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One of these things is not like the other: Time to differentiate between relative age and biological maturity selection biases in soccer?

Authors:

Abstract

Background: Both maturity and relative age selection biases are entrenched within professional academy soccer programmes. Lay opinion, and that of some scholars, holds that relative age effects exist as a product of advanced biological maturity, that is relatively older players succeed as a consequence of the physical and athletic advantages afforded by earlier maturation. There is, however, a growing body of evidence to suggest that this is not the case, and that relative age and maturation should be considered and treated as independent constructs. Purpose: To avoid a disconnect between contemporary academic evidence and practitioner practice, the aim of this commentary is to provide a discussion of pre-existing and new evidence relating to maturity and relative age selection biases in soccer. It is hoped that this commentary will provide an overview of new insight regarding the differences between the two selection phenomena and enable practitioners who are responsible for the (de)selection of academy soccer players for talent development programmes to make more informed decisions regarding their retention/selection strategies.
Running title: Relative age and maturity bias commentary
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One of these things is not like the other: Time to
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differentiate between relative age and biological maturity
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selection biases in soccer?
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Authors:
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Chris Towlson 1, Calum MacMaster 2 James Parr 3 & Sean Cumming 4
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Affiliations:
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1 Department of Sport, Health and Exercise Science, University of Hull, Hull, UK.
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2 School of Sport and Exercise Science, University of Birmingham, UK
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3 Manchester United Football Club, Manchester, UK
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4 Department for Health, University of Bath, Bath, UK
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For submission to:
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Journal of Science and Medicine in Football (commentary)
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Words count: 1808
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Abstract: 165
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Tables: 0
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Figures: 0
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Running title: Relative age and maturity bias commentary
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ABSTRACT
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Both maturity and relative age selection biases are entrenched within professional academy soccer
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programmes. Lay opinion, and that of some scholars, holds that relative age effects exist as a product
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of advanced biological maturity. That is relatively older players succeed as a consequence of the
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physical and athletic advantages afforded by earlier maturation There is, however, a growing body of
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evidence to suggests that this is not the case, and that relative age and maturation should be considered
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and treated as independent constructs. To avoid a disconnect between contemporary academic evidence
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and practitioner practice, the aim of this commentary is to provide discussion of pre-existing and new
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evidence relating to maturity and relative age selection biases in soccer. It is hoped that this commentary
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will provide an overview of new insight regarding the differences between the two selection phenomena
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and enable practitioners who are responsible for the (de)selection of academy soccer players for talent
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development programmes to make more informed decisions regarding their retention/selection
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strategies.
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Key words: Soccer, relative age effect, maturation, peak height velocity, talent identification
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Running title: Relative age and maturity bias commentary
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Introduction
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To promote ‘home-grown’ talented soccer players, professional soccer clubs and national governing
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bodies have developed long-term player development frameworks to optimise talent (de)selection and
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development strategies 1. To safeguard the sustained effectiveness of such frameworks, it is important
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that talent development systems are free from (sub)conscious, temporary, maturity and relative age-
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related selection bias which threaten the ‘strength of each soccer club’s talent pool of players available
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for domestic and national team selection. Such is the importance of developing successful talent
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development frameworks, there has been a marked increase (⁓314%; n = 323) in soccer specific growth
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and maturity-related peer-reviewed, published research since the conception of the English Premier
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Leagues, Elite Player Performance Plan (EPPP) directive in 2011. Given that the onset of the adolescent
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growth spurt (i.e. peak height velocity [PHV]) is highly individualised2 and the onset and cessation of
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PHV likely occurs at 10.7 to 15.2 years of age 2 3 in male soccer players, much of this research has
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focussed upon the confounding influences of biological maturation and relative age upon talent
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selection and development processes within the youth development phase (i.e. under 11 to 16) of
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academy soccer systems 4-6. Where the influence of maturation timing and status can confound the talent
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selection and player development processes 2 5-9
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Biological maturation
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Biological maturation can be defined as the process and progress of a person achieving a fully mature
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state within the constituent biological systems 10. Variation in maturation results from a combination of
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genetic and environmental factors, and children of the same chronological age can vary by as much as
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five to six years in terms of skeletal age; an established proxy of maturation in youth. Of these systems,
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the maturation of the skeletal system is of relevance to soccer practitioners given that a non-linear
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relationship exists between the growth of skeletally related anthropometric characteristics (e.g., stature
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and body-mass) with decimal age 2 3. The asynchronous relationship between stature development and
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age is caused by the variation in the timing of the onset of PHV 11, eliciting accelerated phases of stature
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growth (approximately +7.5 to 9.7 cm. year-1) across adolescence in male soccer players. Therefore, it
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Running title: Relative age and maturity bias commentary
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is commonplace within chronologically ordered playing age groups which span PHV (e.g., U11 to U15)
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that early maturing players (i.e. post-PHV) will likely be characterised as having temporary
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enhancements in maturity-related anthropometric (i.e. typically stature, mass, lean mass) and/or
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physical fitness characteristics, in comparison to their less mature counterparts (i.e. pre-PHV) 5 6 12. The
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extent to which variation in maturation status impacts technical, tactical, or psychological ability is less
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clear, although emerging evidence suggests that later maturing players must be more advanced in these
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areas if they are to be retained in the academy system 13-17. Such advantages may contribute to the
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misidentification of talent, and over-selection of early maturing soccer players for talent development
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programmes 6 7.
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The Relative Age Effect (RAE)
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The over-representation of academy 4-6 18 and professional 19-22 players born in the first three months
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(quartile[Q]) of the domestic soccer season is referred to as the relative age effect (RAE) 23. This
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phenomenon has been argued to occur within soccer (and other football codes 24-27) due to the
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application of arbitrary and chronologically aged (bi)annual (i.e. 12 or 24 months) groupings (e.g. under
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[U]10, U11, U12 etc.) that do not account for transient, large between-player maturity-related
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differences in anthropometry and physical fitness characteristics 18. A long-held belief in soccer is that
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relatively older players are beneficiaries of advanced maturation 18 23 and, thus, possess superior
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anthropometrical dimensions (stature and weight) and performance characteristics (power, speed,
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strength and endurance) 28-30; resulting in the over-selection of players born in Q1 and Q2 in professional
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academies 4 6 18 31. With the concentration of relatively older players likely becoming strengthened if
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relatively younger players are systematically deselected or drop-out from the development pathway.
