-
S2-42
BRIEF REVIEW
International Journal of Sports Physiology and Performance,
2017, 12, S2-42 -S2-49
© 2017 Human Kinetics, Inc.
The author is with the Athletics Dept, University of Oregon,
Eugene, OR. Address author correspondence to
[email protected].
http://dx.doi.org/10.1123/ijspp.2016-0334
Managing the Training Load in Adolescent Athletes
Andrew Murray
While historically adolescents were removed from their parents
to prepare to become warriors, this process repeats itself in
modern times but with the outcome being athletic performance. This
review considers the process of developing athletes and managing
load against the backdrop of differing approaches of conserving and
maximizing the talent available. It acknowledges the typi-cal
training “dose” that adolescent athletes receive across a number of
sports and the typical “response” when it is excessive or not
managed appropriately. It also examines the best approaches to
quantifying load and injury risk, acknowledging the relative
strengths and weaknesses of subjective and objective approaches.
Making evidence-based decisions is emphasized, while the
appropriate monitoring techniques are determined by both the
sporting context and individual situation. Ultimately a systematic
approach to training-load monitoring is recommended for adolescent
athletes to both maximize their athletic development and allow an
opportunity for learning, reflection, and enhancement of
performance knowledge of coaches and practitioners.
Keywords: youth, sport, stress, dose, response
Athlete Development: A Modern Phenomenon?
The 2007 film “300” portrayed the Spartan army in the battle of
Ther-mopylae and mentioned the process of agoge, the rigorous
education and training regimen mandated for all male Spartan
citizens. The males were meant to compete in athletics and in
battle. The training involved learning stealth, military training,
pain tolerance, and social preparation. The process typically
started at age 7 when the boy was separated from his mother and
went through a process of training to become a soldier in the
Spartan army. This process involved fighting, starvation and where
necessary stealing and killing. The boys were taught to show no
pain across the trials and no mercy to others—if they were
successful in their training they returned to their families as a
Spartan or otherwise they were outcast from society.
This process may have happened over 2300 years ago but now the
process of athlete development moves along similar lines. Young
athletes can be separated from their families as they enroll in
acad-emies or travel overseas for opportunities.1 Coaches and
practitioners attempt to develop them as athletes, using the
long-term athlete-development model and chasing 10,000 hours of
deliberate practice. They “force” them to train and compete for
their development and in some systems, they deal only with the
champions who succeed in the system (perhaps in spite of). Despite
this increased investment in youth academies, little is known about
the physiological implications of putting adolescents through
structured, intense training regimens.2
Developing Athletes With Sound Scientific Principles
The first consideration for every organization that is working
with youth athletes is to consider if the objective/aim of the
institution is about sport for all or sport for the elite. A recent
consensus state-
ment from the IOC mentions the need for development of healthy,
capable, resilient young athletes “while attaining widespread and
enjoyable participation for all levels of athletic
achievement.”3(p843) Many institutions and/or national systems that
develop talents look to use a broad talent pool and are comfortable
with a “survival of the fittest” approach. While this has seen
overuse injuries in young people become more common4,5 there is
evidence for a relation-ship between training load, (load can be
defined as “the cumulative amount of stress placed on an individual
from multiple sessions over a period of time, external workloads
performed or the internal response to that workload”6[p992]) and
injury and illness in young athletes.7
The Darwinian approach common in large talent pools such as
China and Russia sees the “survivors” (those that are genetically
predisposed to adapt to higher training loads8) emerge from
ado-lescence with fewer injuries and a greater training volume
behind them.9 In countries where the talent pools are limited, the
develop-ment of adolescent athletes should be directed to preserve
the best talents (ie, minimize injury) and develop them to compete
at the senior level. For this reason, managing training loads
appropriately and understanding how to apply progressive overload
to young cohorts can be a successful strategy to retain a large
talent pool in countries with big populations and to preserve the
limited talent pools when the population is small.
