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Strength Training for
Endurance Athletes:
Theory to Practice
Caleb D. Bazyler, MA, Heather A. Abbott, M.Ed, Christopher R. Bellon, MA, Christopher B. Taber, MS, and Michael H. Stone, PhD
Department of Exercise and Sport Science, East Tennessee State University, Johnson City, Tennessee
Conflicts among coaches exist
regarding the role of strength
training for endurance athletes
despite over 25 years of research
supporting its efficacy and applica-
tion (34-36,46,47,58,64,65,67,71,82).
Historically, resistance and endurance
training have been viewed as training
modalities at opposite ends of a contin-
uum with divergent adaptations (17,41).
In a recent meta-analysis, Wilson et al.
(92) reported an inverse relationship
between frequency and duration of
endurance training and subsequent
changes in hypertrophy, strength,
and power. Alternatively, strength
training has been shown to have
a positive effect on endurance perfor-
mance (46,49,51,65,73). Previous research
reports that concurrent strength and
endurance training can increase endur-
ance performance in high-level athletes
to a greater extent than endurance train-
ing alone (46,47,58,64,65,82). The inter-
ference effects between strength and
scope of this review and have been
discussed extensively in previous stud-
ies (23,24,44,54,92). Endurance in
sport has been defined as the ability
to maintain or repeat a given force or
power output (80). Endurance training
can be further subdivided into low-
intensity exercise endurance (LIEE)
and high-intensity exercise endurance
(HIEE). LIEE can be defined as long-
duration endurance activities or the
ability to sustain or to repeat low-
intensity exercise. HIEE can be defined
as the ability to sustain or to repeat
high-intensity exercise and has been
associated with sustained activities of
#2 minutes (80). Competitive endur-
ance athletes need more than enhanced
aerobic power (V
max) and LIEE
(34). Requirements for endurance ath-
letes should also include muscular
strength, anaerobic power, and HIEE
(34-36,46,58,68,82). Furthermore,
strength training has been shown to
positively influence both LIEE and
HIEE across a spectrum of endurance
events with greater effects observed in
HIEE (34,46,50,58,82,83).
Strength can be defined as the ability to
produce force (76). Strength is a skill,
which can be expressed in a magnitude
of 0–100% (80). In the current endur-
ance literature, 2 primary forms of
strength training have been investigated:
maximal, high-force, low-velocity,
strength training (HFLV) and explosive,
low-force, high-velocity strength train-
ing (LFHV). Previous studies have
examined the effectiveness of concurrent
endurance and circuit resistance train-
ing, but have demonstrated inferior re-
sults (49,73,84). Maximum strength can
be defined as the maximal amount of
can exert against an external resistance
and corresponds with the high-force,
low-velocity portion of the concentric
force-velocity relationship (15,81). The
term “explosive strength training” has
been used in previous studies in refer-
ence to low-force, high-velocity training
(0–60% 1 repetition maximum [RM]
loads) with maximal movement intent
periodization; endurance performance;
concurrent training
Copyright ÓNational Strength and Conditioning Association Strength and Conditioning Journal | 1
(59,69). The use of this terminology is
misleading, as explosive strength (alter-
natively defined as rate of force develop-
ment [RFD] or power output) (15,81),
can be developed across a continuum of
loads (0–100% 1RM) (19).
In fact, HFLV training has been shown
to elicit improvements in explosive abil-
ity (measured as power output) across
a larger spectrum of loads compared
with LFHV training in weak subjects
(20). The ability to improve power out-
put across a larger spectrum of loads,
among other reasons, likely explains
why HFLV and endurance training may
provide superior alterations in endurance
performance compared with concurrent
LFHV and endurance training for weak
endurance athletes (9,60,73). Thus,
explosive strength training performed
in previous research on endurance per-
formance is alternatively defined here
as LFHV training.
Previous research on untrained and rec-
reationally trained individuals has dem-
onstrated that concurrent strength and
endurance training can augment LIEE
and HIEE, aerobic power, maximal
strength, muscle morphology, and body
composition (27,28,32,34,42,47,49,71,85).
There is also research demonstrating
HFLV and LFHV strength training en-
hance performance in high-level endur-
ance athletes (58,59,61,64,66,72,73). In
a recent review of the literature, Beattie
et al. (10) reviewed results from 26 studies
examining the effects of strength training
on endurance performance of well-
trained athletes (10). Their findings
showed that strength training is effective
for improving movement economy,
velocity at V
max (vV
max), power
output at V
max (wV
max), maximal
anaerobic running test velocity (V
and time trial performance, and suggested
that HFLV strength be developed before
LFHV strength in endurance athletes
with limited strength training experience.
Considering these ndings, this article
focuses primarily on studies examining
the effects of HFLV and LFHV strength
training on HIEE and LIEE of moderate
to high-level endurance athletes. The
purpose of this review is twofold: to elu-
cidate the utility of resistance training for
endurance athletes, and provide the prac-
titioner with evidenced-based periodiza-
tion strategies for concurrent strength
and endurance training for competitive
endurance athletes.
In one of the earliest studies examining
the effects of concurrent strength and
endurance training on HIEE, Hickson
et al. (34) had moderately trained
max: 60 mL
ners and cyclists perform 10 weeks of
endurance and HFLV strength training
(.80% 1RM). They reported improve-
ments in treadmill running (13%) and
ergometer biking (11%) to exhaustion
at maximal work rates (4–8 minutes)
and cycling to exhaustion (20%) at 80%
max (33). In addition, there were no
statistical changes in muscle fiber cross-
sectional area or thigh girth, although
1RM leg strength increased on average
by 30%, which suggests primarily neural
In a more recent investigation by
Aagaard et al. (2), highly trained
national team cyclists (V
max: 71–75
) performed HFLV
strength training (mostly 5–6RM loads)
for 16 weeks concurrently with regular
endurance training. The strength and
endurance training group improved
average power output and total distance
covered in a 45-minute cycling test
(8%), whereas the endurance only
group did not. Concomitant increases
were found for maximal voluntary iso-
metric contraction (MVIC) of the knee
extensors (12%), peak RFD (20%),
mean power output in 5 minutes of
all-out cycling (3–4%), and mean power
output during a 45-minute time trial
(8%) with no changes in muscle fiber
area, capillarization, and V
max in
the strength and endurance training
group (2). The superior LIEE perfor-
mance in the strength and endurance
training group may have been due to
a shift in vastus lateralis muscle fiber
type from type IIx to type IIa.
Increased MVIC as a result of strength
training may enhance HIEE and LIEE
by decreasing the relative external
resistance, which reduces the number
of motor units required to produce
a given amount of force (13). In addition,
improvements in RFD contributed to the
improved LIEE performance by reduc-
ing time to reach peak concentric forces
necessary to produce the desired move-
ment and increasing the length of the
eccentric phase lending to greater muscle
perfusion and longer capillary mean tran-
sit times (1,86).
Strength training has been reported to
increase musculotendinous unit stiffness
(21,43,51,87). This results in an enhanced
ability to store elastic energy in the series
and parallel elastic component during
eccentric muscle actions, which in turn
increases concentric muscle force. This
is thought to be one of the reasons
why improvements in running economy
(35,51,81), cycling economy (8,12,66,83),
and cross-country skiing economy
(35,36,58) have been observed after
a period of HFLVstrength and endur-
ance training. However, not all studies
show improvements in movement econ-
omy as a result of strength training
(2,9,14,45,46,64) possibly due to differ-
ences in training variables (e.g., mode,
volume-load, frequency, duration) and
subjects’ training status. For example,
elite athletes who already possess a high
level of efficiency may not further
improve movement economy with
strength training (64).
