RESEARCH ARTICLE
Anthropometry-driven block setting improves
starting block performance in sprinters
Valentina Cavedon1☯, Marco SandriID1, Mariola Pirlo2, Nicola Petrone3, Carlo Zancanaro1,
Chiara MilaneseID1☯*
1 Department of Neurosciences, Biomedicine and Movement Sciences, University of Verona, Verona, Italy,
2 OMR Automotive, Brescia, Italy, 3 Department of Industrial Engineering, University of Padua, Padua, Italy
☯ These authors contributed equally to this work.
* chiara.milanese@univr.it
Abstract
This study tested the effect of two block setting conditions i.e., the usual block setting [US]
and an anthropometry-driven block setting [AS] on the kinematic and kinetic parameters of
the sprint start. Furthermore, we verified whether this effect is influenced by the relative
lengths of the sprinter’s trunk and lower limbs i.e., the Cormic Index by subdividing sprinters
into brachycormic, metricormic and macrocormic groups. Forty-two sprinters performed 6
maximal-effort 10 m sprints using the US and AS conditions. Dynamometric starting blocks
measured forces generated by the sprinters. The times at 5 m and 10 m in the sprint trials
were measured with photocells. Results showed that the anteroposterior block distances
were significantly different between the two conditions (P<0.001). Across the sample, the
horizontal block velocity, the rear peak force, the rear force impulse, the total force impulse,
the horizontal block power, the ratio of horizontal to resultant impulse in the rear block, the
first and second step lengths and the times at 5 m and 10 m improved in AS vs. US (P values
from 0.05 to 0.001). Considering the interaction between the block setting condition and the
Cormic Index, the rear peak force and the rear force impulse were significantly increased in
the metricormic and brachycormic groups (P0.001) and the metricormic group (P<0.001),
respectively. Kinetic variables in the rear block and the difference (Delta) in the front block/
starting line distance between US and AS were related with each other (Adjusted R2 values
from 0.07 to 0.36). In conclusion, AS was associated with improvement in the kinematic
and kinetic parameters of the sprint start performance vs. US; however, AS is apparently
best suited for metricormic sprinters. Further work is needed to verify how the sprint start
kinetic and kinematic parameters are related to the front block/starting line distance and
whether a block setting driven by the sprinter’s Cormic Index is able to improve sprint start
performance.
Introduction
In track sprints, the success of the sprint start performance depends on the ability of the
sprinter to generate a large impulse over the shortest time and reach the highest running speed
as soon as possible [1–3]. This phase is especially important in the 100 m sprint [4–7].
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OPEN ACCESS
Citation: Cavedon V, Sandri M, Pirlo M, Petrone N,
Zancanaro C, Milanese C (2019) Anthropometry-
driven block setting improves starting block
performance in sprinters. PLoS ONE 14(3):
e0213979. https://doi.org/10.1371/journal.
pone.0213979
Editor: Alena Grabowski, University of Colorado
Boulder, UNITED STATES
Received: June 25, 2018
Accepted: March 5, 2019
Published: March 27, 2019
Copyright: © 2019 Cavedon et al. This is an open
access article distributed under the terms of the
Creative Commons Attribution License, which
permits unrestricted use, distribution, and
reproduction in any medium, provided the original
author and source are credited.
Data Availability Statement: All relevant data are
within the paper and its Supporting Information
files.
Funding: This work was supported in part by
Departmental intramural funds (Joint Projects
2009) to CM. The funders had no role in study
design, data collection and analysis, decision to
publish, or preparation of the manuscript. There
was no additional external funding received for this
study. The funding organization (OMR Automotive)
did not play any role in the study design, data
Acceleration at the start of a race is influenced by the way sprinters positions themselves in
the blocks at the set command and the mechanics of leaving the blocks at the sound of the gun
[8,9]. The kinematic and kinetic patterns of elite athletes during the starting block phase and
acceleration phase have received considerable attention and many variables have been studied
to account for the effects of starting technique [2,3,5, 9–18].