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Whereas some studies suggests that U10-U13 players born in Q1 of the soccer season likely possess a
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small anthropometric (e.g., stature and body-mass) and physical (e.g., speed and lower-limb power)
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advantage over their relatively younger counterparts born in Q4 5 32, an equivalent number of studies
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document no such advantages 29 33. The existence of RAEs in non-physical achievement domains also
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challenges this assumption. Despite the persistence of RAE and maturity selection biases in academy
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soccer 5 6 34 35, talent practitioners state that they do not consider enhanced maturity or relative age
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Running title: Relative age and maturity bias commentary
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characteristics as a desirable factor when selecting players for talent development programmes 36. This
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suggests a likely disconnect between knowledge of child development and applied talent selection
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practices.
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New evidence within soccer
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Contrary to the widely held position that maturity-related differences in growth and development are
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the primary contributor to the RAE 37, recent evidence from academy soccer research confounds the
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certainty of this theory 33 38, showing strong evidence to suggest that relatively older, academy soccer
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players are not beneficiaries of advanced maturation. Therefore, we feel such evidence in soccer should
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be brought to the fore and discussed within the context of pre-existing and new evidence so that
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practitioners who are responsible for the (de)selection of academy soccer players for talent development
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programmes can make informed decisions regarding their retention/selection strategies.
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A recent study by Parr, et al. 33 has shown that the effect of both maturation and relative age
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upon physical performance measures in youth soccer players are discrete, highlighting that these
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measures should not be considered mutually influential. This implies that the underpinning mechanisms
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for these selection phenomena in this scenario are separate entities. However, relative age did have a
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weak (R = 0.19 to 0.23) correlation with physical performance measures; that said, it was biological
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maturation which likely acted as the underpinning mechanism for change within these phenotypes
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evidenced by strong (R = 0.75 to 0.71) and significant (P < 0.01) correlation values of the examined
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physical fitness characteristics, with only maximal vertical jump height being significantly (P < 0.05;
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R2 = 0.23) influenced by relative age. It is, therefore, likely, that individual biological development is
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responsible for regulating these physical characteristics. Despite limitations associated with the
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participant group, specifically a small sample size representing Q4 and all players being from the same
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academy setup, the results agree with previous research by Johnson, et al. 38
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The influence of maturation and the onset of relative age upon physical development and
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subsequent talent selection (dis)advantages manifest at different stages of development, with previous
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literature highlighting the onset of a maturational bias emerges concomitantly with the commencement
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of puberty 10 38 39, whilst the existence of the RAE in children as young as six. Studies by Johnson, et al.
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38 and Hill, et al. 8 suggest that maturity selection and relative age bias exist and operate independent of
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one another. Whereas the RAE is present and marked from late childhood and maintained through
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adolescence; the selection bias towards males advanced in maturation emerged with puberty and
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increased in magnitude with age. Further, the study by Hill, et al. 8 suggested little to no association
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between maturation and relative age within age groups. Both of these studies suggest that relative age
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serves as the strongest predictor of player selection at the foundation level (i.e., childhood); whereas
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maturational status is unequivocally a stronger selection factor during adolescence 38. The influence of
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relative age upon player selection with the Johnson, et al. 38 study peaked with players born earliest in
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the selection year being 2.2 times more likely to be selected for development programmes than those
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born in the last months. However, according to Johnson, et al. 38, at the period of greatest influence
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upon talent selection, within the U17 age group, enhanced skeletal age exerted a 20-fold increase in
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likelihood of selection to the elite teams. Despite Johnson, et al. 38 not reporting an underpinning
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explanation for this phenomena, it might be postulated that this is due to temporary, maturity-related
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enhancements in physical fitness and anthropometric characterises often afforded to earlier maturing
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players 33. It was noted by Johnson, et al. 38 that advantages associated with a developed physical profile,
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such as increased speed and strength 6, will only manifest when all players, irrespective of maturational
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tempo and timing, reach full development. By this point, deselected later maturing/developing players
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will have likely been lost from soccer development programmes 39-41. Subsequently, likely
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concentrating the talent pool which domestic soccer clubs and national teams can select from with early
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maturing players, characterised as likely having underdeveloped psychological and technical
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characteristics due to the absence of their regular exposure to challenging experiences to develop such
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traits in comparison to the later maturing counterparts 15. The deselection of later maturing players, in
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favour of those who express their developmental traits earlier in their biological development only
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serves to diminish the available talent from which a club can hope to nurture young future players.
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Take home messages for key stakeholders
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Relative age and maturity clearly confound the physical and talent development processes implemented
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by professional soccer academies 4-6 39 41. These effects do, however, exist and operate independent of
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one another and, as a consequence will likely require separate solutions and will be implemented at
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difference stage of player development. Strategies designed to addresses the impact of biological
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maturation (i.e., bio-banding) 42-46 should be delayed until late childhood and early adolescence (i.e.,
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11-12 years). In contrast, strategies designed to counter the RAE age-ordered (e.g., shirt numbering47,
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birthday banding48 and biological date of birth 4) are best implemented in early-to mid-childhood and
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in advance of entry to the academy system. Similarly, bio-banding should not be discussed as a solution
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49 , or misplaced solution 50, for the RAE. Bio-banding is not designed as a solution for the RAE and,
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thus, would have little to no benefit on this bias. It is equally important that coaches, scouts and
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practitioners also recognise maturation and relative age as separate constructs. It is entirely possible for
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a player to be the oldest yet least mature individual with an age cohort, and vice versa. Those players at
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greatest risk for deselection or under-representation include those who are both relatively young and
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late maturing. We have highlighted in this commentary that since the introduction and implementation
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of national governing body player development frameworks, both practitioner and academic researcher
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knowledge/appetite to understand how the intricacies of maturation and relative age confound player
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development programmes are constantly evolving. To avoid a disconnect between contemporary
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academic evidence and practice, we feel it important for practitioners and researchers to reconsider the
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application of historical, research-informed soccer practices, and readily acknowledge that maturation
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and relative age in soccer should be considered as independent entities. It is hoped that by recognising
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this will contribute to optimising player development and selection initiatives and reduce early and
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unnecessary deselection of players who are either relative younger or later maturing.
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Disclosure statement:
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The authors declare they have no competing interests.
