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Ballistic performances are determined by both the maximal lower limb power output (P max ) and their individual force-velocity (F-v) mechanical profile, especially the F-v imbalance (FV imb ): difference between the athlete's actual and optimal profile. An optimized training should aim to increase P max and/or reduce FV imb . The aim of this study was to test whether an individualized training program based on the individual F-v profile would decrease subjects' individual FV imb and in turn improve vertical jump performance. FVimb was used as the reference to assign participants to different training intervention groups. Eighty four subjects were assigned to three groups: an "optimized" group divided into velocity-deficit, force-deficit, and well-balanced sub-groups based on subjects' FV imb , a "non-optimized" group for which the training program was not specifically based on FV imb and a control group. All subjects underwent a 9-week specific resistance training program. The programs were designed to reduce FV imb for the optimized groups (with specific programs for sub-groups based on individual FV imb values), while the non-optimized group followed a classical program exactly similar for all subjects. All subjects in the three optimized training sub-groups (velocity-deficit, force-deficit, and well-balanced) increased their jumping performance (12.7 ± 5.7% ES = 0.93 ± 0.09, 14.2 ± 7.3% ES = 1.00 ± 0.17, and 7.2 ± 4.5% ES = 0.70 ± 0.36, respectively) with jump height improvement for all subjects, whereas the results were much more variable and unclear in the non-optimized group. This greater change in jump height was associated with a markedly reduced FV imb for both force-deficit (57.9 ± 34.7% decrease in FV imb ) and velocity-deficit (20.1 ± 4.3%) subjects, and unclear or small changes in P max (-0.40 ± 8.4% and +10.5 ± 5.2%, respectively). An individualized training program specifically based on FV imb (gap between the actual and optimal F-v profiles of each individual) was more efficient at improving jumping performance (i.e., unloaded squat jump height) than a traditional resistance training common to all subjects regardless of their FV imb . Although improving both FV imb and P max has to be considered to improve ballistic performance, the present results showed that reducing FV imb without even increasing P max lead to clearly beneficial jump performance changes. Thus, FV imb could be considered as a potentially useful variable for prescribing optimal resistance training to improve ballistic performance.
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ORIGINAL RESEARCH
published: 09 January 2017
doi: 10.3389/fphys.2016.00677
Frontiers in Physiology | www.frontiersin.org 1January 2017 | Volume 7 | Article 677
Edited by:
Gregoire P. Millet,
University of Lausanne, Switzerland
Reviewed by:
Chris R. Abbiss,
Edith Cowan University, Australia
Davide Viggiano,
University of Molise, Italy
*Correspondence:
Jean-Benoît Morin
jean-benoit.morin@unice.fr
Specialty section:
This article was submitted to
Exercise Physiology,
a section of the journal
Frontiers in Physiology
Received: 02 September 2016
Accepted: 20 December 2016
Published: 09 January 2017
Citation:
Jiménez-Reyes P, Samozino P,
Brughelli M and Morin J-B (2017)
Effectiveness of an Individualized
Training Based on Force-Velocity
Profiling during Jumping.
Front. Physiol. 7:677.
doi: 10.3389/fphys.2016.00677
Effectiveness of an Individualized
Training Based on Force-Velocity
Profiling during Jumping
Pedro Jiménez-Reyes 1, Pierre Samozino 2, Matt Brughelli 3and Jean-Benoît Morin 3, 4*
1Faculty of Sport, Catholic University of San Antonio, Murcia, Spain, 2Laboratoire Interuniversitaire de Biologie de la motricité
(EA7424), University of Savoie Mont Blanc, Le Bourget du Lac, France, 3Sports Performance Research Institute New Zealand
(SPRINZ), Auckland University of Technology, Auckland, New Zealand, 4Université Côte d’Azur, LAMHESS, Nice, France
Ballistic performances are determined by both the maximal lower limb power output
(Pmax) and their individual force-velocity (F-v) mechanical profile, especially the F-v
imbalance (FVimb): difference between the athlete’s actual and optimal profile. An
optimized training should aim to increase Pmax and/or reduce FVimb. The aim of this study
was to test whether an individualized training program based on the individual F-v profile
would decrease subjects’ individual FVimb and in turn improve vertical jump performance.
FVimb was used as the reference to assign participants to different training intervention
groups. Eighty four subjects were assigned to three groups: an “optimized” group divided
into velocity-deficit, force-deficit, and well-balanced sub-groups based on subjects’
FVimb, a “non-optimized” group for which the training program was not specifically based
on FVimb and a control group. All subjects underwent a 9-week specific resistance
training program. The programs were designed to reduce FVimb for the optimized groups
(with specific programs for sub-groups based on individual FVimb values), while the
non-optimized group followed a classical program exactly similar for all subjects. All
subjects in the three optimized training sub-groups (velocity-deficit, force-deficit, and
well-balanced) increased their jumping performance (12.7 ±5.7% ES =0.93 ±0.09,
14.2 ±7.3% ES =1.00 ±0.17, and 7.2 ±4.5% ES =0.70 ±0.36, respectively)
with jump height improvement for all subjects, whereas the results were much more
variable and unclear in the non-optimized group. This greater change in jump height
was associated with a markedly reduced FVimb for both force-deficit (57.9 ±34.7%
decrease in FVimb) and velocity-deficit (20.1 ±4.3%) subjects, and unclear or small
changes in Pmax (0.40 ±8.4% and +10.5 ±5.2%, respectively). An individualized
training program specifically based on FVimb (gap between the actual and optimal F-v
profiles of each individual) was more efficient at improving jumping performance (i.e.,
unloaded squat jump height) than a traditional resistance training common to all subjects
regardless of their FVimb. Although improving both FVimb and Pmax has to be considered
to improve ballistic performance, the present results showed that reducing FVimb without
even increasing Pmax lead to clearly beneficial jump performance changes. Thus, FVimb
could be considered as a potentially useful variable for prescribing optimal resistance
training to improve ballistic performance.
Keywords: jumping, ballistic training, explosive performance, resistance strength training, maximal power output
Jiménez-Reyes et al. Force-Velocity Optimized Training for Jump Performance
INTRODUCTION
Advancements in strength and conditioning methodologies
alongside evolution in physical demands of competition in
sports such as rugby, football, volleyball, basketball, or athletics,
have led to an increased relevance of high-intensity, ballistic
actions. Physical performance in these kinds of sports is clearly
determined by high levels of force, power, and velocity during
ballistic movements such as sprints, changes of direction, or
jumps (Cronin and Sleivert, 2005; Cormie et al., 2010).
Ballistic performances, notably jumping, can be defined as
the ability to accelerate body mass, both as much as possible
and within the shortest time possible (Samozino et al., 2012).
From a mechanical point of view, ballistic push-off performance
is thus directly related to the net mechanical impulse produced
onto the ground (Winter, 2005). The capability to develop a high
net impulse during one lower limb push-off has been associated
with muscular mechanical power output capabilities (Newton
and Kraemer, 1994; Yamauchi and Ishii, 2007; Samozino et al.,
2008; Frost et al., 2010; McBride et al., 2010). Numerous
studies have highlighted neuromuscular power as the primary
variable related to ballistic performance, yet this analysis only
provides a partial representation of the athlete’s true maximal
mechanical capabilities (Cronin and Sleivert, 2005). Specifically,
in the recent years, a new paradigm supports the fact that
although ballistic performance such as jumping height is largely
determined by maximal power output (Pmax) that lower limbs
can generate (Yamauchi and Ishii, 2007), it is also influenced
by the individual combination of the underlying force and
velocity mechanical outputs, known as force-velocity (F-v) profile
(Samozino et al., 2012, 2014; Morin and Samozino, 2016). Thus,
the inclusion of F-v relationship and their contribution to ballistic
performance may provide a more accurate and integrative
mechanical representation of the athlete’s maximal capabilities
(Samozino et al., 2012), since they encompass the entire force-
velocity spectrum, from the theoretical maximal force (F0) to the
theoretical velocity (v0) capabilities (Morin and Samozino, 2016).
As shown theoretically (Samozino et al., 2008, 2012) and
confirmed experimentally (Samozino et al., 2014), there is,
for each individual, an optimal F-v profile that maximizes
the ballistic performance (e.g., vertical or inclined jumping)
and represents the optimal balance between force and velocity
qualities for these movements (Samozino et al., 2012, 2014). The
relative difference between actual and optimal F-v profiles for
a given individual represents the magnitude and the direction
of the unfavorable balance between force and velocity qualities
(i.e., force-velocity imbalance, FVimb in %), which makes possible
the individual determination of force or velocity deficit. The
actual individual F-v profile and Pmax can be easily determined
from a series of loaded vertical jumps (Samozino et al., 2008,
2014; Jiménez-Reyes et al., 2014, 2016; Giroux et al., 2015,
2016), while the optimal F-v profile can be computed using
previously proposed equations based on a biomechanical model
(Samozino et al., 2012, 2014). For a given Pmax, vertical jump
performance has been shown to be negatively correlated to FVimb,
which supports the importance of considering this individual
characteristic in addition to Pmax when designing training
programs to improve ballistic performance (Samozino et al.,
2012, 2014; Morin and Samozino, 2016).
Quantifying FVimb on an individual basis could therefore help
improve the effectiveness of training prescription by adapting
it to each athlete’s individual needs. In theory, this would lead
to improved ballistic performance through an effective shift in
the individual actual F-v profile toward the optimal value (FVimb
reduction), and/or an increase in Pmax (Samozino et al., 2014).
For instance, the individual jumping F-v profile has been shown
sensitive to training over different periods of a season in high-
level rugby players (de Lacey et al., 2014), and to training history
and sport activities of various populations (Vuk et al., 2012;
Markovic et al., 2013; Samozino et al., 2014; Giroux et al., 2016).
Therefore, we can reasonably expect (personal unpublished pilot
observations) that the individual F-v profile would respond to
specific training. Moreover, the individual jumping F-v profile
has been shown sensitive to the kind of strength training
performed (Cormie et al., 2010).
