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Strength, Endocrine, and Body Composition Alterations across Four Blocks of Training in an Elite 400 m Sprinter

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The ability to produce force rapidly has the potential to directly influence sprinting performance through changes in stride length and stride frequency. This ability is commonly referred to as the rate of force development (RFD). For this reason, many elite sprinters follow a combined program consisting of resistance training and sprint training. The purpose of this study was to investigate the strength, endocrine and body composition adaptations that occur during distinct phases of a block periodized training cycle in a 400 m Olympic level sprinter. The athlete is an elite level 400 m male sprinter (age 31 years, body mass: 74 kg, years of training: 15 and Personal Best (PB): 45.65 s). This athlete completed four distinct training phases of a block periodized training program (16 weeks) with five testing sessions consisting of testosterone:cortisol (T/C) profiles, body composition, vertical jump, and maximum strength testing. Large fluctuations in T/C were found following high volume training and the taper. Minor changes in body mass were observed with an abrupt decrease following the taper which coincided with a small increase in fat mass percentage. Jump height (5.7%), concentric impulse (9.4%), eccentric impulse (3.4%) and power ratio (18.7%) all increased substantially from T1 to T5. Relative strength increased 6.04% from T1 to T5. Lastly, our results demonstrate the effectiveness of a competitive taper in increasing physiological markers for performance as well as dynamic performance variables. Block periodization training was effective in raising the physical capabilities of an Olympic level 400 m runner which have been shown to directly transfer to sprinting performance.
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Journal of
Functional Morphology
and Kinesiology
Article
Strength, Endocrine, and Body Composition Alterations across
Four Blocks of Training in an Elite 400 m Sprinter
Amit Batra 1, *, Alex B. Wetmore 2, W. Guy. Hornsby 3, Patrycja Lipinska 4, Zbigniew Staniak 5,
Olga Surala 6and Michael H. Stone 1


Citation: Batra, A.; Wetmore, A.B.;
Hornsby, W.G..; Lipinska, P.; Staniak,
Z.; Surala, O.; Stone, M.H. Strength,
Endocrine, and Body Composition
Alterations across Four Blocks of
Training in an Elite 400 m Sprinter. J.
Funct. Morphol. Kinesiol. 2021,6, 25.
https://doi.org/10.3390/jfmk6010025
Academic Editor: Cristina Cortis
Received: 8 February 2021
Accepted: 5 March 2021
Published: 9 March 2021
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Copyright: © 2021 by the authors.
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distributed under the terms and
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Attribution (CC BY) license (https://
creativecommons.org/licenses/by/
4.0/).
1Department of Sport, Exercise, Recreation, and Kinesiology, East Tennessee University,
Johnson City, TN 36714, USA; STONEM@mail.etsu.edu
2Department of Athletics, Westminster College, Salt Lake City, UT 16172, USA; WETMORE@mail.etsu.edu
3College of Physical Activity and Sport Sciences, West Virginia University, Morgantown, WV 26505, USA;
william.hornsby@mail.wvu.edu
4Institute of Physical Education, University of Bydgoszcz, 85-064 Bydgoszcz, Poland; patlip@ukw.edu.pl
5Department of Biomechanics, Institute of Sport, National Research Institute, 01-982 Warsaw, Poland;
zbigniew.staniak@insp.waw.pl
6Department of Nutrition Physiology and Dietetics, Institute of Sport-National Research Institute,
02-776 Warsaw, Poland; olga.surala@insp.waw.pl
*Correspondence: apilatu.amit@gmail.com
Abstract:
The ability to produce force rapidly has the potential to directly influence sprinting
performance through changes in stride length and stride frequency. This ability is commonly referred
to as the rate of force development (RFD). For this reason, many elite sprinters follow a combined
program consisting of resistance training and sprint training. The purpose of this study was to
investigate the strength, endocrine and body composition adaptations that occur during distinct
phases of a block periodized training cycle in a 400 m Olympic level sprinter. The athlete is an elite
level 400 m male sprinter (age 31 years, body mass: 74 kg, years of training: 15 and Personal Best
(PB): 45.65 s). This athlete completed four distinct training phases of a block periodized training
program (16 weeks) with five testing sessions consisting of testosterone:cortisol (T/C) profiles, body
composition, vertical jump, and maximum strength testing. Large fluctuations in T/C were found
following high volume training and the taper. Minor changes in body mass were observed with an
abrupt decrease following the taper which coincided with a small increase in fat mass percentage.
Jump height (5.7%), concentric impulse (9.4%), eccentric impulse (3.4%) and power ratio (18.7%) all
increased substantially from T1 to T5. Relative strength increased 6.04% from T1 to T5. Lastly, our
results demonstrate the effectiveness of a competitive taper in increasing physiological markers for
performance as well as dynamic performance variables. Block periodization training was effective in
raising the physical capabilities of an Olympic level 400 m runner which have been shown to directly
transfer to sprinting performance.
Keywords: periodization; sprinter; track and field; athlete monitoring; endocrine; force plate
1. Introduction
The 400 m sprint is a speed endurance event that demands a high level of anaerobic
metabolism, buffering capacity and aerobic processes to maintain maximum velocity [
1
4
].
Although stride frequency and stride length have been shown to influence sprinting speed,
stride length seems to be the more important biomechanical parameter when distinguishing
between levels of performance in 400 m races [
5
]. Elite sprinters have demonstrated the
ability to apply greater forces into the ground, resulting in longer stride lengths, faster
stride frequencies, and subsequently, faster sprint times compared to less experienced
sprinters [
6
,
7
]. Although the 400 m race is classified as “sprint distance” it is characterized
by unique metabolic, neuromuscular, and technical requirements in comparison to 100 and
200 m races [5,8].
J. Funct. Morphol. Kinesiol. 2021,6, 25. https://doi.org/10.3390/jfmk6010025 https://www.mdpi.com/journal/jfmk
J. Funct. Morphol. Kinesiol. 2021,6, 25 2 of 17
Agreement exists that, from a bioenergetics/metabolic standpoint, anaerobic capacity
is the main factor discriminating 400 m performance [
2
]. Nevertheless, the need to generate
high forces in a small amount of time underscores the importance of qualities such as
rate of force development (RFD) and power in developing sprinting speed [
9
]. Currently,
there is very little long term, descriptive, observational research regarding the experience
of elite 400 m sprinters who have followed combined resistance and running training
programs. In terms of maximizing strength/power adaptations, block periodization and
appropriate programming can result in superior strength/power gains [
10
14
]. Block
periodization depends upon “stages”, each containing three fitness phases: accumulation,
transmutation, and realization [
15
]. The sequenced order of these phases, along with
appropriate programming, allows for early adaptations to further potentiate adaptations in
the later blocks, termed phase potentiation [
16
18
]. For example, the development of work
capacity and basic strength during the accumulation phase allows for greater development
of maximal strength and power during the later phases of training [
11
13
,
16
,
17
,
19
21
]. The
block model depends upon several levels of programming variation, including the use of
heavy and light days, in which intensity and or volume may be increased or decreased
through programmatic means such as sets, reps and relative intensities. This type of
loading paradigm has the potential to enhance the recovery and adaptation processes,
leading to a superior performance [
11
14
,
22
]. The combination of resistance training
in a block periodized manner and track and field specific training resulted in a more
efficient and efficacious improvement of maximal strength, rate of force development
(RFD) and superior fatigue management in comparison to other forms of training. These
studies [
12
,
13
] are characterized by a high degree of ecological validity and lend support
to a combined approach in training, but more research is warranted within elite track and
field settings including 400 m runners. Despite a growing evidence base for the value of
a block periodized approach to training [
15
18
,
23
,
24
] there is a need for understanding
whether/how elite athletes apply these strategies operate within the real-world annual
training/competition calendar.
Several methods exist to better understand physical adaptations to a combined, peri-
odized training plan including the isometric midthigh pull and vertical jump testing. The
isometric midthigh pull (IMTP) is a commonly used method to monitor changes in perfor-
mance potential through quantification of peak force (PF), force at a variety of epochs, and
the RFD. The diagnostic ability of these measures may be of importance when considering
time-constrained tasks within sports, such as jumping, sprinting, and change of direc-
tion [
25
,
26
]. Large negative correlations have been observed between PF, RFD and impulse
(IP) and 0–5 m split time performance in highly trained sprinters [
27
]. Contrary, Healy et al.
(2019) [
28
] found no statistically significant (but moderate to strong) relationships between
IMTP peak force and relative peak force and sprint performance over 40 m with 10 m splits,
among a group of twenty-eight national and international level sprinters. However, the
authors did not measure 0–5 m or fully diagnose the force–time curve, examining measures
of strength such as RFD or impulse. In regards to the maximal power capabilities and
for identifying high-velocity power spectrum changes, the countermovement jump (CMJ)
is primarily used. A substantial relationship between 400 m performance and average
height of 30 s repeated CMJs was noted, but this relationship was not noted for a single
CMJ height performance [
4
,
29
]. The lack of association between jump height (JH) and
400 m performance may be due to the fact that athletes may employ varying movement
strategies (such as increasing the time of force application) to achieve a desired outcome
(e.g., jump height) and therefore jump performance may be influenced by a variety of
factors [
30
,
31
]. Undoubtedly the importance of a sprinter ’s ability to produce high forces
in a brief time period is paramount as elite sprinters have demonstrated foot contact times
around 90 ms [
6
,
7
]. Comprehensive insight into athletes’ neuromuscular function can be
gained through detailed analyses using force plates.