According to the literature an effective sprint start mainly depends on the start block posi-
tioning and the joint angles of the lower limbs in the set position [8,9,11]. Furthermore, the
pushing time on the blocks and the forces generated by the front and rear legs in the pushing
phase [3,9–18] are also important. Recent studies found that the most predictive factor of
sprint start performance was the magnitude of force generated by the rear leg [16,19]. What is
more, the average horizontal external power (i.e., the ability to translate the centre of mass in
the running direction in a short period of time) was identified as an excellent descriptor of
start performance in sprinters [2].
The starting technique is greatly influenced by the setting of the block positions with
regards to spacing and obliquities [8,20,21]. Bezodis, Salo, & Trewartha [3] demonstrated that
“a single optimal set position” for everybody is not recommended due to varying physical fac-
tors, and therefore sprinters generally find their own preferred distance between the blocks
according to sensations or outcomes. For example, one of the most popular adjustments fre-
quently modified by the sprinters is the anteroposterior inter-block spacing and finding the
optimum setting for each athlete may take a long period of training. Furthermore, athletes
may not actually be selecting their ideal block setting for best performance when only basing
their preference on sensation.
The importance of anteroposterior inter-block spacing on the sprint movement during the
block start phase has been extensively investigated in several studies [3,6,9,12, 21–24]. The three
main types of block spacing investigated in the literature [20] are the bunched start (spacing gen-
erally <30 cm), the medium start (30 to 50 cm) and the elongated start (>50 cm). A number of
studies found that the velocity of the centre of mass at block clearing is higher when the inter-
block spacing increases due to an increase of force impulse [2,11,22]. This is due to an increased
duration of force generated against the blocks and a greater contribution of total force impulse
from the rear leg [21,25–27]. What is more, an increase in force generation from the rear leg has
been associated with higher block clearing velocities in elite sprinters [7,14,18]. However, a
recent study [12] demonstrated that in the elongated start, despite a greater velocity of the center
of mass at block clearing, the performance at 5 m and 10 m is significantly worse compared to
the bunched start. It is known that in the elongated start, the duration of force application is
increased during the block phase [9]. Spending longer on the blocks increases the total run time
which then conflicts with the objective of a sprint. Instead, at 10 m the best performance results
were obtained from the medium start. Further, a number of studies [3,9,12,22–24] suggested
that the medium start creates the best balance between total force generated and the increased
time of force generation to obtain the best performance in the early acceleration phase.
When looking for the best front block/starting line and inter-block distances for an individ-
ual athlete, it would seem obvious that the block distances should be relative to the individual’s
body dimensions. However, very few studies considered the anteroposterior block distances in
relation to the individual body dimensions of the athlete [11,20,22]. A study conducted by
Dickinson [20] stated that the distance of the front block from the starting line should depend
on the height of the individual, and the distance of the rear block from the starting line on the
leg and the thigh lengths, irrespective of the type of the start used (bunched, medium, elon-
gated). Henry [22] investigated if the optimum block spacing is related to the individual leg
length by analyzing the interaction between four experimental inter-block distances (27.9,
40.6, 53.3 and 66.0 cm) and the individual’s leg length. Contrary to Dickinson, Henry
Starting block performance in sprinters
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collection and analysis, decision to publish, or
preparation of the manuscript. The funder provided
support in the form of salaries for an author [PM],
but did not have any additional role in the study
design, data collection and analysis, decision to
publish, or preparation of the manuscript. The
specific roles of this author are articulated in the
‘author contributions’ section.
Competing interests: We confirm that the
commercial affiliation (OMR Automotive) does not
alter our adherence to all PLOS ONE policies on
sharing data and materials.
concluded that leg length is not important in determining the best block spacing. A later study
conducted by Schot & Knutzen [11] went further in associating the athlete’s physical charac-
teristics with the anteroposterior block spacing. In this study, the authors stated that a medium
start could be achieved according to a calculation based on the individual’s leg length from the
greater trochanter to the lateral malleolus (60% of this length was used as the front block/start-
ing line distance and 45% for the inter-block spacing).
