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Within the UK, the "Long Term Athlete Development" (LTAD) model has been proposed by a variety of national governing bodies to offer a first step to considering the approach to talent development. The model, which is primarily a physiological perspective, presents an advancement of understanding of developing athletic potential alongside biological growth. It focuses on training to optimize performance longitudinally, and considers sensitive developmental periods known as "windows of opportunity". However, it appears that there are a number of problems with this theoretical model that are not necessarily transparent to coaches. Principally, the model is only one-dimensional, there is a lack of empirical evidence upon which the model is based, and interpretations of the model are restricted because the data on which it is based rely on questionable assumptions and erroneous methodologies. Fundamentally, this is a generic model rather than an individualized plan for athletes. It is crucial that the LTAD model is seen as a "work in progress" and the challenge, particularly for paediatric exercise scientists, is to question, test, and revise the model. It is unlikely that this can be accomplished using classical experimental research methodology but this should not deter practitioners from acquiring valid and reliable evidence.
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The Long-Term Athlete Development model: Physiological evidence and
application
Paul Ford
a
; Mark De Ste Croix
b
; Rhodri Lloyd
c
; Rob Meyers
c
; Marjan Moosavi; Jon Oliver
c
; Kevin Till
d
;
Craig Williams
e
a
School of Health and Bioscience, University of East London, London, UK
b
Faculty of Sport, Health
and Social Care, University of Gloucestershire, Gloucester, UK
c
Cardiff School of Sport, University of
Wales Institute, Cardiff, UK
d
Carnegie Faculty of Sport and Education, Leeds Metropolitan University,
Leeds, UK
e
Children's Health and Exercise Research Centre, University of Exeter, Exeter, UK
First published on: 04 January 2011
To cite this Article Ford, Paul , De Ste Croix, Mark , Lloyd, Rhodri , Meyers, Rob , Moosavi, Marjan , Oliver, Jon , Till,
Kevin and Williams, Craig(2011) 'The Long-Term Athlete Development model: Physiological evidence and application',
Journal of Sports Sciences, 29: 4, 389 — 402, First published on: 04 January 2011 (iFirst)
To link to this Article: DOI: 10.1080/02640414.2010.536849
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The Long-Term Athlete Development model: Physiological evidence
and application
PAUL FORD
1
, MARK DE STE CROIX
2
, RHODRI LLOYD
3
, ROB MEYERS
3
,
MARJAN MOOSAVI
4
, JON OLIVER
3
, KEVIN TILL
5
, & CRAIG WILLIAMS
6
1
School of Health and Bioscience, University of East London, London, UK,
2
Faculty of Sport, Health and Social Care,
University of Gloucestershire, Gloucester, UK,
3
Cardiff School of Sport, University of Wales Institute, Cardiff, UK,
4
Independent Consultant,
5
Carnegie Faculty of Sport and Education, Leeds Metropolitan University, Leeds, UK, and
6
Children’s Health and Exercise Research Centre, University of Exeter, Exeter, UK
(Accepted 29 October 2010)
Abstract
Within the UK, the ‘‘Long Term Athlete Development’’ (LTAD) model has been proposed by a variety of national
governing bodies to offer a first step to considering the approach to talent development. The model, which is primarily a
physiological perspective, presents an advancement of understanding of developing athletic potential alongside biological
growth. It focuses on training to optimize performance longitudinally, and considers sensitive developmental periods known
as ‘‘windows of opportunity’’. However, it appears that there are a number of problems with this theoretical model that are
not necessarily transparent to coaches. Principally, the model is only one-dimensional, there is a lack of empirical evidence
upon which the model is based, and interpretations of the model are restricted because the data on which it is based rely on
questionable assumptions and erroneous methodologies. Fundamentally, this is a generic model rather than an
individualized plan for athletes. It is crucial that the LTAD model is seen as a ‘‘work in progress’’ and the challenge,
particularly for paediatric exercise scientists, is to question, test, and revise the model. It is unlikely that this can be
accomplished using classical experimental research methodology but this should not deter practitioners from acquiring valid
and reliable evidence.
Keywords: Long-Term Athlete Development Model, growth and maturation, youth athletes
Introduction
Talent development is holistic in nature due to the
complex interaction of interdisciplinary issues that
directly impact on athletic opportunity and progres-
sion. Such concepts have been critically acknowl-
edged and documented in a recent comprehensive
report (Bailey et al., 2010). Bailey and colleagues
(2010) discuss such interactions methodically and
recommend future considerations to sport and
physical activity stakeholders who wish to enhance
participation and performance levels. Such discus-
sion has also been documented in recent review
articles (Burgess & Naughton, 2010; Phillips, Da-
vids, Renshaw, & Portus, 2010). Although we
recognize such considerations are significant, this
review focuses upon the popular ‘‘Long-Term
Athlete Development’’ (LTAD) model (Balyi &
Hamilton, 2004), which by design is fundamentally
based upon physiological principles and which will
be the sole focus here. The requirement to identify
new methods by which talent can be nurtured (which
in itself is contentious as to its definition) is
paramount for coaches and practitioners. In parti-
cular, direct techniques to advance paediatric sport-
ing development are of significant interest. However,
within this specific population there are many
extraneous factors (including degree of maturation,
and anatomical, neurological, hormonal, and mus-
culoskeletal changes in structure) that must be
incorporated within the planning of any form of
physical training (Malina, Bouchard, & Bar-Or,
2004; Tihanyi, 1990). These factors relate to an
integrated development of genes and hormones that
are coordinated according to a biological clock and
other factors (i.e. nutrients and environmental
factors), which are time independent but which all
affect the physiological systems of the body (Malina
Correspondence: P. A. Ford, School of Health and Bioscience, University of East London, Stratford Campus, Romford Road, London E15 4LZ, UK.
E-mail: p.a.ford@uel.ac.uk
Journal of Sports Sciences, February 15th 2011; 29(4): 389–402
ISSN 0264-0414 print/ISSN 1466-447X online Ó 2011 Taylor & Francis
DOI: 10.1080/02640414.2010.536849
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et al., 2004; Tihanyi, 1990). However, prior to the
last decade, the amalgamation of all these factors had
not been accounted for, something which has
hindered our understanding of the effects of training
on paediatric athletes (Balyi & Hamilton, 2004).
Currently, the most relevant and well-known model
to include such paediatric developmental considera-
tions has been held to be the LTAD model (see
Figure 1).