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Running title: Relative age and maturity bias commentary
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References
222
1. The English Premier League. Elite Player Performance Plan, 2011.
223
2. Philippaerts RM, Vaeyens R, Janssens M, et al. The relationship between peak height velocity and
224
physical performance in youth soccer players. J Sports Sci 2006;24(3):221-30. doi:
225
10.1080/02640410500189371 [published Online First: 2005/12/22]
226
3. Towlson C, Cobley S, Parkin G, et al. When does the influence of maturation on anthropometric and
227
physical fitness characteristics increase and subside? Scand J Med Sci Sports 2018;28(8):1946-
228
55. doi: 10.1111/sms.13198 [published Online First: 2018/04/19]
229
4. Helsen WF, Thomis M, Starkes JL, et al. Levelling the playing field: A new proposed method to
230
address relative age and maturity-related bias in soccer. Frontiers in Sports and Active Living
231
- section Movement Science and Sport Psychology 2021;Accepted
232
5. Lovell R, Towlson C, Parkin G, et al. Soccer Player Characteristics in English Lower-League
233
Development Programmes: The Relationships between Relative Age, Maturation,
234
Anthropometry and Physical Fitness. PLoS One 2015;10(9):e0137238. doi:
235
10.1371/journal.pone.0137238 [published Online First: 2015/09/04]
236
6. Towlson C, Cobley S, Midgley AW, et al. Relative Age, Maturation and Physical Biases on Position
237
Allocation in Elite-Youth Soccer. Int J Sports Med 2017;38(3):201-09. doi: 10.1055/s-0042-
238
119029 [published Online First: 2017/02/22]
239
7. Deprez D, Fransen J, Boone J, et al. Characteristics of high-level youth soccer players: variation by
240
playing position. J Sports Sci 2015;33(3):243-54. doi: 10.1080/02640414.2014.934707
241
[published Online First: 2014/07/08]
242
8. Hill M, Scott S, Malina RM, et al. Relative age and maturation selection biases in academy football.
243
J Sports Sci 2020;38(11-12):1359-67. doi: 10.1080/02640414.2019.1649524 [published Online
244
First: 2019/08/02]
245
9. Towlson C, Salter J, Ade JD, et al. Maturity-associated considerations for training load, injury risk,
246
and physical performance within youth soccer: One size does not fit all. J Sport Health Sci 2020
247
doi: 10.1016/j.jshs.2020.09.003 [published Online First: 2020/09/23]
248
Running title: Relative age and maturity bias commentary
9
10. Malina RM, Bouchard C, Bar-Or O. Growth, maturation, and physical activity: Human kinetics
249
2004.
250
11. Malina RM, Coelho ESMJ, Figueiredo AJ, et al. Interrelationships among invasive and non-invasive
251
indicators of biological maturation in adolescent male soccer players. J Sports Sci
252
2012;30(15):1705-17. doi: 10.1080/02640414.2011.639382 [published Online First:
253
2012/02/07]
254
12. Carling C, le Gall F, Reilly T, et al. Do anthropometric and fitness characteristics vary according to
255
birth date distribution in elite youth academy soccer players? Scand J Med Sci Sports
256
2009;19(1):3-9. doi: 10.1111/j.1600-0838.2008.00867.x [published Online First: 2008/11/13]
257
13. Borges PH, Cumming S, Ronque ERV, et al. Relationship Between Tactical Performance, Somatic
258
Maturity and Functional Capabilities in Young Soccer Players. Journal of human kinetics
259
2018;64:160-69. doi: 10.1515/hukin-2017-0190
260
14. Towlson C, MacMaster C, Gonçalves B, et al. The effect of bio-banding on technical and tactical
261
indicators of talent identification in academy soccer players. Jornal of Science and Medicine in
262
Football 2021;Under review
263
15. Cumming SP, Searle C, Hemsley JK, et al. Biological maturation, relative age and self-regulation
264
in male professional academy soccer players: A test of the underdog hypothesis. Psychology of
265
Sport and Exercise 2018;39:147-53.
266
16. Zuber C, Zibung M, Conzelmann A. Holistic Patterns as an Instrument for Predicting the
267
Performance of Promising Young Soccer Players - A 3-Years Longitudinal Study. Front
268
Psychol 2016;7:1088. doi: 10.3389/fpsyg.2016.01088 [published Online First: 2016/08/12]
269
17. Saward C, Morris JG, Nevill ME, et al. The effect of playing status, maturity status, and playing
270
position on the development of match skills in elite youth football players aged 1118 years: A
271
mixed-longitudinal study. European Journal of Sport Science 2019;19(3):315-26. doi:
272
10.1080/17461391.2018.1508502
273
18. Helsen WF, Van Winckel J, Williams AM. The relative age effect in youth soccer across Europe. J
274
Sports Sci 2005;23(6):629-36.
275
Running title: Relative age and maturity bias commentary
10
19. Yagüe JM, Molinero O, Alba J, et al. Evidence for the Relative Age Effect in the Spanish
276
Professional Soccer League. J Hum Kinet 2020;73:209-18. doi: 10.2478/hukin-2019-0145
277
[published Online First: 2020/08/11]
278
20. Bezuglov EN, Nikolaidis PT, Khaitin V, et al. Prevalence of Relative Age Effect in Russian Soccer:
279
The Role of Chronological Age and Performance. Int J Environ Res Public Health 2019;16(21)
280
doi: 10.3390/ijerph16214055 [published Online First: 2019/10/28]
281
21. Rađa A, Padulo J, Jelaska I, et al. Relative age effect and second-tiers: No second chance for later-
282
born players. PLoS One 2018;13(8):e0201795. doi: 10.1371/journal.pone.0201795 [published
283
Online First: 2018/08/09]
284
22. Mujika I, Vaeyens R, Matthys SP, et al. The relative age effect in a professional football club setting.
285
Journal of sports sciences 2009;27(11):1153-58.
286
23. Cobley SP, Baker J, Wattie N, et al. Annual age-grouping and athlete development. Sports Medicine
287
2009;39(3):235-56.
288
24. Till K, Cobley S, Wattie N, et al. The prevalence, influential factors and mechanisms of relative age
289
effects in UK Rugby League. Scand J Med Sci Sports 2010;20(2):320-9. doi: 10.1111/j.1600-
290
0838.2009.00884.x [published Online First: 2009/06/03]
291
25. Lewis J, Morgan K, Cooper S-M. Relative age effects in Welsh age grade rugby union. International
292
Journal of Sports Science & Coaching 2015;10(5):797-813.
293
26. Tribolet R, Watsford ML, Coutts AJ, et al. From entry to elite: The relative age effect in the
294
Australian football talent pathway. J Sci Med Sport 2019;22(6):741-45. doi:
295
10.1016/j.jsams.2018.12.014 [published Online First: 2019/01/02]
296
27. Physical performance profile of sub-elite juvenile Gaelic Games players and the prevalence of a
297
Relative Age Effect (RAE). Proceedings of The Physiological Society; 2012. The Physiological
298
Society.
299
28. Vaeyens R, Malina RM, Janssens M, et al. A multidisciplinary selection model for youth soccer:
300
the Ghent Youth Soccer Project. Br J Sports Med 2006;40(11):928-34.
