested by agents. The analysts evaluated the names on the list and found a player who was cheaper than those on the shortlist and who the data suggested would be better. That player was Lorenzo Ebecilio, a Dutch midfielder playing in the Cyprus.

‘It’s a good example of being able to widen the net using data that you just can’t do with traditional scouting or just using agents,’ says Omar Chaudhuri, Chief Intelligence Officer at Twenty First Group. ‘There’s not much data on players in Cyprus, but based on the information we do have we’re able to create real intelligence on players like that and try to understand the way they can translate across to a league like Serbia’s.’[5]

Another product available to modern clubs is TransferLab from Analytics FC. The software has a lot of built-in metrics which make the data easier to understand without the need for the club to have its own in-house data experts. It also makes use of predictive algorithms to help clubs unearth talented players who may not have yet reached their peak levels of performance. Their database includes over 90,000 players in the men’s game, and over 5,000 from the women’s game. Clients include Leeds United in England, Motherwell in Scotland and K.A.A. Gent in Belgium.

With data use expanding, Twenty First Group and TransferLab are far from being the only ones offering data analytics for player recruitment. One of the biggest names in football analytics is Wyscout. Founded in Italy in 2004, the company offer services for a range of people involved in football, including agents, coaches, referees and journalists. As its name suggests, scouting is a major part of the service it offers.

The Wyscout platform includes data on more than half a million players and teams. There are more than 100 filters which users can apply when searching through the database. Visualisation tools can also be used to help make sense of the data. The company also provides videos of over 200,000 matches, so that after sifting through the data, scouts can watch hours of footage without having to travel to far flung corners of the globe.

Using Data to Scout from Home

Because the new technology means that scouts no longer need to travel and attend matches in person in order to recommend players, a new type of scout is emerging. 

It is possible for anyone to search through the data from anywhere. As well as working with football clubs, databases like Wyscout are open to anyone willing to pay a subscription. Other companies, such as StatsBomb, make some of their football data freely available online.

This has led to online analysts building up a portfolio of work showcasing their ability and gaining work as scouts at professional clubs. 

Oli O’Connell is one such scout. The 23-year-old is based in Lancaster but has been employed as a scout and analyst for clubs in Belgium and Sweden. He started out as a student by analysing the performances of the football team at his university before moving on to analysing the professional game. Sharing his work online, he built up a following on Twitter and began to be noticed by people in the professional game as well as those in the online analytics community. His Twitter followers include Lee Dunn, Head of Performance and Recruitment Analysis at Norwich City, and Lee McCulloch who has managed Kilmarnock and is currently Assistant Manager at Hearts.

‘Clubs are realising they don’t have to do things the traditional way,’ O’Connell says. ‘There’s no reason why I cannot work for a Belgian club from my bedroom in Lancaster.’[6]

The distance from Lancaster, in the North West of England, to Belgium is not nearly as far as the distance from Scotland to India. Ashwin Raman, a teenager who was hired by Dundee United as a part-time scout and analyst, works for the club from his home in Bangalore, India.

Like O’Connell, Raman started off by sharing his analytical work online before he was spotted by the Scottish club. 

‘People say, “oh, it is a mad thing that you are doing with Ashwin.” It’s not really, he’s just good at his job,’ explains Stevie Grieve, who was responsible for appointing Raman. ‘Why does it matter that he’s a teenager from Bangalore?’[7]

Why Transfers Go Wrong

Using data in player recruitment is still relatively new. It is also part of a complex process alongside video analysis, human judgement and financial considerations which means that a successful or unsuccessful transfer can never solely be attributed to data. There are times, though, when the carefully made recommendations of the data analysts do not work out. 

Naby Keita may have looked good on paper when Ian Graham was looking at midfield options, but since he joined Liverpool, Keita has been hampered by injuries and played a fringe role at the club. He has certainly not matched the success of Mo Salah. Even with the help of data, football transfers are not an exact science.

When things do go wrong, data can be a useful tool for working out why a transfer has not been successful.

In 2015, Liverpool spent £32.5 million on singing striker Christian Benteke from Aston Villa. This was just £4 million less than they would spend on Ma Salah two years later and at the time was the second highest transfer fee the club had ever paid. Benteke was signed in the summer when Brendon Rodgers was manager. By autumn, Jürgen Klopp was in charge and the style he wanted to play was not one that suited the striker.

Stephen Smith, who is CEO of the sports science technology company Kitman Labs, has crunched the numbers to show exactly why Benteke was not as successful at Liverpool as he had been at Aston Villa. 

At Aston Villa, Benteke had been part of a team that played direct football. In the 2015/16 season, Liverpool made an average of 519 passes per game, compared to Villa’s 402. But out of the two teams, Villa won more aerial duels. Benteke, a 6 ft 3 in target man who is great at heading the ball, was clearly more suited to Villa’s style than Liverpool. A year after he joined, Benteke was sold to Crystal Palace. In his first season at his new club, the player scored 17 goals. He was back in form.

‘Did the Belgium international simply under-perform for Liverpool, or was he overvalued?’ asks Smith. ‘The likelihood is a combination of both when you consider the playing style of Liverpool AND the tactical and physical traits of the forward.’[8]

If Brendon Rodgers had stayed at Liverpool, maybe his tactics would have suited Benteke more than those introduced by Klopp. If Keita hadn’t struggled with injuries, perhaps he would have become an important part of the Liverpool team over the last couple of seasons. 

Football is a complex game and there is a lot that can happen on and off the pitch which can impact the performance of a player. No signing is ever guaranteed to be a success. But when used thoughtfully alongside other forms of scouting, data is starting to have a noticeable impact on the ability of club to find the players who are right for them.