J. Funct. Morphol. Kinesiol. 2021,6, 25 3 of 17
Particularly important is the taper/peaking strategy utilized towards the end of
the macrocycle in an effort to allow the athlete to express their cumulative adaptations
and increase the potential of success on the day of competition. Much of the conceptual
framework of the fitness–fatigue paradigm and peaking for a specific competition deals
with the alterations and fluctuations of an athlete’s preparedness across many blocks of
training [32]. Force–time characteristics (underpins power expression) may be influenced
by alterations in hormonal status which may be strongly affected by training variables:
volume and intensity. Testosterone (T), cortisol (C) and the T/C ratio are often used as
valuable tools for the evaluation of athlete preparedness [
11
,
13
,
32
,
33
]. The high-volume
training typically observed in the accumulation block generally decreases T/C ratio as
indicative of accumulated fatigue and training stress, whereas the decreased volume
load observed in the transmutation and realization phases can result in pattern rebound
and augments the T/C ratio, promoting preparedness [
11
,
13
,
25
,
34
]. This rebound effect
has been associated with a greater ability to generate maximal forces, and explosive
strength (rate of force development) [
13
,
33
36
]. Additionally, the T/C ratio may have an
effect on the development of hypertrophy and tissue repair, which play a role in strength
development. Increases in the size of a muscle from resistance training have been well
established. However, little is known about the extent and time course of the changes in
muscle hypertrophy as a result of resistance training combined with relatively high volume
loads of specific 400 m training.
Despite the importance of monitoring physiological/performance adaptation and the
growing popularity of using force plates [
37
] in monitoring strength/power capabilities
in athletes, there are no (to our knowledge) studies related to 400 m sprinters. Therefore,
understanding the magnitudes and direction of adaptations using case studies of elite level
athletes can provide better insight into individual responses, serve as a better communica-
tion tool with coaches, and can also contribute to generating hypotheses for future research
questions [38].
Thus, the purpose of this study was to examine the time course of the physiological
and performance changes in an elite level 400 m male sprinter throughout four resistance
training phases in combination with a sport-specific running program over a 16-week
training period.
2. Methods
Subject (Athlete)
The athlete was an elite level 400 m male sprinter (age 31 years, body mass: 74 kg,
years of training: 15 and Personal Best (PB): 45.65 s. He was a 400 m Relay Indoor World
Record holder from 2018 (3:01:77) and final participant of 4
×
400 m race in 2016 Olympics
(Rio de Janeiro). Currently, he is part of the national team program preparing for the Tokyo
Olympics. These data arose from the monthly monitoring program in which each athlete’s
(from the National Team) physiological and motor abilities are routinely measured over the
course of the season. The study was approved by the Institute of Sport Committee of Ethics,
and written informed consent was obtained. The subject was informed of the benefits and
risks of the investigation prior to signing an institutionally approved informed consent
document to participate in the study. The study conformed to the recommendations of the
Declaration of Helsinki.
3. Training Program and Testing Timeline
This study was a comparison of pre- and postblock testing results from four specific
training phases throughout a single macrocycle leading up to a control indoor competi-
tion. The first testing session was held two weeks after the 2019 IAAF World Athletics
Championships (after active recovery period). Testing dates corresponded to the start of
a new block of training. The training program followed a single-factor block periodized
design. The three periodization blocks consisted of four distinct training blocks. The
initial training block (Accumulation 1: T1–T2) consisted of four weeks of high volume and
J. Funct. Morphol. Kinesiol. 2021,6, 25 4 of 17
low-to-moderate relative intensities, termed a Strength-Endurance Phase (SE). The second
block of training (Accumulation II: T2–T3) consisted of four weeks of moderate volumes
at higher intensities, termed a Maximal Strength Phase. The third block (Transmutation)
termed Strength–Speed consisted of 4 weeks of low volumes, and high intensities com-
bined with more velocity dominant exercises. The emphasis within this phase of training
is to move relatively heavy loads quickly to enhance RFD characteristics [
17
,
39
]. The final
block (Realization) of training consisted of 4 weeks of complex training where the primary
exercises were combined with plyometric-type exercises which place greater emphasis on
the high velocity end of the force-velocity spectrum while maintaining strength qualities
(Speed–Strength phase). Each training session was completed within 1.5 h. The basic
structure of the block periodized training program is presented in Table 1. Testing occurred
at the beginning of the week 1 (T1), and after completion of week 4 (T2), 8 (T3), 12 (T4),
16 (T5).
Table 1. Training program structure.
Block Week Sets Repetitions Intensity/Day
Monday Tuesday Wednesday Thursday Friday Saturday
Strength Endurance
1 3 10 * M Running ML Running L Running
2 3 10 * MH Running M Running L Running
3 3 10 * H Running MH Running ML Running
4 3 5 * M Running M Running L Running
Max Strength Phase
5 3 5 * H Running MH Running M Running
6 3 5 * H Running H Running M Running
7 3 5 * VH Running H Running MH Running
8 3 5 * ML Running L Running L Running
Strength–Speed
9 3 3 * Running H Running MH Running Running
10 3 3 * Running VH Running H Running Running
11 3 3 * Running VVH Running M Running Running
12 3 3 * Running ML Running L Running Running
Speed–Strength
13 3 3 * Running MH Running L Running Running
14 3 3 * Running H Running M Running Running
15 3 3 * Running VH Running MH Running Running
16 3 3 * Running L Running L Running Running
Note: SE = Strength—Endurance, SP = Strength—Power, VL = very light (65–70%), L = light (70– 75%), ML = medium light (75–80%),
M = medium
(80–85%), MH = medium heavy (85–90%), H = heavy (90–95%), VH = very heavy (95–100%). Intensities are based off a set-rep
best system [14,40]. * represent a single drop set at approximately 60% of the working sets.
Following baseline testing, the athlete completed both resistance (RT) and running
programs on alternating days. RT was completed on Mondays, Wednesdays, and Fridays,
whereas a rudimentary running program was completed on Tuesdays, Thursdays and
Saturdays. At the onset of T2, RT frequency was reduced to 2 day/week while running
frequency was increased to 4 day/week. RT was completed on Tuesdays and Thursdays
while running training was completed on Mondays, Wednesdays, Fridays and Saturdays.
Resistance training loads were prescribed using relative intensities for a given set and
repetition range [
14
,
17
,
19
]. This approach has been shown to produce superior performance
adaptations when compared to traditional loading methods such as repetition maximum
zones [14]. Exercises employed in each block are presented in Table 2.
Running training intensity was based on a distribution of training into 7 specific
intensities zones presented in Table 3. It should be added that this running training method
has been used since 1994 when the head coach became the Polish national 400 m relay
male team’s coach. This method helped the Polish 400 m relay team reach the world record
for the fifth time in history (2:58:00 Uniondale, New York, Goodwill Games) and achieve
the Indoor World Record in 2018. The average lactate and RPE values in each training
mean are presented based on more than 40 years of collecting data on national team
athletes. Due to the fact that test dates are dictated by resistance training programs, it is
reasonable to present running training programs with respect to this. Although this study is
primarily concerned with adaptations to resistance training, physical performance potential
J. Funct. Morphol. Kinesiol. 2021,6, 25 5 of 17
is affected by external stressors including physical stress from both resistance training and
running training. Therefore, it is important to analyze all aspects of the athlete’s physical
preparation before testing to better understand their response to training. Therefore, the
frequency of each type of training (units
·
week
1
) and percentage distribution to each
resistance training block was recorded (Table 4).
Table 2. Resistance training program and organization.
Day Strength—Endurance Strength Strength–Speed Speed–Strength
Monday
Back squat
Overhead press
Lunges
Bench press
Back squat
Overhead press
Dumbell step-up
Bench press
Tuesday
1/4back squats and squat jumps
Push press and vertical medicine
ball toss
Midthigh pull from box and CG
CM shrug
Nordics *
Bench press
Depth jumps *
Hurdle hops
Loaded countermovement
jump (CMJ)
Back Squat and box jumps ($)
Wednesday
Clean pull to knee
Pull-up
Stiff leg deadlift
Band assisted Nordics
Clean pull from floor
Clean pull from knee
Pull-up
Stiff leg deadlift
Thursday
CG CM shrug
Push press and vertical medicine
ball toss
Half squat and AEL (#)
Deadlift
Barbell prone row
Assisted band jumps
AEL (#)
1/4loaded CMJ
Clean pull and power clean ($)
Friday
front squat
overhead press
lunges
bench press
front squat
midthigh pull
bench press
stiff leg deadlift
* Depth jumps from 30 cm; $—complex training. Back squat at VVH—4 min rest–box jumps. Clean pull at VVH—4 min rest–power
clean, #—accentuated eccentric loaded jumps with 2
×
15 kg dumbbells in eccentric phase. CG = clean grip, CM = countermovement,
AEL = accentuated eccentric loading.