Some traditional training methods have been considered for
power improvement, such as: power and ballistic training (e.g.,
Wilson et al., 1993; Newton et al., 1996; Cormie et al., 2007,
2010; Argus et al., 2011; Markovic et al., 2011; Sheppard et al.,
2011; Zaras et al., 2013), heavy-load training (focusing more on
strength; e.g., Gorostiaga et al., 1999; Harris et al., 2000; Chelly
et al., 2009; Rønnestad et al., 2012, 2016) and combined training
(strength-power training; e.g., Wilson et al., 1993; McBride et al.,
2002; Kotzamanidis et al., 2005; Cormie et al., 2007, 2010;
Smilios et al., 2013; Zaras et al., 2013). This kind of global
power training prescription similar for all athletes resulted in
contrasting findings as to the effects on jumping performance
(e.g., Wilson et al., 1993; Gorostiaga et al., 1999; Harris et al.,
2000; McBride et al., 2002; Kotzamanidis et al., 2005; Cormie
et al., 2007, 2010; Chelly et al., 2009; Rønnestad et al., 2012,
2016; Smilios et al., 2013; Zaras et al., 2013), likely because
of the various levels and F-v characteristics of the populations
tested. Indeed, a training program leading to improve Pmax while
increasing FVimb could result in a lack of change, or even a
decrease in jumping performance. We propose here that tailoring
the training prescription to the athlete’s individual F-v profile
would improve the effectiveness of such training. This innovative
approach will be designed as follows.
In the case of a force deficit, training should be aimed
to increase Pmax while decreasing FVimb, by increasing force
capabilities (F0) as a priority (Samozino et al., 2012). Previous
studies clearly shows the effectiveness of strength training aiming
at specifically increasing maximal force capabilities (Cormie et al.,
2007, 2010; Rønnestad et al., 2012, 2016; Zaras et al., 2013).
They have shown improvements in maximal strength parameters
(e.g., 1RM, 1RM/BM ratio) through trainings involving the
use of high loads (>70% RM), in order to achieve the
maximal neuromuscular adaptations, in periods ranging from
6 to 12 weeks. Note that these training-induced adaptations
were not systematically associated to ballistic performance
improvements.
At the other end of the F-v spectrum, in case of a velocity
deficit, training should aim to increase Pmax by improving
maximal velocity capabilities (i.e., capacity to produce force at
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Jiménez-Reyes et al. Force-Velocity Optimized Training for Jump Performance
very high contraction velocities). It should be oriented toward
maximal velocity efforts during high accelerated movements with
minimal or null braking phase, for example a throw at the end of
a lift and displacing low (<30% RM) or negative loads (Argus
et al., 2011; Markovic et al., 2011; Sheppard et al., 2011). The
effects of this type of training, commonly referred to as ballistic,
can be observed in studies where protocols with a removed
deceleration phase during liftings have been shown more effective
(Newton et al., 1996; Cormie et al., 2010). These studies and
others (Markovic and Jaric, 2007; Argus et al., 2011; Markovic
et al., 2011, 2013; Sheppard et al., 2011) show how employing
loads lower than body mass (referred to as negative loads) may
result in a training-induced shift in force-time curves and force-
velocity relationships toward more velocity-related capabilities
(Djuric et al., 2016).
Finally, in case of a low deficit (i.e., actual F-v profile close
to the computed optimal profile), the training program should
target a balanced combination of force, velocity, and power in
order to shift the entire F-v relationship to the right, and so to
increase Pmax as a priority (Wilson et al., 1993; Harris et al., 2000;
McBride et al., 2002; Kotzamanidis et al., 2005; e.g., Cormie et al.,
2007; de Villarreal et al., 2011) while maintaining the F-v profile
close to the optimal value (and thus FVimb close to 0%). The
effects of studies aiming to both increase maximal power and shift
the entire F-v curve show how combining a wide range of loads
(heavy, optimal, and ballistic loads) is an appropriate stimulus
(Harris et al., 2000; McBride et al., 2002; Kotzamanidis et al.,
2005; Cormie et al., 2007).
In light of the three latter paragraphs showing the sensitivity
of the F-v profile to specific training programs can result in
either maximal force or velocity capabilities improvements, it
is reasonable to hypothesize that specific resistance training
programs can be designed on an individual basis to both reduce
FVimb (i.e., to increase preferably the F0or v0component of an
individual’s F-v profile and shift it toward his optimal profile) and
increase Pmax (in case of well-balanced F-v profile). This is what
we will term “optimized training” or “individualized training
based on FVimb” in the present study.
Theory (Samozino et al., 2012, 2014) and case studies (Morin
and Samozino, 2016) show that, ceteris paribus, such a training
approach could result in a decreased FVimb and in turn, in an
improved jumping performance. To date no direct controlled
experiment has been performed to confirm the effectiveness of
this optimized training approach.
The aim of this study was to experimentally test the
hypothesis that an individualized training program based on
the imbalance in the F-v profile of each individual is more
effective in improving jump performance than a traditional
resistance training common to all subjects and designed without
taking account of individual differences in the initial F-v profiles
and imbalances. We also hypothesized that in such a case, the
improved vertical jump performance would result from both
a shift in the F-v profile toward the optimal and an increase
in Pmax, while the “non-optimized” group would only increase
Pmax. Note that vertical jump height was used here as the index
of performance since it represents the archetype of ballistic
movements.
MATERIALS AND METHODS
Subjects
Eighty-four trained athletes (age =23.1 ±4.4 year, body
mass =75.5 ±8.5 kg, stature =1.79 ±0.046 m) gave their
written informed consent to participate in this study, which
was approved by the local ethical committee of the Catholic
University of San Antonio (Murcia) in agreement with the
Declaration of Helsinki. All subjects were semi-professional
soccer and rugby players. All athletes had a strength-training
background ranging from 1 to more than 3 years, were highly
trained (average weekly training volume of 12 h at the time of the
study), and familiar with the testing procedures.
Testing Procedure and Data Processing
F-v Relationships of Lower Limb Neuromuscular
System in SJ
To determine individual F-v relationships, each subject
performed vertical maximal SJ without loads and against five to
eight extra loads ranging from 17 to 87 kg in a randomized order.
The test was performed on a Smith machine (Multipower Fitness
Line, Peroga, Spain) that allows a smooth vertical displacement
of the bar along a fixed vertical path. Before each SJ condition
with no additional load, participants were instructed to stand
up straight and still on the center of the jumping area. They
kept their arms on their hips for jumps without load and on the
bar for loaded jumps, this hand position remaining the same
during the entire movement. Subjects were asked to maintain
their individual starting position (90knee angle) for about 2 s
and then apply force as fast as possible and jump for maximum
height. Countermovement was verbally forbidden and carefully
checked. If all these requirements were not met, the trial was
repeated. Two valid trials were performed with each load with
2 min of recovery between trials and 4–5 min between loads
condition.
Mean mechanical parameters were calculated for each loading
condition using Samozino’s method (Samozino et al., 2008),
based on Newton’s second law of motion. This method
establishes that mean force (F), velocity (v), and power (P) can
be calculated during a vertical jump from jump height and squat
jump positions measurement. Jump height was obtained using
an OptoJump optical measurement system (Microgate, Bolzano,
Italy). Force, velocity and power were calculated using three
equations considering only simple input variables: body mass,
jump height and push-off distance. The latter corresponds to the
distance covered by the center of mass during push-off, i.e., to the
extension range of lower limbs from the starting position to take-
off (Samozino et al., 2008), and was a priori measured for each
subject by the difference between the extended lower limb length
(iliac crest to toes with plantar flexed ankle) and the height in the
individual standardized starting position (iliac crest to ground
vertical distance).
F-v relationships were determined using the best trials of each
loading condition and least squares linear regressions. F-v curves
were extrapolated to obtain F0(then normalized to body mass)
and v0, which respectively correspond to the intercepts of the
F-v curve with the force and velocity axis. The F-v profile, that
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Jiménez-Reyes et al. Force-Velocity Optimized Training for Jump Performance
is the slope of the F-v linear relationship was then computed
from F0and v0according to Samozino et al. (2012). Values of
Pmax (normalized to body mass) were determined as: Pmax =
F0·v0/4 (Samozino et al., 2012, 2014). From Pmax and hpo values,
there is an individual theoretical optimal F-v profile (normalized
to body mass, in N.s.kg1.m1) maximizing vertical jumping
performance that was computed for each subject using equations
proposed by Samozino et al. (2012). The F-v imbalance (FVimb,
in %), was then individually computed as recently proposed by
Samozino et al. (2014):
Fvimb =100. |1SFv
SFv opt |
AFVimb value around 0% indicates a F-v proifile equal to 100%
of the optimal proifile (perfect balance between force and velocity
qualities), whereas a F-v profile value higher or lower than the
optimal indicates a profile too oriented toward force or velocity
capabilities, respectively.
Experimental Design
The present study used a longitudinal pre-post design with
testing sessions separated by 9 weeks. All tests were conducted
at the same time of day, from 17:00 to 21:00. Each subject
underwent anthropometric assessment and performed loaded
squat jumps (SJ) to determine the individual force-velocity (F-
v) relationships, Pmax values and F-v imbalance (computations
are detailed in the next section). FVimb was then used as the
reference to assign participants to different training intervention
groups and sub-groups. Since the main line of the approach
tested is that performance improvement would result from
increasing Pmax and/or decreasing FVimb (Morin and Samozino,
2016), and given our main hypothesis, FVimb was the criterion
used for designing an individualized training program in this
study.
After initial testing of their individual F-v properties,
participants were assigned to optimized training group [force
deficit (FD) sub-group (n=22; body mass =72.2 ±8.3 kg,
stature =1.78 ±0.062 m], velocity deficit (VD) sub-group (n
=18; body mass =80.6 ±9.6 kg, stature =1.811 ±0.042 m),
well-balanced (WB) sub-group (n=6; body mass =75.6 ±4.9
kg, stature =1.783 ±0.049 m), a non-optimized training group
(NO, n=18; body mass =77.0 ±6.6 kg, stature =1.791 ±0.033
m), or a control group (CG, n=20; body mass =73.0 ±7.9 kg,
stature =1.785 ±0.032 m). The training program was adjusted
to the needs of participants in the optimized group according to
the FVimb. As a consequence, the training program was slightly
different regarding loading but similar in volume among groups,
and all subjects were familiar with the exercises used. The training
intervention was performed at the middle of the competitive
season for all participants.
During the 9 weeks of training, the FD sub-group performed
mainly force-oriented (very high loads) training, while the
VD sub-group performed velocity-oriented (ballistic, very high
velocity of limbs extension) training. The WB sub-group followed
a training program covering the entire force-velocity spectrum
in equal proportions: heavy loads, power, and ballistic training.
