International  Journal  of
Environmental Research
and Public Health
Article
Acute Eﬀects of a Speed Training Program on
Sprinting Step Kinematics and Performance
Krzysztof Mackala 1,*, Marek Fostiak 2, Brian Schweyen 3, Tadeusz Osik 4 and Milan Coch 5
1
Department of Track and Field University School of Physical Education in Wroclaw, Poland, Ul.
Paderewskiego 35, 51-612 Wrocław, Poland
2
Department of Track and Field, Gdansk University of Physical Education and Sport, ul. Kazimierza
Górskiego 1, 80-336 Gdansk, Poland
3
PZLA (Polish Track and Field Association), Mysłowicka 4, 01-612 Warszawa, Poland
4
Athletics Department, University of Montana, Adams Center 32 Campus Drive, Missoula, MT 59812, USA
5
Faculty of Sport, University of Ljubljana, Gortanova ulica 22, 1000 Ljubljana, Slovenia
*
Correspondence: krzysztof.mackala@awf.wroc.pl; Tel.: +48-605-272-433
Received: 4 July 2019; Accepted: 24 August 2019; Published: 28 August 2019


Abstract: The purpose of this study was to examine the eﬀects of speed training on sprint step
kinematics and performance in male sprinters.
Two groups of seven elite (best 100-m time:
10.37 ± 0.04 s) and seven sub-elite (best 100-m time: 10.71 ± 0.15 s) sprinters were recruited.
Sprint performance was assessed in the 20 m (ﬂying start), 40 m (standing start), and 60 m (starting
block start). Step kinematics were extracted from the ﬁrst nine running steps of the 20-m sprint
using the Opto-Jump–Microgate system. Explosive power was quantiﬁed by performing the CMJ,
standing long jump, standing triple jump, and standing ﬁve jumps. Signiﬁcant post-test improvements
(p < 0.05) were observed in both groups of sprinters. Performance improved by 0.11 s (elite) and
0.06 s (sub-elite) in the 20-m ﬂying start and by 0.06 s (elite) and 0.08 s (sub-elite) in the 60-m start
block start. Strong post-test correlations were observed between 60-m block start performance and
standing ﬁve jumps (SFJ) in the elite group and between 20-m ﬂying start and 40-m standing start
performance and standing long jump (SLJ) and standing triple jump (STJ) in the sub-elite group.
Speed training (ST) shows potential in the reduction of step variability and as an eﬀective short-term
intervention program in the improvement of sprint performance.
Keywords: sprinting; speed; sprint exercises; step variability; kinematics
1. Introduction
Past investigations have indicated a signiﬁcant commonality between sprinting performance
(across distances from 20 to 100 m) and explosive power [1–5]. As the largest inhibitor in the sprinting
movement is gravity, sprinters must produce large vertical ground reaction force during step take-oﬀ
to achieve maximal velocity [6]. This is achieved via application of plyometric training as it uses
jump-based movements to train and improve explosive power. However, this training modality does
not involve a running component.
A mixture of plyometric characters exercises (skips and bounds) and some speed running drills
created an alternative sprint-speciﬁc running methodology, which represents a high-intensity speed
training (ST). ST is treated as a low-volume training strategy and credited with producing signiﬁcant
gains in maximal running velocity [7]. This form of training is based on short bouts of all-out sprints
separated by rest periods from 90 s to 5–6 min to enhance post-exercise recovery and avoid fatigue,
including central nervous system fatigue [8–10]. Similar in one regard to plyometrics, sprint-speciﬁc
running also involves a rapid eccentric movement followed by a short amortization phase that is
Int. J. Environ. Res. Public Health 2019, 16, 3138; doi:10.3390/ijerph16173138
www.mdpi.com/journal/ijerph
Int. J. Environ. Res. Public Health 2019, 16, 3138
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then followed by an explosive concentric movement [6]. This enables the synergistic muscles to
engage the myotatic-stretch reﬂex during the stretch-shortening cycle [11]. Such a training stimulus
activates the elastic properties of the muscle ﬁbers and connective tissue, allowing the muscles to
store more elastic energy [11–13]. This then enhances the release of the accumulated mechanical
energy during step take-oﬀ, a process which is easily visible during skipping and speed bounding.