301
Running title: Relative age and maturity bias commentary
11
29. Carling C, Le Gall F, Reilly T, et al. Do anthropometric and fitness characteristics vary according
302
to birth date distribution in elite youth academy soccer players? Scandinavian Journal of
303
Medicine & Science in Sports 2009;19(1):3-9.
304
30. Carling C, Le Gall F, Malina RM. Body size, skeletal maturity, and functional characteristics of
305
elite academy soccer players on entry between 1992 and 2003. J Sports Sci
306
2012;7(30(15)):1683-93.
307
31. Helsen WF, Baker J, Michiels S, et al. The relative age effect in European professional soccer: Did
308
ten years of research make any difference? Journal of sports sciences 2012;30(15):1665-71.
309
32. Deprez D, Coutts AJ, Fransen J, et al. Relative age, biological maturation and anaerobic
310
characteristics in elite youth soccer players. Int J Sports Med 2013;34(10):897-903. doi:
311
10.1055/s-0032-1333262 [published Online First: 2013/05/24]
312
33. Parr J, Winwood K, Hodson-Tole E, et al. The Main and Interactive Effects of Biological Maturity
313
and Relative Age on Physical Performance in Elite Youth Soccer Players. Journal of Sports
314
Medicine 2020;2020:1957636. doi: 10.1155/2020/1957636
315
34. Helsen WF, Thomis M, Starkes JL, et al. Leveling the Playing Field: A New Proposed Method to
316
Address Relative Age- and Maturity-Related Bias in Soccer. Frontiers in Sports and Active
317
Living 2021;3(24) doi: 10.3389/fspor.2021.635379
318
35. Skorski S, Skorski S, Faude O, et al. The Relative Age Effect in Elite German Youth Soccer:
319
Implications for a Successful Career. 2016;11(3):370. doi: 10.1123/ijspp.2015-0071
320
10.1123/ijspp.2015-0071
321
36. Towlson C, Cope E, Perry JL, et al. Practitioners’ multi-disciplinary perspectives of soccer talent
322
according to phase of development and playing position. International Journal of Sports
323
Science & Coaching 2019;14(4):528-40. doi: 10.1177/1747954119845061
324
37. Cobley S, Baker J, Wattie N, et al. Annual age-grouping and athlete development. Sports medicine
325
2009;39(3):235-56.
326
38. Johnson A, Farooq A, Whiteley R. Skeletal maturation status is more strongly associated with
327
academy selection than birth quarter. Science and Medicine in Football 2017;1(2):157-63. doi:
328
10.1080/24733938.2017.1283434
329
Running title: Relative age and maturity bias commentary
12
39. Malina RM, Rogol AD, Cumming SP, et al. Biological maturation of youth athletes: assessment
330
and implications. Br J Sports Med 2015;49(13):852-9. doi: 10.1136/bjsports-2015-094623
331
[published Online First: 2015/06/19]
332
40. Meylan C, Cronin J, Oliver J, et al. Talent Identification in Soccer: The Role of Maturity Status on
333
Physical, Physiological and Technical Characteristics. International Journal of Sports Science
334
& Coaching 2010;5(4):571-92. doi: 10.1260/1747-9541.5.4.571
335
41. Hill M, Scott S, McGee D, et al. Are relative age and biological ages associated with coaches’
336
evaluations of match performance in male academy soccer players? International Journal of
337
Sports Science & Coaching 2020:1747954120966886. doi: 10.1177/1747954120966886
338
42. Towlson C, MacMaster C, Gonçalves B, et al. The effect of bio-banding on physical and
339
psychological indicators of talent identification in academy soccer players. Science and
340
Medicine in Football 2020:1-13. doi: 10.1080/24733938.2020.1862419
341
43. Abbott W, Williams S, Brickley G, et al. Effects of Bio-Banding upon Physical and Technical
342
Performance during Soccer Competition: A Preliminary Analysis. Journal of Sports 2019;7(8)
343
doi: 10.3390/sports7080193 [published Online First: 2019/08/17]
344
44. Romann M, Lüdin D, Born D-P. Bio-banding in junior soccer players: a pilot study. BMC Research
345
Notes 2020;13(1):240. doi: 10.1186/s13104-020-05083-5
346
45. Bradley B, Johnson D, Hill M, et al. Bio-banding in academy football: player's perceptions of a
347
maturity matched tournament. Ann Hum Biol 2019;46(5):400-08. doi:
348
10.1080/03014460.2019.1640284 [published Online First: 2019/07/11]
349
46. Cumming SP, Brown DJ, Mitchell S, et al. Premier League academy soccer players' experiences of
350
competing in a tournament bio-banded for biological maturation. Journal Sports Science
351
2018;36(7):757-65. doi: 10.1080/02640414.2017.1340656 [published Online First:
352
2017/06/20]
353
47. Mann DL, van Ginneken PJ. Age-ordered shirt numbering reduces the selection bias associated with
354
the relative age effect. J Sports Sci 2017;35(8):784-90. doi: 10.1080/02640414.2016.1189588
355
[published Online First: 2016/05/31]
356
Running title: Relative age and maturity bias commentary
13
48. Kelly AL, Jackson DT, Taylor JJ, et al. " Birthday-banding" as a strategy to moderate the relative
357
age effect: A case study into the England Squash Talent Pathway. Frontiers in Sports and Active
358
Living 2020;2:145.
359
49. Till K, Baker J. Challenges and [possible] solutions to optimizing talent identification and
360
development in sport. Frontiers in psychology 2020;11
361
50. Collins D, MacNamara A. Talent development: a practitioner guide: Routledge 2017.
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... The age distribution of our study population showed a clear RAE for the overall dataset. Relative age and maturity selection bias can both confound academy soccer talent selection and development strategies (6,48). Relatively old children within chronological annual age categories are more likely to be selected in talent development teams, with selection accompanied by additional training, and access to higher quality coaching with better opponents, likely leading to accumulated performance advantages (4,6,9,19,24). ...
... We remarked a nearly threefold overrepresentation for youth players born in the first quartile of the selection year as well as a clear underrepresentation of players born in the last quartile in our study. All this happens in spite of the fact that, maturational effects may result in large development inequalities between chronological and biological age (48). This is particularly true throughout puberty. ...
... That may be an explanation for why no differences in median scores were observed in this study for personality constructs like self-development and managing emotions (Tables 1, 2). Rather, it can be suggested that relative age and maturity selection biases exist and operate independently in elite soccer academies (48). ...