Although the LTAD model is not novel (Bompa,
1995; Riordan, 1977), it has been constructed on the
basis that it combines successfully employed training
methods alongside a greater scientific basis for
children and adolescents (Balyi & Hamilton, 2004;
Harre, 1982). Worldwide, as the LTAD model has
been advanced it has been adopted and applied by
national governing bodies, and consequently practi-
tioners, for the development of children into elite
athletes (Badminton England, 2006; British Gym-
nastics, 2006; England and Wales Cricket Board,
2005). The model attempts to balance training load
and competition throughout childhood and adoles-
cence, as previously it has been suggested that there
has been too much focus placed upon results rather
than assisting optimal development processes (Balyi
& Way, 1995; Bompa, 1995). Although Platonov
(1988) highlights the number of hours required to
maximize each development stage from initial basic
training through to adult maintenance, the LTAD
model principally distinguishes four stages of train-
ing development that account for enhancing general
athletic capabilities and sport specialization after
pubertal changes: FUNdamental phase, Training to
train phase, Training to compete phase, and Train-
ing to win phase (Balyi & Hamilton, 2004). It is
suggested that through objective physiological assess-
ment tools (e.g. peak height velocity, peak weight
velocity), coaches can account for individual matura-
tion rates for each athlete so that they can apply the
relevant training protocols depicted in each phase of
the model. Such practice advances chronological age
classification, which seems to be inherently flawed
due to variation in growth and maturational rates
between individuals and subsequent variance in
training ‘‘readiness’’ as will be discussed later in this
review (Balyi & Hamilton, 2004; Bompa, 1995). In
addition, using appropriate training stimuli linked to
natural growth and maturation processes (an addi-
tional factor from this model) utilizes the concept
that there are ‘‘windows of opportunity’’ to accel-
erate and enhance physical development.
Two contemporary UK coaching texts have
directly advocated the underlying concepts and
application of the LTAD model for practitioners in
sports performance and athletic development (Balyi
& Stafford, 2005; Balyi & Williams, 2009). The texts
highlight to practitioners that the model is a coaching
framework that has been constructed using a variety
of sources and experiences.
However, at present and to the best of the authors’
knowledge, there is a distinct lack of empirical data
to support such a long-term periodized model.
Therefore, the LTAD model must be viewed as a
work in progress and caution is urged to ensure that
the model does not become too enshrined as ‘‘fact’’.
Much of the evidence lacks any significant long-
itudinal or experimental data, and includes animal-
based literature to rationalize its structure (Szmodis,
1991). Indeed, Balyi and Hamilton (2004) highlight
that their work is based on ‘‘empirical observations’’,
which although apparently well informed, lack
scientific validity due to inherent subjectivity issues.
In addition, it appears that there is no evidence that
failure to exploit these ‘‘windows of opportunity’’
with appropriate training will result in inhibited
development and that the athlete will experience a
‘‘ceiling’’ effect on performance. Bailey et al. (2010)
correctly question whether the ‘‘windows of op-
portunity’’ actually raise the ceiling for future
potential or just allow an athlete to reach their
ceiling performance level at a younger age. Beunen
and Malina (1996) clearly show individual variance
in the rate of athletic performance development
associated with growth and maturation, but there
seems to be a lack of clarity on the training
stimulus required to facilitate these developmental
spurts. Due to the lack of an agreed method of
quantifying training per se, and the lack of
paediatric data, plus the wide range of stimuli
needed for different sports, it appears an almost
impossible task to elucidate the stimulus–training
response question. The model has recently come
under some direct criticism from practitioners for
such reasons (e.g. Bailey et al., 2010), indicating a
scientific examination of the LTAD model speci-
fically would seem to be very appropriate. The aim
of this review is to examine physiological fitness
components located within the LTAD model with
regards to trainability, to distinguish if this has
been effectively encompassed within the prescrip-
tions of the model, and to directly evaluate the
concept of ‘‘windows of opportunity’’.
Impact of growth and maturation on athletic
performance
Physical literacy
There have been numerous references to physical
literacy in the literature over the years and also many
philosophical and physiological debates, mainly by
physical educators, over its importance throughout
the human life span (Whitehead, 2001, 2004).
Physical literacy has been defined as the extent of a
390 P. Ford et al.
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Figure 1. Adaptation to training and optimal trainability (adapted from Balyi & Way, 2002; in Balyi & Hamilton, 2004).
Long-Term Athlete Development model 391
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person’s ability to capitalize on his or her embodied
dimension (Whitehead, 2004) or as a combination of
kinaesthetic intelligence and the ability for skilful
actions (Arnold, 1979). Physiologically, physical
literacy is the development and the competence in
fundamental movement skills (e.g. walk, run, jump,
throw) and fundamental sport skills (e.g. catch, hop,
gallop) that permit a child (or adult) to move
confidently in a wide range of physical activity,
rhythmic, and sport situations (Higgs et al., 2008). It
is has been shown that, compared with the typically
developing child, children with motor learning
difficulties demonstrate less physical literacy, are less
active and more disruptive in regular physical
education classes and during ‘‘school holidays’’
(Bouffard, Watkinson, Thompson, Dunne, &
Romanow, 1996), and have lower overall fitness
(Hands & Larkin, 2006). While the negative effects
of reduced movement proficiency on health-related
fitness have been well documented in children
(Okely, Booth, & Chey, 2004; Okely, Booth, &
Patterson, 2001a, 2001b), the literature regarding
the importance of developing physical literacy and
motor skill fitness for LTAD is limited.
The development of fundamental movement skills
starts at birth and may continue until 11–12 years of
age, depending on the complexity of the skill
(Gabbard, 1992). Many scientists have proposed
that each of the fundamental movements has a series
of developmental stages, with each stage possessing a
different degree of complexity (Flinchum, 1975;
Gabbard, 1992; McClenaghan & Gallahue, 1978).
Children need to acquire mature fundamental
movement patterns to improve their performance
(Gabbard, 1992; McClenaghan & Gallahue, 1978),
and acquiring mature patterns requires greater
speed, balance, control, strength, and coordination
to be able to pass through different stages. The
scientific literature regarding the natural process of
motor development fitness may partly support the
LTAD model for the development of physical
literacy. From a neurological perspective, Rabino-
wicz (1986) noted the periods of peak brain
maturation through childhood. Such development
at 6–8 years and 10–12 years of age seems to
coincide with the ‘‘windows of opportunity’’ for
physical literacy tasks (fundamental and sports
specific) in the LTAD model (Balyi & Hamilton,
2004; Higgs et al., 2008) and improvements in
motor coordination (Cratty, 1986). However, such
developments may represent accelerated periods of
development, but there is no evidence that such
periods offer greater ‘‘sensitivity’’ to training.
The literature regarding the trainability of physical
literacy provides some scientific evidence to support
the LTAD model, although it is not completely
convincing. The variety and diversity of the indica-
tors chosen to express the proficiency of physical
literacy makes it particularly difficult to draw clear
conclusions, and further work to provide clarification
in this area is certainly required. The importance of
providing learning opportunities in the early years of
life for the development of cross-body coordination
and fundamental movement skills has been reported
previously (Dennis, 1960; McGraw, 1935, 1959).
