From data to the goal box

Data has always been at the forefront of decisions, which is no different in football.

Thanks to these data trends, scouts have more in-depth access to the possible potential of a player than ever.
A scout can, for example, give us more information on whether a player has a good mindset and is a team player or if his mentality on the field will fit in well with a team’s goals and management styles.

Why are statistics important in football scouting?
Based on ratings, we have this idea of who the best player is.
In the Premier League, for example, players like Erling Halaand or Harry Kane might be the best strikers.
Still, they might not be the best strikers for every single team.
Different teams have different needs and resources.
This is why it is so important to be able to find a player that fits nicely into a specific team.
Ultimately, these decisions have to be data-driven.
If not, we are just looking at players subjectively.
Even people who know football, such as the traditional scouts, can get it wrong.

The traditional way of sending out a scout to go and watch a game of a specific player to see how they might fit into a team is still being done today.
Subjective scouting has always been a part of football and identifying players that might fit the profile of what a specific team is looking for.
Today, however, teams will use data and data analysts to help them make sense of the information available to them.
This is used to identify players who look like a fit for the team.
A scout is then sent to look at specific parts of a player’s game.
A scout can give us more information on whether a player has a good mindset and is a team player or what his mentality on the field is like.

How does establishing these statistics work?
Initially, data needs to be collected.
The more data we have, the better and more accurate the information will be at the end of the day.
A framework is then built, using the data to understand the different components of a player’s game and then it is quantified.
The team then looks at what their needs and requirements are.
The models work differently for different positions, as other skills are essential for various roles on the field.

Are there benefits to traditional and data-driven scouting?
Data can ensure that you look at a complete profile of a player’s performance in terms of how they have performed over a season versus one match.
All the available data has to be considered and translated in a way that makes sense to everyone involved in the decision-making process.
All the coaches, analysts and scouts need to understand what it is that they want to achieve when the recruiting of new players starts.
A scout is then sent to look at specific parts of a player’s game, where they can access information like the mindset and performance strengths of a player.
One could say that traditional scouting and data-driven innovation must be used collaboratively to discover the best possible players.