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Introduction Youth soccer academies are challenged with the constant recruitment process of young talented players to select those who will achieve long-term success as an athlete. Youth soccer academies strive to enhance the physical and technical skill development as well as personality development of talented players because psychological characteristics play a crucial role in players’ future success in their transition to professional soccer. The least mature players and relatively young players may have a greater need to possess superior technical/tactical or psycho-behavioral skills than those relatively older counterparts because of the higher selection rates of early maturing players. Due to RAEs, a significant decrease in the overall quality of professional soccer teams might be observed because of the loss of talent of physically smaller, but psychologically stronger and more versatile relatively young players who possess proper technical and tactical attributes at an early age. The first objective of this study was to examine any possible relationship between RAE and personality constructs. A second objective was to identify factors and effects that can help in the further improvement of talent selection and equal opportunities for elite youth soccer players based on their underlying RAE. The third objective was to consider the impact of RAE on long-term career development. Methods In this retrospective observational study, 151 elite youth soccer players between 15 and 18 years of age were first grouped in birth quartiles. Personality constructs were then assessed, using a combination of observations, interviews, and a self-assessment questionnaire. Next competition level after 8 years was evaluated to identify RAEs, differences in personality characteristics and opportunities to reach professional soccer player status between relatively older vs. younger players. Results A clear significant RAE was observed for the whole database (Q1 = 38.4% vs. Q4 = 13.9%) with OR of 2.61 ( χ ² = 19.46, p < 0.01, r = −0.85). Relatively young players had higher median scores on personality constructs such as self-confidence ( p = 0.04), while relatively old players had higher median scores on personality constructs such as team orientation ( p = 0.03). In the long term, more players of the youngest birth quartile were signed as professional players (76.2%), compared with relatively old players (46.6%). 65.0% of the 20 players had the highest total score on personality constructs developed as a professional soccer player, vs. 35.0% of the 20 players with the lowest scores. Discussion In conclusion, this study showed not only further evidence of the RAE but also provided evidence supporting “the underdog hypothesis” in national elite youth teams. Relatively young players were also more likely to get higher value senior professional contracts in the long term. We propose that this may be due to the relatively young players developing superior psychological skills and technical expertise to compensate for their early physical disadvantage. This in turn suggests the need for greater awareness of the importance of personality constructs in the future development of youth elite soccer players. Therefore, the crux of the issue is how youth soccer academies elicit the “best of both worlds” ie. moderating RAE whilst also gaining the benefits of the underdog hypothesis by creating the right environment for every player to develop to their full potential in elite youth soccer academies.
... The emergence of the selection bias in terms of biological maturation operates independently from relative age. 11,12 Recent evidence from talent research in soccer suggests that relatively older (academy) soccer players are not beneficiaries of advanced maturation. 12 Indeed, maturation biases and those by RAE do not emerge at the same age. ...
... 11,12 Recent evidence from talent research in soccer suggests that relatively older (academy) soccer players are not beneficiaries of advanced maturation. 12 Indeed, maturation biases and those by RAE do not emerge at the same age. Johnson et al. 13 point out that individual variation in maturity status has a higher impact than the RAE when selecting players. ...
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The importance of considering information related to athletes’ biological maturation within talent identification and development processes is frequently emphasized by both sport scientists and practitioners. Although there is evidence for the use of objective diagnostics for assessing biological maturation, little is known about its subjective determinations by coaches. Such approaches are particularly relevant when scientific support is limited. Therefore, the current study aimed to compare a practical subjective approach (coaches’ eye) to assess biological maturity timing (BMT) with objective reference diagnostics (MRI). For this purpose, data were collected from 63 male elite soccer players of the U12 and U14 age group who were part of the German talent promotion program. Players’ BMT (i.e., skeletal – chronological age) was assessed by MRI and a subjective rating of two coaches. Data analyses revealed high-rank correlations ( r s = .55; p < .001) for the total sample as well as for U14 players ( r s = .65; p < .001) and moderate rank correlations for U12 players ( r s = .42; p < .05). Single case analyses showed substantial agreements between the diagnostics. However, particularly for U12 players, judgements did not always correspond with the MRI rankings. Although coaches seem to have the ability for recognizing the earliest and latest maturing players in the sample, inconsistencies exist in single cases, especially for players that were identified on-time by objective MRI diagnostics. Although utilizing subjective coach assessments as an alone-standing tool to assess a player's BMT is not recommended in applied practice, its use can be beneficial when applied in addition to common objective diagnostics or in circumstances where objective data are not available.
... For the same reasons, it is possible that this study was unable to show age and developmental differences in terms of shooting accuracy. This also contradicts findings of other studies [13,29,30]. Given that there are no detectable effects, no conclusions can be drawn about the differences between the age and development effects that Towlson et al. [29] confirm. ...
... This also contradicts findings of other studies [13,29,30]. Given that there are no detectable effects, no conclusions can be drawn about the differences between the age and development effects that Towlson et al. [29] confirm. ...
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Due to poor results, the German talent identification and development of the German soccer association DFB no longer performs a shooting test since a few years. The aim of this study was to create and validate a new soccer shooting test that allows valid conclusions to be drawn from the shooting quality of youth soccer players about their overall soccer skills. The shooting test was performed with a total of 57 male club players (age: 15.24 ± 0.864 years) from four different teams from the first, second, fifth, and the seventh division of the respective age group (under 15-year-olds until under 17-year-olds). Each subject took one shot at maximum shot speed and eight target shots, measuring accuracy and the shot speed. A multivariable linear regression analysis with forward selection revealed significant values for the variables average shot speed nondominant leg (p < 0.001) and total score (p = 0.004; accuracy × speed of every target shot). Based on these two variables, the soccer skills could be derived from the shooting skills of the adolescents in 57.4% of the cases. The study shows the importance of a good technique with the nondominant leg and of the ability to shoot accurately as well as fast simultaneously.
... It is revealed that the broad topic of TID is a vibrant area of research, ranging from a large number of books, systematic reviews, 2018, narrative reviews, and empirical papers published in the last 20 years. 55 The sub-themes in this area are predictors for selection of the youth players, 56 relative age effect, 57 biological maturity, 58 and methodological issues. 7 The studies in cluster 2 are relatively comprehensive, as the most centralized betweenness words are in this cluster, such as soccer, football, and youth. ...
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In recent years, there has been an increase in the scientific production of youth soccer. However, a panoramic map of research on this subject does not exist. The aim of this study was to identify global research trends in youth soccer over time, among the main levels of analysis: sources, authors, documents, and keywords. The bibliometric software Biblioshiny was used to analyze 2606 articles in Web of Science (WoS) published between 2012 and 2021. The main conclusion is that US and UK scholars dominate the research; the topics of research are changing with the real needs, and research on the topic of performance has been of interest to scholars; talent identification and development, performance, injury prevention, and concussion are the studies of interest to scholars in this area. This finding, which offers a global picture of youth soccer research over time, can help future research in this or similar domains.