Table 3. 400 m training means.
Training Zone/Kind of
Training
Lactate
(mmol/L) Rpe Description Training Example
1 Aerobic long intervals <4 mmol <3
8–10 km interval
run with changing
intensity
4 km jog
4×(20/20)
4×(1:3000 /1:3000)
2 Speed endurance type 1 6–8 mmol/L 3–5
100–200 m runs
with medium and
long intervals and
submaximal pace
(70–85% Vmax)
4×(5 ×100 m)
1st set: 5 ×100 (16 s)/1:150 0
2nd set: 5 ×100 (15 s)/1:300 0
3rd set: 5 ×100 (14 s)/1:4500
4th set: 5 ×10 (13 s)
Interset recovery: 40, 60and 80after
1st, 2nd and 3rd set respectively
3 Speed endurance type 2 10–12 mmol 5–7
100–200 m runs
with medium and
long intervals and
submaximal to
maximal pace
(85–100% Vmax)
5×(2 ×200 m) in
3200 ; 3000; 2800; 260 0 (spikes); 2400
(spikes
Inter-repetitions recovery 20, 20, 20,
30, 30
Interset recovery: 80, 100, 120, 140
J. Funct. Morphol. Kinesiol. 2021,6, 25 6 of 17
Table 3. Cont.
Training Zone/Kind of
Training
Lactate
(mmol/L) Rpe Description Training Example
4 Special endurance 10–15 mmol 7–9
200–400 m runs
with medium and
long intervals with
submaximal to
near maximum
pace
(70–95% Vmax)
7
×
400 m in 80
00
; 76
00
; 72
00
; 68
00
; 64
00
;
6000 ; 5600
Rest between reps 20, 40, 60, 80, 100
120
5 Tempo endurance 12–17 mmol 8–10
300–500 m runs
with medium
interval and
submaximal
intensity
4×(500 m + 300 m)
1st set
500 m in 104000
300 m in 5700
(50rest between)
4th set
500 m in 101000
300 m in 3900
(100rest between sets)
6 speed No data 4–5
40–120 m runs
with near maximal
intensity
(95–100% Vmax)
2×40 m
2×60 m
2×80 m
1×120 m
Inter repetitions recovery: 4 min
Interset recovery 8 min
7 running strength No data 4–5
Bounding,
skipping and
explosive throws
Jumps to 30 m or 10 repetitions
Standing long jumps
3–10 alternate leg hops or bounding
Table 4. Distribution and number of running sessions in each block throughout 16 weeks.
Block Aerobic
Intervals
Speed
Endurance
Type 1
Speed
Endurance
Type 2
Special
Endurance
Tempo
Endurance Speed Running
Strength
Number of
All Training
Sessions
Strength endurance
50% 25% 25% 0% 0% 0% 0% 24
Strength 0% 25% 33% 25% 16% 16% 0% 24
Strength–speed 5% 11% 16% 16% 16% 5% 27% 40
Speed–strength 5% 5% 35% 50% 0 5% 0 5
4. Blood Collection
All testing sessions were completed at the Polish Institute of Sport. On each occasion,
the subject arrived at the Institute 24 h before testing began. Blood draws were conducted
by a medical doctor at the same time of day (7:00 to 9:00 a.m.) to account for diurnal
variation [
41
], but at least 45 min after waking to eliminate early morning variation in hor-
mones [
42
,
43
]. Commercially available ELISA kits (DRG Diagnostics, Marburg,
Germany
)
were used to determine total cortisol and testosterone concentrations in serum. All samples
were assayed in duplicates and the coefficients of variation of the intra-assays were less
than 6% for cortisol and testosterone; moreover, the reference material (Bio Rad Laborato-
ries, Plano, TX, USA) was attached to each analytical run. The hormonal analyses were
carried out in the laboratory of the Department of Biochemistry with an implemented
quality system (with accreditation of the Polish Centre for Accreditation no. AB946).
J. Funct. Morphol. Kinesiol. 2021,6, 25 7 of 17
5. Body Composition
Body composition was assessed via DXA (Hologic Inc., Bedford, MA, USA; Apex
Software Version 3.3). Athletes were asked to arrive fasted, but hydrated, and rested to their
testing session wearing only lightweight athletic clothing. Upon arrival, athletes were asked
to remove all metal to avoid interference with the DXA scan. Height, weight, ethnicity, sex,
and date of birth were entered into the DXA computer. Athletes were asked to lie supine
in the middle of the scanning table with all extremities fitting inside of the measuring
parameter. If an athlete was taller than the parameter of the scan, they were positioned so
that their head was as close to the top of the scan parameter as possible and the ends of
their toes were excluded from the scan. DXA test-retest reliability for male from Kutáˇc et al.
(2019) [
44
]: intraclass correlation coefficient (ICC) = 0.99 and typical error of measurement
(TEM) = 0.29 kg for body mass (BM), ICC = 0.98 and
TEM = 0.52
for fat mass in kg (FM),
ICC = 0.98 and TEM = 0.66% for % fat mass (FM %),
ICC = 0.99
and
TEM = 0.42 kg
for
fat–free mass and ICC = 0.99 and TEM = 0.02 kg for bone mineral content.
6. Vertical Jump Assessments
Countermovement jumps (CMJ) were assessed at 5 time points as indicated in Table 1.
Following a standardized dynamic warm-up, subject performed 2 warm-up CMJs with
their hands-on-hips and feet shoulder-width apart and self-selected countermovement
depth. Following 50% and 75% effort warm-up jumps, 3 maximal effort CMJs were
performed on a force plate (“JBA” Zb. Staniak, Poland) with a 400 Hz sampling rate. The
force plate was connected via an analog-to-digital converter to a PC with the MVJ v.3.4
software (“JBA” Zb. Staniak, Poland). The vertical component of ground reaction force was
used to calculate a number of kinetic and kinematic variables characterizing each jump.
Kinetic and kinematic data were collected and processed using MVJ v.3.4 software (“JBA”
Zb. Staniak, Poland). Height of the rise of the body center of mass (COM) during vertical
jumps was calculated from the recorded ground reaction force of the platform [
45
]. The
onset of profile calculation for each jump considered to have occurred 10 milliseconds prior
to the instant when vertical force had changed to 2% in relation to the body weight as
derived during the silent period of standing. The jump analysis application calculates net
impulse via trapezoidal integration of the force–time data, while center of mass (COM)
velocity is calculated by normalizing the impulse to body mass. Jump height is then
determined from the impulse-momentum theorem using takeoff velocity via TOV jump
height = TOV
2
/2 g where TOV = takeoff velocity and g = 9.81 m/s
2
[
46
]. Aside from
the flight phase, three additional phases are determined prior to takeoff: unweighting,
braking (eccentric), and propulsion (concentric). The unweighting phase represents the
area of the force–time curve that is below BW and instants of peak negative COM velocity.
The braking phase continues from the end of the unweighting phase until the instant
COM velocity increases to zero. The propulsion phase of the CMJ was deemed to have
occurred between the instant that COM velocity equal or exceeded 0 and the instant of
takeoff. Readers are referred to McMahon et al. (2018a) [
37
] for further discussion on
phase determination. Eccentric and concentric force and power (peak) were defined as the
maximum or average vertical force and power values, respectively, attained during the
eccentric and concentric phases of the jump. The ratio between average eccentric (ECC)
power and average concentric (CON) power was also determined and termed the power
ratio [
47
]. Reactive strength index modified was calculated as jump height divided by
movement time [
48
]. Previous data from our lab indicate high reliability (ICCs 0.81–0.93)
and low variability (CV < 10%) for all CMJ variables. We demonstrated high reliability
(ICCs range = 0.81–0.93) and acceptable variability (CV < 10%) for all CMJ variables in
our lab.
J. Funct. Morphol. Kinesiol. 2021,6, 25 8 of 17
7. Isometric Midthigh Pull Assessments
Isometric peak force (IPF) and accompanying RFD were assessed from isometric
midthigh pulls (IMTP) performed at each testing time point. Specifically, RFDs from 0
to 100 ms (RFD 100), from 0 to 200 ms (RFD 200), and from 0 to 300 ms (RFD 300) were
considered. During 400 m races, ground contact times of between 110 ms and 145 ms have
been reported [
49
51
]. Following a standardized warm-up, the athlete was positioned
in a custom-built power rack with an affixed bar. The athlete’s internal knee and hip
angles were measured manually using a goniometer and were required to be 130
and 150
,
respectively. The distance between the force plate top surface and the weightlifting bar was
set in with an accuracy of 2 mm. Each power rack contained force plate (“JBA” Zb. Staniak,
Poland) with a 400 Hz sampling rate which has been previously shown to be reliable and
valid [
52
,
53
]. The athlete was secured to the bar using straps and athletic tape to eliminate
grip strength as a confounding variable during testing. Prior to maximal effort trials, a 50%
and a 75% effort warm-up pull was completed, separated by 60 s of rest. Three minutes
of rest was given following the final warm-up effort. The athlete completed 3 maximal
effort IMTP trials and was instructed to “pull as fast and as hard” as he could. The athlete
continued to pull until peak force dropped off. Additional trials were completed if the
IPF differed between trials >250 N or if there was a >200 N countermovement in any trial.