The superior performance changes with
heavier strength training may be attrib-
uted to greater increases in musculoten-
dinous unit stiffness, greater recruitment
of high-threshold motor units, and
greater capacity to store and release elas-
tic energy, which lead to a right and
upward shift in the force-velocity and
force-power relationships (58). This does
not preclude LFHV strength training for
endurance athletes because, although the
loads used are typically lighter, there are
notable improvements in RFD, which
has been linked to greater movement
economy and enhanced LIEE and HIEE
performance (59,72,85,88).
Strength Training for Endurance Athletes
Furthermore, an increase in musculo-
tendinous stiffness has a greater applica-
tion to running than cycling because of
the greater contribution of the stretch-
shortening cycle (69). In contrast,
strength training induced improve-
ments on cycling economy and perfor-
mance are more evident at the end of
long cycling tests. Rønnestad et al. (66)
found that cycling economy improved
more during the final hour of a 185-
minute cycling test as a result of HFLV
strength with endurance training (3 3
4–10RM, 2 d/wk for 12 weeks) com-
pared with endurance training alone
(66). They also reported reduced HR
and blood lactate concentrations dur-
ing the final hour in the strength-
trained group. In addition, the subjects
completed a 5-minute sprint at the end
of the 180 minutes during which the
strength-trained group improved average
power production, but the endurance on-
ly group did not. This “anaerobic reserve”
may have been due to increased contrac-
tile strength of type I fibers delaying the
contribution of the less economical type
II fibers, sparing them for the sprint finish
(69). The “anaerobic reserve” for late race
sprint performance may also be ex-
plained by the sparing of substrate stores
within a muscle. Goreham et al. (25) re-
ported that 12 weeks of HFLV strength
with endurance training (3 36–8RM,
3 d/wk for 12 weeks) resulted in greater
muscle phosphocreatine and glycogen
content, and lower lactate concentrations
at the end of a 30-minute cycle at 72%
max compared with endurance train-
ing alone (25).
Previous research has shown that endur-
ance athletes who strength train with
loads .70% 1RM exhibit larger changes
in movement economy and endurance
performance than endurance athletes
who strength train with lighter loads
(36,48,73). Sedano et al. (73) reported
greater magnitudes of change in running
economy, countermovement jump
(CMJ) height, vV
max, and 3-km
time trial performance after 12 weeks
of heavy strength training (.70%
1RM) compared with lighter strength
training (,40% 1RM) and a control
group (circuit training) in Spanish
national level runners (V
max .65
Guglielmo et al. (26) found that after
only 4 weeks of concurrent running
and heavy strength training (3–5 sets
at 6RM loads), there were larger mag-
nitudes of change in running econ-
omy, 1RM strength, and CMJ height
compared with concurrent running
and lighter strength training (3–5 sets
at 12RM loads) in middle- and long-
distance runners (V
max ;61.9
) who competed at
the regional and national level (26).
Mixed results have been reported for
effects of HFLV strength training on
cycling economy; however, there are
still improvements in LIEE and HIEE
performance (2,64,65,83). Furthermore,
previous findings suggest that HFLV
strength training may exhibit its effects
most prominently during high-intensity
bouts of endurance events (9,49,66),
although there is evidence to the con-
trary (23,45) (Table 1).
LFHV strength training has been re-
ported to elicit improvements in HIEE
and LIEE performance (59,74,85);
however, research conclusions are
mixed (7,45,60) (Table 2). Paavolainen
et al. (59) found that LFHV strength
training (,40% 1RM) improved 5k run
time, running economy, V
sprint speed, and distance covered on
a 5-jump test in male cross-country run-
ners (V
max ;64.4 mL
whereas no changes in these measures
were observed in the endurance only
group (59). The LFHV strength training
involved various plyometric exercises
and short sprints (20–100 m), which
suggests that although the absolute bar-
bell loads during strength training ses-
sions were relatively light, the forces
placed on the musculoskeletal system
were much larger than to what the ath-
letes were previously accustomed.
Considering that gaining body mass is
a concern for endurance athletes, one
of the purported benefits of LFHV
strength training is the lower degree
of muscle hypertrophy compared with
HFLVstrength training (28,70), but still
being able to achieve increases in
strength. In addition, increased muscle
fiber cross-sectional area (CSA), maxi-
mal strength, and power output can be
diminished or fully blunted by concur-
rent strength and endurance training
with the degree of decrement depend-
ing on the mode, frequency, and dura-
tion of endurance training (2,14,34,42).
Rønnestad et al. (64) found that increased
CSA of the quadriceps muscle was asso-
ciated with increased peak power output
and cycling time trial performance after
combined heavy strength training
(twice/week, 3 34–10RM) and endur-
ance training in well-trained cyclists with-
out a noticeable change in body mass
(64). Therefore, altering the strength to
body mass ratio should be more of a con-
cern for endurance athletes than body
mass alone. Furthermore, although in-
creases in “nonfunctional” hypertrophy
may be detrimental to performance
(3,86,91), increases in task specific
hypertrophy may be an important factor
in enhancing endurance performance,
as the typical ectomorphic endurance
athlete is unlikely to gain significant
amounts of hypertrophy through
strength training (89).
It has been suggested that LFHV
strength training may provide an addi-
tive effect to those elicited by HFLV
strength training on HIEE and LIEE
performance (85). Taipale et al. (85)
tested this hypothesis by dividing endur-
ance runners into 3 groups (LFHV,
HFLV, combination) and found no dif-
ferences between groups in measures of
strength (1RM), power (CMJ height),
and endurance performance (85). Con-
sidering there is a delay between when
a training stimulus is implemented and
the subsequent effects on perfor-
mance (90), a sequenced approach
may be more appropriate than trying
to improve strength, power, and endur-
ance simultaneously (15,81).
The primary goals of any successful
training program are to reduce the likeli-
hood of injury and optimize perfor-
mance (81). Before designing a training
Strength and Conditioning Journal | 3
Table 1
Effects of concurrent HFLV strength training and endurance training on HIEE and LIEE
Study Athletes V
Strength training HIEE LIEE
Støren et al. (82) 17 M and F well-trained
59.9 4 34RM, 33’s/wk for 8 wk 21.3% increase in TE at MAS
Jackson et al. (39) 23 M and F cyclists with
.0.5 y competing
52 4 34RM, 33’s/wk for 10 wk NS for vV
max NS for 30-km TT
Levin et al. (45) 14 M cyclists with .1y
62.8 4 35RM, 33’s/wk for 6 wk
Control .ST for PP during
last 1-km sprint
NS for 30-km TT
Rønnestad et al.
20 M and F well-trained
66.4 4–10RM, 23’s/wk for 12 wk 4.2% increase in W
7% increase in MP during final
5 min of 185 min TT
Rønnestad et al.
20 M and F national
level cyclists
66.4 4–10RM, 23’s/wk for 12 wk 9.4% increase wingate PP,
4.3% increase in W
6% increase in MP during 40-min
Rønnestad et al.
12 M and F national
level cyclists
66.3 4–10RM, 23’s/wk for 25 wk 8% increase in W
increase wingate PP
Rønnestad et al.