... As TI research matures, open debates continue to represent challenges to progress in TI. TI researchers' fixation with age and maturation for identification across the fields of sports, psychology, and education has implications for individual physical and mental health (Matthews and Rhodes, 2020;Bilgiç and Işın, 2022;Towlson et al., 2022). Such challenges call for urgent action on revising the goals of TI according to some authors. ...
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This paper describes the general status, trends, and evolution of research on talent identification across multiple fields globally over the last 80 years. Using Scopus and Web of Science databases, we explored patterns of productivity, collaboration, and knowledge structures in talent identification (TI) research. Bibliometric analysis of 2,502 documents revealed talent identification research is concentrated in the fields of management, business, and leadership (~37%), sports and sports science (~20%), and education, psychology, and STEM (~23%). Whereas research in management and sports science has occurred independently, research in psychology and education has created a bridge for the pollination of ideas across fields. Thematic evolution analysis indicates that TI has well developed motor and basic research themes focused on assessment, cognitive abilities, fitness, and youth characteristics. Motor themes in management and sports science bring attention to talent management beyond TI. Emerging research focuses on equity and diversity as well as innovation in identification and technology-based selection methods. Our paper contributes to the development of the body of TI research by (a) highlighting the role of TI across multiple disciplines, (b) determining the most impactful sources and authors in TI research, and (c) tracing the evolution of TI research which identifies gaps and future opportunities for exploring and developing TI research and its broader implications for other areas of research and society.
... However, most arguments posited against biobanding misrepresent or fail to understand its purpose and practice, and the fundamental principles of auxology. Proponents of the 'talent needs trauma' expression [60], for example, describe bio-banding as a 'misplaced solution for the relative age effect (over representation of players being born in the first quarter of the selection year [61,62])', failing to recognise that maturation and relative age are independent constructs that exist and operate independently (see Towlson, MacMaster [21]). Simply put, bio-banding is not designed to address the relative age effect. ...
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The primary aims of this study were to examine the application of maturity status bio-banding within professional soccer academy programmes and understand the methods employed, the intended objectives, and the potential barriers to bio-banding. Using a mixed method design, twenty-five professional soccer academy practitioners completed an online survey designed to examine their perceptions of the influence of maturation on practice, their perceptions and application of bio-banding, and the perceived barriers to the implementation of this method. Frequency and percentages of responses for individual items were calculated. In the next phase of the study, seven participants who had experience with, or knowledge of, the bio-banding process within an academy youth soccer setting were recruited to complete a semi-structured interview. Interview data was transcribed and analysed using a combination of deductive and inductive approaches to identify key themes. The main findings across the two phases of the study were that [1] there is consensus among the practitioners that the individual effect of maturation impacts their ability to accurately assess the soccer competencies, [2] the majority (80%) of the sample had implemented bio-banding, with practitioners showing a clear preference for using the Khamis and Roche method to bio-band players, with the greatest perceived benefit being during maturity-matched formats, specifically for late or post-PHV players, [3] Practitioners perceived that bio-banding enhances their ability to assess academy soccer players, and [4] practitioners who have used bio-banding believe that the method is an effective way of enhancing the perception of challenge thereby providing a number of psycho-social benefits. Findings suggest that a collaborative and multi-disciplinary approach is required to enhance the likelihood of bio-banding being successfully implemented within the typical training schedules across the adolescent phase of the player development pathway.
... Indeed, we may find players with a different maturational state within the same chronological age group. Some studies have shown maturational differences of 5-6 chronological years between subjects of the same age group [38,39], being early maturing players taller and heavier than their later maturing peers [12,36,40], and with physical advantages that can lead to greater motor and sports performance [41][42][43]. ...
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This study aimed to explore the relevance of the relative age effect (RAE), maturity status and anthropometry, and their influence on coaches' assessment of players' performance, analyzing both genders and different types of academies (elite vs. non-elite). The sample included 603 soccer players (385 male), from the under 12 (U12), under 14 (U14) and under 16 (U16) categories, belonging to elite and nonelite teams. Coaches' assessment of players´ performance, chronological age, anthropometric characteristics, maturity offset (MO) and peak height velocity (PHV) were registered. Our results showed that RAE was present in both genders within the elite, but not in the nonelite academies. Early maturity players were overrepresented in the male elite, but not in the female academies. No relationship was found between RAE and anthropometry in male elite academies. Male elite players showed better anthropometric characteristics than nonelite players, while this pattern of results was not found for female players. The coaches´ assessment on players´ current performance was not influenced by the chronological age nor anthropometry, but it was linked to the PHV. Coaches from nonelite academies rated better in current assessment of performance the taller players. Our findings suggest that maturity status and RAE play an independent and important role in the talent selection process.
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Background: Age differences between athletes born in the same year, as well as an over-representation of older players, are known as the Relative Age Effect (RAE). It is one of the best indicators for choosing players at academy level. Players born at the beginning of the selection year have a physical and anthropometric advantage over their younger peers. Due to sport performance and economic importance, experts keep looking for new prediction variables for talent identification goals in elite soccer academies. Purpose: To correlate anthropometric, strength and power variables with the relative age (RA) of players in an elite academy of a Spanish soccer club. Methods: All players (n= 366) from an elite soccer academy volunteered to participate in the study. The players were grouped into age categories from U10 to U23. A set of anthropometric, strength and power variables were analyzed in order to find correlations with players’ RA and the level of the teams in which players played in each age category. Results. There was a significant correlation between the RA of the players and the level of the team in which they played in each age category (p< 0.001; r> 0.41) but no correlation between trimester of birth and level of the team (p> 0.062; CC> 0.28). We found significant correlations between the players’ physical capacities, anthropometry, RA and the level of the team in which they played for the same age category, mainly from U16 to U10. U23 did not show any correlation between RA and physical or anthropometric variables (p> 0.093; r> 0.21.). Conclusion: coaches should be cautious of choosing players based only on anthropometric or physical attributes as they mature and loose this advantage, making technical ability the most important aspect in success.