All the subjects of the NO training group followed the latter
kind of training, independently from each subject’s FVimb. NO
group was composed by 18 subjects with different initial F-v
profile and FVimb before the training intervention (10 with force
deficit and 8 with velocity deficit), with the purpose to match the
distribution of the optimized groups as much as possible. Finally,
the CG maintained their normal level of activity throughout the
duration of the study without performing any kind of strength
training. For each subject, jumping F-v profile and performance
were tested exactly 1 week before the first training session (pre-
training), and again 1 week after the completion of the 9-week
training (post-training). The training intervention for all groups
was organized following recommendations from the literature:
more than three sets/session (Rhea et al., 2002) and a frequency of
2–3 sessions/week for strength (Rhea et al., 2003; Peterson et al.,
2004), including plyometrics (Markovic, 2007). All intervention
groups performed 18 sets/week (details in Tables 1, 2), which is
similar to previous research (Harris et al., 2000; McBride et al.,
2002; Cormie et al., 2007, 2010; Argus et al., 2011; Markovic
et al., 2011; Sheppard et al., 2011). The training dose required
to develop strength is generally described as high frequency (3–5
weekly sessions per muscle group), moderate volume (3–6 sets ×
2–6 repetitions ×load mass), and high intensity (85–100% one-
repetition maximum (1RM) and non-ballistic nature of strength
training exercises; while power differs mainly in the intensity (20–
70% 1RM) and high movement velocity (i.e., explosive-ballistic;
Baechle and Earle, 2000; Fleck and Kraemer, 2004).
TABLE 1 | Force-velocity imbalance categories, thresholds, and
associated resistance training load ratios.
FVimb categories F-v profile in % of optimal
thresholds (%)
Training loads ratio*
High force deficit <60 3 Strength
2 Strength-power
1 Power
Low force deficit 60–90 2 Strength
2 Strength-power
2 Power
Well-balanced >90–110 1 Strength
1 Strength-power
2 Power
1 Power-speed
1 Speed
Low velocity deficit >110–140 2 Speed
2 Power-speed
2 Power
High velocity deficit >140 3 Speed
2 Power-speed
1 Power
FVimb, F-v imbalance. *Ratio based on six exercises/wk, three sets/exercise and 18
sets/wk.
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Jiménez-Reyes et al. Force-Velocity Optimized Training for Jump Performance
TABLE 2 | Loading target for the F-v spectrum and exercises and training
loads for each exercise.
Loading focus/target Exercises Training loads
Strength Back squat 80–90% 1RM
Leg press 90–95% 1RM
Deadlift 90–95% 1RM
Strength-power Clean pull 80% 1RM
Deadlift 80% 1RM
SJ >70% of BW
CMJ >80% of BW
Power SJ 20–30% of BW
CMJ 35–45% of BW
Single leg SJ BW
Single leg CMJ 10% of BW
Clean pull jump 65% 1RM
Power-speed Depth jumps
SJ BW
CMJ 10% of BW
Maximal Vertical Box Jump
Speed Maximal Roller Push-off <BW
CMJ with arms BW
RM, repetition maximum; SJ, Squat Jump; BW, body weight; CMJ, Countermovement
Jump.
Training Intervention
Due to the pilot feature of this study, we designed
straight-forward and simple training programs in the context
of a first attempt to test our hypotheses. All training programs
involved two sessions per week, each separated by 48 h of
recovery. Subjects refrained from any additional lower body
resistance training outside the experimental training throughout
the course of the study. Their competitive activities and
sport-specific training was maintained.
Considering the aforementioned elements on the specificity
of training to improve the specific components of maximal force
or velocity parts of the F-v spectrum (e.g., Wilson et al., 1993;
Newton et al., 1996; Harris et al., 2000; McBride et al., 2002;
Cormie et al., 2007, 2010; Argus et al., 2011; Markovic et al., 2011;
Sheppard et al., 2011; Rønnestad et al., 2012, 2016; Zaras et al.,
2013), the FD and VD training groups were established according
to individuals’ FVimb. For each one of these sub-groups, we
considered not only the type of deficit (either in force or in
velocity), but also its magnitude. Therefore, in each sub-group,
the training program was established according to specific FVimb
thresholds, as detailed in (Table 1).
According to previous findings showing improvements in
maximal strength, power and ballistic performance after specific
training (e.g., Cormie et al., 2007, 2010), the individualized
training programs proposed here included maximal efforts and
were mainly designed by setting the loads to vary the movement
velocity, and in turn to target the different parts of the F-v curve.
For example, “Strength” exercises used high loads F0moved at
low v such as >80% of one repetition maximum in back squat
whereas “Speed” exercises used Fof body mass moved at high
v. The high vwas greater than a squat jump, using the stretch-
shortening cycle (e.g., CMJ) or assisted/low resistance push-offs
(e.g., band assisted SJ or horizontal assisted roller).
Statistical Analysis
All data are presented as mean ±SD. In order to clearly assess
the practical meaning of the results, data were analyzed using the
magnitude-based inference approach (Hopkins et al., 2009).
Within-group difference in pre and post-training jump height,
F-v profile in (%) of Optimal F-v, F0, and v0were assessed using
standardized effect size (ES). Between-group (optimized group
vs. non-optimized group) differences in pre and post-training
jump height and F-v profile in (%) of Optimal F-v were also
assessed using standardized ES. The magnitude of the within-
group and between-group changes was interpreted by using
values of trivial (<0.20), small (0.20 to <0.60), moderate (0.60
to <1.20), large (1.20 to <2.00), and extremely large of the
between-athlete variation at pre (i.e., smallest worthwhile change,
SWC).
The probability that these differences actually exist was then
assessed via magnitude-based qualitative inferences (Batterham
and Hopkins, 2006). Qualitative inferences were based on
quantitative chances of benefit outlined in Hopkins et al. (2009).
Clinical chances are percentage chances that an observed effect
is clinically positive/trivial/negative e.g., (40/40/20%) means an
effect has 40% of chances to be positive, 40% to be trivial, and 20%
to be negative. Probabilities that differences were higher than,
lower than, or similar to the smallest worthwhile difference were
evaluated qualitatively as possibly, 25–74.9%; likely, 75–94.9%,
very likely, 95–99.5%; and most (extremely) likely, >99.5%.
Since the findings of present study could be used for athletes
considered in isolation, individual analyses were performed
to quantify for each variables and each group the number
of responders and no responders. Monitoring progression of
an athlete with performance requires taking into account the
magnitude of the SWC in performance and the uncertainty
or noise in the test result (Hopkins, 2004), SWC being
computed as one-fifth of the between-athlete standard deviation
(a standardized or Cohen effect size of 0.20, Hopkins, 2004).
Subjects were then considered as harmful (individual change <
1 SWC), trivial (from 1 SWC to +1 SWC) or beneficial (+1
SWC) responders.
RESULTS
Mean ±SD values for all performance and mechanical variables
pre and post training intervention are shown for all groups
and sub-groups in Table 3, along with within-group changes
qualitative inferences.
FD and VD sub-groups showed large and extremely large
changes in FVimb, respectively, whereas this change was unclear
for the WB group, who showed a small increase in Pmax (Table 3).
Contrastingly, the changes for the “non-optimized” group were
overall likely trivial, with a very high inter-subject variability
(Table 3;Figures 1,2). The most important improvements in
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Jiménez-Reyes et al. Force-Velocity Optimized Training for Jump Performance
TABLE 3 | Changes in variables associated to Force-velocity profile in different groups.
Pre Post Post-pre Individual response
¯
x±SD ¯
x±SD %1±SD ES; ±90% CL Inference and probability Harmful/Trivial/Beneficial
F-v (%) OPTIMAL F-v
Force deficit 45.1 ±14.3 68.8 ±17.7 57.9 ±34.7 1.60 ±0.26 Large +ive most likely 1 – 0 – 21
Velocity deficit 130 ±11.5 103 ±6.3 20.1 ±4.3 2.20 ±0.26 Ext. Large –ive most likely 0 – 0 – 18
Well-balanced 101 ±7.0 100 ±1.4 0.50 ±6.7 0.11 ±0.20 Trivial unclear 3 – 1 – 2
Non-optimized 88.6 ±38.1 81.8 ±34.7 5.54 ±17.6 0.17 ±0.15 Trivial possibily 7 – 3 – 8
Control 77.9 ±33.1 79.3 ±34.5 1.91 ±17.1 0.01 ±0.08 Trivial most likely 1 – 14 – 5
Pmax (W·kg1)
Force deficit 30.7 ±5.6 30.5 ±5.8 0.40 ±8.4 0.04 ±0.17 Trivial likely 7 – 12 – 3
Velocity deficit 24.2 ±4.8 26.6 ±5.0 10.5 ±5.2 0.48 ±0.08 Small +ive most likely 0 – 1 – 17
Well-balanced 23.9 ±2.2 25.2 ±2.2 5.53 ±4.5 0.50 ±0.33 Small +ive likely 0 – 1 – 5
Non-optimized 23.5 ±3.5 24.0 ±3.3 2.42 ±6.1 0.13 ±0.16 Trivial likely 5 – 3 – 10
Control 23.2 ±2.5 23.4 ±5.6 0.61 ±15.7 0.09 ±0.58 Trivial unclear 7 – 11 – 2
F0(N·kg1)
Force deficit 29.1 ±4.1 35.9 ±4.2 24.0 ±10.8 1.60 ±0.17 Large +ive most likely 0 – 2 – 20
Velocity deficit 43.4 ±6.1 40.6 ±5.2 6.16 ±3.3 0.43 ±0.10 Small -ive most likely 17 – 1 – 0
Well-balanced 38.5 ±1.5 39.1 ±1.9 1.76 ±3.5 0.38 ±0.64 Small +ive unclear 2 – 1 – 3
Non-optimized 34.1 ±7.4 33.2 ±7.1 2.32 ±6.8 0.12 ±0.13 Trivial likely 9 – 6 – 3
Control 31.9 ±6.8 31.9 ±7.0 0.21 ±3.8 0.00 ±0.06 Trivial most likely 2 – 17 – 1
v0(m·s1)
Force deficit 4.29 ±0.93 3.44 ±0.78 18.9 ±11.8 0.88 ±0.24 Moderate -ive most likely 21 – 0 – 1
Velocity deficit 2.21 ±0.16 2.60 ±0.17 17.9 ±4.2 2.73 ±0.21 Ext. Large +ive most likely 0 – 0 – 18
Well-balanced 2.48 ±0.17 2.57 ±0.11 3.70 ±4.1 0.44 ±0.41 Small +ive likely 1 – 1 – 4
Non-optimized 2.88 ±0.72 3.00 ±0.67 5.57 ±11.9 0.17 ±0.21 Trivial possibly 5 – 3 – 10
Control 3.05 ±0.82 3.10 ±1.25 1.18 ±21.2 0.06 ±0.36 Trivial unclear 3 – 16 – 1
JUMP HEIGHT (m)
Force deficit 0.323 ±0.04 0.367 ±0.04 14.2 ±7.3 1.00 ±0.17 Moderate +ive most likely 0 – 0 – 22
Velocity deficit 0.319 ±0.06 0.357 ±0.05 12.7 ±5.7 0.93 ±0.09 Moderate +ive most likely 0 – 0 – 18
Well-balanced 0.315 ±0.03 0.338 ±0.03 7.22 ±4.5 0.70 ±0.36 Moderate +ive very likely 0 – 0 – 6
Non-optimized 0.305 ±0.04 0.312 ±0.04 2.33 ±4.7 0.14 ±0.13 Trivial likely 1 – 10 – 7
Control 0.292 ±0.04 0.288 ±0.04 1.43 ±3.3 0.09 ±0.10 Trivial very likely 9 – 10 – 1
Values are mean ±standard deviation, percent change ±standard deviation and standardized effect size; ±90% confidence limits. ¯
x, mean; SD, standard deviation, %, percent
change; ES, effect size; 90% CL, 90% confidence limits; Ext, extremely; +ive, positive effect; -ive, negative effect; Pmax, maximal power output; W, watt; kg, kilogramme; F0, theoretical
maximal force; N, newton; v0, theoretical maximal velocity; m, metre; s, second. Qualitative inferences are trivial (<0.20), small (0.20 to <0.60), moderate (0.60 to <1.20), large (1.20 to
<2.00) and extremely large moderate (>2.00): possibly, 25 to <75; likely, 75 to <95%; ver y likely, 95 to <99.5%; most likely, >99.5. Positive, neutral and negative descriptors qualitatively
describe the change between post and pre values and its importance relative to the specific variable.