17 M national/
international cross-
country skiers
66.2 3–5 34–8, 4–5 33–5RM, 23’s/
wk for 12 wk
NS in 7.5-km rollerski TT
Rønnestad et al.
16 M national/
international cyclists
75.5 4–10RM, 23’s/wk for 10 wk,
13/wk for 15 wk
3% increase in W
earlier peak torque in
pedal stroke
6.5% increase in MP during
40 min TT
Sunde et al. (83) 13 M and F competitive
61.1 4 34RM, 33’s/wk for 8 wk 17.2% increase TE at MAP
Aagaard et al. (2) 14 M international level
72.5 3 312, 3 310, 3 38, 2–3 3
6RM, 2–33’s/wk for 16 wk
8% increase in 45-min TT
Hoff et al. (36) 15 F cross-country
skiers, trained
8.8 h/wk
55.3 3 36RM (pulldowns), 33’s/wk
for 9 wk
137% increase in TE at W
Hoff et al. (35) 19 M well-trained cross-
country skiers
69.4 3 36RM (pulldowns), 45 min/wk
for 8 wk
56% increase in TE at vV
˚s et al. (58) 19 M well-trained cross-
country skiers with
.5 y competing
61.2 3 36RM (pulldowns), 45 min/wk
for 9 wk
61% increase in TE at vV
Strength Training for Endurance Athletes
program, however, the coach and the
athlete must understand that training is
a comprehensive process that harmo-
nizes a myriad of factors to foster athlete
development. Figure 1 depicts some of
these factors that affect athletic perfor-
mance. Therefore, the sport coaches,
strength and conditioning staff, and
sports medicine professionals each play
an important role within their own dis-
ciplines to contribute to an athlete’s
development. In addition, the manage-
ment of external stressors in the athlete’s
daily life is also an important component
in the optimization of performance.
To achieve this objective, however, train-
ing variables must be integrated in
a sequence over the course of the train-
ing process (79). The training process
is traditionally organized into 3 basic
levels: macrocycles, mesocycles, and
microcycles (79). A macrocycle is
a long-duration training cycle, typically
classified as 12 months of training, which
are composed of multiple mesocycles.
Mesocycles are moderate-length periods
of training, which can focus on develop-
ing specific fitness characteristics within
the macrocycle. Finally, each mesocycle
is composed of shorter training periods
referred to as microcycles (79). The tool
used to structure each phase of training
within a macrocycle is referred to as an
“annual training plan” (15).
More specifically, the annual plan is
a long-term training template used to
guide the coach and athlete in the
design and implementation of vari-
ous training phases (15). The annual
training plan can be separated into
phases: the general preparatory phase,
competitive phase, peak phase, and
active rest (Figure 2). For a detailed
description of each phase, the reader
is encouraged to examine the work of
Bompa and Haff (15).
To reduce the likelihood of injury and
maximize athletic performance, strength
and conditioning professionals should
organize training adaptations in a logical
manner to minimize fatigue and high-
light technical and fitness characteristics
(e.g., strength, speed, endurance, etc.) at
Table 1
Losnegard et al.
19 M and F national
level cross-country
64.7 3 36–10, 3 35–8, 4 38, 3 3
4–6RM, 1–23’s/wk for 12 wk
NS in 20, 40, 60, 80, and
100 m velocity during
sprint roller skiing
7% increase in 1.1-km double
poling TT, increase in W/kg
during 5-min double poling
Millet et al. (51) 15 elite/international
level triathletes
68.7 3 35, 4 35, 5 35RM, 23’s/wk
for 14 wk
2.6% increase in vV
Hausswirth et al.
14 M regional/national
level triathletes
69.2 3–5 33–5RM, 33’s/wk for 5 wk Maintenance of FCC during last
hour of 2-h cycling test
Sedano et al. (73) 18 M national level
69.5 Leg exercises 3 37 at 70% 1RM,
23’s/wk for 12 wk (HFLV
increase in vV
max (ES:
HFLV .LFHV .control for 3 km TT
Guglielmo et al.
16 M regional/national
level runners
61.9 3–4 36RM, 23’s/wk for 4 wk
(HFLV group)
6.7% increase in vOBLA
Barnes et al. (7) 42 M and F collegiate
cross-country runners
63.8 2–4 36–15, 4 35–10, 4 34–8, 2
33–6RM, 23’s/wk for 7/10 wk
(HFLV group)
10% increase in PF during
5-jump test, 1.6%
increase in vV
Mean 5k times were worse than
control for men, but better than
control for women
ES 5effect size; F 5female; FCC 5freely chosen cycling cadence; HFLV 5high force low velocity; HIEE 5high-intensity exercise endurance; LFHV 5low force high velocity; LIEE 5low-
intensity exercise endurance; M 5male; MAP 5maximal aerobic power; MAS 5maximal aerobic speed; ME 5movement economy; MP 5mean power; NS 5no statistical change; OBLA 5
onset of blood lactate accumulation; PF 5peak force; PP 5peak power; TE 5time to exhaustion; TT 5time trial performance; V
5maximal velocity in maximal anaerobic running test;
max 5maximal oxygen uptake; W
5peak power at V
Strength and Conditioning Journal | 5
Table 2
Effects of concurrent LFHV strength training and endurance training on HIEE and LIEE
Study Athletes V
Strength training HIEE LIEE
et al. (59)
18 M elite cross-
country runners
67.7 Jumps (unilateral and bilateral, drop, hurdle), short
sprints (20–100 m), 5–20 reps/set at 0–40% 1RM
for 9 wk
3.4% increase in 20-m
velocity, increased V
5.1% increase in
5-km TT
Spurrs et al. (74) 17 M trained runners 57.6 Plyometric drills, progressed from 60–180
contacts, 23’s/wk for 6 wk
2.7% increase in
3-km TT
Mikkola et al.
25 M and F, high
school runners
62.1 Short sprints (30–150 m), 2–3 36–10, 33’s/wk
for 8 wk
NS 1.2% increase in
max, 3% increase in
Berryman et al.
28 M provincial
standard runners
56.9 Drop jumps and concentric squat jumps, 13/wk
for 8 wk
Increase in vV
(ES: 0.43)
Increase in 3-km TT
(ES: 0.37)
Bastiaans et al.
14 M competitive
cyclists (.6y)
2–4 330, squats, leg press/pull, step-ups,
midsection 33’s/wk for 9 wk
4.7% increase in W
7.9% increase in
60 min TT
Mikkola et al.
19 M national cross-
country skiers
66.5 Double pole sprints (10 310 s), leg exercises 3 3
6–10, sprints, jumps, pogos, 33’s/wk for 8 wk
NS 2-km poling velocity,
1.4% increase in 30-m
double poling
Guglielmo et al.
16 M regional/
national level
61.9 3–4 312RM, 23’s/wk for 4 wk 1% increase in vV
Sedano et al.