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Current trends in attacking strategies and increases in external workload have led to a need for fast and well-conditioned athletes in modern soccer. More recently, progressions in speed, coordination, power and endurance were found over a decade in elite Austrian youth players. However, possible confounders such as relative age, maturation, learning effects, and academy philosophy may have influenced these changes. The present study aimed to determine the decade effect on fitness under statistical control of players' exact age, height, body mass, test location as well as total number of pretests and time interval between test and pretest. Players annually completed a battery of anthropometric, general and soccer-specific fitness tests. MANCOVA was calculated to identify the overall impacts of the covariates on fitness. To balance the covariates of initially 2,530 “former” (2002 to 2005) and 2,611 “recent” (2012 to 2015) players, 1:1 nearest neighbor propensity score (PS) matching was used, resulting in 587 U13, 573 U14, 475 U15, 325 U16, 262 U17, and 129 U18 matched pairs. The decade effect on fitness was assessed by independent t -tests and Cohen's d separately at each age group. Superior performances of recent players were found for linear sprint across all age categories ( d = 0.154–0.476) as well as for agility ( d = 0.125–0.340) and change-of-direction speed ( d = 0.172–0.466) in U15 to U18. Reaction speed increased in U13 ( d = 0.288) and U15 ( d = 0.310). Flexibility reduced over the decade in all age categories ( d = −0.151 to −0.589) and upper-limb power decreased ( d = −0.278 to −0.347) in U13 and U14. Balancing the covariate distribution via PS matching generally confirmed previous findings, with fitness decade effects reflecting the athletic needs for modern soccer. Since fitness performance changed over time, reference values should be periodically updated. Coaches favor both physical and cognitive fast players nowadays. Thus, training should target all aspects of speed, without disregarding flexibility, upper-limb power and other preventive strategies that keep the players on the pitch.
Article
The aim of the study was to examine the birth quartile and maturity status distributions of male academy cricketers. Participants included two hundred and thirteen junior cricket players, aged between 9 and 18 years. Players were separated into birth quartiles, and also grouped as early, average, or late maturers. For the whole cohort, there was a medium effect bias towards players born in BQ1, but the number of early, average, and late maturers was as expected. However, there were significantly more early maturers in the U10 and U11 groups than expected, and maturity distributions of the BQ groups showed there was a small effect size bias towards early maturers in BQ4. Selection biases towards cricketers who are born earlier in the competitive year are consistent from U9 to U16, but more prevalent in U12 and U14 age groups. There is a bias towards early maturers at U10 and U11, but this reduces as age increases. Practitioners working in academy pathways should be encouraged to assess maturity status of players to assist in the retention and progression of players. The relative age effect should also be considered, and strategies may be required to identify players born later in the year.
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Despite various solutions proposed to solve the Relative Age Effect (RAE), it is still a major problem confounding talent identification and selection processes. In a first phase, we sampled 302 under 7 to 21 academy soccer players from two Belgian professional soccer clubs to explore the potential of a new approach to solve the inequalities resulting from relative age and maturity-related bias. This approach allocates players into four discrete quartile groups based on the midway point of their chronological and estimated developmental (ED) birth dates (calculated using the growth curves for stature of Belgian youth). Using Chi Square analyses, a RAE was found (p < 0.01) for the overall sample (Q1 = 41.4% vs Q4 = 14.9%) that completely disappeared after reallocation (Q1 26.5%; Q2 21.9%; Q3 27.5%; Q4 24.2%). According to the new allocation method, the stature difference was reduced, on average, by 11.6 cm (from 24.0 cm ±9.9 to 12.4 cm ±3.4, d = 1.57). Body mass difference between the two methods was 1.9 kg (20.1 kg ±11.3 to 18.2 kg ±13.1, respectively, d = 0.15). The new method created a maximum chronological age difference of 1.9 y versus 0.8 years for the current method. Using this method, 47% of the players would be reallocated. Twenty-three percent would be moved up one age category and 21% would be moved down. In a second phase, we also examined 80 UK academy soccer players to explore if reallocating players reduces the within-playing group variation of somatic and physical fitness characteristics. The percentage coefficient of variation (%CV) was reduced (0.2% to 10.1%) in 15 out of 20 metrics across U11 to U16 age categories, with the U13 age category demonstrating the largest reductions (0.9% to 10.1%) in CV. The U12 and U13 age categories and associated reallocation groupings showed trivial to small (ES = 0.0 to 0.5) between method differences and trivial to moderate (ES = 0.0 to 1.1) differences within the U14 to U16 age categories. A reduction in RAE may lead to fewer dropouts and thus a larger player pool, which benefits, in turn, talent identification, selection and development.
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The relative age effect (RAE) is almost pervasive throughout youth sports, whereby relatively older athletes are consistently overrepresented compared to their relatively younger peers. Although researchers regularly cite the need for sports programs to incorporate strategies to moderate the RAE, organizational structures often continue to adopt a one-dimensional (bi)annual-age group approach. In an effort to combat this issue, England Squash implemented a "birthday-banding" strategy in its talent pathway, whereby young athletes move up to their next age group on their birthday, with the aim to remove particular selection time points and fixed chronological bandings. Thus, the purpose of this study was to examine the potential effects of the birthday-banding strategy on birth quarter (BQ) distributions throughout the England Squash talent pathway. Three mixed-gender groups were populated and analyzed: (a) ASPIRE athletes (n = 250), (b) Development and Potential athletes (n = 52), and (c) Senior team and Academy athletes (n = 26). Chi-square analysis and odds ratios were used to test BQ distributions against national norms and between quartiles, respectively. Results reveal no significant difference between BQ distributions within all three groups (P > 0.05). In contrast to most studies examining the RAE within athlete development settings, there appears to be no RAE throughout the England Squash talent pathway. These findings suggest that the birthday-banding strategy may be a useful tool to moderate RAE in youth sports.