Verbal encouragement was provided during every IMTP effort. The pretension level was
standardized every time by visual feedback of the force–time curve. Zero moment of time
was assumed when the limit value of force 300 N was obtained. In the case where a value
of 300 N occurred between samples resulting from the sampling rate (400 Hz) the zero time
was determined by taking a linear course of force between samples. In the same way, the
force values were determined at specific RFD time moments. The course of isometric effort
force (IMTP) was digitally smoothed with a 20 Hz four-pole low-pass Butterworth filter.
Kinetic data were processed using MTP v. software (“JBA” Zb. Staniak, Poland). IMTP
pretension was not standardized during the first testing session. Because pretension has an
effect on RFD, RFD data from the first testing session cannot be directly compared with
the following testing sessions and has been excluded from analysis. Peak force was not
significantly affected by pretension levels and is reported from the first testing session. All
kinetic data were also divided by body mass to allow for a normalized comparison of these
data between time points. Reliability data of all IMTP variables for our lab are listed in
Table 5.
Table 5. Reliability of IMTP variables.
Variable ICC CV (%)
PF 0.97 4%
RFD100 0.85 12%
RFD150 0.91 10%
RFD200 0.93 7.7%
RFD300 0.94 6.4%
8. Statistical Analyses
Descriptive statistics are reported as mean
±
SD. Comparisons between baseline (T1)
and testing data points (T2, T3, T4 and T5) throughout the 16-week training mesocycle were
assessed through the percentage (%) difference in change scores. (ES) data were calculated
to determine the magnitude of the change score and were assessed using the following
criteria for highly trained subjects [
54
] <0.25 = trivial, 0.25–0.50 = small, 0.5–1.0 = moderate,
1.0–2.0 = large, and >2.0 = very large.
9. Results
Testosterone: Cortisol Ratio, Testosterone, and Cortisol
The mean values for the testosterone, cortisol and T/C ratio are shown in Table 6.
J. Funct. Morphol. Kinesiol. 2021,6, 25 9 of 17
Table 6. Anabolic-to-catabolic hormone alterations over the 16 weeks.
Descriptive Values Percent Change (%) for T, C and T/C
T1 T2 T3 T4 T5 T2–T1
%
T3–T2
%
T4–T3
%
T5–T4
%
Testosterone [nmol/L] 27 28.9 30.9 25 31.5 7% 6.90% 19.10% 26%
Cortisol [nmol/L] 305 518 557 573 386 69% 7.50% 2.87% 32%
T/C [nmol/L] 8.9 5.6 5.5 4.4 8.2 37% 1.78 20% 86%
The T/C ratio changes was affected mainly by greater fluctuations in cortisol than
testosterone. The greatest percent change in cortisol upward trend was noted from T1 to
T2 which coincides with the largest downward trend of T/C ratio (37% decrease). The
lowest value of T/C ratio was observed in T4; however, in this case, it was primarily
due to the decrease in testosterone (
19%) concentration while cortisol concentration
was relatively stable from T2–T4. The largest upward trend of T/C ratio was noted from
T4 to T5 (86%) which was the effect of 32% decrease and 26% increase of cortisol and
testosterone, respectively.
10. Body Composition
Minor changes (<2%) were observed in body mass at all five testing points during
the study (Table 7.) The greatest changes were observed between T1–T4 (12th week) in fat
mass (
3%) and fat–free mass (+3.7%) alterations. An abrupt decrease in body mass was
observed between T4–T5, which also corresponded to a decrease in fat free mass and an
increase in percent fat and fat mass. The previous literature has suggested these changes in
body mass may be a function of a competitive taper [55,56].
Table 7. Body Composition Alterations across the 16 weeks.
T1 T2 T3 T4 T5
Body mass 76.2 75.1 75.8 76.3 74.1
BMI [kg/m2]22 21.6 22 22 21.6
Fat mass [kg] 8.8 7.9 7.0 6.5 6.9
Fat mass [%] 11.5 10.6 9.2 8.5 9.3
Fat–free body mass [kg] 64.3 63.9 65.7 66.7 64.6
Bone mineral content [kg] 3.2 3.2 3.1 3.2 3.2
11. Vertical Jumping
For each gross measure, the mean output of the three CMJs trials was used for further
analysis. Alterations in CMJs phase variables between testing dates are presented in
Table 8.
Results are expressed as mean ±SD.
Effect sizes and % changes between testing time points are presented in Table 9.
During the SE phase (T1–T2) there were small to large decreases in the number of CMJ
performance. Jump height, take-off velocity and concentric impulse showed the greatest
decrements. From T2 to T3, after the maximum strength phase, there were only trivial
to small alterations in most variables. Large increases in jump height, take-off velocity,
peak negative velocity, CON and ECC impulse, power ratio and CMJ depth (greater dip)
between T3 and T4 were observed. Small increases in contraction time were noted, mostly
due to moderate increase in propulsion time rather than changes in unweighting or braking
phase duration. After the speed-strength phase (T4–T5) the large increases in JH, take-off
velocity, RSImod, Peak and mean CON power and moderate increases in peak force (CON
and ECC) and ECC mean power. A moderate decrease in contraction time was found,
mostly due to moderate and small decreases in unweighting and braking phase time,
respectively, as there was no change in propulsion phase time. When comparing T5 to
pretraining cycle values (T1) there was a large increase in JH, CON and ECC Peak Power,
take-off and peak negative velocity, CON and ECC impulse and in power ratio.
J. Funct. Morphol. Kinesiol. 2021,6, 25 10 of 17
Table 8. Countermovement jump kinetic and kinematic data across 16 weeks.
T1 T2 T3 T4 T5
Jump Height [cm] 53
0.01
50
0.00
49.8
0.01
52.3
0.00
55.9
0.00
RSI mod 0.815
0.04
0.759
0.05
0.748
0.00
0.771
0.02
0.852
0.01
Velocity at take–off [m/s] 3.21
0.03
3.12
0.04
3.11
0.05
3.18
0.01
3.3
0.02
Time to take off [s] 0.65
0.01
0.66
0.04
0.66
0.02
0.67
0.02
0.65
0.01
Unweighting phase time [s] 0.295
0.006
0.310
0.035
0.314
0.006
0.316
0.025
0.299
0.015
Braking phase time [s] 0.141
0.009
0.141
0.009
0.142
0.014
0.143
0.006
0.138
0.005
Propulsion phase time [s] 0.215
0.005
0.211
0.001
0.210
0.014
0.219
0.004
0.219
0.006
CMJ depth [cm] 38
0.00
36.2
0.00
35.6
0.02
38.3
0.01
39.7
0.01
Peak negative velocity [m/s] 1.53
0.05
1.48
0.03
1.49
0.03
1.64
0.09
1.68
0.03
Peak Eccentric Force [N·kg1]17.3
1.04
16.43
0.8
16.43
0.97
16.6
0.81
17.4
0.2
Peak Concentric Force [N·kg1]17.6
0.95
17.23
0.49
16.96
1.06
17.16
0.3
17.9
0.36
Peak Eccentric Power [W·kg1]12.4
2.49
11.6
1.3
11.83
0.92
14.16
2.51
15.53
0.66
Peak Concentric Power [W·kg1]41.7
1.13
40.36
1.44
41.23
1.04
41.06
0.92
44.6
1.68
Mean ECC Power [W·kg1]8.04
1.17
7.49
0.89
7.62
0.50
9.1
1.45
9.85
0.26
Mean CON Power [W·kg1]24.56
1.07
23.53
0.56
23.56
0.86
23.66
0.20
25.46
0.86
Power Ratio [%] 32.64
3.25
31.81
3.39
32.31
1.11
38.52
6.44
38.7
2.27
Eccentric Impulse [N·s1·kg1]1.49
0.06
1.43
0.02
1.46
0.04
1.6
0.1
1.63
0.03
Concentric Impulse [N·s1·kg1]3.28
0.04
3.20
0.04
3.18
0.04
3.25
0.01
3.39
0.01
J. Funct. Morphol. Kinesiol. 2021,6, 25 11 of 17
Table 9. Effect sizes and % change from CMJ test.