Training Young Athletes: Training Dose and Adaptations
Based on a perceived change in the focus in adolescent sport
from participation to specialization, studies have developed
guidelines on how to train youth athletes that caution against
intense training in a single sport10; where intensity and
specialization are encour-aged.11 Guidelines have nowadays been
provided to advise that young athletes should not spend more hours
per week than their age playing sport. They should avoid
specializing in one sport before adolescence and should have at
least 1 day a week off from training.4 There is no specific
information if this advice is aimed at the elite (by
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IJSPP Vol. 12, Suppl 2, 2017
Managing Adolescent Training Load S2-43
elite in this context we consider athletes training more than 14
h/wk) or recreational adolescent athlete. The reality of training
volumes in terms of hours and age has been examined in elite youth
track and field athletes.12 Looking at a sample of distance, track,
jumps, throws, and multievent athletes the typical training volumes
of 13- to 14-, 15- to 16-, and 17-year-old athletes was reported as
5.69 ± 2.53, 7.30 ± 3.3, and 8.92 ± 3.69 h/wk, respectively; all
below the advice to train “less than your age.” These training
exposures are similar to the ones reported in other youth athletic
studies13,14 but significantly less than the training hours of
elite youth athletes in gymnastics, tennis, and swimming.15 Young
male gymnasts age 15 averaged 14.7 h/wk, but the range was from 8.5
to 20 hours. Male swimmers of the same age averaged a little over
13 h with a range from 3.5 h to 22.5 h). In no case for the elite
populations reported in the literature does the “average” elite
performer do more hours training than their age, but this
particular oxymoron (average elite) reminds us that the exceptional
performers at any age are not aver-age and lie at the extremes.
A large variety of training exposures are also due to the sport
of choice for young athletes. In fact, while gymnastics and
swimming can be considered early specialization sports, track and
field is regarded as a late specialization sport with athletes
peak-ing in their mid- to late 20s. This typically determines an
earlier increase in training loads in these sports as compared with
late specialization sports due to the early competitive rewards
sought. For example in London 2012 the majority of female gymnasts
were under 18 years of age while there were 24 swimmers under the
age of 16.16 The downside of this approach in sports where early
specialization is not necessary is the possible shortening of
sporting careers. In track and field it has been shown that only 7%
of the top-20-ranked athletes at U-15 level are still ranked in the
top-20 ten years later.12 Burnout and/or athlete dropout are very
common in adolescents and the causes can be various but are most
likely to be because of injury or overreaching and overtraining (or
a combination).10,17
Research has shown that training intensity and load at 13 to 14
years and high intensity training at 15 to 16 years increases the
likelihood of sustaining an injury as a 13- to 17-year-old.12
Athletes who were forced to retire trained at a significantly
higher weekly intensity and trained “harder” at the age of 13 to 14
years. They completed a significantly higher yearly training load
at 13 to 14 years when part of an emerging talent squad and trained
at a significantly higher intensity throughout the year. This tells
us that having a better understanding of appropriate training load
patterns and training load management is important. Research from
England showed that individual sports featured highly in the number
of nonfunctional overreaching or overtraining cases possibly
suggesting that coaching prescriptions at this age might be
inappropriate and dangerous.17
Useful Approaches to Quantifying Training Load and Injury
Risks
The catastrophic outcome of injury in an adolescent athlete can
sometimes be identified not only in the interruption of
competi-tive activities, but also as the end of access to physical
activity and sport participation. For this reason, young athletes
should be properly managed so as to try and reduce the possibility
of injury. Within youth sport typically 20% of injuries are severe
(no sport for 4 wk or more), with chronic overuse injuries
accounting for up to 40% of all injuries.18 The typical injury
incidence is in a range of 1 to 10 injuries/1000 h, though based on
athlete exposure
this rate can be inflated in sports such as cross country
running (10.9–15 injuries/1000 exposures).19 The differing
definitions of injury rates highlight that the measurement of
“injury” needs a clear definition and a common language as given in
the AIS data dictionary:
Any recordable incident sustained while undertaking training or
competition related to the athlete’s sport that results in an
athlete being unable to participate in training or competition, as
planned by coaching staff, for greater than 24 hours.20(p20)
Recent work highlights these issues in longitudinal research21
and suggest that the management of load considering the
accumula-tion over the last week (acute) and month (chronic) to
measure the training stress balance22,23 and avoiding spikes in
training of more than 10% might represent a successful training
strategy to avoid injury.11,24,25 This concept has been mentioned
previously in the adolescent literature as a guideline to avoid
overuse injury.4 More recently a replacement for the term overuse
with training load error has been proposed.26 Regardless of the
nomenclature, measurement of load allows some form of
quantification and assessment of how to recover from catastrophe
and return to training.27
Previous studies have shown links between training load and
injury in adolescent populations. Cricket fast bowlers age 14.7 ±
1.4 years had 3.1 times the risk of an injury that affected
availability when they had less than 3.5 days rest between bowling
episodes.28 Soccer players age 16.5 ± 1.2 years showed higher risk
of traumatic injury if they trained more or had higher monotony or
strain.29 If they trained more they also had a higher risk of
illness. Another study suggested that a history of training volume
could have a protective benefit on groin injury in elite junior
footballers age 15 to 17.30 In baseball, pitchers age 8 to 14
showed a U-shaped rela-tionship where a moderate volume of pitches
was protective from injury, a low volume made no difference and a
high volume (>600 pitches in a season) gave a high risk of
injury which increased with each additional pitch.31,32 Volleyball
athletes age 16 to 18 showed an increased risk of jumper’s knee
with each additional hour they trained in a week (odds ratio [OR]
1.72) or each additional set they played (OR 3.88),33 although
another study in a similar group showed no difference in jump
frequency between asymptomatic and symptomatic athletes.34 There
may also be links between the types of sport and the injury risk.35
This is possibly related to the training types; that is, endurance
sports will generally have longer durations at lower intensity
while other sports may focus on higher intensity and lower
duration.