18 M national level
69.5 Leg exercise 3 320 at 40% 1RM, 23’s/wk
for 12 wk
Increase in vV
(ES: 0.61)
Small improvement
in 3k TT (P,0.05)
ES 5effect size; F 5female; FCC 5freely chosen cycling cadence; HFLV 5high-force low velocity; HIEE 5high-intensity exercise endurance; LFHV 5low force high velocity; LIEE 5low-intensity
exercise endurance; M 5male; MAP 5maximal aerobic power; MAS 5maximal aerobic speed; ME 5movement economy; MP 5mean power; NS 5no statistical change; OBLA 5onset of blood
lactate accumulation; PF 5peak force; PP 5peak power; ST 5strength training; TE 5time to exhaustion; TT 5time trial performance; V
5maximal velocity in maximal anaerobic running
test; V
max 5maximal oxygen uptake; W
5peak power at V
Strength Training for Endurance Athletes
precise times of the training year “to
increase the potential to achieve spe-
cific performance goals” (79). This pro-
cess of chronologically manipulating
physiological adaptations is referred to
as periodization. Although varying defi-
nitions of this term have been proposed,
periodization has been most recently
defined as, “The strategic manipulation
of an athlete’s preparedness through the
employment of sequenced training
phases defined by cycles and stages of
workload” (22). Furthermore, if the train-
ing stimuli are sequenced appropriately,
each phase of training will enhance or
“potentiate” the next training phase
(15,79,81). This concept, referred to as
phase potentiation, is essential in the
development of endurance-specific per-
formance characteristics.
The development of high-power out-
puts and high RFDs are vital to suc-
cess in most sporting events (76) and
can differentiate levels of athletic per-
formance (5,6,29). Maximal power out-
put and RFD have conventionally been
viewed as fitness characteristics that
are less important for endurance sports.
This is misguided, however, because
there is evidence indicating that
Figure 1. Factors affecting athletic performance, modified from Stone et al. (81).
2007, Principles and practice of resistance training (Champaign, IL: Human
Kinetics), 203.
Figure 2. Cross-country runner macrocycle.
Strength and Conditioning Journal | 7
average power output over the course
of a long-distance race and maximal
power output during the final sprint
may be critical factors determining
the outcome of the event (56,58,80).
Power is defined as “the rate of doing
work” (40) and is quantitatively ex-
pressed as power 5force 3velocity
(55). Therefore, an athlete can either
achieve greater power outputs by
increasing the force production or by
increasing the shortening velocity capa-
bilities of skeletal muscle. It is important
to note, however, that skeletal muscle
shortening velocities are limited by the
activity of myosin ATPase, which ulti-
mately dictates the rate of cross-bridge
cycling through ATP dissociation (57).
Accordingly, this elucidates the vital role
of maximal strength in the development
of power (76). Simply put, an increased
ability to produce force provides the ath-
lete with the opportunity to enhance
power production.
Originally proposed by Stone et al. (78),
strength and power should be developed
by cycling 4 distinct phases of training:
strength-endurance, basic strength,
strength, and power (78). This model
of strength and power development, in
addition to the concept of phase poten-
tiation, has since been supported by
further evidence (30,52,93) and is also
referred to as block periodization (38)
or the conjugate-sequencing system
(90). A 4-week training phase has been
previously suggested, using the first 3
weeks to progressively load the ath-
lete, and the final week as an unload-
ing period to modulate recovery
(15,63,81). Although the duration of
the phase is dependent on the relative
training intensity, training volume, time
of the season, needs of the athlete, and
other external factors. Regardless of the
length of each training cycle, however, it
is important for practitioners to remem-
ber that the rate of decay, or involution
of training effects, seems to be directly
proportional to the length of the training
period (81,94). Consequently, proper
sequencing of training phases with
appropriate durations will enhance fit-
ness characteristics from prior stages
of training and make them more resil-
ient to decay. In addition, the subse-
quent training phase can be redirected
to focus on another fitness characteristic
to further the athlete’s preparedness and
dissipate accumulated fatigue from the
previous training cycle (81).
matics to choose from when manipulat-
ing these variables, a traditional model
fits the previously described sequence
of strength and power development
(79,81). During the general preparation
phase, higher volumes of strength train-
capacity and increase lean body mass
(15). Despite concerns over increases in
body mass, for many endurance athletes,
the general preparation phase is one of
the few times during the annual plan
where small increases in muscle hyper-
trophy can be achieved. This in turn will
potentiate gains in maximal strength and
power in subsequent phases of training.
As the athlete progresses from the gen-
eral preparation period to the specific
preparation and competition phases of
the macrocycle, strength training volume
is progressively diminished while training
intensity increases, as strength and power
become the primary fitness characteris-
tics of interest, respectively (38). Before
a culminating event in the competitive
season (e.g., championship race), the
peaking phase or taper requires “a reduc-
period of time, in an attempt to reduce
the physiological and psychological stress
of daily training and optimize perfor-
mance” (53). After the peaking phase,
the athlete transitions into the off-
season with a period of active rest con-
sisting of recreational activities in which
both intensity and volume are reduced
and recovery is the objective (81).
The selection of appropriate training
volumes and intensities within each
training phase is vital in the facilitation
of the desired physiological response.
For endurance athletes with limited
strength training experience, a traditional
model is appropriate (79,81). These ath-
letes should begin with building a neuro-
muscular base using HFLV strength
training, and after a certain strength level
is achieved, LFHV strength training can
then be implemented (10). This is sup-
ported by evidence indicating that
among well-trained athletes, LFHV is
necessary to make further alterations
in the high-velocity end of the force-
velocity curve (30,77). Thus, HFLV and
LFHV strength training are both impor-
tant components in the endurance ath-
lete’s strength and conditioning program
provided they are included at the appro-
priate time and in the correct sequence
(Figure 2).
Regarding high-level endurance ath-
letes, however, the use of a traditional
model with a single peaking phase is
often impractical, as most athletes will
compete in multiple significant events
throughout the course of a competitive
season. Accordingly, manipulating vol-
ume and intensity to produce specific
physiological adaptations must coincide
with this competitive schedule (80).
Unlike the traditional model, after the
athlete completes the peaking phase
and competes in a key event of the sea-
son, further planning will be necessary to
prepare the athlete for future competi-
tions of importance (80,81). More spe-
cifically, if adequate time exists before
the next major event, strength training
volume may be increased to re-establish
strength levels (63,79). Conversely, if
time is insufficient, strength training vol-
ume should be increased cautiously to
avoid undue fatigue before the next con-
test (63,80,81).
When selecting exercises for specific
phases of training, it is important for
practitioners and athletes to consider
the transfer of training effect. That is,
the degree of performance adaptation
that can result from a training exercise
(11,81). Therefore, choosing exercises
with similar movement patterns and
Strength Training for Endurance Athletes
kinetic parameters (e.g., peak force,
RFD, acceleration, etc.) will result in
a greater transfer to performance (11).
Although some endurance sport move-
ments have both closed and open
kinetic chain sequences, in movements
such as running, closed kinetic chain
exercises should be prioritized as they
have been suggested to require greater
levels of intermuscular coordination
(76) and result in greater performance
enhancement compared with open
chain movements (62,75). Traditional
squatting and weightlifting movements
are primary examples. Moreover, squat
strength has been strongly correlated to
athletic movements that require rela-
tively high-velocity, high-power outputs
and RFD (6,18). Weightlifting exercises
and their derivatives have also shown
a strong transfer of training to such
movements as well (4,16,37). Practically,
these exercises may assist with passing
an opponent, enhancing movement
economy, increasing average power out-
put, and sprinting the final 100 m of
a race (56,58,80). Considering the essen-
tial role that these exercises play in the
development of strength and power and
subsequent effects on HIEE and LIEE,
squatting and weightlifting movements
should be staples throughout the training
year for endurance athletes.
