How Soccer Coaches Can Use Data to Better Develop Their Players and Be More Successful

Introduction: In soccer, coaches try to enhance the performance of their athletes in physical, technical, and tactical aspects. In this context, match data can potentially help to objectively quantify the behavior of the players on the pitch to ultimately optimize training processes and performance. Therefore, this chapter analyzes how coaches in soccer can use data to guide their decision-making processes. Validity and reliability of devices: The match performance of soccer players can be recorded using different systems. In detail, three measurement techniques were predominantly used in soccer: Global Positioning Systems [GPS], Local Positioning Systems [LPS], and multi-camera systems. All three measurement systems reveal satisfactory validity and reliability. However, there exist differences regarding quality criteria between the three systems when capturing in different scenarios. In terms of application in soccer, LPS can be prioritized for data collection. Furthermore, multi-camera systems also outperform GPS in the soccer context. Bearing the differences regarding the application of the systems in mind, all three systems can be used to gain valuable insights into match performance. Physical match performance: The physical match performance of players has been investigated frequently. For example, players run between 10 and 13 km per match while only sprinting 2–3% of this distance. Furthermore, recent research tries to contextualize running performance. Concluding, insights into the physical match performance of players help to (1) manage the current squad and scout players that fit the physical profile, (2) design position-specific drills and performance tests, and (3) build a base for load management. Technical match performance: Similar to physical aspects, technical aspects of the match performance have already been well researched. For example, a professional player possesses the ball 57 times, passes the ball 38 times, and dribbles once per game. Initial attempts already tried to contextualize technical performance variables. Concluding information regarding technical aspects of the soccer game can be used to (1) give coaches instructions on how to build appropriate training drills, (2) provide information on how to rate match performances, and (3) evaluate the technical profiles of individual players and how these players fit the playing style of a club. Tactical match performance: Using data in soccer, tactical match performance can already be quantified objectively. Different models already help to evaluate the offensive passing and shooting behavior of players at a tactical level (e.g., xGoals, D-Def). Recently, there is an increasing interest in defense. For instance, defensive pressure seems to be an insightful performance indicator for defensive play. Concluding, information gained regarding tactical match performance can (1) assist coaches in evaluating tactical performance aspects of single players, player groups, or a whole team and (2) offer opportunities for improvement of pre- or postgame analysis. Conclusion: Overall, the use of data in soccer can help to objectively support decisions, thereby complementing subjective observations. In the future, more and more data will become accessible in professional soccer. Therefore, coaches that find ways to benefit from this development will have a competitive advantage in the future. The coming years will show who is best able to follow this path of data.