However, in more recent years, several studies have
investigated the effect of training on physical literacy
during childhood. Ingle and colleagues (Ingle, Sleap,
& Tolfrey, 2006) showed that a mixture of plyo-
metrics and resistance training could improve
fundamental sport skills temporarily among early
pubertal boys, although the authors only measured
strength-related performance outcomes and not the
actual quality of fundamental sport skills. Graf et al.
(2005) showed that a long-term school-based inter-
vention can improve aspects of physical literacy
among 6- to 9-year-olds, but a 6 year follow-up
study demonstrated that a year-long intervention
during childhood did not have long-lasting effects on
overall physical literacy (Barnett et al., 2009). In both
instances, however, movement quality was not
assessed. These data would seem to contradict the
‘‘windows of opportunity’’ concept proposed in the
LTAD model, whereby training within certain
physical literacy skills at certain stages may result in
greater long-term development of those skills.
Gallahue and Ozmun (1998) and Gallahue and
Donnelly (2003) also suggest a ‘‘proficiency barrier’’,
whereby progression onto more advanced specialized
or sports-specific skills are dependent on the prior
foundation of fundamental movement patterns,
reinforcing the motor development literature. Evi-
dently there is much inconsistency in the current
literature surrounding the long-term effects of
fundamental movement/sport skills training, both in
terms of methodology and outcome, and further
multidisciplinary, longitudinal research is required.
Flinchum (1975) have shown the importance of
providing instruction for rapid development of more
complex movements such as mature throwing
patterns among 5-year-olds. Furthermore, Derri
and colleagues (Derri, Tsapakidou, Zachopoulou,
& Kioumourtzoglou, 2001) conducted a 10 week
music and movement programme with children aged
4–6 years, and reported significant improvements in
the quality of more complex movement patterns.
Further work by Deli and colleagues (Deli, Bakle, &
Zachopoulou, 2006) suggested that ‘‘free play’’
(compared with instruction) seemed unable to
guarantee the development of more complex skills,
lending support to Gabbard (1992), who suggested
that ‘‘Proficient kicking, like proficient throwing,
may not be achieved through the natural course of
childhood development’’ (p. 295).
392 P. Ford et al.
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In summary, it appears that there is reasonable
anecdotal and some physiological evidence to sup-
port the idea of enhanced neural and muscular
adaptations (due to the plasticity of the neuromus-
cular system) through exposure to regular and
structured fundamental movement skills and funda-
mental sport skills training in childhood. However,
further research is needed to quantify the existence of
the ‘‘window of opportunity’’ concept for funda-
mental movement/sport skills, and if training these,
especially in the earlier years, could manifest it
through the later stages of the athletic development
models.
Aerobic performance
The development of aerobic fitness and its impact on
performance is influenced by growth-related changes
to an individual’s central and peripheral cardiovas-
cular system, muscular function, cellular capacity,
body composition, and metabolic capability (Row-
land, 1985). The intra- and inter-degree of influence
these components have upon aerobic fitness varies
throughout childhood and adolescence (Naughton,
Farpour-Lambert, Carlson, Bradney, & Van Praagh,
2000). Peak oxygen uptake, acknowledged as the
‘‘gold standard’’ criterion method of assessing an
individual’s aerobic fitness (Jones & Carter, 2000;
Naughton et al., 2000), increases from infancy into
adulthood, possibly in a linear fashion with body size
(Armstrong & Welsman, 1994; Bouchard, Malina, &
Pe´russe, 1997; Viru et al., 1999). Although there is a
large amount of supportive literature to suggest that
from a young age children naturally possess a well-
developed aerobic capacity (Boisseau & Delamarche,
2000), different methods of physical training have
been shown to enhance the development of aerobic
capacity in children and adolescence (Viru et al.,
1999). For example, it has been suggested that
relatively high-intensity prolonged training will pro-
duce significant gains (Tolfrey, Campbell, & Batter-
ham, 1998; Williams, Armstrong, & Powell, 2000).
In support of this, Mahon (2008) noted that low-
intensity training often results in a minimal training
stimulus response during paediatric interventions.
Nevertheless, several authors have suggested that
there are natural accelerated and decelerated periods
of development during maturation (Baquet, Van
Praagh, & Berthoin, 2003; Harro, Lintsi, & Viru,
1999; Viru et al., 1999). These are highly individua-
lized, which can be attributed in part to the
fluctuating rates of anatomical, neurological, mus-
cular, metabolic, and hormonal development
(Naughton et al., 2000; Viru et al., 1999). Kobayashi
et al. (1978), Payne and Morrow, (1993), and
Baquet et al. (2003) suggest that there is an
exponential rise in peak oxygen uptake following
peak height velocity and puberty, in what Katch
(1983) and Rowland (1997) describe as the ‘‘trigger
hypothesis’’. Although there is discrepancy in the
literature, Viru et al. (1999) have reviewed several
longitudinal studies to show that peak development
of relative aerobic capacity (ml kg
71
min
71
)
occurs between 12 and 16 years in both boys and
girls. However, Viru et al. (1999) also reported that
cross-sectional research shows that the peak devel-
opment period for aerobic capacity occurs at 10–16
and 7–13 years in boys and girls, respectively.
Nevertheless, the credibility of the latter evidence
can be questioned because it is based on non-
causative observations. Furthermore, results from
previous studies suggest that children and adoles-
cents are significantly less efficient (related to aerobic
metabolism) in energy expenditure during move-
ment than adults and that children consume more
energy per unit of body mass during locomotion at a
given speed (Cavagna et al., 1983; De Jaeger et al.,
2001; Schepens et al., 2004). Plausible explanations
can be attributed to differences in body size, lack of
neuromuscular maturity, and an inability to effec-
tively deliver oxygen to the required muscles in
children, which become adult-like with increasing
growth and maturation (Cavagna, Franzetti, &
Fuchimoto, 1983; De Jaeger, Willems, & Heglund,
2001; Schepens, Bastien, Heglund, & Willems,
2004). However, it seems that the potential for
improving economy of movement and physical
performance is likely influenced by training as well.
However, few investigations have specifically ad-
dressed appropriate training prescription or identifi-
cation of sensitive periods to enhance economy of
movement subsequent to improvements through
physical development (Naughton et al., 2000). It
might be postulated that overall economy of move-
ment will be continuously enhanced with physical
activity and exercise through childhood and adoles-
cence (Baquet et al., 2003).