Anthropometry has been shown to play an important role in sports where body proportion-
ality differences may affect the biomechanics of movement and the resulting performance (e.g.
in running and in gymnastics) [28,29]. However, there is a lack of research addressing anthro-
pometric characteristics in the sprint start. Accordingly, research is needed to elucidate any
connection between the physical characteristics of the athlete, the block settings and the kine-
matic and kinetic parameters during the sprint start. In starting block performance, it is rea-
sonable to assume that body proportionality would influence optimal anteroposterior block
distances. The starting block performance involves a closed kinematic chain of movements
where the body extremities are in a fixed position and the only modifiable parameters are the
anteroposterior block distances. Thus, it can be argued that, in addition to body dimensions,
the proportion between the leg and trunk length may also affect the optimal anteroposterior
block distances. It is well known that individuals present different proportionality characteris-
tics between the leg and the trunk lengths and a way to assess such a proportionality is the Cor-
mic Index [30]. The Cormic Index expresses sitting height as a proportion of the total height,
representing a measure of the relative lengths of the trunk and lower limbs. Individuals are
classified as brachycormic, metricormic and macrocormic according to a Cormic Index
51%, 51–53%, or 53%, respectively [31].
Using instrumented starting blocks and high speed video cameras, the first aim of this
study was to test the effect of two different block settings in terms of anteroposterior block dis-
tances on the kinematic and kinetic parameters of well-trained sprinters. The two setting con-
ditions were the usual personal block setting used by the athlete and a block setting based on a
proportion of the individual’s leg length [11]. We hypothesized that an anthropometry-driven
intervention may improve the sprint start performance outcome. The second aim was to verify
whether an effect of the two block settings persists when the Cormic Index of the participants
is considered. The body proportionality characteristics of the sprinters may be of relevance in
a sprint start, a skill where the entire body is involved in a closed chain of movements. We
hypothesized that the Cormic Index of participants could influence the effect of a block setting
based on the leg length. It is expected that results of this work would help coaches and athletes
to improve sprint start performance using a quick anthropometry-driven procedure.
Materials and methods
Participants
The required sample was estimated “a priori” and calculated using GPower ver.3.1.9.2 [32].
Setting the type I error [SS3] at α = 0.05, the effect size at f = 0.25 and the correlation among
repeated measures at 0.6, the minimum sample size required for a within-between interaction
in a mixed-design ANOVA for having an 80% power (i.e., β = 0.20) was 36 subjects. In order
to comply with a possible ~15% dropout, forty-two participants were initially recruited. Partic-
ipants were well-trained skilled sprinters (20 women and 22 men) with a competitive athletic
career of at least 2 years in sprint running. Female and male participants’ age, height and body
mass (±SD) were 19.70 ± 2.23 and 19.36 ± 2.11 y, 165.4 ± 5.2 and 176.7 ± 5.9 cm, 55.6 ± 6.8
and 67.1 ± 9.8 kg, respectively. All sprinters were involved in regional and national level com-
petitions and trained at least 6 times a week for 2/3 hours per day. Their best time over 100 m
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ranged between 10.45 s and 11.30 s for men and between 11.45 s and 12.68 s for women.
According to the Cormic Index, the sprinters were brachycormic (n = 12), metricormic
(n = 19) and macrocormic (n = 11). The mean Cormic Index in the three groups was 50.62% ±
1.14, 52.48% ± 0.98 and 53.78% ± 0.51, respectively. All participants gave their written
informed consent to participate in the study, and the protocol was performed in accordance
with the Declaration of Helsinki. Ethics approval was obtained from the University of Verona
Institutional Review Board.
Experimental procedure
The sprint testing took place on an outdoor track (Olimpic Plast SWD surface, Olimpia Cost-
ruzioni, Forlı`, Italy) during the early competition phase of the outdoor season. One operator
(VC) attached ten retro-reflective passive flat markers (14 mm diameter) bilaterally over spe-
cific anatomical landmarks on the participant’s body (i.e., right [R] and left [L] acromion, R
and L femur greater trochanter, R and L femur lateral epicondyle, R and L fibula apex of lateral
malleolus, R and L 5th metatarsal).
