Every professional football club today relies on technology and information, and most of the world’s top ones have an extensive scouting and analysis department. A good example is Sevilla FC, which is famous for great transfers of players on the principle of “buy cheap, sell expensive”. It is enough to mention such football players as Dani Alves, Ivan Rakitić, Julio Baptista, Seydou Keita and Grzegorz Krychowiak. Each of them had a huge impact on the team’s performance, and then they were sold for a much higher price. This philosophy is shared by the sports director and club’s legend – Ramón Rodríguez Verdejo, known as Monchi. Formerly the Sevilla goalkeeper, today an outstanding strategist and visionary.
He has been working at the club since 2000, with a two-year break at AS Roma (2017-2019). After ending his football career, he began to lay the groundwork for the player observation system, which is known today as scouting. Initially, he was guided by his intuition, having only two people at his disposal and games recorded on videotape. Nobody remembers those times anymore, because today the club relies on Big Data in its activities.
Big Data is any activity in the virtual world that leaves a digital footprint (or not) that can be collected, transformed and analyzed for decision making.
At the beginning of 2020, Monchi was one of the main speakers at the Football Data International Forum event, which was attended by analysts, physical preparation coaches and technology companies. The conference was held at Wanda Metropolitano stadium in Madrid, and representatives of the three leading Spanish clubs using Big Data – Atlético Madrid, FC Barcelona and Sevilla FC agreed that the digitization of football can no longer be stopped. These clubs use data analysis not only to define their actions on the pitch, but also off it.
“Today, even more than scouts, we have started looking for engineers, mathematicians, physicists, experts in statistics and algorithms. Big Data is the future of football as it minimizes risk and helps to make the right decisions” – convinces Monchi. To this end, Sevilla collects huge amounts of data not only about its players, but also about players who may be in their interest. It is thanks to the database containing profiles of thousands of players that the club makes great transfers on which it earns millions.
How is Sevilla using Big Data in player transfers?
Today, Monchi has access to the latest technologies. Sevilla has created the departments of Artificial Intelligence, Machine Learning and Big Data. In the football community it is commonly referred to as “Monchi’s laboratory”. The director personally analyzes the process of each transfer operation, and on his “radar” he has 18,000 players from around the world.
During the Madrid conference, Monchi described in detail what the process of finding a good player for a transfer in Sevilla FC looks like:
- Sevilla FC has 18,000 players from around the world, who potentially match the profile of the club, both in terms of sport and economic opportunities.
- The first team’s coach describes his needs to the sports department, i.e. reports the position on which the team needs reinforcements. For example, if it is a right-back, the number of profiles automatically drops from 18,000 to 1,500.
- With the coach, work begins on determining the type of player needed: what qualities should he have? It depends on how the team plays and what the coach wants. The number of candidates then drops to 500.
- Identification of key features to facilitate decision making. The goal is to narrow down the selection field from 500 profiles to 30 players, whose final choice of a player is made after analyzing his price, skills, personal characteristics and personal situation. “We want to reduce random, subjective judgment and the risk of error in this way” he explains.
Importance of Market Value
“Research and development department is a great support in making decisions. It forces us to constantly improve in order to be up to date. Anyone who does not understand this will be left behind,” explains Monchi, for whom data analysis is not limited to purely football issues. “We are trying to draw conclusions from our transfer history that will help us make better choices. It’s very similar to investing in the stock market”.
Clubs like Sevilla have to buy cheaper and sell as expensive as possible. Investing time in being able to estimate the true worth of a player allows them to make better decisions. Therefore, the club develops models to help both in attracting and selling a player. “Earlier, everything was done intuitively. We followed the stock exchange model: buy at low prices (reasons: injuries, mistrust from the last coach) and sell on the verge of sports growth,” says Monchi.
Dani Alves, Krychowiak, Sarabia, Baptista, Ben Yedder, Carlos Bacca, Kanouté … There are many examples of footballers bought by Monchi at a bargain price and sold as stars. Valued today at € 50 million, Brazilian center-back Diego Carlos is the last example of a player Sevilla has recalculated. “We got him for € 15 million in the summer from FC Nantes and it was a bit of a risk, but for today that value seems low,” says Monchi. A similar increase in value also occurred in the case of Lucas Ocamposa (bought for €15 mln, today priced at €45 mln) and Jules Koundé (bought for € 20 million, reduced value of € 50 million).
The club also uses the data to calculate the bonus for signing a contract. “When you buy a player for 30 million euros, you might think it’s a good price for your gut and experience, but without objective data, it’s just an opinion,” explains Monchi.
Big Data for Injury Prevention
The profit and loss account always influences the decisions of a sports director and injuries are a huge challenge here. “This is a very important economic aspect. Last season, first-team players missed 15% of their games due to injury, and at a club like Sevilla, which has a budget of 200 million euros, is equivalent to losing 30 million. Therefore, if we had a turnover decrease from 15% to 10%, we would be talking about big money,” says Monchi.
Sevilla FC works with data, looking for patterns and algorithms to find out why certain injuries are happening. Today, for example, we know that some injuries occurred among players wearing a certain type of footwear, while others resulted from the type of pitch surface. “Instead of working with a player who is recovering from an injury, it’s better not to get injured at all,” says Monchi. “That’s why we try to prevent injuries and use all possible measures to reduce their risk and reach the right conclusions.”
This is extremely important, especially at the highest level because competition forces athletes to exceed physical limits, overload, increasing the risk of injury or reducing performance. It is thanks to the data analysis that we know that half of the reported injuries in football are the result of overload and not traumatic events 90% are soft tissue injuries resulting from overtraining or under-training, most of the injuries are suffered by players until the age of 24, and half by the age of 15. That is why, regardless of the age category and the level of games, players today use GPS vests, and strength and conditioning coaches analyze dozens of statistics to choose the right training load.
Sports advantage and the context of interpretation
The Andalusian club uses data analysis primarily in scouting, transfers and injury prevention. Big Data also allows you to collect data that can translate into sports results and provide an advantage over the opponent. The key, however, is the contextualization of the data.
“Data without context are meaningless,” explains Monchi. This is where knowledge comes into play, not just raw information. The hobbyist will see numbers and interesting facts in this, and the analyst will see information related to a number of environmental variables, context and situation that allows a correct interpretation. “We do not need to analyze and observe 1,500 right-backs from the major leagues, filtering them according to the characteristics needed and narrowing down to 50”
Of course, the player also has to be monitored on the pitch, because most of the data we have comes from the action with the ball, in which you can see how he is positioning himself or reading the game. There is also a personal aspect to consider: “Sometimes we forget that footballers are people and not Swiss watches. A footballer does not always perform at the highest level and it has to do with what his personality is, what a human being is,” notes Monchi. “After all, there are personal and subjective decisions, but it’s easier to make fewer mistakes if you have more objective than subjective arguments.”