After acknowledging this literature and when
focusing on the concept of ‘‘windows of opportu-
nity’’, Naughton et al. (2000) state that the growth-
related improvements from aerobic training in well-
trained male adolescent athletes (compared with
well-trained pre-adolescent males) relate to changes
in hormone secretions during maturation. Moreover,
Naughton et al. (2000) suggest that training aerobic
fitness when there is a lack of circulating metabolites,
thus resulting in a reduced training adaptation
response, supports the ‘‘windows of trainability’’
concept of the LTAD model. For example, Weber
and colleagues (Weber, Kartodihardjo, & Klissouras,
1976) have suggested that there is a decreased
sensitivity to aerobic fitness training response that
occurs in the middle of the peak height velocity
when compared with the years surrounding it.
Long-Term Athlete Development model 393
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Alternatively, some authors have suggested that most
sensitive training adaptations to aerobic fitness
actually occur before peak height velocity, including
Rowland (1985) who identified a 10.1% and 8.8%
improvement in peak oxygen uptake during this
period in boys and girls, respectively. Thus it would
appear that there are discrepancies in the literature in
terms of when these actual ‘‘windows’’ occur.
Perhaps this discrepancy can be related to the fact
that much of the evidence for this fitness component
is based on cross-sectional studies, which restricts
inferences due to methodological restraints. The lack
of longitudinal data is also coupled with the
imprecise assessment of training stimulus, which is
required to elicit peak development (Baquet et al.,
2003). Both Naughton et al. (2000) and Baquet et al.
(2003) conclude that the findings are obscured
further by genetic background and training load,
which are rarely reported. Therefore, attributing any
adaptive response in line with physical development
is flawed due to the variation in the magnitude of the
stimulus. In addition, it appears that research has
focused on participants during pre-pubertal years
rather than adolescents, and has not accounted for
initial peak oxygen uptake values (Tolfrey et al.,
1998). Such a lack of the recognition of these
fundamental aspects limits the direct investigation
of the ‘‘windows of trainability’’ concept, and may
indeed mean that application by practitioners is
inappropriate at present.
Long-term studies that map changes in aerobic
capacity during growth and measure the influence
of physical activity or training concurrently are
required. As discussed previously, the complexity
of the research design to answer such a problem
may render the project impractical, and thus
progression in this area will perhaps not occur.
Nevertheless, until more comprehensive consistent
evidence is available, it is inappropriate to state
that young participants should only train aerobic
fitness during prescribed ‘‘windows of opportu-
nity’’. Aerobic fitness should be actively developed
throughout childhood and adolescence (Shephard,
1992).
Anaerobic performance
Speed. Both boys and girls show similar sprint speed
during the first decade of life (Borms, 1986; Malina
et al., 2004), with a period of accelerated adaptation
suggested to occur between the ages of 5 and 9 years
in both sexes (Borms, 1986; Viru et al., 1999). From
the age of 12 years, the rate of progression of speed
development is dramatically reduced in females
compared with males (Whitall, 2003), with the
arrival of the fourth puberty stage being suggested
to mark the end of maximal speed development in
girls not involved in sport (Szczesny & Coudert,
1993). This disparity between the sexes is attributed
to maturational changes in body dimensions and
composition (Beunen & Malina, 1988; Butterfield,
Lehnhard, Lee, & Coladarci, 2004). A second period
of accelerated adaptation has been reported to occur
around the age of 12 years in girls and between 12
and 15 years in boys (Borms, 1986).
The development of speed throughout childhood
will be influenced by quantitative changes in muscle
cross-sectional area and length, biological and
metabolic changes, morphological alterations to the
muscle and tendon, neural/motor development, as
well as biomechanical and coordination factors. The
integration of all of these systems makes it difficult to
identify precise mechanisms responsible for any
speed gains achieved throughout childhood. The
initial period of accelerated adaptation observed
before the end of the first decade of life has been
suggested to be linked to the development of the
central nervous system and improved coordination
(Borms, 1986; Viru et al., 1999). This assumption is
supported by the rapid growth of the central nervous
system during the first 7 years of life (Malina et al.,
2004), and the observation that coordination pat-
terns of locomotor skills reach adult levels by the
same age (Whitall, 2003).
Increased muscle size and length during adoles-
cence support a maturational influence on speed
development, although Butterfield et al. (2004)
found no association between longitudinal growth
rates of height and body mass and improved running
speed in children aged 11–13 years. Although 2 years
may be considered brief for a longitudinal study, the
above findings may also reflect a limitation of the
current LTAD model, which relies on growth rates
to identify maturational status. Increases in muscle
substrates and enzymes associated with anaerobic
energy production provide another means for im-
proving speed immediately before and during the
teenage years (Eriksson, 1980). Physical properties of
the muscle and tendon architecture will also influ-
ence the ability to produce speed. These properties
include the reported marked increases in the surface
area of the muscle–tendon junction from childhood
into adulthood, which is accompanied by a reduced
number of Golgi organs in the mature state (Ovalle,
1987). As a consequence of these changes in the
biomechanical properties of muscle and connective
tissue, a ten-fold increase in muscle–tendon stiffness
has been observed in the first two decades of life
(Lin, Brown, & Walsh, 1997). Changes in muscle
stiffness will also be influenced by neural factors,
with firing rates (Whitall, 2003), twitch times (Lin
et al., 1997), reflex muscle activity (Grosset, Mora,
Lambertz, & Perot, 2007), and co-activation
(Lambertz, Mora, Grosset, & Perot, 2003) all being
394 P. Ford et al.
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shown to develop through childhood in a manner
that would favour increased speed production.
The current LTAD model speculates that two
‘‘windows of opportunity’’ exist to maximize training
gains in childhood. These ‘‘windows’’ are related to
chronological age and occur at approximately 7–9
years in both boys and girls, with a second window
between 11 and 13 years in girls and between 13 and
15 years in boys. The fact that the second window is
staggered by 2 years between girls and boys can be
interpreted as more of a maturational, as opposed to
a chronological, ‘‘window of opportunity’’. A ma-
turational role in the second ‘‘window of opportu-
nity’’ is supported by Viru et al. (1999), who
speculated that speed training gains during this
period were related to hormone-dependent selective
hypertrophy of fast-twitch fibres in both boys and
girls. Surprisingly, research examining the trainabil-
ity of speed during childhood is sparse. Venturelli
and colleagues (Venturelli, Bishop, & Pettene, 2008)
found that the magnitude of speed gains were similar
for pre-adolescent soccer players involved in coordi-
nation training and traditional straight-line sprint
training. This finding supports a role of coordination
and neural control in speed development prior to
maturation, although whether these factors are more
trainable during pre-adolescence is not known.
Philippaerts et al. (2006) reported that sprint speed
in youth footballers showed the largest gains around
the time of peak height velocity, suggesting a
combined training and maturational affect. How-
ever, the longitudinal data presented by Philippaerts
et al. (2006) showed a decline in sprint performance
in the 12 months preceding peak height velocity, and
any subsequent gains may simply have reflected a
correction of the previously impaired performance.