Work in track and field athletes has shown that across a sample
of 33 internationals (walkers, sprinters, endurance, jumpers, and
throwers) there was a threshold of less than 20% modified train-ing
that was a key factor in determining the likelihood of success.
Exceeding 20% modified training increases the risk of failure
regard-less of how it is reached.36 This 20% figure is remarkably
similar to AFL data that showed in a team sport that if you are
available for greater than 85% of training sessions then you should
last the year.37 Modifying the training load of first year
professionals in team sports has been suggested,38 but it is
unclear if this is objectively done and there are no guidelines in
the literature. While most data are currently drawn from adult
athletes, the opportunity to train is extremely important for the
adolescent athlete who is learning his craft and needs exposure to
the volume of training.
Recently, at the elite level the effect of missed training days
has been highlighted in a study analyzing self-reports of training
and illness symptoms of elite Norwegian cross-country skiers (N =
37) over a 9-year period.39 The 16 athletes in the group who
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IJSPP Vol. 12, Suppl 2, 2017
S2-44 Murray
had won individual medals at the Olympics or World
Champion-ships reported an average of 14 d/y with symptoms of
respira-tory or gastrointestinal infection, compared with 22 d/y
among the nonmedalists. Here we are not dealing with catastrophe
but the shades of gray between—the accumulation of small periods of
missed training can be just as devastating as long periods out to
injury in a truly elite cohort of athletes. Equal consideration
should be given to multiple single-day and -week absences as
multiweek absences.
This consistent absence can be considered an absence of
con-sistency in training and could potentially lead to
underperformance. Within human resources there is a formula for
dealing with absence that could be implemented in sport to quantify
training consistency. The Bradford factor (BF) has thresholds of
45, 100, and 900. These relate to increasing levels of concern with
the absence and, in the human resources world, escalate to concern,
disciplinary action and dismissal. In the sport setting this
approach could provide guidelines to reassess and modify an
athletes’ program.
BF = (number of absences)2 × total days of absence
We have analyzed the data of an adolescent sports academy to
highlight the benefit of this approach (Figure 1). The top-10 young
athletes (according to their BF) were analyzed over 7 months. The
highest BF (3060 AU) was associated with a young athlete in his
first year of the full-time program, the second-highest with an
ath-lete in his second year, and the third with an athlete in his
fourth year (2475 and 931 AU, respectively). This may reinforce
what previous studies suggested: managing the transition into
full-time training may be highly important to allow a progressive
accumula-tion of training at a young age with limited risks, in
particular as it is hypothesized that every time-loss event affects
one’s ability to resume the preinjury training load.40
Objectifying Decision Making
Athletes’ training and competition data can be used to quantify
the risk associated with changes in load. The review of these data
should drive decision making to create a safe and successful
envi-ronment.7 All decisions pertaining to athletes should
increasingly be based on evidence—be that about performance,
training load or injury. It is commonplace in elite sport to use a
data management system to underpin decisions and to measure the
impact coaches and service providers have on performance. Indeed,
quantifica-tion and monitoring of both the dose (training load) and
response (performance) is imperative to maximize the likelihood of
optimal athletic preparation.
Coaches and practitioners attempt to modify and control the dose
to maximize the positive influences and minimize the negative
effects. This modification occurs on the basis of information they
obtain through various feedback methods on the response. Any data
collected should assist the decision-making process to ultimately
provide meaningful information that informs the decision or
training outcome and becomes knowledge on which to base future
decisions. The transition of data into knowledge can provide a
deeper level of understanding.41 Putting data in context transforms
numbers and evidence to information. Summarizing information in
meaningful outcomes can inform and affect a performance plan. It
should be the case that performance discussions account for the
data and do not rely solely on the opinion of influential members
of the group. Which markers are important to each sport needs to be
balanced alongside what is practical to be monitored and ultimately
how they will be stored and acted on to influence performance.