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The aim of this study was to examine the effect of bio-banding on indicators of talent identification in academy soccer players. Seventy-two 11 to 14-year-old soccer players were bio-banded using percentage of estimated adult stature attainment (week 1), maturity-offset (week 2) or a mixed-maturity method (week 3). Players contested five maturity (mis)matched small-sided games with physical and psychological determinants measured. Data were analysed using a series of Bayesian hierarchical models, fitted with different response distributions and different random and fixed effect structures. Few between-maturity differences existed for physical measures. Pre-peak height velocity (PHV) and post-PHV players differed in PlayerLoadTM (anterior-posterior and medial-lateral) having effect sizes above our criterion value. Estimated adult stature attainment explained more of the variance in eight of the physical variables and showed the greatest individual differences between maturity groups across all psychological variables. Pre-PHV and post-PHV players differed in positive attitude, confidence, competitiveness, total psychological score (effect sizes = 0.43-0.69), and session rating of perceived exertion. The maturity-offset method outperformed the estimated adult stature attainment method in all psychological variables. Maturity-matched bio-banding had limited effect on physical variables across all players while enhancing a number of psychological variables considered key for talent identification in pre-PHV players. Keywords: maturation; bio-banding; soccer; talent identification; psychological; physical;
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Talent identification and selection in soccer has been shown to be confounded by individual differences in relative age and biological maturation. Limited research has however, investigated whether these effects are reflected in coaches’ evaluations of performance. This study investigated relative and biological age associated differences in coach perceptions of performance in a professional soccer academy across four seasons. The performances of 279 male players were evaluated on a 4-point Likert-scale. Multi-level modelling was used to examine predictive relationships between biological age, chronological age, result and opposition of game, on match grades. Result of the games was a statistically significant predictor of players perceived performance in every age-group; category of opposition was only significant in the under 13 and 14 age-groups. Biological age significantly predicted players perceived performance grades in the under 10, 14 and 15 age-groups, whereby advanced maturity predicted a higher grade. Across all age-groups, a relative age effect was observed, however age half was not a significant predictor of perceived performance grade in any age-group. Coaches evaluations of match performance appear to vary in accordance with maturity, opposition, and result of game. Academy staff should recognise and account for individual differences in biological maturation when retaining and releasing players.
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Background Biological maturation can be defined as the timing and tempo of progress to achieving a mature state. The estimation of age of peak height velocity (PHV) or percentage of final estimated adult stature attainment (%EASA) is typically used to inform the training process in young athletes. In youth soccer, maturity-related changes in anthropometric and physical fitness characteristics are diverse among individuals, particularly around PHV. During this time, players are also at an increased risk of sustaining an overuse or growth-related injury. As a result, the implementation of training interventions can be challenging. The purpose of this review was to (1) highlight and discuss many of the methods that can be used to estimate maturation in the applied setting and (2) discuss the implications of manipulating training load around PHV on physical development and injury risk. Methods We have provided key stakeholders with a practical online tool for estimating player maturation status (see Online Supplementary Maturity Estimation Tools). Results Whilst estimating maturity using predictive equations is useful in guiding the training process, practitioners should be aware of its limitations. Conclusions To increase the accuracy and usefulness of data, it is also vital that sports scientists implement reliable testing protocols at predetermined time-points.
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The main and interactive effect of biological maturity and relative age upon physical performance in adolescent male soccer players was considered. Consistent with previous research, it was hypothesised that participants of greater maturity or born earlier in the selection year would perform better in terms of physical performance tests. This cross-sectional study consisted of 84 male participants aged between 11.3 and 16.2 years from a professional soccer academy in the English Premier League. Date of birth, height, weight, and parental height were collected. Sprint, change of direction, countermovement jump, and reactive strength index were considered for physical performance. Relative age was based on the birth quarter for the selection year. Maturity status was based upon the percentage of predicted adult height attained. Linear regression models highlighted that maturation was associated with performance on all but one of the physical performance tests, the reactive strength index. In contrast, relative age only served as a significant predictor of performance on the countermovement jump. This study indicated that physical performance (in the tests studied) seems to be related to the biological maturity status of a player but not their relative age. This finding is important because it suggests that early-maturing players perform better in the majority of physical performance tests, and the commonly held belief that relative age effect influences performance may be overstated.
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Objective: Bio-banding (BB) has been introduced to account for varying maturity and to improve the talent development of junior soccer players. To date, research that investigated the physiological and technical effects of BB is sparse. Therefore, the aim of the study was to compare effects of BB with CA on selected technical and tactical parameters in U13 and U14 soccer players. Results: BB significantly increased the number of duels (p = 0.024) and set pieces (p = 0.025) compared to chronological age. The mean time of ball possession per action was reduced (p = 0.021) and the rate of successful passes was lower with BB (p = 0.001). Meanwhile, the total number of passes was unaffected (p = 0.796), and there was a trend towards a lower difference in ball possession between BB teams (p = 0.058). In addition, BB reduced the distances covered while jogging (p = 0.001), running (p = 0.038) and high-speed running (p = 0.035). With BB, an increased number of duels, unsuccessful passes and set pieces resulted in a quicker change of match play situations between teams. While physical demand was reduced, BB seems to result in a more technically and tactically challenging game. Benefits in long-term player development, however, require further investigation.
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The modern-day landscape of Olympic and Professional sport is arguably more competitive than ever. One consequence of this is the increased focus on identifying and developing early athletic talent. In this paper, we highlight key challenges associated with talent (athlete) identification and development and propose possible solutions that could be considered by research and practice. The first challenge focuses on clarifying the purposes of talent identification initiatives such as defining what talent is and how its meaning might evolve over time. Challenge two centers on ways to best identify, select and develop talent, including issues with different approaches to identification, the need to understand the impact of development and the need to have appropriate resourcing in the system to support continued development of knowledge. Finally, we discuss two challenges in relation to the ‘healthiness’ of talent identification and development. The first examines whether a talent identification and development system is ‘healthy’ for athletes while the second focuses on how sport stakeholders could discourage the apparent trend toward early specialization in youth sport settings. Whilst this paper discusses the research in relation to these challenges, we propose multiple possible solutions that researchers and practitioners could consider for optimizing their approach to talent identification and development. In summary, talent is a complex and largely misunderstood phenomenon lacking robust research evidence, and given concerns that it is potentially unhealthy, talent identification and selection at younger ages is not recommended.
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This study assessed the contribution of relative age, anthropometry, maturation, and physical fitness characteristics on soccer playing position (goalkeeper [GK], central-defender [CD], lateral-defender [LD], central-midfield [CM], lateral-midfielder [LM], and forward [FWD]) for 465 elite-youth players (U13-U18`s). U13-14 CD were relatively older than LD and CM (likely small effects). CD and GK were generally taller and heavier (likely small to very-likely moderate effects) than other players at each developmental stage and were advanced maturers at U13-14 (very-likely small to likely moderate effects). GK had inferior agility (very-likely small to likely moderate effects), endurance (very-likely small to likely moderate effects), and sprint capacities (likely small-moderate effects) versus outfield positions at U13-14, but deficits in anaerobic phenotypes were diminished in U15-16 and U17-18. Position specific fitness characteristics were distinguished at U15-16 (likely small) and U17-18 (likely moderate), where LM were faster than their central counterparts. In summary, relative age, maturation and anthropometric characteristics appear to bias the allocation of players into key defensive roles from an early development stage, whereas position-specific physical attributes do not become apparent until the latter stages of talent development in outfield players. Given the inter-individual trajectories of physical development according to biological maturation, playing position allocation might be considered 'plastic' by selectors, until complete-maturity is achieved.