Improvements in speed around peak height velocity
may also be related to increased lower limb length,
reflecting an entity that is clearly not trainable. Rapid
periods of physical growth may disrupt motor
coordination in some individuals, a phenomenon
known as ‘‘adolescent awkwardness’’ (Beunen &
Malina, 1988; Philippaerts et al., 2006). However,
the timing and magnitude of this phenomenon is still
unknown and it is difficult to evaluate if this
observation is being enshrined as ‘‘fact’’ when based
on limited empirical evidence.
While there is limited research available on the
trainability of speed throughout childhood, some
research has investigated possible mechanisms re-
sponsible for training gains during childhood. Sprint
training has been shown to increase concentrations
of substrates and enzymes utilized during anaerobic
metabolism in 11-year-olds (Eriksson, 1980) and
adolescent boys (Cadefau et al., 1990; Fournier
et al., 1982). However, the magnitude of the
training-induced change is reported to be below that
of adults and any adaptation is lost following a
detraining period (Fournier et al., 1982). The
magnitude of the response and rapid detraining
would suggest metabolic factors are unlikely to be
constrained to maximizing gains during a window of
opportunity in childhood. Sprint training has also
been shown to have a limited effect on catecholami-
nergic responses to sprint exercise in adolescent girls,
which disappears with detraining (Botcazou et al.,
2006). Therefore, any combined speed training and
maturational effects appear to have a limited
influence on the sympo-adrenal response. In a 6
month study of youth soccer players, Gravina et al.
(2008) reported a significant correlation between
changes in testosterone concentrations and changes
in sprint performance. Although these findings
support a maturational relationship for improved
speed for players involved in a training programme,
the correlation was only modest (r ¼ 0.34, P 5 0.05)
and with 512% shared variance between the two
variables other factors need to be considered.
Identifying a single mechanism responsible for
improved speed during childhood is unlikely. In-
stead, a number of biological, neural, and biome-
chanical factors will influence the development of
speed. These factors may develop at different rates
for different individuals and may be linked to both
age and maturation. The trainability of factors
associated with speed development during childhood
remains unclear.
Strength. The development of muscle strength is a
multi-faceted, performance-related fitness compo-
nent that is underpinned by muscular, neural, and
mechanical factors (De Ste Croix, 2008). The
complex interaction of these components makes the
study of the increase in muscle strength during
growth and maturation challenging. As strength is an
essential component of most aspects of performance,
it is surprising that very little is known about the
factors associated with strength development during
childhood compared with the other fitness compo-
nents discussed in this review. This may be
attributed to the difficulty in measuring internal
forces and the inherent methodological problems
associated with determining external force. As there
are no physiological markers that a maximal effort
has been given, the methodological and assessment
choices are critical in paediatric studies of muscle
strength (De Ste Croix, 2007). However, the
findings of studies on the age- and sex-associated
changes in strength are relatively consistent, espe-
cially for the lower limbs. Caution, however, must be
taken when transferring this knowledge to other
muscle joints, as the development in strength appears
to be both muscle action and joint specific (De Ste
Croix, 2008).
Long-Term Athlete Development model 395
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Strength increases in both boys and girls until
about the age of 14 years, when it begins to plateau in
girls and a spurt is evident in boys. By 18 years there
are few overlaps in strength between boys and girls,
although this simplistic model utilizing chronological
age as a marker for development in strength does not
take into account the individual timing and tempo of
growth and maturation (an issue seen with all the
fitness components). The exact ages at which sex
differences become apparent appear to be both
muscle group and muscle action specific and data
have indicated that differences in upper body
strength between the sexes occur earlier than
differences in lower body strength (Gilliam, Villa-
nacci, Freedson, & Sady, 1979; Round, Jones,
Honour, & Nevill, 1999). What is less clear is the
complex interaction of factors that contribute to
strength (the production of force) during childhood
and adolescence. Few well-controlled longitudinal
studies have concurrently examined the influence of
known variables using appropriate statistical techni-
ques (De Ste Croix, Armstrong, Welsman, &
Sharpe, 2002; Round et al., 1999; Wood, Dixon,
Grant, & Armstrong, 2004). Most studies that have
determined maturation have shown that it does not
exert an independent effect when other factors, such
as stature and body mass, are accounted for (De Ste
Croix et al., 2002; Hansen, Klausen, & Muller,
1997; Maffulli, King, & Helms, 1994). Also, the
assumption that muscle cross-sectional area is the
most important parameter in strength development
throughout childhood and adolescence does not hold
when examined with other known variables (Deigh-
an, Armstrong, & De Ste Croix, 2003; De Ste Croix
et al., 2002). Consistently, stature appears to play a
key role in strength development and this may be
attributed to the strength spurt that has been linked
to peak height velocity, and the muscle moment arm
(for a detailed explanation of the muscle moment
arm, see Wood et al., 2004).
Strength training is now deemed to be safe and
effective for children and adolescents when appro-
priately designed and supervised (Christou et al.,
2006; Falk & Tenenbaum, 1996). Well-established
guidelines for youth resistance training (e.g. Faigen-
baum et al., 2009; Stratton et al., 2004) recommend
resistance training for enhancement of muscular
strength in youths, with improvements in body
composition (Sothern et al., 2000) and motor
performance (Christou et al., 2006), and reductions
in injury (Faigenbaum et al., 2009) further advan-
tages. Research studies have demonstrated that
strength is trainable during childhood and adoles-
cence, with Faigenbaum and colleagues (2001)
reporting strength gains in children as young as 5
years. However, a large variation in strength gains
exists between studies, with improvements ranging
from 5.3% (Faigenbaum, Westcott, Loud, & Long,
1999) to 87.0% (Faigenbaum, Zaichkowsky, West-
cott, Micheli, & Fehlandt, 1993) in untrained
participants. Several factors may contribute to this
variation, including the baseline measure of strength,
the age range of participants, training programme
designs (e.g. frequency, volume, and intensity),
muscle group/action assessed, and exercises/assess-
ments used. These all make the evaluation of training
responses difficult.
The LTAD model states that strength is always
trainable but recommends the optimal ‘‘window of
trainability’’ for boys is 12–18 months following peak
height velocity, while for girls it is immediately after
peak height velocity or at the onset of the menarche
(Balyi & Hamilton, 2004). However, research
examining the optimal ‘‘window of trainability’’ is
limited and there appear to be no longitudinal
strength training studies that have determined peak
height velocity and that have appropriately controlled
for growth and maturation. Only three studies
(Lillegard, Brown, Wilson, Henderson, & Lewis,
1997; Pfeiffer & Francis, 1986; Vrijens, 1978) could
be found that compared the trainability of strength
across different maturational ages. Vrijens (1978)
found greater arm and leg strength improvements in
a post-pubertal (16.8 years) group compared with a
pre-pubertal (10.5 years) group, who improved lower
back and abdominal strength to a greater degree
following an 8 week training programme. However,
both Lillegard et al. (1997) and Pfeiffer and Francis
(1986) found no differences in the percentage
magnitude of strength training response between
different maturational training groups. Therefore,
current research supporting the LTAD model’s
optimal ‘‘window of trainability’’ for strength is
speculative, with only one study concluding that
the strength training response is greater after pub-
erty. Based on current research, strength training can
be undertaken by children, as long as the programme
is designed and supervised by professionals. Further
research examining strength training gains against
biological age (age at peak height velocity; Mirwald,
Bailey, Cameron, & Rasmussen, 1981) are required
to determine if an optimal window of strength
trainability does exist. In addition, research should
also focus on the training variables (e.g.
volume, frequency, load, and rest periods) for
optimum strength training gains in children and
adolescents.