Following a warm-up consisting of jogging, dynamic stretching and sprints of submaximal
intensity, all participants performed a total of 6 maximal-effort 10 m sprints using two differ-
ent starting conditions: 1) the athlete’s usual personal block setting (US), and 2) an anthro-
pometry-driven setting (AS). The order of the two starting conditions was randomized for
each athlete. In the AS condition, the start block positions were set according to a calculation
based on the individual’s leg length from the greater trochanter to lateral malleolus [11]; 60%
of this length was used as the front block/starting line distance and 45% as the inter-block
spacing. The anteroposterior block distances in both the US and AS conditions were measured
to the nearest 0.1 cm in the outdoor track with a fiberglass tape. The obliquity of the blocks
was that usually used by the participants and was the same in both conditions. Participants
used their own spiked shoes for sprint running. For all trials, each sprint was initiated by the
same experimenter (MP), who provided standard ‘on your marks’ and ‘set’ commands. The
experimenter then pressed a custom-designed trigger button to provide the auditory start sig-
nal through a sounder device. The rest period between trials was 5–7 minutes.
After an adequate rest period, the standing long jump test was used to measure lower
extremity strength. Participants stood behind a line marked on the ground with their feet
slightly apart. A two-foot take-off and landing was used, with swinging of the arms and bend-
ing of the knees to provide forward drive, the subject attempting to jump as far as possible.
The horizontal distance between the starting line and the back of the heel closest to the starting
line at landing was recorded via tape measure to the nearest 0.1 cm. Three trials were per-
formed (with adequate rest between trials) and the maximum distance was recorded. Although
the standing long jump performance is usually expressed in absolute terms as the overall dis-
tance covered, it has been suggested that the subject’s leg length can play a significant role in
the performance [33]. Accordingly, performance in the standing long jump test was expressed
relative to the leg length (SLJ-relative).
Data collection
Anthropometric data. Anthropometric data were taken by one operator (VC) using con-
ventional criteria and measuring procedures [34]. Body mass was assessed to the nearest 0.1 kg
using a certified electronic scale (Tanita electronic scale BWB-800 MA, Wunder SA.BI. Srl,
Milano, Italy). Standing height and sitting height were measured to the nearest 0.1 cm using a
Harpenden portable stadiometer (Holtain Ltd., Crymych, Pembs. UK). For the sitting height,
the subject was asked to sit on a flat stool of a known height. Measurement was taken with the
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subject sitting in a standard position. The sitting height was then obtained by subtracting the
height of the stool from the reading on the stadiometer. The lower limb length was measured
with a Harpenden anthropometer (Holtain Ltd., Crymych, Pembs. UK) as the distance
between the greater trochanter and the lateral malleolus (cm). Body circumferences were mea-
sured with a fiberglass tape at the mid-thigh and the calf. The Cormic Index was calculated for
each participant as sitting height (cm)/standing height (cm)100. The body mass index (BMI)
was also computed for each participant as body mass (kg)/standing height (m)2.
Kinetic and kinematic data.
Each trial was performed using a set of dynamometric start-
ing blocks equipped with a set of load cells (CU K5D and CU K1C models, GEFRAN SpA, Bre-
scia, Italy) enabling the measurement of the magnitude and direction of forces generated by the
sprinter during the starting block phase. The acquisition frequency was 1 kHz and the sensitiv-
ity was 0.01 N. These blocks respected all the features of those normally used in the track sprint
start, as well the output characteristics of similar blocks used in previous works [13,16]. There
were four monoaxial load cells installed on each block, which were used to determine the loads:
three cells were used to measure the vertical loads and one to measure the horizontal loads. The
force data were resolved into horizontal and vertical components for each foot (Fig 1). The
Fig 1. Example of resultant force curves of the front and rear blocks during a sprint start recorded by the instrumented starting blocks. RT, reaction
time; RBT, rear block time; FBT, front block time; TBT, total block time; RPF, rear peak force; FPF, front peak force.
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blocks were connected to a portable personal computer (SoftPLC, GEFRAN SpA, Brescia, Italy)
that stored data, and handled signal processing and parameter calculation. The dynamometric
starting blocks were developed at OMR Automotive (Officine Meccaniche Rezzatesi, Brescia,
Italy).