Hence, improvements in elastic energy storage via ST could be interrelated with improvements in
single sprint step performance and, therefore, maximal velocity.
Running velocity is a product of step frequency (SF) and step length (SL) [3,14,15] in which
a step deﬁnes half a running cycle or the interval between ground contact of one foot to the moment
when contact is made by the opposing foot [16]. SF and SL are mutually interdependent in which
an increase in SL results in a decrease in SF and vice versa [17–21]. Both variables are determined
by anthropometric characteristics, movement regulation processes, motor abilities, and energetic
processes [16,22]. Hence, the relationship between SF and SL is unique for each sprinter [19,23].
Previous research investigating the interaction between SL and SF in running has generally been
inconclusive. There is much debate as to whether sprinters achieve greater beneﬁts from increased SL
or SF. Nonetheless, the strong interdependency between SL and SF and performance at sub-maximal
and maximal velocities posits that these are important outcome measures when assessing variability in
sprinting technique [3,24]. In addition, little is known on how other kinematic variables such as ﬂight
phase time, ground contact time, and step velocity interact and inﬂuence maximal running velocity.
The fundamental goal of this study was to investigate the potential eﬀects of acute ST on sprint
steps kinematics—how these spatial-temporal characteristics can inﬂuence sprint running. A secondary
goal was to examine performance including maximal running velocity and power of lower extremity.
Sprinters of diﬀerent competitive levels were recruited to better generalize the results of the study.
To mitigate the eﬀects of overtraining, only eight sessions were administered in two 10- and 12-day
modules separated with 10 days of recovery. Furthermore, the intervention was administered during
the pre-season period to avoid additional confounding variables. A pre-test/post-test design was
adopted and included a wide battery of tests and exercises commonly applied in sprint training.
Based on this consideration, it was hypothesized that the information of selecting the relevant
biomechanical parameters obtained after high-speed training, may indicate the elite of the sprinters
(seniors and 100 m < 10.50 s) will show less variability of the sprinting step in the 20-m sprint from
a ﬂying start than the sub-elite sprinters (juniors and 100 m > 10.50 s).
2. Materials and Methods
2.1. Participants
Seven elite and seven sub-elite healthy male sprinters with a minimum of four to ﬁve years of
regular sprint training were recruited. Sprinters participating in the experiment were members of
the national team. For the purposes of the experiment, they were divided into two groups: Elite and
sub-elite. The main division criterion was age (juniors up to 19 years, seniors above) and the personal
best times in the 100 m sprint (below 10.50 s—elite). Each participant was medically cleared to
participate in sprint training and presented no orthopedic or physiological limitation or injury that
could aﬀect sprint performance. All participants had previous experience (minimum six months)
in sprint-related strength, speed, and plyometrics training before enrollment. Written consent was
obtained after the protocol and procedures were explained in full. Parental consent was also obtained
from those individuals under 18 years of age. Sprinters were instructed to maintain their normal intake
of food and ﬂuids during the study period. Additionally, they were instructed to avoid any strenuous
physical activity 24 h prior to testing as well as refrain from eating 3 h before test commencement.
The study design was approved by the Institutional Ethics Committee.
Int. J. Environ. Res. Public Health 2019, 16, 3138
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2.2. Design
The study was performed over a four-week period during the pre-season (April–May) just
prior to the outdoor racing season.
All participants had been engaged in a standard sprint
training regimen (ﬁve to seven days of a weekly microcycle) from October to November until
inclusion in the study. This training regimen involved general and specialized ﬁtness exercises
designed to enhance sprinting technique, increase maximal velocity, and develop strength, power,
and endurance. Additionally, many of the participants competed during the indoor competition season
(January–February).
Eight ST sessions were executed in a 10-day and then 12-day module (Table 1). The modules
were separated by 10 days of recovery training with minimal load to promote central nervous system
regeneration. ST in the ﬁrst 10-day module was executed every other day and in the 12-day module every
third day. The days with training involved the main SST workout and one short supplementary workout
(general ﬁtness) with the order reversed in each subsequent training session. Post-workout recovery
was also provided and predominately involved massage treatment and low-intensity swimming.
Table 1. Training characteristics of the training modules.