Figure 2 shows output from of heart-rate data from an
ado-lescent endurance athlete—the highlighted area is a training
camp (period of intensified training). This figure highlights a
number of
Figure 1 — The Bradford factor (BF) may give guidelines to
reassess and modify an athlete’s program based on absence. It is
calculated by (number of absences)2 times the total days of
absence. (A) The BF heat map (based on injury occurrence and
average duration [d] of each) highlights how values can increase
with changes in either variable. (B) Example data for athletes in
an adolescent academy in March when the season started the previous
September.
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IJSPP Vol. 12, Suppl 2, 2017
Managing Adolescent Training Load S2-45
metrics that are tracked from session type to time spent in
specific heart-rate zones,42 load calculations, and subsequent
calculations of load and its derivatives such as monotony,
strain,43 and training-stress balance (TSB)44 are also presented.
In this example we see an athlete with high monotony and strain
values across this period of intensified training, which is to be
expected from the design. We do not however see an elevation of the
TSB to a level that would cause concern as suggested in the
literature (>1.25).11
The use of objective data with youth athletes is fundamental for
appropriate training load monitoring and reliance on simple methods
like session RPE may be of limited application. The main source of
concern stems from the ability of young people to be able to
reli-ably assess the perceived exertion,45 as well as potential
language46 and cultural issues with anchoring scales when
translated from the original constructs. This means that
objectively, depending on the sport, you can measure a number of
factors such as volume, loads, jumps,47 or pitch counts48,49
without relying too much only on the perception of load.
The collection of data can initially be wide as we decide what
to measure and then narrow over time as we attempt to ask questions
that can create a collective series of statements to form a
definite proposition. Having the data is important, as it can
reflect differences in coaching approaches and potential impact on
athletes. Coaches have an enormous influence on young athletes, not
only with regards to the emotional elements of developing
youngsters but also in the loading paradigms used.
Changing a coach at a young age can also represent a change in
the risks of injury for young athletes due to the differences in
coaching philosophies, experience, planning, and perceived needs
for high workloads. As the literature is limited with regards
longi-tudinal studies of youth training loads, it is difficult for
coaches to
develop appropriate training programs for youngsters. There is a
risk of adult-type prescriptions being applied. Different coaching
styles not only refer to teaching aspects but are also reflected in
differences in the training dose. As we monitor closely training
loads in our academy we routinely analyze not only year-on-year
approaches but also coaching styles in terms of training
prescription. Figure 3 shows an individual endurance athletes’
average volume of train-ing performed and the velocity in track
sessions as an acute (7-d), chronic (28-d) load and the balance
between the 2. The dashed line shows the break between seasons.
Each individual box highlights a different coach leading the
program. The first was a coach who favored low-volume,
high-intensity workouts. The second from a coach favoring
progressions in volume before speed. The final coach with a
moderate approach using both volume and speed to get a desired
result. Of course we also see differences in the phase of the
season but this raises more questions about what is important to
monitor and hence manipulate across the year. The current
literature does not provide useful guide-lines on how to use this
information to suggest appropriate training loads for young
athletes. In adults it seems there is consensus with a 7- and
28-day moving average balance of 0.8 to 1.3 across a number of
sports.11 For adolescents this level may be different and it may be
also linked to the training experience (in terms of years of
full-time training). The periods to use in this equation may also
differ. There may also be different latent periods for injury to
occur following an inappropriate training load for the age and
training experience of the athlete.
Within the limits of what is ethically sound in young athletes,
some use of biomarkers could be implemented. Recent research has
highlighted the individuality of responses in a number of blood
markers during an intense training camp.50 The authors
identified
Figure 2 — Example of heart-rate (HR) data stored in
data-management-system format for 1 athlete across a period of
intensified training including a camp (bordered). This includes
percentage of time in each HR zone (Z5 = 90–100% of HR max, Z4 =
80–90%, Z3 = 70–80%, Z2 = 60–70%, and Z1 = 50–60%), Edwards score
(calculated by accumulated time in each zone42), TL/min (relative
training load; Edwards score/session duration), load bal-ance (7-d
training load/28-d training load), daily average Edwards score
(average Edwards score over last 7 d), work load (WL; sum of
Edwards score in last 7 d), monotony43 (daily mean of Edwards/SD of
Edwards), and strain43 (product of weekly Edwards and
monotony).