Previous research on concurrent train-
ing for endurance athletes suggests
that maximum strength is associated
with endurance factors, a relationship
that is likely stronger for HIEE activi-
ties than for LIEE. HFLV strength
training can affect increases in HIEE
and LIEE through increasing peak
force and RFD. LFHV strength training
ments in HIEE and LIEE performance,
however, not all studies agree. When
considering findings from studies
examining changes in endurance per-
formance and related measures after
strength training, it seems that concur-
rent HFLV strength and endurance
training may provide superior results
compared with LFHV strength and
endurance training for relatively weak
endurance athletes. For endurance
athletes with more strength training
experience, a sequenced approach
(e.g., block periodized model) may
be more appropriate than trying to
improve strength, power, and endur-
ance simultaneously.
A limitation to the current research
exists in the design and implementa-
tion of training protocols. Some stud-
ies comparing different strength
training modalities fail to control for
differences in strength and endurance
training volume between experimental
conditions. Another limitation, only
controlled for in a few studies, is the
addition of strength training without
a simultaneous reduction in the vol-
ume of endurance training. Practically,
if applied in an athletic setting, this
could result in poor fatigue manage-
ment and an increased risk of
overtraining syndrome. The imple-
mentation of an annual training plan
where endurance and strength training
variables are carefully manipulated will
maximize athletic performance while
reducing injury risk by more appropri-
ately managing training volume.
Future research should examine the
effectiveness of monitoring programs
in determining when to manipulate
training variables throughout a macro-
cycle and the subsequent effects on
endurance performance.
Conflicts of Interest and Source of Funding:
The authors report no conflicts of interest
and no source of funding.
The authors thank Jacob Goodin for
his corrections and editorial comments
in preparation of this article.
Caleb D.
Bazyler is cur-
rently completing
his PhD at East
Tennessee State
University with
the Department
of Exercise and
Sport Science in
conjunction with
the Center of Excellence for Sport Science
and Coach Education.
Heather A.
Abbott is cur-
rently completing
her PhD at East
Tennessee State
University with
the Department
of Exercise and
Sport Science in
conjunction with the Center of Excellence
for Sport Science and Coach Education.
Christopher R.
Bellon is cur-
rently completing
his PhD at East
Tennessee State
University with
the Department
of Exercise and
Sport Science in
conjunction with the Center of Excellence
for Sport Science and Coach Education.
Christopher B.
Taber is currently
completing his
PhD at East
Tennessee State
University with
the Department
of Exercise and
Sport Science in conjunction with the
Center of Excellence for Sport Science
and Coach Education.
Michael H. Stone is the Laboratory
Director and PhD Coordinator in the
Center of Excellence for Sport Science
and Coach Education/Department of
Exercise and Sport Science at East Ten-
nessee State University.
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Strength Training for Endurance Athletes
... However, human is made of complex biological systems acting as a network in which several processes exchanges between each other at various orders (Bazyler, Abbott, Bellon, et al. 2015;Lambert, Gibson, and Noakes 2005). Not surprisingly, traditional system models of training effects lack of descriptive and predictive powers (Hellard, Avalos, Lacoste, et al. 2006), since they resume training effects to a very few features if it is not a single one in most cases. ...
... Previously, we described the primary methods for quantifying training loads with their benefits and drawbacks. As a final note, aiming at understanding the relationship between training and athletic performance is a matter of a systemic issue since athletic performance is a complex system in which many systems interact with each other (Bazyler, Abbott, Bellon, et al. 2015). Hence, two goals arise from the modelling with: ...
... Fitness-Fatigue model suffers from its univariate configuration in modelling athletic performances. While it is known that athletic performance is multifactorial (Avalos, Hellard, and Chatard 2003;Bazyler, Abbott, Bellon, et al. 2015;Mujika, Busso, Lacoste, et al. 1996;Stone, Stone, and Sands 2007), variations in performances may not be fully explained by the dynamics of training loads only, resulting in poor predictive capability (Chiu and Barnes 2003;Pfeiffer 2008;Taha and Thomas 2003). Recently, Piatrikova, Willsmer, Altini, et al. 2021 provided a multivariate alternative to the original FFM. ...
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The first models of training effects on athletic performance emerged with the work of Banister and Calvert through the so-called Fitness-Fatigue model (FFM). One major drawback of FFMs is that the features stem from a single source of data. That is not in line with the existing consensus about a multifactorial aspect of athletic performance. Hence, multivariate modelling approaches from statistics and machine-learning (ML) emerged. A research issue arises from the quantification of training Loads (TL) in resistance training (RT) which lack of physiological evidence. In the first study, we provided a new method of TL quantification in RT based on physiological observations. To achieve that, we initially modelled the torque-velocity profiles of fifteen participants during an isokinetic leg extension task and assessed a set of physiological responses to various resistance exercises intensities. Each session was volume-equated according to the formulation of volume load (i.e. the product of the number of repetitions and the relative intensity). Higher led to greater muscular fatigue described by neuromuscular impairments. Conversely, systemic and local pulmonary responses (measured through oxygen uptake) and metabolic changes (according to blood lactate concentrations) were more significant at low intensities, suggesting different contributions of metabolic pathways. From these results, we provided a new index of TL based on the neuromuscu- lar impairments observed at exercise. We showed that to exponentially weight TL by the average rate decay of force development rate yielded better correla- tions with any of the significant physiological responses to exercise. In addition, information compressed within a principal component could be a valuable TL index. In the second study, we provided a robust modelling methodology that relies on model generalisation. Using data from elite speed skaters, we compared a dose-response model to regularisation methods and machine-learning models. Regularisation procedures provided the greatest performances in both generalisa- tion and accuracy. Also, we highlighted the pertinence of computing one model over the group of athletes instead of a model per athlete in a context of a small sample size. Finally, ML approaches could be a way of improving FFMs through ensemble learning methods. In the third study, we modelled acceleration-velocity directly from global posi- tioning system (GPS) measurements and attempted to predict the coefficients of the relationship between acceleration and velocity. First, a baseline model was defined by time-series forecasting using game data only. Then, we proceeded to multivariate modelling using commercial features. A regularised linear regression and a long short term memory neural network were compared. Finally, we extracted features directly from raw GPS data and compared these features to the commercial ones for prediction purposes. The results showed only slight differences between model accuracy, and no models significantly outperformed the baseline in the prediction task. Given the multi- factorial nature of athletic performance, using only GPS data for predicting such athletic performance criterion provided an acceptable accuracy. Using time-domain and frequency-domain features extracted from raw data led to similar performances compared to the commercial ones, despite being evidence-based. It suggests that raw data should be considered for future athletic performance and injury occurrence analysis. Lastly, we developed an athlete management system for long-distance runners. This application provided an athlete monitoring module and a predictive module based on a physiological model of running performance. A second development was realised under the SAP analytics cloud solution. Team management and automated dashboards were provided herein, in close collaboration with a professional Rugby team.
... Although there are numerous studies supporting the implementation of ST to improve performance and physiological variables in endurance athletes (10,11,25,61,71,72,79,80,83,90,91,98,, practical application papers primarily focus on running (8), singlemode sports (9), or are outdated (20). Therefore, the purpose of this paper is to educate coaches and athletes on the benefits of completing concurrent strength and endurance training to improve physiological factors contributing to LD triathlon performance. ...
... Although the use of a power or hang clean is not commonly incorporated in concurrent strength and endurance training literature, 2 recent practical review papers have recommended the inclusion of these exercises because they focus on posterior chain muscles that are used during endurance events and have a strong training transfer effect (8,9). Furthermore, a power or hang clean can improve hip extension RFD while also improving upper body strength (8,9). ...
