In the digital and technological era, the use of data analytics has revolutionized the way sports are practiced and managed.
In all high-performance sports, data analysis has become an essential tool for teams and athletes in strategic decision making and performance optimization.
Through the collection and analysis of a wealth of information, the data provides deep insight into patterns, trends and strengths of teams and players.
With this information, coaches can devise more effective strategies, managers can make more informed transfer decisions and athletes can improve their personal performance.
Data analysis for human resources in soccer
Today, it comes as no surprise that soccer clubs in Europe's top leagues are leveraging advanced data analytics in their decision-making process to sign players.
This approach, based on the exhaustive analysis of large amounts of information, has proven to be highly beneficial.
An outstanding example is the case of Leicester City, a club that implemented this methodology in order to discover talented human resources and build a team that, in just a few years, went from competing in the English second division to winning the Premier League title in the 2015/2016 season.
An important milestone in this trajectory was the signing of N'Golo Kanté, who joined Leicester from the French league for a fee of 3.5 million euros.
Following the club's crowning as champions, Kanté was transferred to Chelsea for a significantly higher figure, reaching €35.8 million.
Another notable example is the signing of Riyad Mahrez in 2014 from French second division side Havre Athletic Club for just €750k.
Subsequently, Leicester transferred Mahrez to Manchester City for an impressive €67.8 million.
These examples illustrate how Leicester City used data analytics to make sound transfer decisions, enabling them to identify high-potential players and maximize their value in the transfer market.
These successes underscore the importance of advanced data analytics in today's soccer world.
Other notable examples of recruitment analysis
Another great example of the use of data in soccer is Monchi's work at Sevilla.
He has spoken openly about the team of engineers, physicists and statisticians with whom the club has collaborated to design an algorithm aimed at identifying talented players.
In this regard, there are several significant cases that support this claim, including Ivan Rakitic, Joules Kounde and Diego Carlos.
Arsène Wenger, renowned soccer coach and former manager of Arsenal Football Club, has been an advocate and pioneer in the use of data analytics in soccer.
Wenger is known for his innovative approach and his interest in incorporating new technologies and scientific methods into sport.
During his tenure at Arsenal, Wenger introduced the concept of "scouting" based on data and advanced analytics.
He implemented a comprehensive data collection system covering various aspects of the game, such as player performance, match statistics and tactical analysis.
This data was used to identify emerging talent, evaluate player performance and improve decision making in terms of signings and game strategies.
How can my organization benefit from these models?
Unlike soccer teams, companies in Mexico tend to use traditional methods to recruit talent.
In most cases, candidates must pass a first filter based on a curriculum vitae (CV), which, in many cases, is impersonal, can be manipulated and does not provide a complete description of the candidate's job profile.
This approach neglects the candidate's soft skills, such as ambition, commitment, performance self-management and leadership, among others.
However, it is true that, unlike soccer teams, companies lack detailed information to facilitate decision-making.
However, at Mind Capital we have been inspired by the talent acquisition method of professional sports and have developed a unique algorithm.
This algorithm has the ability to identify candidates that most closely resemble a reference profile, taking into account both technical skills (years of experience, area of expertise, languages, among others) and soft skills (resilience, decision making, proactivity, etc.).
The reference profile can be another employee who successfully performs similar functions or even a profile specifically designed for the position in question.
The algorithm generates a report that allows the candidate to be compared with the ideal profile and includes two numerical indicators that help to assess whether the candidate is more or less similar to the ideal profile.
This provides guidance to the decision maker and complements the process by providing meaningful information.
What does my organization, in human resources, gain from this model?
This tool does not completely replace the recruiting process; instead, it complements the process and eliminates typical recruiting biases, streamlining the process by synthesizing information quickly and concisely.
The major benefit of this model is the reduction of staff turnover.
According to the Huffington Post, losing an employee can represent between 1.5 and 2 times the annualized salary, considering the costs of attracting talent, as well as the loss of knowledge.
Selecting your candidates correctly, knowing in detail the characteristics they can bring to the table, can result in success for your organization, as Leicester City demonstrated in the 2015/2016 season.
In a highly competitive market such as soccer, where strategic decision making can make the difference between success and failure, data analysis has become an essential tool.
Are you aware of the benefits this can generate for your company or organization?
Interested in discovering how data analytics can empower your recruitment and selection processes?
Contact Mind Capital for more information about the product we have developed.
If you are interested in being considered as a candidate in the selection processes that we have open or future, we invite you to leave your data in our form.
Our team will be happy to evaluate your skills and experience for future job opportunities.
Andoni Goicoechea Pederzini