Type of Exercise Modality
Training Module
10-day Module
12-day Module
Number of Workouts (n)
Strength (combined with a short
plyometrics session)
3
2
Plyometrics
−
1
Speed
4
4
Speed−endurance
1
2
Tempo
2
1
General ﬁtness (supplementary session)
4
4
Recovery (swimming, massage,
cryotherapy)
5
5
Day oﬀ (rest)
−
1
Testing
−
1
Total training workouts per module
36
ST focused primarily on developing sprint technique and maximal velocity by various exercises
that consisted of various skips, bounds, accelerations, starts, and maximal intensity sprints (Table 2).
Training duration was approximately 90 min. This included a 20–30 min warm-up of jogging, stretching,
light jumping, skipping, and submaximal accelerations and a 10–15 min cooldown. Training load
was progressively ampliﬁed by varying task complexity (running distance or number of foot contacts
during skip and bound exercises) and by increasing running velocity (from 85–90% to 100%).
Int. J. Environ. Res. Public Health 2019, 16, 3138
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Table 2. Speed training (ST) characteristics.
Exercises
Module 1
Module 2
1st
session
2nd
session
3rd
session
4th
session
5th
session
6th
session
7th
session
8th
session
Sub−maximal speed
(85–90%)
10 m skip A + 20 m
acceleration
2 rep.
3 rep.
2 rep.
2 rep.
10 m skip C + 20 m
acceleration
2 rep.
3 rep.
2 rep.
2 rep.
20 m sprint bounding + 20
m acceleration
3 rep.
3 rep.
3 rep.
4 rep.
Falling start + 20 m
build-up
3 rep.
2 rep.
3 rep.
2 rep.
Block starts + 20 m build-up
4 rep.
4 rep.
4 rep.
4 rep.
40 m acceleration
3 rep.
4 rep.
3 rep.
6 rep.
Total distance [m]
540
600
540
640
Maximal speed (ca. 100%)
Falling start + 20 m build
up
2 rep.
2 rep.
2 rep.
2 rep.
Block starts + 20 build up
3 rep.
4 rep.
3 rep.
4 rep.
30 m sprint
3 rep.
4 rep.
3 rep.
4 rep.
40 m sprint
3 rep.
4 rep.
3 rep.
4 rep.
50 m sprint
1 rep.
0 rep.
1 rep.
1 rep
Total distance [m]
360
400
360
450
2.3. Testing Protocol
Maximal running velocity and lower extremity explosive power were measured one day before
the intervention and 48 h after the last training session was completed to ascertain acute training
eﬀects. Pre- and post-testing was executed at the same time of the day and under identical conditions.
No familiarization was provided as all of the testing protocols were well-known to the participants.
A warm-up similar to the one used during the training intervention was administered prior to testing
(light jogging, stretching, skipping drills, light jumps and bounds, and 30- to 50-m accelerations).
The test battery included the countermovement jump (CMJ), standing long jump (SLJ), standing triple
jump (STJ), and standing ﬁve jump (SFJ) to assess explosive power. After 60 min of rest, the participants
performed the 20-m sprint (from the ﬂying start) to evaluate sprint step kinematics and then 40 m
(from a standing start) and 60 m (using starting blocks) to determine maximal running velocity.
2.4. Assessment of Lower Extremity Explosive Power
The CMJ was used to determine vertical jumping performance. The OptoJump–Microgate optical
measurement system (Optojump, Bolzano, Italy) determined contact and ﬂight times with an accuracy
of 0.001 s. No restrictions were placed on knee angle during the eccentric phase and the participants
were instructed to perform a dynamic double arm swing to attain maximal height. Three trials were
separated by 1 min of rest with the highest jump selected for analysis.
Horizontal jump performance was measured in the following order: SLJ, STJ, and SFJ. From an
erect position with parallel feet placement, the participant executed the SLJ and was required to land
on both feet in the long jump pit without falling backwards. Jumping distance was measured to the
nearest 1.0 cm. The starting position for the STJ and SFJ was similar. In these jumps, after one or
more arm and leg swings, the participant performed the required number of forward jumps with
each step on an alternating leg and was required to land on both feet in the half-squat position on
a special jumping mattress. Three trials were executed for each jump and the longest distance to the
nearest 1.0 cm was recorded. A 2 min rest was provided between each trial and 5–6 min between each
jump modality.