T1 vs. T2 T2 vs. T3 T3 vs. T4 T4 vs. T5 T1 vs. T5
ES; %
Jump height [cm] 1.58
5.7%
0.16
0.6%
1.34
4.0%
2.0
7.7%
1.60
5.7%
RSImod 1.04
7.3%
0.33
1.3%
0.46
2.7%
1.63
10.4%
0.72
3.7%
Velocity at take–off [m/s] 1.61
2.8%
0.18
0.3%
1.37
2.6%
2.08
3.4%
1.67
2.8%
Time to take off [s] 0.26
1.5%
0.09
0.6%
0.31
2%
0.54
3.2%
0.13
0.8%
Unweighting phase time [s] 0.43
4.85%
0.12
1.29%
0.07
0.74%
0.5
5.27%
0.12
1.35%
Braking phase time [s] 0
0%
0.06
0.7%
0.06
0.7%
0.34
3.5%
0.2
2.1%
Propulsion phase time [s] 0.31
1.9%
0.11
0.5%
0.8
4.3%
0
0%
0.37
1.9%
CMJ Depth [cm] 0.78
4.5%
0.26
1.7%
1.18
7.3%
0.62
3.7%
0.75
4.5%
Peak negative velocity [m/s] 0.58
3.3%
0.18
1.4%
1.55
9.3%
0.47
2.4%
1.62
9.8%
Peak eccentric force [N·kg1]0.67
5.0%
0.0
0.0%
0.13
1.0%
0.61
4.8%
0.08
0.6%
Peak concentric force [N·kg1]0.33
2.3%
0.24
1.2%
0.18
1.2%
0.66
4.1%
0.27
1.7%
Peak eccentric power [W·kg1]0.29
6.5%
0.08
2.0%
0.84
19.8%
0.49
9.6%
1.12
25.2%
Peak concentric power [W·kg1]0.66
3.1%
0.43
2.0%
0.08
0.2%
1.75
8.5%
1.44
7.0%
Peak eccentric power [W·kg1]0.29
6.5%
0.08
2.0%
0.84
19.8%
0.49
9.6%
1.12
25.2%
Mean ECC power [W·kg1]0.36
6.84%
0.08
1.73%
0.98
19.51
0.49
8.23%
1.19
22.5%
Mean CON power [W·kg1]0.84
4.2%
0.02
0.14%
0.08
0.42%
1.46
7.6%
0.73
3.66%
Power ratio [%] 0.14
2.5%
0.08
1.6%
1.05
19.2%
0.03
0.6%
1.03
18.7%
Eccentric impulse [N·s1·kg1]0.61
4%
0.25
2.1%
1.47
9.6%
0.27
1.9%
1.38
9.4%
Concentric impulse [N·s1·kg1]1.4
2.4%
0.41
0.6%
1.31
2.2%
2.44
4.3%
1.9
3.4%
12. Isometric Midthigh Pull
Relative peak force (N/kg) alterations are presented in Figure 1and raw values in
Table 10. The upward and downward phase of peak force changes coincides with alterations
in fat-free mass (reverse U shape). From T1 to T2 the subject displayed moderate (ES = 0.88;
% = 8.6%) increase in relative peak force and this upward trend was observed until T3
(week 8). From T2 to T3 (ES = 0.63;
% = 5.74%) increase was noted. A small decrease from
T3 to T4 (ES =
0.26;
% =
2.27%) and from T4 to T5 (ES =
0.3;
% = 2.63%
) was
reported. There was large increase in RFD 100 (ES = 1.5
% = 50.43%), RFD 150 (ES = 1.51;
J. Funct. Morphol. Kinesiol. 2021,6, 25 12 of 17
% = 34.43%), RFD 200 (1.76,
% 31.4%), and moderate increase in RFD 300 (ES = 0.84;
13.46%) from T2 to T3 (Figure 2). RFD 100 trended downward from T3 to T4 (
ES = 0.66
;
% =
14.87%) while no substantial (trivial) changes were observed for 150 and 200 ms
time epochs and small upward trend (ES = 0.38;
% = 5.46%) was noticed for RFD 300.
From T4 to T5 where small downward change was observed for RFD 100 (ES =
0.29;
% = 7.6
) while moderate to large decrease in RFD 150 (ES =
0.97;
% =
16.9), 200
(
1.53;
% =
21.2), and 300 (
1.74;
% =
23.3%) was reported. Raw RFD values are
presented in Table 11.
J. Funct. Morphol. Kinesiol. 2021, 6, x FOR PEER REVIEW 12 of 17
Concentric impulse [N·s1·kg1] 1.4
2.4%
0.41
0.6%
1.31
2.2%
2.44
4.3%
1.9
3.4%
12. Isometric Midthigh Pull
Relative peak force (N/kg) alterations are presented in Figure 1 and raw values in
Table 10. The upward and downward phase of peak force changes coincides with altera-
tions in fat-free mass (reverse U shape). From T1 to T2 the subject displayed moderate (ES
= 0.88; Δ% = 8.6%) increase in relative peak force and this upward trend was observed
until T3 (week 8). From T2 to T3 (ES = 0.63; Δ% = 5.74%) increase was noted. A small
decrease from T3 to T4 (ES = 0.26; Δ% = 2.27%) and from T4 to T5 (ES = 0.3; Δ% =
2.63%) was reported. There was large increase in RFD 100 (ES = 1.5 Δ% = 50.43%), RFD
150 (ES = 1.51; Δ% = 34.43%), RFD 200 (1.76, Δ% 31.4%), and moderate increase in RFD 300
(ES = 0.84; 13.46%) from T2 to T3 (Figure 2). RFD 100 trended downward from T3 to T4
(ES = 0.66; Δ% = 14.87%) while no substantial (trivial) changes were observed for 150
and 200 ms time epochs and small upward trend (ES = 0.38; Δ% = 5.46%) was noticed for
RFD 300. From T4 to T5 where small downward change was observed for RFD 100 (ES =
0.29; = 7.6) while moderate to large decrease in RFD 150 (ES = 0.97; Δ% = 16.9), 200 (1.53;
Δ% = 21.2), and 300 (1.74; Δ% = 23.3%) was reported. Raw RFD values are presented in
Table 11.
Figure 1. Peak force from the IMTP test.
Figure 2. Rate of force development in 100, 150, 200 and 300 ms throughout 16-week training.
Figure 1. Peak force from the IMTP test.
Table 10. Relative peak force data [N·kg1]. Mean (±SD).
Peak Force [N·kg1] T1 T2 T3 T4 T5
34.51 36.40 38.49 37.62 36.63
(2.17) (2.24) (1.09) (1.35) (0.51)
J. Funct. Morphol. Kinesiol. 2021, 6, x FOR PEER REVIEW 12 of 17
Concentric impulse [N·s1·kg1] 1.4
2.4%
0.41
0.6%
1.31
2.2%
2.44
4.3%
1.9
3.4%
12. Isometric Midthigh Pull
Relative peak force (N/kg) alterations are presented in Figure 1 and raw values in
Table 10. The upward and downward phase of peak force changes coincides with altera-
tions in fat-free mass (reverse U shape). From T1 to T2 the subject displayed moderate (ES
= 0.88; Δ% = 8.6%) increase in relative peak force and this upward trend was observed
until T3 (week 8). From T2 to T3 (ES = 0.63; Δ% = 5.74%) increase was noted. A small
decrease from T3 to T4 (ES = 0.26; Δ% = 2.27%) and from T4 to T5 (ES = 0.3; Δ% =
2.63%) was reported. There was large increase in RFD 100 (ES = 1.5 Δ% = 50.43%), RFD
150 (ES = 1.51; Δ% = 34.43%), RFD 200 (1.76, Δ% 31.4%), and moderate increase in RFD 300
(ES = 0.84; 13.46%) from T2 to T3 (Figure 2). RFD 100 trended downward from T3 to T4
(ES = 0.66; Δ% = 14.87%) while no substantial (trivial) changes were observed for 150
and 200 ms time epochs and small upward trend (ES = 0.38; Δ% = 5.46%) was noticed for
RFD 300. From T4 to T5 where small downward change was observed for RFD 100 (ES =
0.29; = 7.6) while moderate to large decrease in RFD 150 (ES = 0.97; Δ% = 16.9), 200 (1.53;
Δ% = 21.2), and 300 (1.74; Δ% = 23.3%) was reported. Raw RFD values are presented in
Table 11.
Figure 1. Peak force from the IMTP test.
Figure 2. Rate of force development in 100, 150, 200 and 300 ms throughout 16-week training.
Figure 2. Rate of force development in 100, 150, 200 and 300 ms throughout 16-week training.
J. Funct. Morphol. Kinesiol. 2021,6, 25 13 of 17
Table 11. Relative RFD data [N·kg1·s1] Mean (±SD).
RFD T2 T3 T4 T5
RFD 100 103.23
(30.45)
155.30
(34.14)
132.20
(16.21)
122.07
(6.76)
RFD 150 102.03
(28.72)
137.17
(9.70)
132.40
(8.07)
109.90
(9.22)
RFD 200 90.00
(17.87)
118.27
(4.70)
114.93
(8.12)
90.47
(10.14)
RFD 300 65.6
(11.6)
74.4
(2.3)
78.5
(5.7)
60.2
(6.9)
13. Discussion
The results of the current study support the use of a block periodized RT program
for improving relative strength and power qualities in an elite 400 m runner. The basis of
block periodization can be traced to the work of Verkoshansky and Issurin. Verkoshansky
described the use of programmed concentrated loads, and a long-term lag of training
effects between the initiation of a training stimulus and when the effects are realized [
57
].
