How soccer scouts identify talented players

Scouts of soccer clubs are often the first to identify talented players. However, there is a lack of research on how these scouts assess and predict overall soccer performance. Therefore, we conducted a large-scaled study to examine the process of talent identification among 125 soccer scouts. Through an online self-report questionnaire, scouts were asked about (1) the players’ age at which they can predict players’ soccer performance, (2) the attributes they consider relevant, and (3) the extent to which they predict performance in a structured manner. The most important results are as follows. First, scouts who observed 12-year-old and younger players perceived they could predict at older ages (13.6 years old, on average) whether a player has the potential to become a professional soccer player. This suggests that scouts are aware of the idea that early indicators of later performance are often lacking, yet do advise on selection of players at younger ages. Second, when identifying talented players, scouts considered more easily observable attributes, such as technical attributes. However, scouts described these often in a broad sense rather than in terms of specific predictors of future performance. Finally, scouts reported that they assess attributes of players in a structured manner. Yet, they ultimately based their prediction (i.e. final score) on an intuitive integration of different performance attributes, which is a suboptimal strategy according to existing literature. Taken together, these outcomes provide specific clues to improve the reliability and validity of the scouting process

Data and R code for "Nonergodicity in Load and Recovery: Group Results Do Not Generalize to Individuals"

This environment contains the data and the R code for the purpose of replication, reanalysis, new analysis, and reinterpretation of the study results. The data set "Data" consists of time series across one football season of 84 professional youth players. More detailed information about what kind of data we collected and how can be retrieved from the article