The reliability of the vertical and horizontal jumping tests was measured using intraclass correlation
coeﬃcients (ICC). A posteriori analysis obtained correlations of 0.92 for CMJ jump height and 0.93 for
Int. J. Environ. Res. Public Health 2019, 16, 3138
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SLJ, 0.93 for STJ, and 0.90 for SFJ jump distances. The large coeﬃcients indicate satisfactory test–retest
reliability and may be explained by the extensive familiarization of all participants with executing
these jumps.
2.5. Assessment of Sprint Performance
The 20-m ﬂying start, 40-m standing start, and 60-m block start were performed on an indoor track
integrated with the Brower Timing TC-System (Draper, Utah, USA). The photocells were positioned on
the track at the start and ﬁnish according to the sprint distance [3]. In the 20-m ﬂying start, the sprinter
began from a standing start and accelerated as quickly as possible to attain maximal running velocity
within a 20 m run-up. Upon reaching the 20 m mark, the sprinter continued to sprint for exactly
20 m at their maximal velocity. This sprint modality had been previously applied in research and is
considered suﬃcient to achieve maximal velocity [3,6,16,25,26]. Two trials were executed and separated
by 2 min of rest. The same OptoJump measuring system was used to measure the spatial-temporal
characteristics of the ﬁrst nine running steps at maximal velocity including step length, step frequency,
ground contact time, ﬂight time, and step velocity. In a track conﬁguration, the measurement system
uses a series of interconnected rods (100 cm x 4 cm x 3 cm) ﬁtted with optical sensors. Each rod (RX bars
and TX bars) is ﬁtted with 32 photocells, arranged 4 cm one from another and 0.2 cm above the ground.
The rods were distributed along the length and width of the track (20 m x 1.22 m). The device was
integrated with a computer for data storage and processing. After completing the 20-m ﬂying start
sprint, the participants performed two trials of the 40 m from a standing start and 60 m from a block
start. Rest intervals of 4 and 6 min were provided between trials, respectively. The fastest time in each
distance was selected for analysis.
2.6. Statistical Analysis
Means (x) and standard deviations (SD) were calculated for all dependent variables. Student’s t-test
was used to examine pre- and post-test diﬀerences in running velocity and jumping performance.
Fisher’s least signiﬁcant diﬀerence (LSD) tests were performed post hoc to determine pairwise
diﬀerences when signiﬁcant F ratios were obtained. Variability in the nine steps was quantiﬁed
by calculating the SD and conﬁdence intervals (95%CI). The associations between the performance
variables (sprint times and jump distance/heights) were determined by Pearson product–moment
correlations. Additionally, hierarchical cluster analysis using Ward’s method was used to determine
the linkage distances among the kinematic characteristics grouped as elementary determinants of
sprint velocity. A statistical power of 0.90 was determined satisfactory and an alpha level of 0.05 was
accepted as statistically signiﬁcant (denoted in bold font).
3. Results
Table 3 provides the anthropometric and personal bests in the 60 m and 100 m of the elite and
sub-elite sprinters.
Table 3. Descriptive statistics and Student’s t-test results of group age, anthropometric characteristics,
and personal best (PB) times.
Variables
Sub-Elite
Elite
t
p
x
SD
x
SD
Age (years)
18.71
0.75
24.71
2.43
−6.24
0.000043
Height (cm)
182.00
5.35
179.42
3.91
0.78
0.449165
Body mass (kg)
73.28
4.49
74.43
8.24
−0.32
0.753007
BMI (kg/m2)
22.17
1.10
22.79
0.74
−1.22
0.244110
60 m PB
6.97
0.08
6.69
0.79
6.52
0.000028
100 m PB
10.71
0.15
10.37
0.04
5.71
0.000097
Bold format: signiﬁcant diﬀerences.
Int. J. Environ. Res. Public Health 2019, 16, 3138
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Height, body mass, and BMI were similar between the groups. The diﬀerences between the elite
and sub-elite group for age and personal bests were signiﬁcant (p < 0.05).
Table
4
presents
the
pre-
and
post-test
results
in
sprint
and
jump
performance.