Issurin described how appropriate programming can produce residual effects which can
potentiate adaptations in a subsequent phase [
15
,
23
]. These ideas have later been termed
phase potentiation programming [
16
]. The results of the current study support the use of a
block periodized and a phase potentiation program with alterations in body composition
during the first phase of training allowing for future gains in maximum strength and
ultimately power during the later phases.
There was an overall increase in relative strength from T1–T5 of 6.04% (ES = 0.81).
Relative strength peaked following the maximum strength training block with an 8.6%
increase from T1–T2 and 5.7% increase from T2–T3. However, once the concentrated load
transitioned to power development there was a small decrease in relative strength from
T3–T4 (
2.27%) and T4–T5 (
2.63%). Despite these reductions, relative strength remained
elevated above baseline. These increments in relative strength may have contributed to the
improvements in dynamic jump performance. Suchomel et al. (2016) [
58
] indicate there
may be a relative strength threshold above which greater gains in power are possible. This
idea is supported by the observations of Wetmore et al. (2020) [
21
] indicating that stronger
subjects realized greater gains in power-related measures during a realization block. Our
current results support this theory as peak eccentric and concentric power, mean eccentric
and concentric power as well as power ratio all improved in the final two blocks following
an increase in relative strength.
Jump height increased 5.7% from T1–T5, which corresponded to a large effect size.
The concentric impulse (9.4%), eccentric impulse (3.4%) and power ratio (18.7%) all sub-
stantially increased over the course of the training program. The trends of changes in jump
variables from block to block were reflective of the concentrated load for each individual
block. For example, as expected, the jump height, velocity at takeoff and power variables
all decreased following the first two blocks of training. This period included the highest
volumes of training and therefore greater fatigue. However, when the concentrated loading
switched towards developing maximum strength and power, jump variables supercom-
pensated above baseline values. These results are quite meaningful as previous work
has demonstrated the strong relationship (r
2
= 0.81) between jump height and sprinting
performance in elite sprinters [59].
Body composition changes as well as hormonal balance changes may also help explain
the physical adaptations to the training program. For example, one goal of early training
is to alter body composition, which can be achieved through higher volume training.
This may also cause an increase in overall stress, which may reduce T:C. In the current
study, fat mass was reduced by 2.3% and lean mass increased by 1.4 kg from T1–T3.
Additionally, T:C was reduced by 37% from T1–T2. However, during the later phases of
J. Funct. Morphol. Kinesiol. 2021,6, 25 14 of 17
training, fatigue management is paramount in order to allow for other qualities such as
power to be expressed. During the last phase of training, body mass was substantially
reduced by 2.2 kg but T:C increased by 86%. The balance of these two factors may have
affected the peak in performance in vertical jump variables and the athlete’s ability to run
400 m.
Lastly, our results support the theoretical basis of a competitive taper. Previous
research [
60
] has indicated that the purpose of a competitive taper is to lower fatigue while
increasing readiness. This can be accomplished by reducing training volume, intensity,
and possibly training cessation. The current literature recommends a taper of 7–14 days
(REFS). Expected outcomes of a taper may include increased power outputs, greater T:C
ratios, increased strength:body mass ratios and ultimately better performance [
61
,
62
]. In
our current study, the resistance training volume as well as the intensity were reduced
for 7 days prior to the final testing session. As mentioned previously, our results showed
an 86% (see above) increase in T:C as well as increases in dynamic performance variables.
Additionally, our subject had a reduced body mass from T4–T5, perhaps as a result of
reduced training volume and could possibly have contributed to the greater jump power
observed in T5.
14. Conclusions
In conclusion, across the macrocycle the athlete appears to have increased prepared-
ness and responded favorably to the planned training. A manner generally “fitting” of the
phase-based progression of higher volume to lower volume along with a gradual rise in
training intensity and sport specific preparation. This is based primarily on the alterations
in T and T:C ratio as well the neuromuscular alterations across the phases. During the
higher volume training the athlete demonstrated lower T and T:C and lower neuromuscular
readiness (based on the jump data). Particularly noteworthy is the elevated preparedness
at the of the taper (e.g., highest T and best jump performance). In high level athletes an
important factor is not simply “does an athlete improve” but the meticulously controlling
of when (e.g., a major competition).
While case studies, particularly case studies performed on very advanced athletes
in a highly ecologically valid setting can be quite valuable, studies such as this are not
without limitations. The nature of a case study limits external validity and the ability to
generalize data to a population. It is important for coaches to understand and appreciate
the advanced level of the sprinter observed and that elite training and coaching is very
nuanced and based on the individual. Second, as mentioned in the methods, the track
running program was designed by the national team coach and thus could not be directly
manipulated along with the RT program. The RT program was manipulated to “fit” the
running program, so as to not produce adverse effects (i.e., poor fatigue management),
subject, case studies, involving detailed reporting of the athletes’ training over extended
periods of time can provide important insight into high level sport. This study, along with
many others of similar design, suggests the importance of: (1) focused training periods,
(2) heavy and light training days, (3) and detailed, inclusive planning [6365].
Author Contributions:
Conceptualization, A.B., A.B.W., P.L. and M.H.S.; data curation, P.L., Z.S. and
O.S.; formal analysis, A.B., A.B.W., P.L. and M.H.S.; investigation, A.B., Z.S. and O.S.; methodology,
A.B., A.B.W., Z.S. and O.S; project administration, A.B., A.B.W., W.G.H. and M.H.S.; supervision,
A.B., A.B.W., W.G.H. and M.H.S.; visualization, A.B., A.B.W., W.G.H. and M.H.S.; writing—original
draft A.B. and A.B.W.; writing—review and editing, A.B., A.B.W., W.G.H. and M.H.S. All authors
have read and agreed to the published version of the manuscript.
Funding: This research received no external funding.
Institutional Review Board Statement:
The data was retrospective in nature and deemed nonhuman
subject research by East Tennessee State University’s Institutional Review Board.
Informed Consent Statement: Not applicable.
J. Funct. Morphol. Kinesiol. 2021,6, 25 15 of 17
Data Availability Statement:
The data that support the findings of this study are available from the
corresponding author upon reasonable request.
Conflicts of Interest: The authors declare no conflict of interest.
References
1. Schiffer, J. The 400 metres. New Stud. Athl. 2008,23, 7–13.
2.
Nevill, A.M.; Ramsbottom, R.; Nevill, E.M.; Newport, S.; Williams, C. The relative contributions of anaerobic and aerobic energy
supply during track 100-, 400- and 800-m performance. J. Sports Med. Phys. Fit. 2008,48, 138–142.
3.
Zouhal, H.; Jabbour, G.; Jacob, C.; Duvigneau, D.; Botcazou, M.; Abderrahaman, B.A.; Prioux, J.; Moussa, E. Anaerobic and
Aerobic Energy System Contribution to 400-m Flat and 400-m Hurdles Track Running. J. Strength Cond. Res.
2010
,24, 2309–2315.
[CrossRef]
4.
Dal Pupo, J.; Arins, F.B.; Guglielmo, L.G.A.; da Silva, R.R.C.; Moro, A.R.P.; Dos Santos, S.G. Physiological and neuromuscular
indices associated with sprint running performance. Res. Sports Med. 2013,21, 124–135. [CrossRef]
5.
Hanon, C.; Gajer, B. Velocity and Stride Parameters of World-Class 400-Meter Athletes Compared with Less Experienced Runners.
J. Strength Cond. Res. 2009,23, 524–531. [CrossRef]
6.
Weyand, P.G.; Sternlight, D.B.; Bellizzi, M.J.; Wright, S. Faster top running speeds are achieved with greater ground forces not
more rapid leg movements. J. Appl. Physiol. 2000,89, 1991–1999. [CrossRef] [PubMed]
7.
Weyand, P.; Sandell, R.F.; Prime, D.N.L.; Bundle, M.W. The biological limits to running speed are im-posed from the ground up.
J. Appl. Physiol. 2010,108, 950–961. [CrossRef] [PubMed]
8. Arnold, M. Year plans for speed and strength endurance for 400 metres runners. Athl. Coach. 1989,23, 33–44.
9.
Thompson, M.A. Physiological and Biomechanical Mechanisms of Distance Specific Human Running Performance. Integr. Comp.
Biol. 2017,57, 293–300. [CrossRef]
10.
Stone, M.H.; Bryant, O.H.; Garhammer, J.; McMillan, J.; Rozenek, R. A Theoretical Model of Strength Training. Natl. Strength
Coach. Assoc. J. 1982,4, 36–39. [CrossRef]
11. Stone, M.H.; Stone, M.E.; Sands, W.A. Principles and Practice of Resistance Training; Human Kinetics: Champaign, IL, USA, 2007.
12.
Painter, K.B.; Haff, G.G.; Ramsey, M.W.; McBride, J.; Triplett, T.; Sands, W.A.; Lamont, H.S.; Stone, M.E.; Stone, M.H. Strength
Gains: Block versus Daily Undulating Periodization Weight Training Among Track and Field Athletes. Int. J. Sports Physiol.