jump performance were observed in the intervention groups
(+7.2 to +14.2% on average, very likely to most likely very large
effects vs. trivial change of +2.3% for the non-optimized and
control group).
An individual approach of the study outcomes shows that in
the optimized group (including FD, VD, and WB sub-groups) all
the 46 subjects improved their jump height, and all of them but
one reduced their FVimb (Table 3). For the non-optimized group,
only 10 subjects out of 18 improved jump height and 11 out of 18
reduced their FVimb. Finally, in the control group, only 8 subjects
out of 20 subjects improved jump height and 12 out of 20 reduced
their FVimb.
In the optimized group (including FD, VD, WB sub-groups),
all the subjects were beneficial responders in jump height, and all
of them but one in FVimb (Table 3). Contrastingly, 7 subjects out
of 18 of the non-optimized group were beneficial responders for
jump height (8 out of 18 for FVimb) and 1 out of 20 in control
group (5 out of 20 in FVimb,Table 3).
The results referring to between-groups differences showed
almost certain large (ES =1.21–100/0/0) and moderate (ES =
0.73 100/0/0) differences in FVimb and jump height, respectively,
in favor of optimized group vs. non-optimized group, which
highlight the findings in our study.
As shown in Table 3, the changes for the non-optimized
and control groups were much more variable and the overall
magnitude less clear.
DISCUSSION
The aim of this study was to experimentally test the hypothesis
that an individualized training program based on the force-
velocity imbalance of each subject was more effective at
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Jiménez-Reyes et al. Force-Velocity Optimized Training for Jump Performance
FIGURE 1 | (A) Individual Pre-Post changes in F-v profile for Optimized Group
and sub-groups. (B) Individual Pre-Post changes in F-v profile for
Non-Optimized and Control Group.
improving jump performance than a traditional resistance
training common to all subjects (designed without taking
account of individual differences in the initial F-v profiles and
imbalances). Our main hypothesis was that this individualized
and optimized training would result in a decreased imbalance for
each individual, and in turn a greater vertical jump performance.
The main findings of this study validate our initial hypothesis:
(i) an optimized and individualized training program specifically
addressing the FVimb is more efficient for improving jumping
performance (all subjects showed improvement in jump height)
than a traditional resistance training common to all subjects (10
subjects out of 18 improved), regardless of their force-velocity
imbalance and optimal force-velocity profile, (ii) for subjects with
an initial substantial FVimb (i.e., force or a velocity deficit) this
higher jump performance was associated with the sensitivity of
the force-velocity profile to the specific training program tailored
to the athlete’s individual needs, which has lead here to a reduced
F-v imbalance with no change in Pmax.
It is important to highlight that jump height improvements
were greater, and for a larger number of subjects, with a
training based on the F-v approach and FVimb as opposed to
traditional training. Although this is not a common practice
in the strength and conditioning field, its application could
be of high interest since the optimal F–v profile, which can
FIGURE 2 | (A) Individual Pre-Post changes in vertical jump height for
Optimized Group and sub-groups. (B) Individual Pre-Post changes in F-v
profile for Non-Optimized and Control Group.
be accurately determined, depends on individual characteristics
(limb extension, Pmax and different loaded squat jumps;
Samozino et al., 2012). Thus it could be a very easy to design
a training program with the focus on increasing Pmax and/or
decreasing FVimb (Morin and Samozino, 2016).
The main novelty of our results was that in order to improve
jump performance, not only should Pmax be considered, but
also the individual force-velocity profile. Indeed, changes in
Pmax were trivial or small in the FD and VD optimized sub-
groups, whereas changes in F0and v0were large and extremely
large. Contrastingly, the “one-size-fits-all” program with the non-
optimized group might not be an efficient training stimulus
for a group of individuals with different FVimb, thus different
training needs. Despite some inevitable limitations that will be
addressed at the end of this discussion, the novelty of the present
experimental study and the clear results obtained may bring
valuable additional knowledge and potential applications to sport
training practice toward a more individualized, specific, and
effective training monitoring and periodization.
Several studies have shown some positive effects of strength
training on improving vertical jump performance, although
with contradictory results, and inconsistancies in the training
prescription (e.g., heavy loads for all subjects; Gorostiaga et al.,
1999; Harris et al., 2000; McBride et al., 2002; Cormie et al., 2010;
de Villarreal et al., 2011; Losnegard et al., 2011; Rønnestad et al.,
2012, 2016), while other studies considered also light loads (e.g.,
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Jiménez-Reyes et al. Force-Velocity Optimized Training for Jump Performance
Wilson et al., 1993; McBride et al., 2002; Cormie et al., 2007;
Zaras et al., 2013), or combined strength training (e.g., Wilson
et al., 1993; Toji et al., 1997; Harris et al., 2000; McBride et al.,
2002; Kotzamanidis et al., 2005; de Villarreal et al., 2011). Two
common features of these studies were that the same training
program was prescribed to all subjects and the great variability in
performance response to training (Wilson et al., 1993; Gorostiaga
et al., 1999; Harris et al., 2000; McBride et al., 2002; Kotzamanidis
et al., 2005; Cormie et al., 2007, 2010; Chelly et al., 2009; de
Villarreal et al., 2011; Losnegard et al., 2011; Rønnestad et al.,
2012, 2016; Smilios et al., 2013). In the present protocol, all the
subjects tested were sub-divided into specific sub-groups and
then assigned to a group-specific training program, which led
to a more appropriate training program and more efficient and
less variable results in terms of jump performance improvement
compared to the aforementioned studies. Each of these groups
will be discussed separately.
Force-Deficit Sub-group
For the FD sub-group, the specific heavy-load program resulted
in moderate to large increases in F0(+24 ±10.8% on average; ES
=1.60 ±0.23), FVimb reduction for all subjects but one (57.9
±34.7%; ES =1.60 ±0.26) and jump height (+14.2 ±7.3%;
ES =1.00 ±0.17). Individual analysis showed that all subjects
improved jump height and all but one reduced FVimb, which
would support the great effectiveness of this kind of training
approach. Thus, as hypothesized, the selected exercises for this
group were likely effective for specifically shifting F-v profile in
accordance with initial FVimb showing a force-deficit (Table 3;
Figures 1,2). These findings are in agreement with other studies
showing high-load training specificity (Wilson et al., 1993; Harris
et al., 2000; McBride et al., 2002; Cormie et al., 2010).
The large increase in F0in the FD sub-group was associated
to an important increase in jump height since vertical jumping is
in the most force-dependent plane for a ballistic movement as
it encounters the maximal magnitude of negative gravitational
acceleration (Minetti, 2002; Samozino et al., 2012) meaning
an increase in F0would influence jump height more than an
increase in v0(Samozino et al., 2010). In line with this, the
FD group had “high” or “low/moderate force deficits and thus
used mainly heavy load resistance training exercises (Tables 1,
2) which should have theoretically increased jump height and
principally via an increase in F0(Harris et al., 2000; McBride et al.,
2002; Cormie et al., 2010; Losnegard et al., 2011; Rønnestad et al.,
2012, 2016).
The increase in F0is observed here in parallel with a decrease
in v0, even if no interrelationships can be supported between
these two qualities, except the fact that when one of these qualities
is trained, the other is not. So, in present study, the maximal
strength improvement (F0) is not associated with the same kind
of increase in Pmax, which would have been the case if subjects
had kept their v0value similar. Consequently, the performance
improvement can be only attributed to FVimb reduction, and not
to an increased Pmax, which is greater support for the interest
of considering FVimb in strength training focusing on improving
ballistic performance.
The possible explanatory mechanisms for these changes in
maximal force after the optimized training may include an
increased neural drive and enhanced intermuscular coordination
(McBride et al., 2002; Cormie et al., 2010), rate of motor
unit recruitment (size principle), and the activation of type
II muscle fibers and subsequent improvement in maximal
strength capabilities (Cormie et al., 2011). These changes may
also be associated with effective changes in synchronization of
action potentials and antagonist co-activations leading to an
improvement in dynamic force and power production (Folland
and Williams, 2007).
As discussed in the limitations, the duration of the training
intervention induced a shift in F-v profile (FVimb reduced by
more than one half), although some additional weeks of training
might have totally removed FVimb in some subjects, since the
time for adjustments at structural level (mainly related to F0)
typically require a longer period (Kenney et al., 2015) beyond the
more acute neuromuscular adaptations.
Velocity-Deficit Sub-group
Concerning the VD group, the specific training caused moderate
to extremely large increases in v0(+17.9 ±4.2%; ES =2.37 ±
0.21), FVimb reduction (20.1 ±4.3%; ES =2.20 ±0.26) and
jump height (+12.7 ±5.7%; ES =0.93 ±0.09), with a majority of
responders (Table 3;Figures 1,2). This suggests that the selected
specific exercises for this group were effective for shifting F-v
profile in accordance with initial FVimb (Table 3;Figures 1,2)
and improving the maximal velocity end of the F-v relationship.