Signiﬁcant diﬀerences were observed in all variables in which jumping distances increased and
running times decreased in both the elite and sub-elite sprinters (p < 0.05). Sprint step characteristics
are presented in Figure 1. In the elite sprinters, contact time (CT) decreased post-test in steps four
to seven whereas the lowest value was attained in the ninth step. CT showed a decreasing trend
from the ﬁrst to ninth step. Among the sub-elite sprinters at pre-test, a trend towards increased CT
between the ﬁrst and ninth steps was observed. At post-test, increased CT was observed in steps
four to eight. The ﬂight time (FT) in both groups increased post-test from the ﬁrst to the eighth step.
Greater FT was achieved by the sub-elite sprinters at post-test. Step length (SL) in both the elite and
sub-elite sprinters showed an upward trend at pre-test, with increased SL from the ﬁrst to the eighth
step, only to become more linear at post-test. Additionally, post-test SL magnitudes increased in
both groups. Step frequency (SF) showed an irregular pre-test trend in both the elite and sub-elite
sprinters. Following the intervention, SF increased in the elite sprinters, particularly in the last three
steps. Changes in step velocity (SV) were more pronounced compared with the other variables in both
groups particularly at pre-test (an increase in two consecutive steps followed by a decrease in the next
two steps).
Table 4. Student’s t test results for the dependent variables.
Variable
x
SD
x
SD
∆x
∆xSD
t
p
Conﬁdence
−95.00%
Conﬁdence
+95.0%
Sub-elite
Pre−test
Post−test
60m–60m_t2 (s)
7.10
0.09
7.02
0.05
0.08
0.04
4.77
0.0030
0.038
0.121
20m ﬂying–20m
ﬂying_2t (s)
2.21
0.08
2.13
0.05
0.07
0.05
3.57
0.0116
0.024
0.129
40m –40m_2t (s)
4.37
0.04
4.32
0.03
0.06
0.01
7.94
0.0000
0.040
0.076
SLJ–SLJ_2t (cm)
2.91
0.06
2.99
0.07
−0.08
0.04
−4.81
0.0029
−0.120
−0.039
STJ–STJ_2t (m)
8.56
0.16
8.80
0.18
−0.24
0.07
−8.67
0.0001
−.0313
−0.175
SFJ–SFJ_2t (m)
14.90
0.62
15.56
0.53
−0.66
0.13
−13.66
0.0000
−0.775
−0.539
CMJ –CMJ_2t
(cm)
76.43
4.89
82.71
5.34
−6.29
1.70
−9.76
0.0000
−7.862
−4.709
Elite
Pre−test
Post−test
60m–60m_t2 (s)
6.79
0.08
6.72
0.08
0.06
0.02
7.17
0.0003
0.040
0.082
20m ﬂying–20m
ﬂying_2t (s)
2.07
0.04
1.97
0.07
0.11
0.07
4.17
0.0058
0.047
0.179
40m –40m_2t (s)
4.12
0.02
4.08
0.01
0.04
0.02
4.58
0.0037
0.018
0.061
SLJ –SLJ_2t (m)
3.15
0.10
3.23
0.11
−0.07
0.05
−3.92
0.0078
−0.118
−0.027
STJ–STJ_2t (m)
9.39
0.52
9.89
0.48
−0.49
0.21
−6.28
0.0007
−0.693
−0.304
SFJ–SFJ_2t (m)
15.81
0.44
16.59
0.57
−0.78
0.50
−4.11
0.0062
−1.244
−0.316
CMJ –CMJ_2t
(cm)
81.57
2.57
87.86
1.07
−6.28
2.06
−8.08
0.0001
−8.189
−4.382
_2t—post−test results, bold format—signiﬁcant diﬀerences.
Int. J. Environ. Res. Public Health 2019, 16, 3138
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Figure 1. Sprint step kinematics characterizing the ﬁrst nine steps (S) in the 20-m ﬂying start sprint.
Post-test variability in the sprint step characteristics was signiﬁcant for group and step (p < 0.05)
(Table 5). The interactions ST × group, SL × group, ST × SL, and ST × SL × group did not show variability
except SV and CT (p < 0.05). Consequently, the consistent generation of high horizontal velocity in the
run-up resulted in greater running velocity with stable SV when sprinting the 20 m distance.
Table 5. ANOVA results of sprint step kinematics.