Perform. 2012,7, 161–169. [CrossRef]
13.
Painter, K.; Haff, G.G.; Triplett, N.T.; Stuart, C.; Hornsby, G.; Ramsey, M.W.; Bazyler, C.D.; Stone, M.H. Resting Hormone
Alterations and Injuries: Block vs. DUP Weight-Training among D-1 Track and Field Athletes. Sports 2018,6, 3. [CrossRef]
14.
Carroll, K.M.; Bernards, J.R.; Bazyler, C.D.; Taber, C.B.; Stuart, C.A.; DeWeese, B.H.; Sato, K.; Stone, M.H. Divergent Performance
Outcomes Following Resistance Training Using Repetition Maximums or Relative Intensity. Int. J. Sports Physiol. Perform.
2018
,
29, 1–28. [CrossRef] [PubMed]
15. Issurin, V. Block periodization versus traditional training theory: A review. J. Sports Med. Phys. Fit. 2008,48, 65–75.
16.
DeWeese, B.H.; Hornsby, G.; Stone, M.; Stone, M.H. The training process: Planning for strength-power training in track and field.
Part 1: Theoretical aspects. J. Sport Health Sci. 2015,4, 308–317. [CrossRef]
17.
DeWeese, B.H.; Hornsby, G.; Stone, M.; Stone, M.H. The training process: Planning for strength–power training in track and field.
Part 2: Practical and applied aspects. J. Sport Health Sci. 2015,4, 318–324. [CrossRef]
18.
Cunanan, A.J.; De Weese, B.H.; Wagle, J.P.; Carroll, M.K.; Sausaman, R.; Hornsby, W.G., III; Haff, G.G.; Triplett, N.T.; Pierce, K.C.;
Stone, M.H. The General Adaptation Syndrome: A Foundation for the Concept of Periodization. Sports Med.
2018
,48, 787–797.
[CrossRef]
19.
Hornsby, W.G.; Gentles, J.A.; Macdonald, C.J.; Mizuguchi, S.; Ramsey, M.W.; Stone, M.H. Maximum Strength, Rate of Force
Development, Jump Height, and Peak Power Alterations in Weightlifters across Five Months of Training. Sports
2017
,5, 78.
[CrossRef]
20.
Suarez, D.G.; Mizuguchi, S.; Hornsby, W.G.; Cunanan, A.J.; Marsh, D.J.; Stone, M.H. Phase-Specific Changes in Rate of Force
Development and Muscle Morphology Throughout a Block Periodized Training Cycle in Weightlifters. Sports
2019
,7, 129.
[CrossRef]
21.
Wetmore, A.B.; Moquin, P.A.; Carroll, K.M.; Fry, A.C.; Hornsby, W.G.; Stone, M.H. The Effect of Training Status on Adaptations to
11 Weeks of Block Periodization Training. Sports 2020,8, 145. [CrossRef]
22.
Foster, C. Monitoring training in athletes with reference to overtraining syndrome. Med. Sci. Sports Exerc.
1998
,30, 1164–1168.
[CrossRef]
23. Issurin, V. Periodization Training from Ancient Precursors to Structured Block Models. Kinesiology 2014,46, 3–9.
24.
Williams, T.D.; Tolusso, D.V.; Fedewa, M.V.; Esco, M.R. Comparison of Periodized and Non-Periodized Resistance Training on
Maximal Strength: A Meta-Analysis. Sports Med. 2017,47, 2083–2100. [CrossRef] [PubMed]
25.
Stone, H.; Bryant, O.H.; Hornsby, G.; Cunanan, A.; Mizuguchi, S.; Suarez, D.; South, M.; Marsh, D.J.; Haff, G.; Ramsey, M.; et al.
Using the Isometric Mid-thigh Pull in the Monitoring of Weightlifters: 25+ Years of Experience. UKSCA J. 2019,54, 19–26.
26.
Santos, C.T.D.; Beckham, G.K.; Stone, M.H.; Guppy, S.N.; Haff, G.G. Standardization and meth-odological considerations for the
isometric midthigh pull. Strength Cond. J. 2019,41, 57–79.
J. Funct. Morphol. Kinesiol. 2021,6, 25 16 of 17
27.
Brady, C.J.; Harrison, A.J.; Flanagan, E.P.; Haff, G.G.; Comyns, T.M. The Relationship Between Isometric Strength and Sprint
Acceleration in Sprinters. Int. J. Sports Physiol. Perform. 2020,15, 38–45. [CrossRef]
28.
Healy, R.; Smyth, C.; Kenny, I.C.; Harrison, A.J. Influence of Reactive and Maximum Strength Indicators on Sprint Performance.
J. Strength Cond. Res. 2019,33, 3039–3048. [CrossRef] [PubMed]
29. Miguel, P.J.; Reis, V.M. Speed strength endurance and 400m performance. New Stud. Athl. 2004,19, 39–45.
30. McMahon, J.J.; Jones, P.A.; Suchomel, T.J.; Lake, J.; Comfort, P. Influence of the Reactive Strength Index Modified on Force– and
Power–Time Curves. Int. J. Sports Physiol. Perform. 2018,13, 220–227. [CrossRef]
31.
Sole, C.J.; Mizuguchi, S.; Sato, K.; Moir, G.L.; Stone, M.H. Phase Characteristics of the Countermovement Jump Force-Time Curve:
A Comparison of Athletes by Jumping Ability. J. Strength Cond. Res. 2018,32, 1155–1165. [CrossRef]
32. Mujika, I. Tapering and Peaking for Optimal Performance. Tapering Peaking Optim. Perform. 2009,1. [CrossRef]
33.
Crewther, B.T.; Cook, C.; Cardinale, M.; Weatherby, R.P.; Lowe, T. Two emerging concepts for elite ath-letes: The short-term effects
of testosterone and cortisol on the neuromuscular system and the dose-response training role of these endogenous hormones.
Sports Med. 2011,41, 103–123. [CrossRef] [PubMed]
34.
Haff, G.G.; Jackson, J.R.; Kawamori, N.; Carlock, J.M.; Hartman, M.J.; Kilgore, J.L.; Morris, R.T.; Ramsey, M.W.; Sands, W.A.;
Stone, M.H. Force-Time Curve Characteristics and Hormonal Alterations During an Eleven-Week Training Period in Elite Women
Weightlifters. J. Strength Cond. Res. 2008,22, 433–446. [CrossRef] [PubMed]
35.
Häkkinen, K.; Pakarinen, A.; Alén, M.; Kauhanen, H.; Komi, P.V. Relationships Between Training Volume, Physical Performance
Capacity, and Serum Hormone Concentrations During Prolonged Training in Elite Weight Lifters. Endoscopy
1987
,08, S61–S65.
[CrossRef] [PubMed]
36.
Cardinale, M.; Stone, M.H. Is Testosterone Influencing Explosive Performance? J. Strength Cond. Res.
2006
,20, 103–107. [CrossRef]
37.
McMahon, J.J.; Suchomel, T.J.; Lake, J.P.; Comfort, P. Understanding the Key Phases of the Countermovement Jump Force-Time
Curve. Strength Cond. J. 2018,40, 96–106. [CrossRef]
38.
Halperin, I. Case Studies in Exercise and Sport Sciences: A Powerful Tool to Bridge the Sci-ence–Practice Gap. Int. J. Sports Physiol.
Perform. 2018,13, 824–825. [CrossRef]
39.
Suchomel, T.J.; Comfort, P.; Lake, J.P. Enhancing the Force-Velocity Profile of Athletes Using Weightlifting Derivatives. Strength
Cond. J. 2017,39, 10–20. [CrossRef]
40.
DeWeese, B.H.; Sams, M.; Serrano, A. Sliding toward Sochi-part I: A review of program-ming tactics used during the 2010–2014
quadrennial. NSCA Coach 2014,1, 30–43.
41.
Hackney, A.C.; Viru, A. Research Methodology: Endocrinologic Measurements in Exercise Science and Sports Medicine. J. Athl.
Train. 2008,43, 631–639. [CrossRef] [PubMed]
42.
Law, R.; Hucklebridge, F.; Thorn, L.; Evans, P.; Clow, A. State variation in the cortisol awakening response. Stress
2013
,16, 483–492.
[CrossRef]
43.
Kuzawa, C.W.; Georgiev, A.V.; McDade, T.W.; Bechayda, S.A.; Gettler, L.T. Is There a Testosterone Awakening Response in
Humans? Adapt. Hum. Behav. Physiol. 2015,2, 166–183. [CrossRef]
44.
Kutáˇc, P.; Bunc, V.; Sigmund, M. Whole-body dual-energy X-ray absorptiometry demonstrates better reliability than segmental
body composition analysis in college-aged students. PLoS ONE 2019,14, e215599. [CrossRef]
45.
Gajewski, J.; Michalski, R.; Bu´sko, K.; Mazur-Ró˙
zycka, J.; Staniak, Z. Countermovement depth–A variable which clarifies the
relationship between the maximum power output and height of a vertical jump. Acta Bioeng. Biomech.
2018
,20, 127–134.
[PubMed]
46.