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S2-46 IJSPP Vol. 12, Suppl 2, 2017
Fig
ure
3 —
Tra
inin
g im
pose
d on
1 a
thle
te h
ighl
ight
ing
a ch
ange
in c
oach
ing
appr
oach
. The
top
grap
h sh
ows
the
volu
me
of s
essi
ons
(sum
of d
ista
nce
cove
red
in m
) and
the
botto
m th
e av
erag
e ve
loci
ty
(m/s
; int
ensi
ty)
of th
e se
ssio
n. E
ach
data
poi
nt is
rep
rese
ntat
ive
of a
trai
ning
day
; the
acu
te (
7-d
rolli
ng a
vera
ge),
chr
onic
(28
-d r
ollin
g av
erag
e), a
nd tr
aini
ng-s
tres
s ba
lanc
e (T
SB: a
cute
:chr
onic
) ar
e sh
own
for
each
day
acr
oss
the
peri
od. T
he 3
dif
fere
nt c
oach
es a
nd th
eir
appr
oach
es a
re h
ighl
ight
ed b
y th
e 3
diff
eren
t-co
lor
boxe
s: th
e fir
st lo
w v
olum
e an
d hi
gh in
tens
ity (
left
), th
e se
cond
pro
gres
sion
s in
vol
ume
befo
re s
peed
(ce
nter
), a
nd th
e th
ird
man
ipul
atio
n of
vol
ume
and
inte
nsity
(ri
ght)
. The
end
of
1 se
ason
and
sta
rt o
f th
e ne
xt is
sho
wn
by th
e da
shed
ver
tical
line
.
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Managing Adolescent Training Load S2-47
differing levels of responses in specific markers dependent on
the type of training across a 7-day period. For creatine kinase
(CK) in endurance athletes they reported an increase of 54 units,
while the strength and high intensity interval training groups
determined acute CK increases 10 to 15 times larger.
In our experience, despite the fact that adolescent athletes are
reported to present CK responses to training lower than the adult
counterparts,51,52 we sometimes observe marked signs of muscle
damage in our cohorts. The example in Figure 4 shows an increase in
CK of approximately 1000 units in just 5 days. This supports our
view that each athlete is an individual and needs to be treated as
such and only evidence collected routinely can help drive
meaningful changes in a training program.
While measures of external loads can be easier to collect and
are potentially more reliable, they only provide limited
information about the implications of the training dose to the
athlete. Efforts should be made to quantify aspects of internal
load measures across all modalities of training where appropriate
and within what is reasonably expected and ethically viable. Young
cohorts should also be assessed with regards to external stresses
contributing to the overall stress experienced by young
athletes.4,10,53 There is the accumulation of the daily schedule of
training and life across the week, which sees an accumulation of
fatigue toward the end of the week in athletes enrolled in sporting
academies and/or structured
training. There are also periods of high stress in life in
general (eg, family and academic commitments). There comes a point
that there may be a need to draw the line with a “Goldilocks” type
approach to find the right training. The decision about what the
correct amount of load is should ultimately come from the team
supporting the individual, in conjunction with the athlete and be
based on the available evidence.
Cautionary notes should be made about any cultural or language
differences that may influence perception of what is stressful,
under-standing of the implications and consequences, and acceptance
of the need to communicate with the coach or coaching staff if
there is a feeling of exhaustion/need to withdraw from training.
While internal load measures such as RPE were commonly used in
adult athletes7 this does not mean that all adolescents understand
and use the scale appropriately.45,46 Ultimately communication
between coach and practitioner is key to serve the needs of the
athlete.
SummaryThe management of training load in young athletes is
fundamental to guarantee a long sporting career and/or engagement
in sporting activities. For this reason, various monitoring
approaches should be implemented which ideally limit the exposure
to invasive mea-sures. The choice of monitoring techniques and
methods should be
Figure 4 — Individual morning monitoring responses to an
intensified training period in an endurance athlete from the day
before travel and throughout. Hydration scores measured via urine
(mOsm; bars), creatine kinase via blood (CK; black line; U/L), and
urea via blood (mg/dL; gray line). The SD is shown via error bars
for the blood measures.
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S2-48 Murray
determined by what is important to the sporting context and the
individual situation and take into account social/behavioral norms
(in particular when psychometric tools are implemented). These data
then need to be gathered to have a holistic approach to the
quantification of the training dose and communicated to the
coach-ing staff with the view of delivering not only appropriate
training corrections but also capture learning for future cases
(ie, turning these data into knowledge). Without a systematic
approach to training load monitoring in young athletes there is no
opportunity for learning and reflection and training prescriptions
may continue to be adapted versions of adult programs. Adolescent
athletes are on a journey to adulthood and their development should
be seen always as a long term project. Future research efforts
should therefore focus on defining appropriate training doses and
risk thresholds for young athletes to make sure that modern
coaching approaches are employed to develop resilient athletes and
reduce the risk of burnout.
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