Feature
Main Eﬀect
Group
ST
PT ×
Group
Step
Step ×
Group
ST × step
ST × step × group
F
p
F
p
F
p
F
p
F
p
F
p
F
p
CT
0.27
0.6129 4.09
0.0660 2.79
0.1206 2.14
0.0388 0.74
0.6540 0.19
0.9918 2.34
0.0240
FT
9.05
0.0109 0.53
0.4789 0.85
0.3756 10.58
0.0000 0.24
0.9812 0.54
0.8220 0.57
0.8016
SF
4.91
0.0468 0.33
0.5763 0.73
0.4100 0.90
0.5167 1.68
0.1121 0.89
0.5247 1.13
0.3484
SL
0.61
0.4489 0.32
0.5841 0.08
0.7828 18.23
0.0000 0.25
0.9798 0.50
0.8503 0.50
0.8519
SV
56.64
0.0000 2.72
0.1249 0.74
0.4080 8.22
0.0000 2.06
0.0475 0.48
0.8703 0.80
0.6012
SST—sprint-speed training; bold format—signiﬁcant diﬀerences.
Table 6 presents the pre- and post-test correlation coeﬃcients for the performance measures in the
20-m ﬂying start, 40-m standing start, and 60-m block start sprints and vertical and horizontal jumping
tests. At pre-test, the only signiﬁcant correlation in the sub-elite group was between the 60-m block
start and SLJ (r = −0.76) and SFJ (r = −0.77). In the elite group, a signiﬁcant relationship was found
between the 60-m block start and the 20-m ﬂying start (r = 0.81) and 40 m standing start (r = −0.76).
No other signiﬁcant pre-test correlations were found. Post-test analysis revealed correlations between
the 20-m ﬂying start and 40-m standing start and SLJ and STJ performance in the sub-elite group.
In the elite sprinters, only the correlation between 60-m block start and SFJ performance was signiﬁcant
(r = −0.87). Many of the horizontal jump tests (SLJ, STJ, SFJ) were strongly associated with each other,
however, no signiﬁcant pre- and post-test correlations were observed between CMJ with any of the
variables in either group.
Int. J. Environ. Res. Public Health 2019, 16, 3138
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Table 6. Spearman rank correlation coeﬃcients between sprint performance and lower extremity
explosive power variables.
Sub-Elite
Variable
Elite
[7]
[6]
[5]
[4]
[3]
[2]
[1]
[1]
[2]
[3]
[4]
[5]
[6]
[7]
-
−0.77
−0.76
0.85
-
-
60 m [1]
-
0.81
−0.76
-
−0.87 *
-
-
-
-
−0.76 *
0.90 *
-
-
-
-
-
-
-
-
-
-
-
−0.85 *
-
-
-
-
20 m ﬂying
start [2]
-
-
-
-
-
-
-
-
-
−0.76 *
-
-
-
-
40 m [3]
-
-
-
-
-
-
-
−0.79
0.82 *
0.79 *
-
-
-
-
SLJ [4]
-
-
-
-
-
0.85
*
-
-
−0.90
-
-
-
-
-
STJ [5]
-
-
-
-
-
0.79
-
-
0.79 *
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
SFJ [6]
-
-
-
-
-
-
-
CMJ [7]
Italic means pre-test result, bold with * means post-test result.
Hierarchical cluster analysis of the grouped variables is illustrated in Figure 2 (pre-test) and
Figure 3 (post-test). Comparison of the two dendrograms did not reveal any diﬀerences between the
emerging clusters. At both time points, the individual clusters were grouped similarly to form two
large characteristic aggregations. This suggests a congruency of the kinematic variables and a relatively
loose relationship with no signiﬁcant eﬀect of one cluster on the other. Additionally, the Euclidean
distances of the clusters in the pre-test and post-test clusters were similar.
Figure 2. Dendrogram clustering of pre-test sprint step kinematics.
Int. J. Environ. Res. Public Health 2019, 16, 3138
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Figure 3. Dendrogram clustering of post-test sprint step kinematics.