Moir, G.L. Three Different Methods of Calculating Vertical Jump Height from Force Platform Data in Men and Women. Meas.
Phys. Educ. Exerc. Sci. 2008,12, 207–218. [CrossRef]
47.
Cormie, P.I.; McGuigan, M.R.; Newton, R.U. Changes in the eccentric phase contribute to improved stretch-shorten cycle
performance after training. Med. Sci. Sports Exerc. 2010,42, 1731–1744. [CrossRef] [PubMed]
48.
Ebben, W.P.; Petushek, E.J. Using the Reactive Strength Index Modified to Evaluate Plyometric Per-formance. J. Strength Cond Res.
2010,24, 1983–1987. [CrossRef]
49. Bates, B.T.; Haven, B.H. An analysis of the mechanics of highly skilled female runners. Mech. Sport 1973,4, 237–245.
50. Bates, B.T.; Osternig, L.R.; James, S.L. Fatigue Effects in Running. J. Mot. Behav. 1977,9, 203–207. [CrossRef]
51.
Hobara, H.; Inoue, K.; Gomi, K.; Sakamoto, M.; Muraoka, T.; Iso, S.; Kanosue, K. Continuous change in spring-mass characteristics
during a 400 m sprint. J. Sci. Med. Sport 2010,13, 256–261. [CrossRef]
52.
Lachlan, J.; Llion, P.A.; Haff, G.; Gregory, K.; Vincent, G.; Beckman, E.M. Validity and Reliability of a Portable Isometric Mid-Thigh
Clean Pull. J. Strength Cond. Res. 2017,31, 1378–1386.
53.
Vanrenterghem, J.; De Clercq, D.; Cleven, P.V. Necessary precautions in measuring correct vertical jumping height by means of
force plate measurements. Ergonomics 2001,44, 814–818. [CrossRef]
54.
Rhea, M.R. Determining the magnitude of treatment effects in strength training research through the use of the effect size.
J. Strength Cond. Res. 2004,18, 918–920.
55.
Bazyler, C.D.; Mizuguchi, S.; Sole, C.J.; Suchomel, T.J.; Sato, K.; Kavanaugh, A.A.; Brad, E.H.; Stone, M.H. Jumping Performance
is Preserved but Not Muscle Thickness in Collegiate Volleyball Players after a Taper. J. Strength Cond. Res.
2018
,32, 1020–1028.
[CrossRef]
J. Funct. Morphol. Kinesiol. 2021,6, 25 17 of 17
56.
Mujika, I.; Padilla, S.; Pyne, D.; Busso, T. Physiological Changes Associated with the Pre-Event Taper in Athletes. Sports Med.
2004,34, 891–927. [CrossRef]
57. Verkhoshansky, V.Y.; Siff, M.C. Supertraining, 4th ed.; Verkhoshansky Publishing: Moscow, Russia, 1999.
58.
Suchomel, T.J.; Nimphius, S.; Stone, M.H. The Importance of Muscular Strength in Athletic Per-formance. Sports Med.
2016
,46,
1419–1449. [CrossRef] [PubMed]
59.
Loturco, I.; Angelo, R.A.; Fernandes, V.; Gil, S.; Kobal, R.; Cesar, C.A.C.; Kitamura, K.; Nakamura, F.Y. Relationship Between
Sprint Ability and Loaded/Unloaded Jump Tests in Elite Sprinters. J. Strength Cond. Res. 2015,29, 758–764. [CrossRef]
60.
Travis, S.K.; Mujika, I.; Gentles, J.A.; Stone, M.H.; Bazyler, C.D. Tapering and Peaking Maximal Strength for Powerlifting
Performance: A Review. Sports 2020,8, 125. [CrossRef] [PubMed]
61.
Bazyler, C.D.; Mizuguchi, S.; Harrison, A.P.; Sato, K.; Kavanaugh, A.A.; DeWeese, B.H.; Stone, M.H. Changes in Muscle
Architecture, Explosive Ability, and Track and Field Throwing Performance Throughout a Competitive Season and After a Taper.
J. Strength Cond. Res. 2017,31, 2785–2793. [CrossRef] [PubMed]
62.
Mujika, I.; Chatard, J.; Padilla, S.; Guezennec, C.Y.; Geyssant, A. Hormonal responses to training and its tapering off in com-petitive
swimmers: Relationships with performance. Eur. J. Appl. Physiol. 1996,74, 361–366. [CrossRef]
63.
Joffe, S.A.; Tallent, J. Neuromuscular predictors of competition performance in advanced international female weightlifters:
A cross-sectional and longitudinal analysis. J. Sports Sci. 2020,38, 985–993. [CrossRef] [PubMed]
64.
Mujika, I.; Villanueva, L.; Welvaert, M.; Pyne, D.B. Swimming Fast When It Counts: A 7-Year Analysis of Olympic and World
Championships Performance. Int. J. Sports Physiol. Perform. 2019,14, 1132–1139. [CrossRef] [PubMed]
65.
Tønnessen, E.; Sylta, Ø.; Haugen, T.A.; Hem, E.; Svendsen, I.S.; Seiler, S. The road to gold: Training and peaking characteristics in
the year prior to a gold medal endurance performance. PLoS ONE 2014,9, e101796. [CrossRef] [PubMed]
... To measure the height attained by the center of body mass and the power output of the lower extremities during vertical jumps, a PJS-4P60S force plate ("JBA" Zb. Staniak, Poland) with a 400 Hz sampling rate [31,54,55] was employed. MVJ v.3.4 software ("JBA" Zb. ...
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... The power output of the lower extremities and the height attained by the center of body mass during vertical jumps were measured with a PJS-4P60S force plate ("JBA" Zb. Staniak, Poland) with a 400 Hz sampling rate (Gajewski et al., 2018;Batra et al., 2021). The force plate was connected via an analog-to-digital converter to a PC with MVJ v.3.4 software ("JBA" Zb. ...
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Purpose This investigation examined the relationships between the isometric mid-thigh pull (IMTP), isometric squat (ISqT) and sprint acceleration performance in track & field sprinters, and to determine whether there are differences between males and females. Methods Fifteen male and ten female sprinters performed 3 maximal effort IMTPs, ISqTs and 3 x 30 m from blocks. Results Among males, results showed significant negative correlations between IMTP and ISqT peak force, relative peak force, force at 100, 150 and 200 ms, rate of force development (0 – 150, 0 – 200 ms) and impulse (0 – 200 ms) and 0 – 5 m time ( r = -0.517 to -0.714; P < 0.05). IMTP impulse significantly predicted 0 – 5 m time (B = -0.582, P = 0.023). ISqT relative peak force significantly predicted 0 – 5 m time (B = -0.606, P = 0.017). Among females, no IMTP or ISqT variables significantly correlated with any sprint times. Males measured significantly higher than females for all IMTP measures except for relative peak force. Males were significantly faster than females at all splits. When comparing measures of the ISqT, there were no significant differences between males and females. Conclusions Variables measured during the IMTP and ISqT significantly correlated with 0 – 5 m sprint performance in male athletes. Isometric strength can have a sizable influence on 0 – 5 m time, but in some cases the maximum effect could be very small.
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International-level swimmers periodize their training to qualify for major championships, then improve further at these events. However the effects of various factors that could impact on performance progressions have not been described systematically. Purpose To quantify the pattern of change in performance between season best qualifying time and the major championships of the year, and assess the influence of time between performance peaks, ranking at the major events, stroke, event distance, sex, age, and country. Methods A total of 7,832 official competition times recorded at 4 FINA World Championships and 2 Olympic Games between 2011 and 2017 were compared with each swimmer’s season best time prior to the major event of the year. Percentage change in performance was related with the time elapsed between season best and major competition, race event, sex, age and country using linear mixed modelling. Results Faster performance (-0.79±0.67%; mean ± SD) at the major competition of the year occurred in 38% of all observations vs. 62% no change or regression (1.10±0.88%). The timing between performance peaks (<34 to >130 days) had little effect on performance progressions (P=0.83). Only medal winners (-0.87±0.91%), finalists (-0.16±0.97%), and U.S.A. swimmers (-0.44±1.08%) progressed between competitions. Stroke, event distance, sex and age had trivial impact on performance progression. Conclusions Performance progressions at Olympic Games and World Championships were not determined by timing between performance peaks. Performance progression at a major competition appears necessary to win a medal or make the final, independent of race event, sex and age.
Article
The isometric mid-thigh pull (IMTP) is commonly used to assess an athlete’s force generation ability. This test is highly reliable and is simple and relatively quick to perform. The data that can be determined from the force-time curves generated by the test have been shown to be closely related to performance capacities in a variety of dynamic athletic tasks. However, within the scientific literature there are inconsistencies in the data collection procedures and methods used for data analysis that may impact the resultant output and the ability to compare and generalize results. Therefore, the primary aim of this review is to identify the differences in IMTP testing procedures and data analysis techniques, while identifying the potential impact this may have on the data collected. The secondary aim is to provide recommendations for the standardization of testing procedures to ensure that future IMTP data is of maximal benefit to practitioners and researchers.