Big data, the ally in transfer management and performance analysis

November 11, 2022

Big data, the ally in transfer management and performance analysis

Brendan Macfarlane (Toulouse FC) and Adrien Tarascon (LOSC Lille) analyze in a webinar organized by Johan Cruyff Institute in collaboration with Portas Consulting the uses and possibilities of big data in the transfer management and the recruitment of talent in academies

One of the great dilemmas of the football industry is how to choose the right players. Whether it is the big clubs looking for a replacement for their top players or those looking to capture talent in the youth ranks, the recruitment process is one of the most complex functions in the industry. For this reason, clubs seek to optimize the resources at their disposal to the maximum and technology applied to big data has taken on a transcendental role in this process. 

Some of these aspects were addressed in the webinar in the Inside Club Football series, organized by Johan Cruyff Institute in collaboration with Portas Consulting, with the participation of two French football professionals, Brendan Macfarlane, head of recruitment at Toulouse FC, and Adrien Tarascon, head of player development, methodology and data at LOSC Lille.

Data analytics has become an irreplaceable working tool in the recruitment departments of sports organizations. In fact, its use is not only limited to helping acquire talent from abroad, but it is also one of the resources most used by coaching staff to learn more about their own team and their rivals. However, there are many factors that condition its use and that can lead a scouting department or coaching staff to make a more or less appropriate decision.

In the webinar, moderated by the consultant and project manager of Portas Consulting, Neel Rajani, the two professionals discussed the strategies to be implemented when measuring the performance of players on the pitch, the understanding or interpretation of statistics, the evolution in analysis models and squad preparation, and the challenges that football clubs are facing and will have to face.

Coordination between areas of the club, key to attracting talent

Both Macfarlane and Tarascon agree on the need to put together a project that involves all areas of the club, in such a way that decisions are made in a coordinated manner between the board, the coaching staff and the rest of the areas. This is how to identify players who fit within the standards demanded by the board in economic terms, and by the coaching staff according to the needs of the squad. “We don’t need to convince the CEO to implement the use of data,” says Macfarlane. “You need to align the idea of the playing model between the board and the coach and promote it in the first team and in the academy,” adds Tarascon.

The case of Toulouse FC is paradigmatic. The club from the south of France, which was promoted to Ligue 1, has stood out for using the Football Manager video game database to make its signings. In addition to this, the know-how received from Betway, the club’s official sponsor, provides the club with direct information in a number of different areas.

The head of scouting at Toulouse FC explains that the working model of his department, made up of four scouts, consists of identifying potentially interesting players for the club through their data analysis tools, watching matches or highlights of the player in question and, ultimately, going to the stadium to watch him play live. “We can’t travel to Tokyo to see a player we can’t afford, it’s a waste of time and money,” adds Macfarlane.

LOSC Lille‘s head of data analysis insists on the need to combine both the results obtained through data analysis and those obtained on the pitch. “The best example of this is Aurelien Tchouameni, a player who experienced spectacular growth both in the data parameters we analyzed and on the pitch,” explains Tarascon.

Big data, the ally in transfer management and performance analysis

The playing model needs to be promoted from the first team to the academy, says Brendan Macfarlane. * Photo: Tolouse FC.

Performance analysis in the world of football is closely linked to the characteristics of each player. Therefore, “the key is to understand their identity and match the right data. It is more flexible than the original recruitment,” he says. In other words, clubs need to tailor this type of tool to their needs and focus the analysis on what they lack or are looking for in the market.”

“Clubs need to tailor this type of tool to their needs and focus the analysis on what they lack or are looking for in the market” – Adrien Tarascon (Losc Lille)

In this way, football clubs have become increasingly specialized in the search for talent and in optimizing the performance of their players in such a way that their teams include more and more scientists, statisticians and/or mathematicians. Thus, clubs like Liverpool FC now have an AI specialist like William Spareman, who acts as the Reds’ data scientist. Spareman moved from the European Organization for Nuclear Research (CERN) in Geneva to the Premier League.

Clubs have also been professionalizing performance analysis and have created innovation hubs through which to encourage the development of technology companies to help find solutions in different areas. Clubs such as FC Barcelona, Valencia CF and RC Celta de Vigo have committed themselves in recent years to creating innovative projects with these characteristics. In the case of FC Barcelona, the Barça Innovation Hub was created five years ago with the aim of becoming a great laboratory for the sports industry. Two of its four areas are related to data analytics in the world of sport and athlete performance.

“Data analysis is often criticized for being slow, but I think it’s not the data that slows down processes. The focus should be on streamlining processes and making sure there is a common attitude in the club” – Brendan Macfarlane (Toulouse FC)

The speakers analyzed the risks and difficulties they have to overcome in order to be able to make an optimal analysis without deviations or misinterpretations of the data. In this sense, Macfarlane points to the difficulties they have in predicting the future performance of footballers. “We can’t identify exactly what potential each player has,” he says.

Tarascon adds that data analysis processes do not slow down decision-making and that they fit in with the way the club works. “Data analysis is often criticized for being slow, but I think it’s not the data that slows down processes. The focus should be on streamlining processes and making sure there is a common attitude in the club,” he says.

Both speakers agree on the need to adapt to the context in which they find themselves and to look for new alternatives. In the current situation, marked by the inflation of certain markets, they point to Scandinavian and Eastern or Central European countries as the best region to find promising players at an affordable price.

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