4. Discussion
Signiﬁcant post-test improvements in 60-m block start times were observed in both the elite and
sub-elite sprinters by 1.04% and 1.23%, respectively. Improvements were also noted in 20-m ﬂying
start performance by 4.84% and 3.62% in the elite and sub-elite sprinters, respectively. Only marginal
improvements (not statistically signiﬁcant) were found for 40-m standing start performance, in which
sprinting time improved by 0.98% in the elite group (Table 5). While indicative that ST has a positive
eﬀect on sprint performance, the ﬁndings are diﬃcult to interpret due to the lack of similar data in the
literature. However, comparisons can be made with studies that examined the eﬀects of plyometrics
training on maximal running velocity. In this context, the results of the present study are comparable
with those reported by Kreamer et al. [27], Hennessy and Kilty [12], and Mackala and Fostiak [3].
There is strong evidence that plyometrics training enhances the stretch-shortening cycle of muscle
to improve elastic energy storage [28] and generate faster and more powerful movements [29]. ST is
similar in this regard in that it can likewise activate the elastic properties of muscle ﬁbers and connective
tissue to also allow greater elastic energy storage that, after its release, can provide additional impetus
during running [6].
An important question in this regard is whether ST is more eﬀective than plyometrics training in
enhancing explosive power and maximal running velocity. The data from this study can be compared
with previous research that used an identical testing protocol to assess the eﬀects of six sessions of
plyometrics training [3]. When compared with this study, ST shows greater improvements in 20- and
60-m ﬂying start sprint times (by 0.5% to 2%, respectively) and horizontal jump performance (STL and
STJ). In turn, the plyometrics intervention showed greater increases in standing jump (SJ) and CMJ
performance [3]. Some studies reported strong correlations (r) from 0.65 to 0.90 between sprinting
Int. J. Environ. Res. Public Health 2019, 16, 3138
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and drop jump (DJ), SJ, CMJ performance, depending on the sprint distance (20–100 m) and type of
jump [12,30,31]. These ﬁndings are comparable with the present investigation, in which signiﬁcant
post-test correlations were observed between 60-m block start times and SLJ in the sub-elite (r = −0.76)
and STJ in the elite (r = −0.85) group. Strong correlations were also observed between 20-m ﬂying start
times and STJ performance (r = −0.85) in the sub-elite group but not in the elite group.
The secondary purpose of the study was to examine the eﬀects of ST on sprint step kinematics
(SL, SF, FT, CT, and SV). Analysis of SL in both groups of sprinters was compared with other research
where high-performance sprinters were investigated [16,22,32–34]. These studies reported that SL
increased with running velocity and with sprint distance. In our study, linear increases in SL (between
steps two and eight in the elite and steps two and six and also step eight in the sub-elite sprinters) were
observed in both groups at both time points. SL increased only in the sub-elite group by approximately
4 cm at post-test with no changes observed in the elite group. SL was maintained at 228 and 230 cm
(sub-elite and elite, respectively) in the last three steps (Figure 1). This may be explained by the fact
that the ﬂying start involved a 20-m run-up and, therefore, a combined distance of 40 m. Therefore, it is
possible that SL was still increasing with each step (build-up phase) that only plateaued at the end of
the 20 m sprint distance when maximal velocity was attained. In turn, the changes in SF were less
pronounced and remained relatively similar in the sub-elite group but slightly decreased from 4.38 to
4.33 Hz in the elite group. Post-test SF in the elite group was similar between the second and sixth step
(diﬀerence of only 0.03 Hz), whereas greater variability was observed between the second and sixth
step in the sub-elite group at pre- and post-test.
Considering both SF and SL, the elite sprinters presented greater SF and slightly longer SL than
the sub-elite sprinters (Figure 1). This result suggests that the improvement in sprint performance
via increased running velocity does not demonstrate the classic dependency between SL and SF.
This contradicts the study of Bezodis et al. [19], who reported a weak correlation (r = –0.192) between
SL and running velocity but a strong correlation between SF and running velocity (r = 0.886). In turn,
Hunter et al. (2004) found a strong correlation between sprint velocity and SL (r = 0.73) and only
a weak correlation between sprint velocity and SF (r = –0.14). While this contradicts the previous
ﬁnding, it does conﬁrm Delecluse et al. [35] who used regression analysis to ﬁnd that ca. 85% of
variance in running velocity can be explained by variance in SL. Similarly, Mackala [34] examined
whether an increase in SF or SL would increase running velocity to ﬁnd that SL was more strongly
associated with running velocity than SF.