Power. Rapid developments in muscular power have
been established in pre-pubescent children between
the ages of 5 and 10 years (Branta, Haubenstricker,
Seefeldt, 1984). These periods of accelerated devel-
opment are largely attributable to enhanced neuro-
muscular coordination. A secondary spurt has been
396 P. Ford et al.
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associated with the onset of puberty in girls between
9 and 12 years, and in boys between the ages of 12
and 14 years (Beunen, 1997), with significant
development in leg power at the ages of 14 and 15
years (Blanksby, Bloomfield, Ackland, Elliott, &
Morton, 1994). The latter spurt is related to a
combination of hormonal, muscular, and mechanical
factors caused by the onset of puberty (as seen with
the other fitness components). When aligning the
velocity curve of lower limb power development in
relation to peak height velocity, previous research has
identified an adolescent spurt beginning 1.5 years
before peak height velocity, and peaking 0.5–1.0 year
after peak height velocity (Beunen & Malina, 1988).
Like muscular strength, therefore, while accelera-
tions in muscular power may occur around the time
of peak height velocity, peak muscular power would
appear to coincide more readily with peak weight
velocity, suggesting that both increases in muscle
mass and motor unit activation are strongly linked to
muscular power. Butterfield et al. (2004) reported a
strong correlation between vertical jump height and
the growth rates of their pre-adolescent sample
(r ¼ 0.95, P 5 0.05). Growth-related changes in both
leg length and muscle mass were associated with
increased vertical jump height, and these structural
changes were deemed to override any negative
effects of the concomitant increase in body mass
(Butterfield et al., 2004).
As with a number of other physical components,
sex-related differences appear to exist in muscular
power from pre- to post-adolescence, with differ-
ences becoming more apparent at the age of 14 years
onwards, as a result of the increased leg length and
muscle volume in males (Temfemo, Hugues, Char-
don, Mandengue, & Ahmaidi, 2009). Observations
of cross-sectional data show sex-related differences
in mean countermovement jump height scores of 7-
to 11-year-old girls and boys (Isaacs, 1998). Butter-
field et al. (2004) reported differences in their
baseline measures of vertical jump height between
boys and girls aged 11–13 years, and also highlighted
that the growth rate of jumping for boys significantly
exceeded that of girls by 1.91 cm every 4 months
over a 9 month period. Research has revealed
significant differences between stages of sexual
maturity and vertical jump height performance in
boys (11–16 years), even when the influences of body
mass and stature were removed (Jones, Hitchen, &
Stratton, 2000). However, differences between sex-
ual maturity stages and vertical jump performance
were not statistically significant among girls. But the
greater effect of sexual maturation on muscular
power output in boys during the adolescent growth
spurt highlights the likely attributable increases in
androgen concentrations – notably growth hormone,
testosterone, and thyroid hormone between boys
and girls (Rogol, 1996; Viru et al., 1999). More
recently, a neuromuscular spurt was evident in male
athletes characterized by an increase in both vertical
jump height and the ability to attenuate landing
forces (Quatman, Ford, Myer, & Hewett, 2006).
Within the female sample, a reduction in both
vertical jump height and take-off force highlighted
the contrasting effects of maturation on lower limb
explosive strength.
In addition to muscle cross-sectional area (Jacobs,
Sjodin, & Svane, 1982), neurological changes
(Blimkie & Bar-Or, 1996), motor coordination
(Isaacs, 1998), fibre type composition (Mero,
Jaakkola, & Komi, 1991), and prior training experi-
ence (Bencke et al., 2002) have all been postulated to
be determining mechanisms for lower limb explosive
strength in youths. Despite these suggestions, limited
data exist for the combined effects of maturation and
trainability on lower limb muscular power adapta-
tions. Chiodera et al. (2008) implemented a 33 week,
three lessons per week motor abilities physical educa-
tion programme for boys and girls between the ages of
6 and 10 years. Results revealed significant improve-
ments (6–10 cm; P 5 0.01) in long jump distance for
all ages and for both sexes, suggesting that trainability,
as well as growth and maturational factors, may have a
positive effect on power development throughout
childhood in both males and females. Other studies
have reported statistical differences between playing
ability and vertical and horizontal jump tests (Gissis,
Kalapotharakos, Sotiropoulos, Komsis, & Manolo-
poulos, 2006; Vaeyens et al., 2006), and significant
improvements in lower limb muscular power follow-
ing a 6 week combination of plyometrics and
resistance training (Faigenbaum et al., 2007). How-
ever, without longitudinal data for corresponding
measures of maturity status and muscular power, the
existence of any ‘‘windows of opportunity’’ remains
unclear, as does the question of whether or not
adaptations are greater for those athletes who are
exposed to power-based training during, as opposed to
outside of, any such ‘‘windows’’.
The current LTAD model provides no indication
of a ‘‘window of opportunity’’ for power develop-
ment during childhood. This may be due to the fact
that as the product of force (strength) and velocity
(speed), the ‘‘windows of opportunity’’ have already
been included in the model for the component parts
of power production. However, given the importance
of muscular power for athletic success, it may be
appropriate to consider the most appropriate period
during which to train for power during childhood.
Owing to the minimal number of longitudinal-based
studies examining the interaction of growth, matura-
tion, and trainability on muscular power, it is
difficult to identify whether a window of opportunity
exists to maximize power development.
Long-Term Athlete Development model 397
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Windows of opportunity
Undeniably, the basis of the LTAD model centres
around annual training and competition design,
which have been well documented previously (Bom-
pa, 1995; Harre, 1982; Norris & Smith, 2002; Wilke
& Madsen, 1986). However, the model also maps
physiological adaptations associated with growth and
maturation, through maximizing training ‘‘windows
of opportunity’’ as repeatedly highlighted throughout
this review. Essentially, these are critical/sensitive
periods for accelerated development of motor
performance based on a suitable training stimulus
during appropriate maturational time periods (Gu-
zalovsky, 1977). Nevertheless, as noted above (in
several previous sections), the actual concept of the
development periods related to increased adaptive
properties to factors stimulating development (i.e.
training and exercise), as well as the potential
negative implications, require further scientific ver-
ification. It seems that the appropriate application of
training in line with maturation highlighted above
may have a significant influence on peak perfor-
mance through cell, tissue, organ, and whole-system
specialization (Balyi & Hamilton, 2004; Wenger,
McFayden, & McFayden, 1996). Certainly in the
applied literature it has been documented that
conducting a training intervention outside of a
‘‘window of opportunity’ will result in few if any
training gains and may actually be detrimental to
future adaptations (Zaichkowsky, Zaichkowsky, &
Martinek, 1980), but there is a clear lack of
supporting evidence for such an assertion.