... Although the use of a power or hang clean is not commonly incorporated in concurrent strength and endurance training literature, 2 recent practical review papers have recommended the inclusion of these exercises because they focus on posterior chain muscles that are used during endurance events and have a strong training transfer effect (8,9). Furthermore, a power or hang clean can improve hip extension RFD while also improving upper body strength (8,9). If the athlete finds the power or hang clean movement too complex, this may be regressed to a triple extension movement through the lower limbs and an emphasis must be placed on managing the load appropriately. ...
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Concurrent training, commonly acknowledged as a training method where strength and endurance training are completed complementary to each other, is a strategy often implemented in endurance cyclists' and runners' programs to improve physiological determinants of success such as exercise economy. Although concurrent training methods and strategies have been examined to a large extent in endurance cyclists and runners, literature examining optimal concurrent training methods to improve physiological variables in long-distance triathletes is minimal, leaving optimal programming relatively unknown. This practical applications paper identifies and outlines current concepts and considerations regarding concurrent training for long-distance triathletes including mechanisms contributing to improved performance, muscle and movement patterns used, exercise selection, load, velocity of movement, scheduling, frequency, and duration of training. Common misconceptions related to concurrent training are also identified and practical considerations for the application of concurrent training for coaches, athletes, and other professionals to improve all 3 disciplines of triathlon are discussed.
... Often researchers will indirectly assess AWC by implementing what historically has been known as a "muscular endurance" test (9,17,18,31,41,42,(45)(46)(47)53). Although endurance has been defined as the ability of the muscle to resist fatigue under a submaximal load (14) or the maximal number of repetitions performed with a specified load (1,31), it is best described as the ability to maintain or repeat a given force or power output (6). "Muscular endurance" has been the term commonly used to described endurance activities that are of high intensity. ...
... It should be noted that the term "muscular endurance" suggests that fatigue is wholly a muscle phenomenon. Indeed even in short-term activities other physiological (and psychological) aspects can contribute to fatigue such as the nervous system (6,50). As endurance activities represent a continuum from low intensity exercise endurance (LIEE) to high intensity exercise endurance (HIEE), a better way to refer to the term "muscle endurance" in this review would be HIEE as the exercises and tests used usually fall ≤ 2 minutes (6,50). ...
... Indeed even in short-term activities other physiological (and psychological) aspects can contribute to fatigue such as the nervous system (6,50). As endurance activities represent a continuum from low intensity exercise endurance (LIEE) to high intensity exercise endurance (HIEE), a better way to refer to the term "muscle endurance" in this review would be HIEE as the exercises and tests used usually fall ≤ 2 minutes (6,50). Additionally, loads used have oscillated from absolute to relative, and relative loads have varied in percentages of one-repetition maximum (1RM). ...
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Performing resistance training (RT) may improve physical performance capabilities, with anaerobic work capacity (AWC) being one of the characteristics targeted by coaches and athletes. High volume resistance training (HVRT) is typically prescribed in RT programs with the expectancy of improving AWC. However, much of the research available is unclear concerning the effects of HVRT on AWC over time. Therefore, this review will focus on the longitudinal effects of HVRT on AWC. Searches were conducted on SportDiscus, PubMed, Google Scholar, relevant articles from references of qualifying studies, and by using strategies previously suggested (20). Fourteen studies met the following inclusion criteria: a) peer-reviewed, b) testing of AWC pre-and post-HVRT, c) subjects between the ages of 18-40 years, d) a study of at least 4 weeks in duration, e) the study had to use a RT intervention with a set and repetition scheme of ≥ 3 x 8 or base volume load (bVL) of 24 reps, f) and training had to occur at least twice a week for multiple muscle groups. Contrasting protocols within qualifying studies made it challenging to compare between them. Many 1/17 studies did not meet our criteria mainly due to lack of required duration and pre-and post-training performance testing. The findings of this review indicate that moderately high-volume load (VL) of 4 ± 1 sets of 12 ± 3 repetitions can improve AWC more efficiently than higher VL protocols while mitigating potential strength losses, especially when enough intra-set rest is provided. Moreover, the various implemented protocols and mixed results make generalizability impractical. Coaches and athletes should use this information with good judgement. Reporting full descriptions of the protocols (ie. VL per day) and the inclusion of performance measurements are warranted for future research to understand the contributions of HVRT to AWC.
... Physical fitness is of great significance to athletes both in single-player and team sports [2,3]. Numerous training techniques (e.g., plyometric jump training) are commonly used by athletes in order to promote physical fitness parameters [3,4]. ...
... Our findings provide a reliable and valid perspective for using the KForce plates in sports and clinical biomechanics, such as in the analysis of functional tests and plyometric jump training. Moreover, the portability of the instrument allows practitioners to evaluate complex parameters, such as jumping height, leg stiffness, velocity, power, and ground reaction forces in either professional or amateur athletes with accuracy, thus allowing the possibility to improve sports performance, reduce the risk of injury, and manage reliable assessments either in a laboratory environment or in the sports field [3][4][5][6]. The use of the portable KForce plates might help to implement improved training-induced performance adaptations, providing accurate feedback to practitioners and athletes, respectively. ...
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Physical fitness is of great significance to athletes in both single-player and team sports. The countermovement jump (CMJ) is one of the most commonly applied jump tests for assessing the mechanical capacities of the lower extremities. The KForce Plates system is a portable force platform that sends action-time audio and visual biofeedback to a smartphone or tablet through the KForce application, making it a suitable instrument for assessing the CMJ. The aim of the present study was to evaluate the test–retest reliability and validity of the portable force platform (KForce Plates) in the evaluation of the CMJ in collegiate athletes compared to a validated application, My Jump 2. Thirty-four collegiate professional athletes, deriving from various sports backgrounds, participated in the present study. The CMJs were reported with the portable KForce Plates and the simultaneous use of the ‘My Jump 2’ application using an iPhone 13 between days 1 and 7. Our findings revealed high test–retest reliability (ICC = 1.00 and ICC = 0.99) in-between measurements. High correlations were monitored amongst the portable KForce plates and the My Jump 2 application for measuring the CMJ (r = 0.999, p = 0.001). The Bland–Altman plot exhibits the limits of agreement amongst the portable KForce plates and the My Jump 2 application, where the bulk of the data are within the 95% CIs with an agreement of ≈1 cm. Our findings suggest that the portable KForce Plates system is a reliable and valid instrument and, therefore, can be used by experts in the sports field.
... Over the years, multiple review articles have been published examining concurrent strength and endurance training, including meta-analyses and systematic reviews that examine the influence of the sequence of concurrent strength and endurance training [14,15], describe and analyze the "interference effect" [10,16,17], and assess the influence of training status on strength gains during concurrent strength and endurance training [18]. Several systematic reviews have also been published that are specific to concurrent strength and endurance training for optimizing endurance performance [19], rowing and canoeing [20], running [21][22][23][24][25], cycling [21,26], soccer [27], multiple training modes [28], and high-intensity interval training [7,29]. Reviews have evaluated the effect of endurance training on muscle hypertrophy [10][11][12], while also exploring topics such as detraining [30]. ...