These findings are in agreement with other studies aiming at
specifically improving velocity qualities (Newton et al., 1996;
Argus et al., 2011; Markovic et al., 2011; Sheppard et al., 2011),
supporting the “principle of velocity specificity” as a specific
stimulus to promote velocity-specific neural training adaptations
(Kanehisa and Miyashita, 1983; Sale, 1988; Newton et al., 1996;
Paddon-Jones et al., 2001). Similarly to the FD sub-group, the
increase in v0in the VD group was observed here in parallel with
a decrease in F0, so following the same interpretation as above,
the performance improvement can only be attributed to FVimb
reduction, and not to increased Pmax. It is almost certain that with
both a FVimb reduction and an increase in Pmax (so keeping F0
at similar level), improvements in performance would have been
greater.
The main exercise used in the VD group was the “horizontal
push” (Figure 3) exercise in which there was an almost total
elimination of the gravitational component. This could be
explained by the fact that power output developed during
maximal efforts is less dependent on muscle strength when the
exercise does not involve gravity (Minetti, 2002), as it would be
the case of a horizontal extension such as our horizontal push
exercise. This training exercise likely had a meaningful impact in
the extremely large increase in v0observed for the VD group.
The main features of this exercise (almost null gravitational
component and limited time available for applying force)
makes it particularly suitable for the development of explosive
muscle contractions (rate of force development and maximal
velocity; Tillin and Folland, 2014). This “overspeed” exercise may
therefore be considered of great interest for improving velocity
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Jiménez-Reyes et al. Force-Velocity Optimized Training for Jump Performance
FIGURE 3 | (A) Representation of starting position for horizontal push-off
exercise. (B) Representation of final position for horizontal push-off exercise.
capabilities and reducing the associated FVimb since it suppresses
the gravitational constraint (Markovic and Jaric, 2007; Sheppard
et al., 2011; Leontijevic et al., 2012; Vuk et al., 2012; Markovic
et al., 2013; Pazin et al., 2013; Suzovic et al., 2013) and helps
athletes reach lower limbs extensión velocity 20–30% higher than
the take-off velocity of a SJ (personal unpublished data; Markovic
et al., 2011). As a result, the most representative effect would be
to shift the early force-time curve to the left (50–100 first ms;
Oliveira et al., 2013, 2016). That said, from a practical standpoint,
we think that any exercise involving an external resistance force
lower than bodyweight can be effective. Although further studies
should investigate whether lighter loads have greater training
effects, these results are in line with studies about the influence
of training with no gravitational negative loads (Argus et al.,
2011; Markovic et al., 2011; Sheppard et al., 2011). Sheppard
et al. (2011) found that volleyball players who trained for 5
weeks with assisted jumps, significantly improved jump height
compared to subjects who performed regular jump training. They
reported that “assisted jumping” was useful at overloading the
velocity aspects of jump propulsión, which is similar to what
we intended to do with a specific work of horizontal push.
Similarly, (Markovic et al., 2011), reported a marked increase in
peak lower limb extension velocity resulting from a 7-week jump
training with negative loading (assisted jumps), supporting the
concept of velocity specificity in resistance training as in previous
ballistic power training studies (Sale, 1988; Markovic and Jaric,
2007; Cormie et al., 2010). Finally, Argus et al. (2011) observed
similar positive effects on jump height after a 4-week assisted
jumps (20% of body weight) training program. Interestingly,
these authors reported the individual changes, which show that
6 of the 9 participants in their study improved jump height
under this “velocity-oriented” program. The fact that these
subjects were highly trained rugby players (thus very likely with
a force-oriented F-v profile, and in turn a velocity deficit) may
explain the counterintuitive result showing that most of them
improved jump height after an assisted jump training program.
We speculate that most of these rugby players needed to correct
a velocity deficit to improve jump height, and this may explain
why they responded well to the assisted jump program.
Although our aim was not to investigate the neuro-
physiological mechanisms underpinning the changes observed
in the VD group, these may include a changes in neural
activation patterns (i.e., lowered motor unit recruitment
thresholds, improved motor unit firing frequency, and possibly
synchronization, greater and/or more effective recruitment
of fast-twitch muscle fibers) and enhanced intra- and inter-
muscular coordination (Sale, 1988; Behm and Sale, 1993;
VanCutsem et al., 1998; de Ruiter et al., 2004, 2006).
Another interesting yet secondary result was that in the
FD and VD groups, the decrease in FVimb was due to both
an increase in the targeted component of the F-v profile (i.e.,
F0and v0, respectively), but also a decrease in the opposite
component. Subjects in the FD groups showed a large decrease
in v0after training (18.9 ±11.8%) and subjects in the VD
group showed a decrease in F0(6.2 ±3.3%). Although at
first sight it may seem that a training program resulting in a
decrease of a physical quality is counterproductive, but these
changes overall contributed here to the effective shift in the F-
v profile toward the optimal value. As previously mentioned,
better improvements might have been observed if subjects had
both an increase in their weak component (e.g., F0for the FD
group) and a maintainance of the other component (e.g., v0
for the FD group), which lead to an optimization of the F-v
profile (certainly slightly less fast than here) and an increase
in Pmax, both of them contributing independently to improve
performance. The training protocols proposed in this study did
not allow subjects presenting a F-v deficit to maintain at a similar
level the muscular quality initially considered as a “strength.”
The latter requires to keep the training quality considered as
a “strength” in addition to focus on reducting the “weakness,
which was not done enough in present protocol. However, the
increase in performance obtained here without any large change
in Pmax well supports the interest to consider FVimb in training
focusing to improve ballistic performance.
Well-Balanced Sub-group
Regarding the WB group results, the training program
encompassed all the components of the force-velocity spectrum
with equal distribution, and resulted in increases in F0(+1.8 ±
3.5%; ES =0.38 ±0.64) and v0(+3.7 ±4.1%; ES =0.44 ±0.41)
capabilities, with an overall maintainance of F-v profile (average
FVimb change of 0.5 ±6.7%; ES =0.11 ±0.20). This group
showed a moderate jump height improvement (+7.2 ±4.5%; ES
=0.70 ±0.36) mainly explained by the small increase in Pmax.
Thus, the training program proposed to this group resulted in an
overall shift of the entire F-v relationship to the right: increasing
Pmax while maintaining a very low FVimb, i.e., F-v profile close to
the optimal value. The findings for this group are in agreement
with previous studies using mixed resistance training loads
(Wilson et al., 1993; Toji et al., 1997; Harris et al., 2000; McBride
et al., 2002; Toji and Kaneko, 2004; Kotzamanidis et al., 2005;
Cormie et al., 2007; de Villarreal et al., 2011) to increase maximal
power output, and in turn ballistic performances.
Non-optimized Group
The “non-optimized” group performed a training program that
was similar to the WB group, and similar among subjects,
whatever their individual FVimb and thus training needs. This
resulted in a less clear changes in jump height (+2.3% on average
±4.7%; ES: 0.14 ±0.13, likely trivial), and substantial inter-
individual variability. Furthermore, only 10 subjects out of 18
improved jump height in this group (although only 7 out of
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Jiménez-Reyes et al. Force-Velocity Optimized Training for Jump Performance
18 were beneficial responders, Table 3) vs. all subjects in the
FD, VD and WB sub-groups. This result was associated with
variable changes (coefficient of variability of 200% or more) in
the F-v mechanical outputs: change in F0was 2.3 ±6.8%;
v0:+5.6 ±11.9%; Pmax:+2.4 ±6.1%; and FVimb :5.5 ±
17.6%. These results show that when addressed as a group,
and not individually, the training program was not effective in
reducing each subject’s FVimb . On the contrary, this common
program induced positive changes for some subjects and negative
changes for others, and overall considerable variability in the
outcome for both mechanical features of the F-v profile and jump
performance (Table 3;Figures 1,2). Comparatively, in terms of
jump height improvement, the number of responders in this non-
optimized group (7 out of 18) was much lower than for the
optimized sub-groups (all subjects of FD, VD, and WB groups,
i.e., 56 out of 56). It is important to note that the NO group
was composed of 18 subjects with different initial F-v profile
and FVimb before the training intervention (10 with force deficit
and 8 with velocity deficit) to match the distribution of the
optimized groups as much as possible. Assigning all subjects of an
intervention group to a common program aiming at increasing
jumping power and performance is the classical modus operandi
(Wilson et al., 1993; Harris et al., 2000; McBride et al., 2002;
Toji and Kaneko, 2004; Cormie et al., 2007, 2010), and these
studies also showed a great inter-individual variation in response
to the resistance training program. This high variability could
be interpreted as if the training program does not target the
initial FVimb of each subjects (as in our FD, VD, and WB
sub-groups), then subjects might not receive the most effective
training prescription on an individual basis, which in turn
results in variable outcomes when considering group results.
Depending on the interaction between subjects’ background and
the training program proposed, an experimental group may
include responders and non-responders in variable proportions
(e.g., Wilson et al., 1993; Gorostiaga et al., 1999; Harris et al.,
2000; McBride et al., 2002; Kotzamanidis et al., 2005; Cormie
et al., 2007, 2010; Chelly et al., 2009; Losnegard et al., 2011; de
Villarreal et al., 2011; Rønnestad et al., 2012, 2016; Smilios et al.,
2013). This has not been controlled for in previous studies, which
we think is a likely explanation for the high variability observed in
the outcome of most studies investigating the effects of strength
training on jump height. Thus, we suggest that the individual
F-v profile and the FVimb are taken into account as a starting
point for prescribing specific loads and training program for a
more effective training to improve jump performance (Tillin and
Folland, 2014; Morin and Samozino, 2016).
LIMITATIONS
Although this is the first study to tailor the strength training
program to the individual characteristics of the F-v profile,
it has limitations that should be discussed. First, our subject
recruitment led to a WB sub-group of only six subjects while
FD and VD sub-groups included 22 and 18 subjects, respectively.