The present authors’ acknowledge the difficulties
in the quantification of physical activity and training
in young participants, as well as controlling this
during applied investigations. This in part can
explain why there is a lack of agreement in the
literature. Loko and colleagues (Loko, Sikkut, &
Aule, 1996) noted that there is evidence to suggest
that the best effect of training and the development of
performance capabilities is achieved when natural
growth is at its peak. However, paradoxically there is
a possible consequence that the full potential of the
individual is not achieved when early specialization
and intensive training occur during these ‘‘windows
of opportunity’’. Without supportive and objective
data to help confirm/reject these ideas, inferring any
optimal training recommendations for successful
athletic pathways for young participants is perhaps
unsuitable. It is the opinion of the present authors
that this needs to be made clearer to coaches and
practitioners by national governing bodies.
Notwithstanding the empirical issues, the actual
terms of reference for ‘‘window of opportunity’’
require clarification. It seems a ‘‘critical period’’,
related to exercise training, is an opening to
effectively exploit a unique situation, which is vital
to adhere to, otherwise full athletic potential will not
be achieved. Whereas the term ‘‘sensitive period’’
implies an opening when extra gains may be
expected for the same efforts. Based upon this
strategy, it is clear that implications to the use of
such labels, together with significant consequences
for important constructs such as specialization,
should be considered too. Furthermore, the term
‘‘window’’ suggests that the periods open and close,
when in fact they may open and remain so on to and
throughout adulthood (Viru et al., 1999).
In short, with issues related to definition and the
obvious lack of objective evidence, the authors’ belief
is that the proposition that if young participants do
not utilize these ‘‘windows of opportunity’’ they will
never reach maximum athletic is unjustified.
Furthermore, when utilizing fundamental training
principles within a long-term periodized plan, the
period of a ‘‘training emphasis’’ should be presented.
Again, coaches and practitioners should be made
more aware of the importance of training to advance
all fitness components throughout childhood and
adolescence during non-sensitive periods as well,
principally because of different individual maturation
development rates and all components are trainable
to some extent (Suslov, 2002). By doing so this
should further help coaches avoid issues around early
specialization, and optimize general athletic devel-
opment of young performers.
Summary and implications
A number of studies have identified the numerous
physical developmental processes that occur during
childhood and adolescence and how they might
influence short- and long-term athletic performance
(Baquet et al., 2003; Boisseau & Delamarche, 2000;
Naughton et al., 2000; Viru et al., 1999). The most
prominent ideology to help to optimize long-term
athletic performance preparation in line with this is the
LTAD model (Balyi & Hamilton, 2004). This model
has received supported in contemporary coaching
texts (Balyi & Stafford, 2005; Balyi & Williams, 2009).
Certainly, the model succeeds in offering practitioners
a coaching framework using plausible principles.
However, from the components reviewed in this paper
(physical literacy, aerobic and anaerobic perfor-
mance), there is little evidence to support the LTAD
claims, possibly due to the number of physiological
factors that influence performance. Similarly, Norris
and Smith (2002) correctly state that the most
essential component of an effective training pro-
gramme is the concept of individualization. This
appears to be a further limitation of the LTAD model
(Balyi & Hamilton, 2004), even with physiological age
classifications due to their own limitations (Beunen,
398 P. Ford et al.
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1990; Janz & Mahoney, 1997). Moreover, Viru et al.
(1999) concisely state that the lack of evidence
between athletic performance and trainability against
ontogenetic development make any conclusions in-
accurate, particularly for the notion of ‘‘windows of
opportunity’’. Similarly, although such information
has been applied to specific physiological development
and training practices for children and adolescents, it
appears that there is a lack of consensus on the impact
of such hormonal and metabolic changes within
review articles (Boisseau & Delamarche, 2000;
Naughton et al., 2000). This is primarily due to the
practical issues and restrictions surrounding paedia-
tric research (Boisseau & Delamarche, 2000).
A key rationale for this review is how the LTAD
model is currently being understood and applied by
coaches and practitioners. It is the opinion of the
authors that coaches should be better educated in
how to interpret and use the information within the
model, in light of its positive and negative issues.
Subjectively, it appears that the model has been
widely prescribed to date, but it seems the knowledge
transfer of the generic principles that make up the
model are not being disseminated to allow coaches to
comprehend and adapt the model to suit the
individual needs of their own athletes. Furthermore,
the model would be more suitable if it were to be
more holistically orientated, encompassing some of
the key interdisciplinary perspectives seen elsewhere
(Bailey et al., 2010).
Therefore, while it should be clearly stated that the
LTAD model has advanced coaches’ and practi-
tioners’ understanding of the importance of physiolo-
gical principles and biological maturation alongside
training young athletes, there are many unexplained/
unsupported premises that undermine it. Preliminary
research to help practitioners to better understand
fundamental development issues of children and
adolescents is urgently required. Whether a situation
is reached whereby an evaluation of the application of
the model is conducted remains uncertain. What is
more certain is that future recommendations to help
enhance physical athletic performance from infant to
adult must be based on empirical evidence (Beunen &
Malina, 1996). With this in mind, we recommend to
key sporting stakeholders that they should look to
advance the scientific underpinning of their recom-
mendations by supporting appropriate applied scien-
tific investigations to enhance our understanding of
developing the youth athlete.
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... To support practitioners in this process, the long-term athletic development model (LTAD) was proposed (Balyi & Hamilton, 2004;Bompa, 1995). The LTAD model attempts to maintain balance between training load and competition throughout childhood and adolescence (Ford et al., 2011). It also proposes specific windows of development, termed "sensitive periods of development" for various components of fitness. ...
... However, since the LTAD model's inception, it has been critiqued for a lack of scientific rigour as the sensitive periods of development are based on chronological age as opposed to biological growth and maturity (Ford et al., 2011). For example, several factors influence speed throughout childhood, including quantitative changes in muscle cross-sectional area and length, morphological alterations to the muscle and tendon, development of SSC through neuromuscular pathways, and biomechanical factors associated with sprinting (kinetics and kinematics) (Ford et al., 2011;Radnor et al., 2018). ...
