With the help of analyses, algorithms for recognizing patterns and trends as well as machine learning, the most promising talents can be filtered out based on the data.
Football clubs use a variety of data sources to gather information on potential talent. In addition to historical performance data from matches or training data, this also includes physiological measurements and even social media. With the help of analyses, algorithms for recognizing patterns and trends as well as machine learning, the most promising talents can be filtered out based on the data. At the same time, a player’s future potential can be assessed by analyzing growth rates in various performance areas, as well as physical development and technical ability. In this way, the best candidates can be selected as new additions to a team or young talents can be promoted. By analyzing statistics, moves, and movement profiles, scouts can also search specifically for players who fit perfectly into the game system or the respective team. In addition, conclusions can also be drawn about mental strengths, team spirit, and leadership qualities – characteristics that are often crucial to a player’s success.