Our personal experience (unpublished data) with hundredths of
athletes in various sports show that well-balanced F-v profile (i.e.,
FVimb close to 0%) are rare compared to subjects with a F-v
deficit (be it a force or a velocity deficit). However, the results
for these six individuals confirmed our hypothesis that a well-
balanced training would maintain their FVimb at low values,
while increasing their Pmax, and in turn their jump height. The
second and main limitation is that the fixed training duration
of 9 weeks for all subjects could be considered as not ideal. We
think that, just as the content of the training program, its duration
should also have been set on an individual basis. The duration of
the program should have been the duration necessary for each
individual to reach a FVimb close to 0. As shown in Figure 1 and
Table 3, this 9-week duration was close to optimal for most of the
VD sub-group subjects, but not long enough for most FD sub-
group subjects. We speculate that should the training duration
have also been individualized, the results of the intervention
would have been even better. We admit that, as explained in the
methods, this 9-week duration has been set under the influence
of previous studies, and we hope for further studies to show
an even more efficient optimized training should individualize
both the training content and the training duration, so that each
subject reduces his FVimb and/or increases his Pmax. This is, to
our opinion, one advantage of this approach: it allows a dynamic
adaptation to each individual’s response to training, both in terms
of training content and timing. Furthermore, as we observed
for only 2 subjects in this study (mid-program assessment of
F-v profile, data not shown), should subjects adapt faster than
others and change sub-group (e.g., from high force deficit to
low force deficit) within the pre-set training period, intermediate
assessments may easily allow to finely tune the training program
and adapt it to the response kinetics of each individual. Finally,
our study is focused on vertical F-v profile and jump performance
only, which is the simplest and most representative movement
for ballistic performances. An interesting point would be to
test whether a more optimal jumping F-v profile would be
associated with improved performance in other maximal effort
contexts such as sprint cycling or running. The latter is a major
physical component of performance in many sports, and many
studies focused on the transfer between lower limbs strength
training and sprint running performance (Cronin and Sleivert,
2005; Seitz et al., 2014; Contreras et al., 2016). This would be
a complementary step for a better understanding of F-v profile
based training for new insights in strength and conditioning
practice. Finally, it is worth highlighting that when we are
referring to optimized training and performance improvement,
we mean ballistic performances performed at body mass without
resistance (i.e., when the aim is to maximally accelerate his own
mass, and in particular vertical jumping). We chose vertical jump
performance in the present study since it is the simplest task
which well represents ballistic movements and it is a key direct or
indirect physical performance variable in many sport activities.
CONCLUSION
An optimized and individualized training program specifically
addressing the force-velocity imbalance is more efficient at
improving jumping performance than a traditional resistance
training common to all subjects regardless of their force-velocity
imbalance and optimal force-velocity profile. FVimb could
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Jiménez-Reyes et al. Force-Velocity Optimized Training for Jump Performance
therefore be considered as a potentially useful variable for
prescribing optimal resistance training to improve ballistic
(e.g., jumping) performance. As discussed recently (Morin and
Samozino, 2016), this force-velocity approach may help improve
the training practice for performance in explosive push-off
actions like jumping, through a more efficient monitoring
and understanding of the individual determinants of athletic
performance. The experimental results obtained in the present
study confirmed the theoretical principles of the optimized
training approach (Samozino et al., 2014; Morin and Samozino,
2016) that jump performance depends not only on maximal
power output, but on an optimal force-velocity profile.
AUTHOR CONTRIBUTIONS
Conceived and designed the experiments: PJ, PS, MB, JM.
Performed experiments: PJ. Analyzed data: PJ, PS, MB, JM.
Interpreted results of research: PJ, PS, MB, JM. Drafted
manuscript and prepared tables/figures: PJ, JM. Edited, critically
revised paper, and approved final version of manuscript: PJ, PS,
MB, JM.
ACKNOWLEDGMENTS
This study was funded by the Spanish Ministry of Education,
Culture and Sport (National Plan 2015; grant reference
CAS15/00171) with the National Program for “Mobility stays
abroad “José Castillejo” for young doctors.” The experimenters
would like to thank Adrián Castaño-Zambudio, Víctor
Cuadrado-Peñafiel, Antonio Del Aguila, Salustiano Campuzano,
and Pete Griffith for their technical support, and the subjects for
having performed this demanding experiment with enthusiasm.
We also thank the numerous colleagues and students who
discussed these issues with us over the recent years. These
discussions were a very important source of reflection in our
writing process. Some of these results have been presented at the
2016 European Congress of Sport Science.
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Conflict of Interest Statement: The authors declare that the research was
conducted in the absence of any commercial or financial relationships that could
be construed as a potential conflict of interest.
Copyright © 2017 Jiménez-Reyes, Samozino, Brughelli and Morin. This is an open-
access article distributed under the terms of the Creative Commons Attribution
License (CC BY). The use, distribution or reproduction in other forums is permitted,
provided the original author(s) or licensor are credited and that the original
publication in this journal is cited, in accordance with accepted academic practice.
No use, distribution or reproduction is permitted which does not comply with these
terms.
Frontiers in Physiology | www.frontiersin.org 13 January 2017 | Volume 7 | Article 677
... The force-velocity (F-v) relationship has been extensively used to assess the muscle function during single-and multi-joint tasks (García-Ramos et al., 2017;Iglesias-Soler, Fariñas et al., 2019). The most standard testing procedure consists of recording force and velocity values under multiple loads (Alcazar et al., 2020;Giroux et al., 2016;Jiménez-Reyes et al., 2017;Sreckovic et al., 2015). Given that the values of force and velocity determined under different loads are inversely related (i.e., the increment of the load is associated with a higher force and a lower velocity), a mathematical function can be applied to the force and velocity values determined against different loads allowing to determine the maximal capacity of active muscles to produce force (F 0 ), velocity (v 0 ) and power (P max ; Alcazar et al., 2020;García-Ramos et al., 2017;Iglesias-Soler, Fariñas et al., 2019). ...
... However, F 0 and v 0 are independent of each other (i.e., a change in F 0 should not necessarily produce a change in v 0 ; Cuevas- Aburto et al., 2018). Furthermore, the F-v relationship can be used for different purposes such as training prescription (Jiménez-Reyes et al., 2017), injury management (Mendiguchia et al., 2016), fatigue monitoring (García-Ramos, Torrejón, Feriche et al., 2018), or bilateral deficit assessment (Samozino et al., 2014). Therefore, the assessment of the F-v relationship is not only of special relevance for a better understanding of the muscular function, but also for guiding sports training. ...
... However, during multi-joint tasks the F-v relationship seems to be approximately linear (see, Jaric (2015) for a review). Therefore, the F-v relationship has been determined by means of linear regression models after collecting force and velocity data under multiple loads ('linear multiple-point'; Alcazar et al., 2020;Giroux et al., 2016;Jiménez-Reyes et al., 2017;Sreckovic et al., 2015) or only two loads ('linear two-point';Garcia-Ramos et al., 2018;Jaric, 2016). Finally, a quadratic polynomial regression model ('quadratic polynomial') has been also used to fit the F-v relationship in several exercises such as the knee extension, vertical jump, bench press or back-squat (Cuk et al., 2014;Iglesias-Soler, Fariñas et al., 2019;. ...
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An a-posteriori multicentre reliability study was conducted to compare the between-session reliability of the force-velocity relationship parameters (force-intercept [F0], velocity-intercept [v0], and maximum power [Pmax]) between different regression models during the bench press (BP) and bench press throw (BPT) exercises. Data from four and three studies were considered for the BP (n = 102) and BPT (n = 81) exercises, respectively. The force-velocity relationships were determined using five regression models: linear multiple-point, linear two-point, quadratic polynomial, hyperbolic, and exponential. All regression models provided F0 and Pmax with acceptable reliability (cut-off CV ≤ 9.45%; cut-off ICC ≥ 0.79) with the exceptions of F0 for the quadratic polynomial and hyperbolic models (BPT) and Pmax for the exponential model (BP and BPT). Only the linear multiple- and linear two-point models provided v0 with acceptable absolute reliability (cut-off CV ≤ 7.72%). Regardless of the exercise, the reliability of the three parameters was generally higher for the linear multiple- and two-point models compared to the other models (CVratio ≥ 1.22), and no significant differences were observed between multiple- and linear two-point models (CVratio ≤ 1.11). Linear regression models are recommended to maximise the reliability of the force-velocity relationship parameters during the BP and BPT exercises.
... The assessment of the force-velocity (F-V) relationship has gained increasing attention in recent years due to its association to physical performance in populations ranging from young athletes to mobility-limited older people (Dorel et al. 2005;Cross et al. 2015;Giroux et al. 2017;Jimenez-Reyes et al. 2016;Alcazar et al. 2018). The F-V relationship Communicated by Olivier Seynnes. ...
... Therefore, its assessment provides relevant information on the individual's ability to yield mechanical work effectively at several movement velocities that may be of interest for specific sport-or daily life-related activities. In this sense, the F-V relationship can be used as a diagnosing tool by identifying weaknesses or strengths at different force or velocity levels, instead of the traditional one-repetition maximum assessment (Jimenez-Reyes et al. 2016;Alcazar et al. 2018). Then, interventions addressing those weaknesses or strengths can be applied to ultimately influence positively over the sport-or daily life-related activity of interest. ...
... Since the first experiments on the F-V relationship during the first half of the nineteenth century (Hill 1922(Hill , 1938Fenn and Marsh 1935), the assessment of the F-V relationship has been utilized to investigate diverse aspects such as the molecular mechanisms of muscle contraction (Piazzesi et al. 2007), the pathogenesis of some myopathies (Mansson 2014), or the development of prosthetic applications exhibiting muscle-like characteristics (Schmitt et al. 2012). In addition, one of the main recent applications of the assessment of the F-V relationship has been the identification of potential deficits in force, velocity, or both, for their subsequent treatment to improve physical performance (Jimenez-Reyes et al. 2016). In this sense, the higher accessibility to measuring instruments and the appearance of simplified protocols to evaluate the F-V relationship (Jaric 2016) have contributed to the exponential increment observed during the last 5 years in the number of records in the literature on applications of the F-V relationship. ...
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The purpose of this study is to provide a force–velocity (F–V) equation that combines a linear and a hyperbolic region, and to compare its derived results to those obtained from linear equations. A total of 10 cross-training athletes and 14 recreationally resistance-trained young men were assessed in the unilateral leg press (LP) and bilateral bench press (BP) exercises, respectively. F–V data were recorded using a force plate and a linear encoder. Estimated maximum isometric force (F0), maximum muscle power (Pmax), and maximum unloaded velocity (V0) were calculated using a hybrid (linear and hyperbolic) equation and three different linear equations: one derived from the hybrid equation (linearhyb), one applied to data from 0 to 100% of F0 (linear0–100), and one applied to data from 45 to 100% of F0 (linear45–100). The hybrid equation presented the best fit to the recorded data (R² = 0.996 and 0.998). Compared to the results derived from the hybrid equation in the LP, significant differences were observed in F0 derived from linear0-100; V0 derived from linearhyb, linear0–100 and linear45–100; and Pmax derived from linearhyb and linear45–100 (all p < 0.05). For the BP, compared to the hybrid equation, significant differences were found in F0 derived from linear0–100; and V0 and Pmax derived from linearhyb, linear0–100 and linear45–100 (all p < 0.05). An F–V equation combining a linear and a hyperbolic region showed to fit adequately recorded F–V data from ~ 20 to 100% of F0, and overcame the limitations shown by linear equations while providing relevant results.