... However, since the LTAD model's inception, it has been critiqued for a lack of scientific rigour as the sensitive periods of development are based on chronological age as opposed to biological growth and maturity (Ford et al., 2011). For example, several factors influence speed throughout childhood, including quantitative changes in muscle cross-sectional area and length, morphological alterations to the muscle and tendon, development of SSC through neuromuscular pathways, and biomechanical factors associated with sprinting (kinetics and kinematics) (Ford et al., 2011;Radnor et al., 2018). Hence, it is important to consider these factors when investigating the potential of speed development in youth across maturation rather than rely completely on the windows of opportunity based on chronological age. ...
... This can be evaluated through morphological age, bone maturation, secondary sexual characteristics, relative height, and height growth velocity peak (51,52). Determining the peak height velocity, which is the maximum height growth rate that occurs during the period of greatest growth, allow to the selection of training stimuli that will be promoted with different athletes (53). This is because the determination of the moment when the peak of growing velocity occurs allows an adequate planning of the optimum moment to develop a certain capacity and/or learning, this moment being called the sensitive period (53). ...
... Determining the peak height velocity, which is the maximum height growth rate that occurs during the period of greatest growth, allow to the selection of training stimuli that will be promoted with different athletes (53). This is because the determination of the moment when the peak of growing velocity occurs allows an adequate planning of the optimum moment to develop a certain capacity and/or learning, this moment being called the sensitive period (53). ...
... The sensitive period is characterized as a period which the individual is particularly predisposed to learning, or susceptible to the influence of a particular stimulus (53). The analysis of several training factors reveals that there are optimal moments for the development of strength, endurance, speed, flexibility and acquisition of motor skills and these factors have been widely studied (54)(55)(56)(57)(58). ...
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... All females in this study surpassed their peak height velocity (PHV) age, and, as calculated using the maturity offset formula, 89.7% of participants were over a year past their PHV age (Moore et al., 2015). Females often experience greater accrued gains in mobility, flexibility and neuromuscular control in the years after PHV, peaking at approximately one-year after their PHV (Ford et al., 2011;Ghasempoor et al., 2018). This may be a factor in their lower level of dysfunction in movements predicated on mobility and flexibility (Ford et al., 2011;Ghasempoor et al., 2018). ...
... Females often experience greater accrued gains in mobility, flexibility and neuromuscular control in the years after PHV, peaking at approximately one-year after their PHV (Ford et al., 2011;Ghasempoor et al., 2018). This may be a factor in their lower level of dysfunction in movements predicated on mobility and flexibility (Ford et al., 2011;Ghasempoor et al., 2018). ...
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... However, considering the above differences in competitive levels, it is important to determine the main contributing factors that influence the training load management [19,20]. From a long-term development perspective, managing physical qualities is an important factor in improving a player's future sporting career [21,22]. Load discrepancies based on starting status may require compensatory training sessions or competitive breaks optimization periods [23,24]. ...
... The eligibility for training data was based on previous studies in sub-elite youth football [10,11] considering the following inclusion criteria: (a) young football players aged between 13 and 20 years old [1]; (b) at least five years of competitive experience in football [21]; (c) training files containing at least 35 consecutive minutes of playing time on the pitch [25]; (d) training data considered a competitive one-game per week schedule and complete full training sessions three times a week (~90 min) [10,11]. The exclusion criteria were: (a) total or partial absence from training due to data collection errors, injury events, rehabilitation sessions, individual training sessions, early withdrawal, and/or missing training; (b) football players aged under 13 or over 20 years; (c) the goalkeeper participated in the training session but was excluded from the analysis [1]. ...
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Compensatory training sessions have been highlighted as useful strategies to solve the differential weekly training load between the players’ starting status. However, the influence of the players’ starting status is still understudied in sub-elite youth football. Thus, the aim of this study was to compare the weekly training load on a standard microcycle in starters and non-starters of a sub-elite youth football academy. The weekly training load of 60 young sub-elite football players was monitored during a 6-week period using an 18 Hz global positioning system (GPS), 1 Hz telemetry heart rate, rating of perceived exertion (RPE), and total quality recovery (TQR). The total distance (TD) covered presented a significant difference between starters and non-starters with a moderate effect (t = −2.38, Δ = −428.03 m, p = 0.018, d = 0.26). Training volume was higher in non-starters than in starter players (TDStarters = 5105.53 ± 1684.22 vs. TDNon-starters = 5533.56 ± 1549.26 m). Significant interactive effects were found between a player’s starting status, playing time, and session duration in overall training load variables for within (F = 140.46; η2 = 0.85; p < 0.001) and between-subjects (F = 11.63 to 160.70; η2 = 0.05 to 0.76; p < 0.001). The player’s starting status seems to only influence the training volume in sub-elite youth football, unless one considers the covariance of the playing time and session duration. Consequently, coaches should prioritize complementary training to equalize training volume and emphasize similar practice opportunities for non-starters. Future studies should evaluate the gap between training and match load, measuring the impact of recovery and compensatory sessions.
... Frameworks for athlete development typically attempt to combine both best practice and experience underpinned by high-quality up-to-date research (9,10). Research in football generally seeks to provide evidence regarding the value and application of business solutions addressing technical, tactical, physical, and psychological components of football performance, thereby supporting practitioners to make evidence-based decisions on the practices they may employ within an applied setting (8). ...
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... Sabendo que os 10 anos e as 10.000 horas não constituem uma regra infalível e uniforme, a ideia base é de que nada substitui a prática. (Ford et al., 2011). ...
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Background Moderate to very large correlation between internal training load, external training load, and recovery status have been reported in elite youth football. However, little is known about subelite youth football training environments. Objective The purpose of this study was to assess the association between training load and recovery status in young subelite football players. Methods Twenty under-15, twenty under-17, and twenty under-19 players were monitored over a 6-week period during the first month of the 2019-2020 competitive season. The global positioning system technology (GPS) was used to collect external training load variables. The internal training load variables were monitored using the rating of perceived exertion (RPE) scale and session RPE (sRPE). The recovery status was assessed by the total quality recovery (TQR). A total of 18 training sessions and 324 observation cases were collected. Results Small to moderate correlation between internal and external load was observed ( r = -0.316 to 0.136, p < 0.05). Correlations between recovery status and external load were moderate for U15 ( r = -0.326 to -0.240, p < 0.05), U17 ( r = -0.316 to 0.136, p < 0.05) and U19 ( r = -0.301 to 0.282, p < 0.05). The association between perceived exertion and external training load is only significant for U19 subelite football players. Conclusion Current research suggested that subelite youth football players were more likely to have lower capacity to judge training exertion. Additionally, recovery status was positively correlated with acceleration and deceleration movements. This study provides a new overview about training load and recovery in subelite youth training environment. Future researche should examine the between- and within-individual nonlinearity across training load and recovery variations.
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