“How Much is that Player in the Window? The One with the Early Birthday?” Relative Age Influences the Value of the Best Soccer Players, but Not the Best Businesspeople

Commentary: “How Much is that Player in the Window? The One with the Early Birthday?” Relative Age Influences the Value of the Best Soccer Players, but Not the Best Businesspeople

“…In line with Furley et al (2016), we agree that any RAE outside of sports deserves closer scrutiny, but unlike Furley et al, we argue that we should not expect to find evidence of RAE for labor market outcomes in the first place, because there is not sufficient evidence of uniform age cut-offs in school .…”

“…To begin, Furley et al (2016) investigate the RAE (data from Poli et al, 2015a), and among the 100 richest billionaires (data from Forbes). Loffing (2016) critiques Furley et al for comparing the soccer players' birthdate distribution to a uniform distribution to find evidence of RAE; this critique should also apply to the analysis on billionaires 1 .…”

“…Furley et al (2016) do not state but implicitly assume that all the businesspeople in their data were educated under the same cut-off date and that this date was January 1st (i.e., the school year equals the calendar year). If such a uniform cut-off existed, it is easy to imagine why it might matter—the maturation gap would mean that the youngest students likely perform worse and/or face lower wellbeing than their older classmates (Bedard and Dhuey, 2006; Schwandt and Wuppermann, 2016) This, it follows, will be mirrored by poor labor market outcomes (Plug, 2001; Black et al, 2011) and wellbeing (Thompson et al, 1999; Matsubayashi and Ueda, 2015).…”

Age-ordered shirt numbering reduces the selection bias associated with the relative age effect

“…Ironically though this may represent a significant failure from the perspective of talent identification, because in the long run, it may be the relatively younger players who are more likely to be successful. Younger children must consistently overcome higher levels of challenge when training against older children, and this can lead to longer term advantages, with latter-born children sometimes found to be more likely to receive a full senior contract (McCarthy & Collins, 2014;McCarthy, Collins, & Court, 2015), less likely to be injured (Wattie et al, 2007) and more likely to earn a higher salary (Ashworth & Heyndels, 2007; though see ;Furley, Memmert, & Weigelt, 2016). Taken together, the over-selection of relatively older children leads not only to a bias against the younger children, but in doing so may also represent a substantial failure in talent identification on the part of sporting teams and organisations.…”

A bioecological perspective on talent identification in junior-elite soccer: A Pan-European perspective

“…All the clubs adopted assessment protocols for measures of functional capacity but combined these with soccer-specific tests for dribbling, ball control, shooting speed and accuracy and perceptualcognitive passing tests in congested areas in an attempt to replicate the decision-making demands of competition. Furthermore, imposed environmental constraints (i.e., a skewed distribution of selecting players born earlier in a predefined age group comparative to those players born later due to an imposed cut-off date), commonly referred to as relative age effects (RAEs; Haycraft, Kovalchik, Pyne, Larkin, & Robertson, 2018) which are known to affect a player's prospect of becoming a full-time professional (Furley, Memmert, & Weigelt, 2016) were understood across all the clubs in this study. We documented pedagogical age group modification strategies similar to those reported by Mann and van Ginneken (2016), where talent scouts were provided with birthdates of players a priori and, in some instances, the decimalisation of players' ages was provided on training vests during real-time scouting assignments.…”