... The decrease in V 0 means a decrease in the ability of runners to produce vertical force at high speeds, which could increase the risk of injury involving a negative influence on the quality of specific sport skills [57]. The decrease of V 0 and P max in men may be favored on this particular ergometer since the push-off starts at low pre-activation level and higher extrapolated values of V 0 (4.7 m/s in PRE for men) are obtained compared to the 2-4 m/s generally reported when using the classical vertical squat jump [58]. Finally, the unilateral fatigue effects found at D2 may be attributed to the asymmetry reported for the knee extensor strength, running kinetics and kinematics of endurance runners [27]. ...
... Differing from the vertical squat jump test, the present ballistic ergometer was particular since the squat jumps were performed while lying in a supine position with little pre-activation compared to a vertical push. Using this ergometer, higher extrapolated values of V 0 were obtained compared to those using the classical vertical squat jump [58]. In this context, Lindberg et al. (2021) [63] reported high repeatability for all FV parameters on a leg press (close to our ergometer) that was attributed to the highly standardized position [63]. ...
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The acute and delayed phases of the functional recovery pattern after running exercise have been studied mainly in men. However, it seems that women are less fatigable and/or recover faster than men, at least when tested in isometric condition. After a 20 km graded running race, the influence of sex on the delayed phase of recovery at 2–4 days was studied using a horizontal ballistic force-velocity test. Nine female and height male recreational runners performed maximal concentric push-offs at four load levels a week before the race (PRE), 2 and 4 days (D2 and D4) later. Ground reaction forces and surface electromyographic (EMG) activity from 8 major lower limb muscles were recorded. For each session, the mechanical force-velocity-power profile (i.e. theoretical maximal values of force (F¯¯ 0), velocity (V¯¯¯ 0), and power (P¯¯¯ max)) was computed. Mean EMG activity of each recorded muscle and muscle synergies (three for both men and women) were extracted. Independently of the testing sessions, men and women differed regarding the solicitation of the bi-articular thigh muscles (medial hamstring muscles and rectus femoris). At mid-push-off, female made use of more evenly distributed lower limb muscle activities than men. No fatigue effect was found for both sexes when looking at the mean ground reaction forces. However, the force-velocity profile varied by sex throughout the recovery: only men showed a decrease of both V¯¯¯ 0 (p < 0.05) and P¯¯¯ max (p < 0.01) at D2 compared to PRE. Vastus medialis activity was reduced for both men and women up to D4, but only male synergies were impacted at D2: the center of activity of the first and second synergies was reached later. This study suggests that women could recover earlier in a dynamic multi-joint task and that sex-specific organization of muscle synergies may have contributed to their different recovery times after such a race.
... These allowed us to verify the current state of the athlete and to focus training on an individual basis depending on the sport modality, as well as to reduce the FVimb. In this way, the athlete can achieve their greatest potential within their competitive level [26]. Our results showed that significant differences exist in the F-V profile between the sports analysed. ...
... Nonetheless, freestyle wrestling has faster and more explosive movements. Hence, a specific training method in Judo and freestyle wrestling disciplines based on the F-V profile should be used, given that it has been demonstrated that an individual training programme focused on F-V imbalance has greater effectiveness compared with a traditional resistance programme [21,26]. ...
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Background: The aim of this study was to gain new knowledge about the force-velocity (F-V) profile in Judoist and freestyle wrestlers, investigating if there were any differences between sports and which physical demands have which fighting modalities. Participants: 24 athletes (male) took part in this study. Twelve Judoist (age: 20.3 ± 3.9 years, weight: 76.4 ± 10.4 kg; height: 179.4 ± 5.3 cm; BMI: 32.2 ± 1.9 kg/m 2) and twelve freestyle wrestlers (age: 19.6 ± 4.5 years, weight: 65.3 ± 13.6 kg; height: 177.5 ± 5.7 cm; BMI: 23.8 ± 1.8 kg/m 2) participated. Methods: To evaluate the F-V profile, the participants performed a squat jump (SJ) without load, as well as with different load conditions (0, 25, 50, 75, and 100% of athlete's body mass). To assess the height of the jump, the OptoGait system was used. Consequently, the theoretical maximal force (F0); the theoretical maximal velocity (V0); maximal mechanical power output (Pmax); slope of the linear F-V relationship (Sfv); optimal F-V profile (Sfvopt); and the differences between Sfv and Sfvopt (FVimb%) were obtained. Results: A higher F0 and lower V0 were found in Judo athletes compared to wrestlers. Significant differences were found in Sfv and FVimb (p<0.001). Conclusion: The F-V profile is an accurate, reliable, and economical method that facilitates the evaluation of the current state of the athlete individually. Practical applications: The F-V profile method allows coaches and athletes to adjust their training objectives to achieve a higher level in their sport.
... high force production within the first 3-sec of the sprint vs. high power outputs within the first few steps [5-10 sec]) may provide insights by which D' could be enhanced (e.g. maximal strength vs. power training) [29]. ...
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... Among those studies that reported the exercise intensity, 98% used some form of maximal-intensity prescription including individualized maximal intensity prescription [21,85,86] (e.g., force-velocity profile; reactive strength index). However, no consensus emerged from these studies regarding a clear evidence-based definition (either conceptually or operationally) of jump training intensity for different jump exercises. ...
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The aim of this review was to describe and summarize the scientific literature on programming parameters related to jump or plyometric training in male and female soccer players of different age and fitness levels. A literature search was conducted in the electronic databases PubMed, Web of Science and SCOPUS, using keywords related to the main topic of the study (e.g., “ballis-tic”, “plyometric”). According to the PICOS framework, the population for the review was re-stricted to soccer players, involved in jump or plyometric training. Among 7,556 identified studies, 90 were eligible for inclusion. Only 12 studies were found for females. Most studies (n=52) were conducted with youth male players. Moreover, only 35 studies determined the effec-tiveness of a given jump training programming factor. Based on the limited available research, it seems that a dose of 7 weeks (1-2 sessions per week), with ~80 jumps (specific of combined types) per session, using near-maximal or maximal intensity, with adequate recovery between repetitions (<15 s), sets (≥30 s) and sessions (≥24-48 h), using progressive overload and taper strategies, using appropriate surfaces (e.g., grass), and applied in a well-rested state when com-bined with other training methods, would increase chances for effective and safe plyome-tric-jump training interventions aimed at improving soccer players physical fitness. In conclu-sion, jump training is effective, and an easy-to-administer training approach for youth, adult, male and female soccer players. However, optimal programming for plyometric-jump training in soccer is yet to be determined in future research.
... High-performance sport requires the development of individual training plans. In power-oriented disciplines, the force-velocity profile emerged as an interesting tool to optimize athlete's conditioning (11,12). The present results suggest that a deficit in force production capability at very high velocity (V 0 ) could be addressed by increasing resistance during the final stage of the acceleration through elastic bands, an easy and cheap procedure to set up. ...
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Le Scouarnec, J, Samozino, P, Andrieu, B, Thubin, T, Morin, JB, and Favier, FB. Effects of repeated sprint training with progressive elastic resistance on sprint performance and anterior-posterior force production in elite young soccer players. J Strength Cond Res 36(6): 1675-1681, 2022-This study aimed to determine whether repeated sprint training with progressive high elastic resistance could improve sprint performance and anterior-posterior (AP) force production capacities of elite young soccer players. Seven elite U19 soccer players underwent 10 sessions of elastic-resisted repeated sprints on 8 weeks, whereas 8 U17 players from the same academy (control group) followed the same protocol without elastic bands. Sprint performance and mechanical parameters were recorded on a 30-m sprint before and after training. The control group did not show change for any of the measured variables. In contrast, the elastic-resisted training resulted in a significant improvement of the sprint time (-2.1 ± 1.3%; p = 0.026; Hedges' g = -0.49) and maximal velocity (Vmax; +3.9 ± 2%; p = 0.029; Hedges' g = 0.61) reached during the 30-m sprint. These enhancements were concurrent with an increase in the maximal power output related to AP force (Pmax; +4.9 ± 5.1%%; p = 0.026; Hedges' g = 0.42). Although the theoretical maximal AP force (F0) remained unchanged in both groups, there was a medium but nonsignificant increase in theoretical maximal velocity (V0; +3.7 ± 2.5%; p = 0.13; Hedges' g = 0.5) only in the elastic group. Therefore, the present results show that sprint capacity of elite young soccer players can be further improved by adding incremental resistance against runner displacement to raise the ability to produce AP force, rather at high velocity in the final phase of the acceleration.
... The development of the mobile application (MyJump2) empowers practitioners with a simple field-based method of assessing jump performance and obtain in-depth analysis of performance metrics (jump height, mean vertical force, velocity and power), comparable to that obtained from force plates (2,24,25). In theory, athletes are biased towards either force or velocity, which may limit them in jumping performance (11). Therefore, measuring force and velocity, independent from power output, is useful for identifying whether an athlete is force-or velocity-deficient. ...
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Vertical jump and sprint performance were assessed in youth football players of different age categories using a field-based method of assessment. 115 males from a football academy (U11-U16) performed countermovement jumps (CMJ) to determine jump height, mean vertical force, velocity and power measurements, and linear sprints to determine 10-,20-and 30-m sprint intervals. There was an overall trend for both anthropometric, CMJ and sprint measurements to increase with increasing chronological age. There was a significant difference in vertical jump height (7.48 cm; P=0.000), mean force (168 N; P=0.027), mean velocity (0.16 ms; P=0.000), and mean power (320 W; P=0.005) of the players between the U12 and U13 teams. There was also a significant difference in 10m (0.09 s; P=0.048), 20m (0.20 s; P=0.023) and 30m (0.40 s; P=0.016) sprint intervals of the players between the U11 and U13 teams. In the same order, only mean force (264 N; P=0.001) and mean power (406 W; P=0.002) continued to be significantly different between the U13 and U14 teams. 10 m (0.10 s; P=0.045), 20 m (0.21 s; P=0.032) and 30 m (0.54 s; P=0.001) sprint intervals also continued to be significantly different between the U12 and U14 teams. There is both an influence of maturity status and short-term disruptions to vertical jump and sprint performance during the formative years of youth football players. The in-depth analysis of CMJ and 30 m sprint performance around peak height velocity gives sports science practitioners further information when planning player development and training program effectiveness of youth football players.