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Background Both strength and endurance training are included in global exercise recommendations and are the main components of training programs for competitive sports. While an abundance of research has been published regarding concurrent strength and endurance training, only a small portion of this research has been conducted in females or has addressed their unique physiological circumstances (e.g., hormonal profiles related to menstrual cycle phase, menstrual dysfunction, and hormonal contraceptive use), which may influence training responses and adaptations. Objective The aim was to complete a systematic review of the scientific literature regarding training adaptations following concurrent strength and endurance training in apparently healthy adult females. Methods A systematic electronic search for articles was performed in July 2021 and again in December 2022 using PubMed and Medline. This review followed, where applicable, the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. The quality of the included studies was assessed using a modified Downs and Black checklist. Inclusion criteria were (1) fully published peer-reviewed publications; (2) study published in English; (3) participants were healthy normal weight or overweight females of reproductive age (mean age between > 18 and < 50) or presented as a group (n > 5) in studies including both females and males and where female results were reported separately; (4) participants were randomly assigned to intervention groups, when warranted, and the study included measures of maximal strength and endurance performance; and (5) the duration of the intervention was ≥ 8 weeks to ensure a meaningful training duration. Results Fourteen studies met the inclusion criteria (seven combined strength training with running, four with cycling, and three with rowing or cross-country skiing). These studies indicated that concurrent strength and endurance training generally increases parameters associated with strength and endurance performance in female participants, while several other health benefits such as, e.g., improved body composition and blood lipid profile were reported in individual studies. The presence of an “interference effect” in females could not be assessed from the included studies as this was not the focus of any included research and single-mode training groups were not always included alongside concurrent training groups. Importantly, the influence of concurrent training on fast-force production was limited, while the unique circumstances affecting females were not considered/reported in most studies. Overall study quality was low to moderate. Conclusion Concurrent strength and endurance training appears to be beneficial in increasing strength and endurance capacity in females; however, multiple research paradigms must be explored to better understand the influence of concurrent training modalities in females. Future research should explore the influence of concurrent strength and endurance training on fast-force production, the possible presence of an “interference effect” in athletic populations, and the influence of unique circumstances, such as hormone profile, on training responses and adaptations.
... Actualmente, cuenta con una presencia activa de 210 asociaciones nacionales en el mundo distribuida en los cinco continentes y, con una participación de más de 60000 deportistas. (World Taekwondo, 2020) La programación del rendimiento deportivo es compleja y resulta esencial abordarla desde un enfoque integral, que armonice una gran cantidad de factores para fomentar el desarrollo del atleta: sus actividades laborales y educativas, vida social, potenciales lesiones y tratamiento, horas de descanso, aspectos nutricionales, potencial genético, las relaciones con el entrenador, entorno y entrenamiento, etc. (Bazyler et al., 2015). Todas estas variables son consideradas en los programas de entrenamiento. ...
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El taekwondo olímpico hace referencia a la modalidad de combate que llegó a instancias olímpicas en los años 2000. Los avances en el análisis de la competición deportiva y las investigaciones científicas de las últimas décadas, han promovido cambios de paradigma en el entrenamiento deportivo. Las diferencias sustantivas entre los deportes acíclicos respecto de los cíclicos, en tanto los primeros presentan variaciones significativas en la intensidad, duración, frecuencia, cinética y cinemática de las acciones musculares durante la competición, han sido fundamentos centrales para analizar y desarrollar nuevas estrategias de entrenamiento. En tal sentido, esta investigación descriptiva, concebida desde el campo práctico, es dirigida al estudio de la resistencia específica para el taekwondista. Los objetivos de este trabajo son: (1) precisar el concepto de resistencia específica para el taekwondo; (2) analizar la estructura de la competición e identificar las demandas fisiológicas a partir de su dinámica intermitente, y (3) proponer pautas para el entrenamiento de la resistencia específica del taekwondista.
... It was traditionally believed that strength training would inhibit running performance, fearing that an increase in overall bodyweight from increased muscle mass and change in cell physiology (16) would slow down the athlete. Also, engaging in a form of exercise that includes lifting weights explosively was seen as very dissimilar from an endurance runner's typical form of training (3). Traditional concerns aside, modern day training programs for elite long-distance runners are certain to include explosive resistance training exercises. ...
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BLUF Appropriate periodisation of explosive-based resistance training methods such as Plyometrics has the ability to improve both physiological and neurological adaptations of musculotendinous units within the major joints of the lower body in endurance runners. ABSTRACT Strength and Power training modalities continue to emerge amongst elite-level endurance athletes. Despite common misconceptions surrounding such training, enhancements in overall running performance, most notably Running Economy, has the ability for individuals to overcome their competitors. A total of seven original experimental articles were used for this review. The primary finding from this review was that endurance performance characteristics, specifically Running Economy, were enhanced after participating in strength and power-based training (2-8%). Improvements in Rate of Force Development with a concomitant decreased demand for oxygen at a given speed showed improvements in time trials and time to exhaustion. Differing magnitudes of results may be due to subjects previous history, exercise selection, volume load and testing protocols. There was shown to be a lack of direct measurement for the stiffness and/or compliance qualities of the Musculotendinous Unit from the studies chosen. Strength and Power based training has the potential to elicit positive enhancements in performance characteristics amongst elite-level endurance athletes. The use of multi-joint explosive exercises such as unloaded and loaded jump squats, scissor jumps, bounding, and wall sprints are recommended as they closely resemble running mechanics. Programming factors such as progressive overload, work:rest ratio, training frequency and intensity must be individualised appropriately in order to maximise training adaptations and limit accumulative fatigue. Based on the reviewed studies, elite distance runners are recommended to engage in specific explosive strength training 2-3 days per week for 8-12 weeks in order to improve overall running performance (decreased energy expenditure and oxygen demand at particular velocities).
... Despite the prioritization of muscular endurance over strength that results from endurance training, increased muscular force and power gained through strength training have repeatedly been shown to improve performance in running, cycling and cross country skiing (Aagaard, et al., 2011;Bazyler, Abbott, Bellon, Taber, & Stone, 2015;Luckin et al., 2018;Rønnestad & Mujika, 2014;Vikmoen, Rønnestad, Ellefsen, & Raastad, 2017). Improved performance metrics include increased time to exhaustion and race/time trial times; the degree of these improvements differs based on strength training modality and variables related to the athlete's endurance training status. ...
Objective The specificity of training principle holds that adaptations to exercise training closely match capacity to the specific demands of the stimulus. Improvements in endurance sport performance gained through strength training are a notable exception to this principle. While the proximate mechanisms for how strength training produces muscular adaptations beneficial to endurance sports are increasingly well understood, the ultimate causes of this phenomenon remain unexplored. Methods Using a holistic approach tying together exercise physiology and evolution, I argue that we can reconcile the apparent “endurance training specificity paradox.” Results and Conclusions Competing selective pressures, inherited mammalian biology, and millennia of living in energy‐scarce environments constrained our evolution as endurance athletes, but also imparted high muscular plasticity which can be exploited to improve endurance performance beyond what was useful in our evolutionary past.
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Optimal protein supplementation is an essential consideration for maximizing adaptive responses and recovery ability from physical and physiological stress of high intensity resistance training. There are several timings of consuming protein supplements based on nutrient timing system such as pre-exercise (energy phase), post-exercise (anabolic phase), and pre-sleep (growth or adaptation phase). However, it is not yet established which protein timing is the most effective way to maximize the adaptive responses to resistance training. Thus, this review was carried out to suggest an optimal timing of protein supplementation by discussing the effects of each timing of protein intake (pre-exercise, post-exercise, both post-exercise and before sleep, both before and after exercise) on muscle adaptations to resistance training. Also, we provide scientific information to develop practical strategies of protein supplementation on prolonged resistance training by combining the results of previous studies. We expect our review to offer relevant information for developing a sport-specific optimal timing of protein ingestion for strength/power athletes.
