Football, Data, and Decisions: The Search for Rafa Benítez’s Perfect Center-Back
By profession, jack of all trades: that’s the definition or the label many of us would give to our role.
Knowledge of all areas of our sport should be fundamental in order to lead a project and a multidisciplinary group that needs to move in the same direction to achieve results. This knowledge doesn’t necessarily have to be practical, as in most cases we will delegate to part of our team, but understanding the subject will allow us to build a better relationship with the group and to have a clearer vision of what we want to achieve.
In my early years in the profession, I worked in several of the areas that make up a coaching staff. Due to my university training, I started by combining the role of coach with that of physical trainer and injury recovery specialist, even creating tools to work with the players (sleds, water tubes for instability exercises, boxes for plyometric work…).
Over the years, after studying academically, I began taking on analyst roles to improve the teams I coached. We’re talking about around 2008, using a video camera and Nacsport.
When the opportunity came to work in professional clubs and elite coaching staffs in Finland, China, Canada… that previous knowledge allowed me to respond more effectively.
But education is something we must never neglect, even in areas that are not our priority. That’s why, in 2019, I decided to train in an emerging field: Big Data.
The world we live in is in constant technological evolution, and these changes directly impact our sport. Today, knowing how to use artificial intelligence tools should be part of our training plans.
Speaking practically: in 2019, while in China, I was part of Rafa Benítez’s coaching staff, made up of Antonio Gómez, Paco de Miguel, Joaquín Valerio, Mikel Antía, and myself. My role was assistant: I helped Rafa and Mikel Antía in training sessions, and in the office, I supported Antonio Gómez with analysis.
After six months of work came the long-awaited vacation… although that word doesn’t really exist when you work with a coach like Rafa. A few days after leaving China, I received an email asking me to evaluate all center-backs under 18 years old with potential to reach the elite level in the coming years.
As you can imagine, the number of players in that age range worldwide could reach into the millions. That’s where my training in Big Data came into play.
Some will say that data isn’t reliable in football, that this sport goes beyond numbers…
We could compare it to that scene in Moneyball where Brad Pitt gathers the old-school scouts at a table along with the “chubby” data analyst.
I’ll just say one thing: “You have to know in order to judge.”
My first step was to gather data on those players. Platforms like Wyscout or InStat Scout help filter the search and create a preliminary list, but even after the initial screening, we still had over 10,000 names. Then came the question: What now?
Every process has errors and doubts, but it’s up to us to overcome them.
I asked myself: What did scouts see in the world’s great center-backs (Sergio Ramos, Van Dijk, Piqué…) before they made it?
I ran a second search, focusing on those specific players, and analyzed their data from the years before they broke into the elite. That’s how I managed to create an “ideal profile,” and after days of work, I designed an algorithm that summarized the key qualities they shared before their success.
To validate it, I ran tests with elite players (of which some succeeded in their careers and others did not). When the data matched, I applied the algorithm to the initial list of under-18 players. This reduced the list to 50 players.
Then came the practical phase: watching matches and specific actions, which helped me narrow the list down to two names.
I researched them on social media, in the press, and even contacted a coach of one of them. Finally, I sent Rafa a report highlighting two center-backs who, at the time, were playing in the youth systems of two South American clubs.
Today, both are playing at the elite level in Europe, and their Transfermarkt value exceeds 50 million euros.
The data didn’t give me the direct answer, but it helped narrow the search so I could decide.
Among all those variables, there was one common trait: ball blocking. I’ve now incorporated that quality into training sessions, and in the next article, I’ll explain a specific drill to work on it.
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