The Power of Data in Youth Football

There’s more than gut feeling to work with.

‘This player will be a pro football player one day.’ We have all heard bystanders say it at the sidelines or even stated it ourselves with much firmness when watching a youth game. We tend to believe our own perception, thinking we can recognize which player has the capabilities to make it to the top. That’s also precisely how scouts try to find that hidden gem between the dirt. Adding relevant data in the mix will make it easier to identify talent and support claims that players will make it to the pros. 

Talent identification 

Claiming a player will make it to the top is always risky business. A football journey to the pros is far from easy. We all know the success stories, but most players who enter an academy at the age of 9 will never make it to the pros. Michael Calvin, author of the book ‘No Hunger in Paradise: The Players. The Journey. The Dream’ even states that less than half of 1% will make a living from the beautiful game. 

A pro career is only for natural talents. But what defines a talented player like Kevin de Bruyne, who decides what that looks like, and the most crucial question: how does one identify talent? Knowing which metrics represent talent and which ones should be monitored is well known. Countless studies have been conducted and published for one to read and to draw conclusions. But how do we objectively measure these metrics without the interference of subjectivity? The answer: reliable data

The world football federation highlights the importance of having access to key technology to collect data to support the identification and development of youth players objectively. Data can be used to help decision-making on every level effectively.  

That’s also the conclusion FIFA drew in the 2021 report ‘Increasing Global Competitiveness – An analysis of the talent development ecosystem’. The world football federation highlights the importance of having access to key technology to collect data to support the identification and development of youth players objectively. Data can be used to help decision-making on every level effectively.  

Data tracking and analytics

Data tracking and analytics is nothing new to the world of sport. Many companies, Catapult, ImeasureU, Polar, have built their empire on it and with new start ups entering the market, the technology and how we use it is only evolving. Some big changes in the past century:

  • Data analysis is made understandable for a larger public, you don’t need to have an expert inhouse to read into your performance data
  • Tracking technology is entering grassroots, making players at every level able to use data for individual improvement.
  • AI is making its appearance in analysis. Making data analysis even more insightful due to pattern recognition.
  • Data is used by individual players to make informed decisions about their career, changing the way we look at the transfer market, including agents and scouts.

JOGO is one of those startups, seeing the potential of helping more players develop their skills and getting seen by those who matter. That said, being seen is the hard part, especially if we consider “to be seen” as looking at a player’s footage, or live game. Even if you do get the opportunity as a scout, trainer or agent to review a player, is it even valuable if this review is of one point in time? Instead of over a certain period of time? Is the development curve of a youth player not far more interesting than the performance of a player at a certain point in time? 

What makes a talent?

Why do you think all top academy scouts watch a talent multiple times before deciding to sign him? “By that time, you will know if a player plays well and how he is composed physically and mentally. You will notice, for example, how he deals with turnovers, how he reacts to fouls, decisions of the referee, and so on”, explains Rene Moonen, an academy youth scout at Manchester United.

“Every season, I start with generally watching games, but once I’ve seen a player that stands out, I will check him out about eight more times that football year. If it’s a player who proves interesting, then I want to see him at least ten more times in action in the following seasons. So by the time I give my blessing, I will have watched him at least 35 times. 

But we are not there yet, talent identification has one very strong placeholder that can not be taken out of the equation: the benchmark. How do you know what ‘good’ even is, if you cannot compare it to bad? Collecting data from players all over the world. Over multiple years or even decades can create a benchmark which we can uphold talented players against and see, based on very specific metrics where a player stands in comparison to other players. Both at a certain point, but especially over time – the development curve compared.

The problem established above is one JOGO is seeking to solve, by collecting objective data from an academy player throughout their career and using analytics to visualize the development curve, including a comparison to peers, JOGO creates a situation where a club, trainer, scout, or agent doesn’t have to “see” a player to know if he or she has talent. The data tells you where to look. Because who knows, we might miss a lot of talented players because we have never been able to spot them. Either they just don’t live near an area where scouts are passing by, or they even have no club to take part in.

There are many places like this, take Brazil, for instance, they have approximately 60.000 registered players.

Now, we believe it is safe to say that this number does not even come close to the actual number of players in Brazil. Creating visibility for these players will only feed the way. We are changing the way we consume football, for the better. Creating more opportunities for those who deserve to be seen and perhaps not giving hope to those who never stood a chance of making it.

To make the JOGO mission a reality, we have built our own sensors to bring an extra layer of reliable data to the mix. The waterproof insole sensors are lightweight, easy to use, measure up to 200 data points, 1000 times a second, and can be worn in all weather conditions during training as well as matches, which is unique and as per FIFA’s rules of the game. Trainers can review the individual player results compared to benchmark data for various age groups, positions, teams, and other players. This feature allows clubs and coaches to optimize personal development and set SMART objectives using global standards.

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