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The subject of study on which this work focuses is related to high-performance track and field, specifically sprinting. The aim is to analyse a weakness in the entity where the university internships have been carried out in order to be able to implement proposals for improvement that optimise, in this case, sport performance. To do this, a group of sprint training belonging to the Club Escuela Atletismo Majadahonda were analysed, using various techniques such as direct observation, monitoring of training sessions or informal conversations with the coach and athletes. The main weakness observed was a high training load in the form of plyometric and strength work, of which the magnitude of metabolic and mechanical stress they can cause is unknown. These aspects are of great interest, as the existence of a relationship between jumping capacity, strength production and performance in high-intensity sprints is being considered. In order to establish a proposal for improvement, a broad theoretical framework will be described in which the determining aspects of the training process on sprinting performance will be presented. Finally, a series of practical tests with their respective technological tools are presented. In addition, recommendations are established in terms of the periodisation of the tests, the programming of the protocol and of these tests throughout the season. Once the effects of the training load are known with greater accuracy, a strength training programming proposal is described, prioritising certain exercises with a greater transfer to sprint performance. By way of conclusion, we reflect on the traditional training programmes with high fatiguing volumes, dismantling this old conception through evidence of the same effects with a reduction in training.
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This study investigated the effects of a 3-week power-oriented resistance training program performed at moderate altitude on the lower-limb maximal theoretical power and force-velocity (F-V) imbalance of elite judokas. Twenty-two elite male judokas were randomly assigned to either a hypobaric hypoxia or normoxia group. Mechanical outputs from an incremental loaded countermovement jump test were assessed at sea level, before and after training, and 1 week later. Results indicated an increase in the maximal theoretical force and a reduction in the F-V imbalance both at moderate altitude and sea level. Altitude training induced additional benefits when compared to sea level for F-V imbalance (8.4%; CI: 0.3, 17.3%), maximal theoretical power (2.09 W·kg-1; CI: 0.13, 4.52 W·kg-1) and force (1.32 N·kg-1; CI: -0.12, 2.96 N·kg-1), jump height (3.24 cm; CI: 2.02, 4.80 cm) and optimal maximal theoretical force (1.61 N·kg-1; CI: 0.06, 3.60 N·kg-1) and velocity (0.08 m·s-1; CI: 0.00, 0.17 m·s-1) after the training period. The hypoxia group achieved their best results immediately after the training period, while the normoxia group achieved them one week later. These results suggest that a power-oriented resistance training program carried out at moderate altitude accelerates and improves the gains in lower-limb muscle power, while minimizing lower-limb imbalances. Therefore, it seems appropriate to compete immediately after the return to sea level and/or use altitude training as a tool to improve muscle power levels of athletes without tapering goals, especially in highly trained power athletes, since their window of adaptation for further power enhancement is smaller.
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Elite cyclists have often a limited period of time available during their short preparation phase to focus on development of maximal strength; therefore, the purpose of the present study was to investigate the effect of 10-week heavy strength training on lean lower-body mass, leg strength, determinants of cycling performance and cycling performance in elite cyclists. Twelve cyclists performed heavy strength training and normal endurance training (E&S) while 8 other cyclists performed normal endurance training only (E). Following the intervention period E&S had a larger increase in maximal isometric half squat, mean power output during a 30-s Wingate sprint (P < 0.05) and a tendency towards larger improvement in power output at 4 mmol ∙ L−1 [la−] than E (P = 0.068). There were no significant difference between E&S and E in changes in 40-min all-out trial (4 ± 6% vs. −1 ± 6%, respectively, P = 0.13). These beneficial effects may encourage elite cyclists to perform heavy strength training and the short period of only 10 weeks should make it executable even in the compressed training and competition schedule of elite cyclists.
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The barbell hip thrust may be an effective exercise for increasing horizontal force production and may thereby enhance performance in athletic movements requiring a horizontal force vector, such as horizontal jumping and sprint running. The ergogenic ability of the squat is well known. The purpose of this study was to compare the effects of six-week front squat and hip thrust programs in adolescent male athletes. Vertical jump height, horizontal jump distance, 10 m and 20 m sprint times, and isometric mid-thigh pull peak force were among the measured performance variables, in addition to front squat and hip thrust three-repetition maximum (3 RM) strength. Magnitude-based effect-sizes revealed potentially beneficial effects for the front squat in both front squat 3 RM strength and vertical jump height when compared to the hip thrust. No clear benefit for one intervention was observed for horizontal jump performance. Potentially beneficial effects were observed for the hip thrust compared to the front squat in 10 m and 20 m sprint times. The hip thrust was likely superior for improving normalized isometric mid-thigh pull strength, and very likely superior for improving hip thrust 3 RM and isometric mid-thigh pull strength. These results support the force vector theory.
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Purpose: 1) to analyze the reliability and validity of a simple computation method to evaluate force (F), velocity (v) and power (P) output during a countermovement jump (CMJ) suitable for use in field conditions; and 2) to verify the validity of this computation method to compute the CMJ Force-velocity (F-v) profile (including unloaded and loaded jumps) in trained athletes. Methods: Sixteen high-level male sprinters and jumpers performed maximal CMJs under six different load conditions (from 0 to 87 kg). A force-plate sampling at 1000 Hz was used to record vertical ground reaction force and derive vertical displacement data during CMJ trials. For each condition, mean F, v, and P of the push-off phase were determined from both force plate data (reference method) and simple computation measures based on body mass, jump height (from flight time), and push-off distance, and used to establish linear F-v relationship for each individual. Results: Mean absolute bias values were 0.9% (±1.6), 4.7% (±6.2), 3.7% (±4.8), and 5% (±6.8) for F, v, P and slope of the F-v relationship (SFv), respectively. Both methods showed high correlations for F-v profile related variables (r = 0.985 - 0.991). Finally, all variables computed from the simple method showed high reliability with ICC > 0.980 and CV < 1.0%. Conclusions: These results suggest that the simple method presented here is valid and reliable for computing CMJ force, velocity, power, and force-velocity profiles in athletes and could be used in practice under field conditions when body mass, push-off distance, and jump height are known.
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Purpose: To explore the effects of training against mechanically different types of loads on muscle force (F), velocity (V), and power (P) outputs. Methods: Subjects practiced maximum bench throws over 8 wk against a bar predominantly loaded by approximately constant external force (weight), weight plates (weight plus inertia), or weight plates whose weight was compensated by a constant external force pulling upward (inertia). Instead of a typically applied single trial performed against a selected load, the pretest and posttest consisted of the same task performed against 8 different loads ranging from 30% to 79% of the subject's maximum strength applied by adding weight plates to the bar. That provided a range of F and V data for subsequent modeling by linear F-V regression revealing the maximum F (F-intercept), V (V-intercept), and P (P = FV/4). Results: Although all 3 training conditions resulted in increased P, the inertia type of the training load could be somewhat more effective than weight. An even more important finding was that the P increase could be almost exclusively based on a gain in F, V, or both when weight, inertia, or weight-plus-inertia training load were applied, respectively. Conclusions: The inertia training load is more effective than weight in increasing P and weight and inertia may be applied for selective gains in F and V, respectively, whereas the linear F-V model obtained from loaded trials could be used for discerning among muscle F, V, and P.
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Recent studies have brought new insights into the evaluation of power-force-velocity profiles in both ballistic push-offs (e.g. jumps) and sprint movements. These are major physical components of performance in many sports, and the methods we developed and validated are based on data that are now rather simple to obtain in field conditions (e.g. body mass, jump height, sprint times or velocity). The promising aspect of these approaches is that they allow for a more individualized and accurate evaluation, monitoring, and training practices; the success of which are highly dependent on the correct collection, generation and interpretation of athletes' mechanical outputs. We therefore wanted to provide a practical vade mecum to sports practitioners interested in implementing these power-force-velocity profiling approaches. After providing a summary of theoretical and practical definitions for the main variables, we have first detailed how vertical profiling can be used to manage ballistic push-off performance with emphasis on the concept of optimal force-velocity profile and the associated force-velocity imbalance. Further, we have discussed these same concepts with regards to horizontal profiling in the management of sprinting performance. These sections have been illustrated by typical examples from our own practice. Finally, we have provided a practical and operational synthesis, and outlined future challenges that will help in further developing these approaches.
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Performance during human movements is highly related to force and velocity muscle capacities. Those capacities are highly developed in elite athletes practicing power-oriented sports. However, it is still unclear whether the balance between their force and velocity-generating capacities constitutes an optimal profile. In this study, we aimed to determine the effect of elite sport background on the force-velocity relationship in squat-jump, and evaluate the level of optimization of these profiles. Ninety-five elite athletes in cycling, fencing, taekwondo, athletics and 15 control participants performed squat jumps in seven loading conditions (range: 0-60% of the maximal load they were able to lift). Theoretical maximal power (Pm), force (F0) and velocity (v0) were determined from the individual force-velocity relationships. Optimal profiles were assessed by calculating the optimal force (F0th) and velocity (v0th). Athletic sprinters and cyclists produced greater force than the other groups (P<0.05). F0 was significantly lower than F0th, and, v0 was significantly higher than v0th for female fencers and control participants, and for male athletics sprinters, fencers and taekwondo practitioners (P<0.05). Our study shows that the chronic practice of an activity leads to differently balanced force-velocity profiles. Moreover, the differences between measured and optimal force-velocity profiles raise potential sources of performance improvement in elite athletes.
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This study examined whether short-term maximal resistance training employing fast-velocity eccentric knee extensor actions would induce improvements in maximal isometric torque and rate of force development (RFD) at early (<100 ms) and late phases (>100 ms) of rising torque. Twenty healthy men were assigned to two experimental groups: eccentric resistance training (TG) or control (CG). Participants on the TG trained three days a week for a total of eight weeks. Training consisted of maximal unilateral eccentric knee extensors actions performed at 180°s-1. Maximal isometric knee extensor torque (MVC) and incremental RFD in successive 50 ms time-windows from the onset contraction were analysed in absolute terms (RFDINC) or when normalised relative to MVC (RFDREL). After eight weeks, TG demonstrated increases in MVC (28%), RFDINC (0-50 ms: 30%; 50-100 ms: 31%) and RFDREL (0-50 ms: 29%; 50-100 ms: 32%). Moreover, no changes in the late phase of incremental RFD were observed in TG. No changes were found in the CG. In summary, we have demonstrated, in active individuals, that a short period of resistance training performed with eccentric fast-velocity isokinetic muscle contractions is able to enhance RFDINC and RFDREL obtained at the early phase of rising joint torque.