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Endurance can be defined as the ability to maintain or to repeat a given force or power output. The sport performance-endurance relationship is a multi-factorial concept. However, evidence indicates that maximum strength is a major component. Conceptually, endurance is a continuum. The literature indicates that (a) maximum strength is moderately to strongly related to endurance capabilities and associated factors, a relationship that is likely stronger for high intensity exercise endurance (HIEE) activities than for low intensity exercise endurance (LIEE); (b) strength training can increase both HIEE and LIEE, the effect being greater for HIEE; (c) the volume of strength training plays a role in endurance adaptation; and (d) mechanical specificity and training program variables also play a role in the degree of adaptation.
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The purpose was to investigate the effect of 25 weeks heavy strength training in young elite cyclists. Nine cyclists performed endurance training and heavy strength training (ES) while seven cyclists performed endurance training only (E). ES, but not E, resulted in increases in isometric half squat performance, lean lower body mass, peak power output during Wingate test, peak aerobic power output (Wmax), power output at 4 mmol L−1 [la−], mean power output during 40-min all-out trial, and earlier occurrence of peak torque during the pedal stroke (P < 0.05). ES achieved superior improvements in Wmax and mean power output during 40-min all-out trial compared with E (P < 0.05). The improvement in 40-min all-out performance was associated with the change toward achieving peak torque earlier in the pedal stroke (r = 0.66, P < 0.01). Neither of the groups displayed alterations in VO2max or cycling economy. In conclusion, heavy strength training leads to improved cycling performance in elite cyclists as evidenced by a superior effect size of ES training vs E training on relative improvements in power output at 4 mmol L−1 [la−], peak power output during 30-s Wingate test, Wmax, and mean power output during 40-min all-out trial.
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Concurrent training is defined as simultaneously incorporating both resistance and endurance exercise within a periodized training regime. Despite the potential additive benefits of combining these divergent exercise modes with regards to disease prevention and athletic performance, current evidence suggests that this approach may attenuate gains in muscle mass, strength, and power compared with undertaking resistance training alone. This has been variously described as the interference effect or concurrent training effect. In recent years, understanding of the molecular mechanisms mediating training adaptation in skeletal muscle has emerged and provided potential mechanistic insight into the concurrent training effect. Although it appears that various molecular signaling responses induced in skeletal muscle by endurance exercise can inhibit pathways regulating protein synthesis and stimulate protein breakdown, human studies to date have not observed such molecular 'interference' following acute concurrent exercise that might explain compromised muscle hypertrophy following concurrent training. However, given the multitude of potential concurrent training variables and the limitations of existing evidence, the potential roles of individual training variables in acute and chronic interference are not fully elucidated. The present review explores current evidence for the molecular basis of the specificity of training adaptation and the concurrent interference phenomenon. Additionally, insights provided by molecular and performance-based concurrent training studies regarding the role of individual training variables (i.e., within-session exercise order, between-mode recovery, endurance training volume, intensity, and modality) in the concurrent interference effect are discussed, along with the limitations of our current understanding of this complex paradigm.
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Economy, velocity/power at maximal oxygen uptake ([Formula: see text]) and endurance-specific muscle power tests (i.e. maximal anaerobic running velocity; vMART), are now thought to be the best performance predictors in elite endurance athletes. In addition to cardiovascular function, these key performance indicators are believed to be partly dictated by the neuromuscular system. One technique to improve neuromuscular efficiency in athletes is through strength training. The aim of this systematic review was to search the body of scientific literature for original research investigating the effect of strength training on performance indicators in well-trained endurance athletes-specifically economy, [Formula: see text] and muscle power (vMART). A search was performed using the MEDLINE, PubMed, ScienceDirect, SPORTDiscus and Web of Science search engines. Twenty-six studies met the inclusion criteria (athletes had to be trained endurance athletes with ≥6 months endurance training, training ≥6 h per week OR [Formula: see text] ≥50 mL/min/kg, the strength interventions had to be ≥5 weeks in duration, and control groups used). All studies were reviewed using the PEDro scale. The results showed that strength training improved time-trial performance, economy, [Formula: see text] and vMART in competitive endurance athletes. The present research available supports the addition of strength training in an endurance athlete's programme for improved economy, [Formula: see text], muscle power and performance. However, it is evident that further research is needed. Future investigations should include valid strength assessments (i.e. squats, jump squats, drop jumps) through a range of velocities (maximal-strength ↔ strength-speed ↔ speed-strength ↔ reactive-strength), and administer appropriate strength programmes (exercise, load and velocity prescription) over a long-term intervention period (>6 months) for optimal transfer to performance.
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Here we report on the effect of combining endurance training with heavy or explosive strength training on endurance performance in endurance-trained runners and cyclists. Running economy is improved by performing combined endurance training with either heavy or explosive strength training. However, heavy strength training is recommended for improving cycling economy. Equivocal findings exist regarding the effects on power output or velocity at the lactate threshold. Concurrent endurance and heavy strength training can increase running speed and power output at VO2max (Vmax and Wmax , respectively) or time to exhaustion at Vmax and Wmax . Combining endurance training with either explosive or heavy strength training can improve running performance, while there is most compelling evidence of an additive effect on cycling performance when heavy strength training is used. It is suggested that the improved endurance performance may relate to delayed activation of less efficient type II fibers, improved neuromuscular efficiency, conversion of fast-twitch type IIX fibers into more fatigue-resistant type IIA fibers, or improved musculo-tendinous stiffness.
To investigate the effects of simultaneous explosive-strength and endurance training on physical performance characteristics, 10 experimental (E) and 8 control (C) endurance athletes trained for 9 wk. The total training volume was kept the same in both groups, but 32% of training in E and 3% in C was replaced by explosive-type strength training. A 5-km time trial (5K), running economy (RE), maximal 20-m speed ( V 20 m ), and 5-jump (5J) tests were measured on a track. Maximal anaerobic (MART) and aerobic treadmill running tests were used to determine maximal velocity in the MART ( V MART ) and maximal oxygen uptake (V˙o 2 max ). The 5K time, RE, and V MART improved ( P < 0.05) in E, but no changes were observed in C. V 20 m and 5J increased in E ( P < 0.01) and decreased in C ( P < 0.05).V˙o 2 max increased in C ( P < 0.05), but no changes were observed in E. In the pooled data, the changes in the 5K velocity during 9 wk of training correlated ( P< 0.05) with the changes in RE [O 2 uptake ( r = −0.54)] and V MART ( r = 0.55). In conclusion, the present simultaneous explosive-strength and endurance training improved the 5K time in well-trained endurance athletes without changes in theirV˙o 2 max . This improvement was due to improved neuromuscular characteristics that were transferred into improved V MART and running economy.
The purpose of this review was to consider the association of measures of maximum strength inrelation to sports performance and performance variables, which rely on high levels of power and speed, in essence it is an expansion of the ideas and concepts presented by 39. Evidence from different types of cross-sectional research as well as observational data was considered. Collectively the data indicate that the association between maximum strength and sport performance related variables such as peak power and peak rate of force development is quite strong. While explaining performance in strength/power sports is a multi-factorial problem, there is little doubt that maximum strength is a key component.