Post-test SV increased from 9.10 m/s to 9.26 m/s in the sub-elite and from 9.93 m/s to 9.98 m/s in
the elite group. Single sprint step execution in the elite sprinters showed a linear increase across steps
one to nine at both pre- and post-test with no changes in SL in step four and seven when compared
with earlier steps three and six. In turn, the sub-elite sprinters showed more pronounced variation in
SV and SL, which, in turn, may have perturbed the sprinting movement and thus explain the slower
running velocity (Figure 1). As SV is a product of reduced CT during the support phase, this may
explain the increased running velocity in the elite sprinters. According to Coh et al. [17], and Alcaraz
et al. [36] the most important factor in sprint step eﬃciency is the support phase, especially the ratio
between the braking and propulsion phases. Therefore, maximal running velocity can be achieved
only if the force impulse is as small as possible during the braking phase and may be possible by
positioning the foot of the push-oﬀ leg as close as possible to the vertical projection of the body’s center
of gravity on the surface. Although this was not measured in the present study, this is the most rational
explanation for the increases in running velocity in the 20-m ﬂying start. Hence, the various sprint
distances involved in the SST intervention may have increased execution economy during the support
phase by positioning the center of gravity closer to the fulcrum upon landing, thereby increasing the
velocity of each step.
No signiﬁcant changes were also observed in CT and FT in either group of sprinters (Figure 1).
The diﬀerence between CT and FT was ca. 0.04 s and was relatively linear from step two to step
eight at both pre- and post-test. More variability was observed in post-test FT in the elite sprinters
Int. J. Environ. Res. Public Health 2019, 16, 3138
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although the diﬀerence between the minimum and maximum values is 0.03 s. CT was reduced in the
elite sprinters and was comparable with values reported in other studies during maximal sprinting
(90–120 ms) [15,37,38] noted a decreasing trend in CT in the ﬁrst 10 sprint steps after which CT stabilizes.
To better understand the eﬀects of ST on the spatial and temporal variability of sprinting,
hierarchical cluster analysis was applied. Post-test analysis revealed that the variables in the ﬁrst cluster
show greater Euclidean distances between CT and FT (6.5 at pre-test and 7.5 at post-test). Changes were
also observed in the grouping order regarding the CT, which are arranged in the order of the executed
steps. Post-test changes in the second cluster (SF and SV) revealed closer sub-cluster linkages (2.5 units
at pre-test and 2 at post-test). These results suggest that SF and SV show considerable dependency and
may be associated with improvements in running velocity. Similar conclusions can be assumed for CT
and FT based on the Euclidean distances.
5. Conclusions
In summary,
this study has shown that the application of eight SST sessions are
eﬀective in signiﬁcantly increasing 60-m block start and 20-m ﬂying start sprint performance.
Signiﬁcant improvements were also observed in lower extremity explosive power as ascertained by
vertical and horizontal jump testing. Greater increases were observed in the CMJ (mean 7.95% increase)
than in the horizontal jumps (mean 2.5–5.3% increase). Increased 20-m running velocity was associated
with increases SV, as CT and FT did not change after SST and only relatively linear increases were
observed in SL and SF from step two to step eight.
Additionally, sprint-speed training can be recommended as an eﬀective short-term intervention
to improve sprint performance and lower extremity explosive power, particularly when considering
the required training volume of eight sessions (across 22 days). Sprint performance gains can also be
optimized by decreasing variability in sprint step kinematics during maximal velocity running in both
lower and higher performing sprinters.
Author Contributions: Conceptualization, M.K., F.M., O.T.; methodology, M.K., F.M., C.M., software, M.K., F.M.;
validation, C.M., O.T.; formal analysis, M.K., F.M., C.M., O.T., S.B.; investigation, M.K., F.M., O.T.; a resources,
F.M.; data curation, M.K., C.M., S.B.; writing—original draft preparation, MK., F.M.; writing—review and editing,
M.K., SB.; visualization, M.K., F.M., C.M.; supervision, M.K., C.M.
Funding: This research received no external funding.
Conﬂicts of Interest: The authors have no conﬂict of interest to declare. The results do not constitute endorsement
of any product or device. The authors would like to thank the sprinters who participated in this study.
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Acute Effects of a Speed Training Program on Sprinting Step Kinematics and Performance.
Mackala, Krzysztof,Fostiak, Marek,Schweyen, Brian,Osik, Tadeusz,Coch, Milan