The reliability and validity tests were performed at the Department of Industrial Engineer-
ing, University of Padua, Italy. Both static and dynamic bench tests were carried out on a
mechanical bench equipped with two MTS 242 servo hydraulic actuators to calibrate the force
transducers. Several tests were performed in the horizontal and vertical directions on each part
of the apparatus in order to obtain the single axis calibration constants of the system. Static
and dynamic load tests with combined loading were also performed to validate the results of a
realistic usage, showing good results with low error: the difference between the maximum
force applied on the block and the measured force was lower than 1% [35]. After bench tests, a
series of in-vivo sprint starts were recorded during a training session with beginner, intermedi-
ate and expert athletes and comparison was made with a commercial force plate (Model 4060–
10, Bertec Columbus, OH, USA) output [35] included in a SMART DX-6000 motion capture
system (BTS Bioengineering, Quincy, MA, USA) after mounting the dynamometric blocks
over the force platform. The results showed that both vertical and horizontal forces measured
by the dynamometric starting blocks and the force plate were very similar to each other: hori-
zontal and vertical forces were able to follow the loads also in the region of rapid loading and
unloading with good accuracy. Regression coefficients were found to be on average R = 0.9946
for horizontal loads and R = 0.9978 for vertical loads. The dynamometric starting blocks appa-
ratus was portable and made resistant to splash water and could therefore be used outdoors.
These dynamometric starting blocks can easily be used on the track during training, giving
precise quantitative data which would usually only be available in a biomechanics laboratory
setting using sophisticated instruments in a controlled environment.
Two high-speed video cameras (Casio Exilim ex-zr 1000, Casio Europe Gmbh, Barcelona,
Spain) captured the movement of each athlete in two dimensions during the starting block
and acceleration phases (first and second stride lengths). One camera (Camera 1) was posi-
tioned for the front block side view of the participant and the other camera (Camera 2) for the
rear block side view of the participant. According to Bartlett [36], in order to limit the potential
technological errors in the filming set-up connected with the 2D videography (e.g. the parallax
errors due to visual distortion), the optical axis of each camera was lined directly perpendicular
to the sprinter’s movement plane. Furthermore, the optical axis of each camera was centred in
correspondence to an imaginary line perpendicular to the ground and passing through the hip
joint of the leg facing the camera at the “on your marks” position. Each camera was placed on
a tripod at a height of approximately 1 m and located at approximately 5 m from the partici-
pant. Each camera’s field of view provided a sagittal view of each sprinter for the first two full
strides. The position of the two cameras was standardized for all participants to ensure no
environmental changes during field testing (Fig 2). Each video was calibrated with a 50 cm
cube positioned to the rear of the blocks and defined by X the horizontal axis and Y the vertical
axis. Images of the starting block phase and acceleration phase were collected at a resolution of
1280 x 1024 pixels using a shutter speed of 1/1000 s and a sampling frequency of 200 Hz.
Three pairs of photocells (Polifemo Light Radio, Microgate SRL, Bolzano, Italy) based on a
radio impulse transmission system and a reflection system were used to measure the times at 5
m and 10 m in the sprint trials. The timing between the dynamometric starting blocks and the
photocells system was synchronized using the digital output available from the block control
system and connecting it to the available input for timing available in the Microgate unit.
Data analysis.
The kinematic and kinetic outputs were stored during the trials in a porta-
ble personal computer connected to the instrumented blocks and were then exported for
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further analysis. Raw data were filtered using a low-pass Butterworth filter (fourth order) with
a cutoff frequency of 120 Hz and analyzed using a custom program written in Matlab R2008a
(MathWorks, Natick, MA, USA).
Force signals were resolved into horizontal and vertical components using a coordinate sys-
tem affixed to the runway. The x-axis pointed forward along the running surface (horizontal
plane), the y-axis pointed vertically upwards. Force data were used to define the force onset
threshold (i.e., when the first derivative of the resultant force-time curve was greater than 500
Ns-1) and the force offset thresholds (i.e., when the resultant force was lower than 50 N). The
pushing phase was defined between the first instant of block start (i.e., corresponding to the
force onset threshold) to block clearance (i.e., corresponding to the force offset threshold on
the front block). The pushing phases of the front and the rear blocks were defined as the period
between the instant of the block start and the end of the respective sub-phases for each block.
The following temporal parameters were extracted for analysis from the instrumented blocks
data: the reaction time (RT), defined as the time from the auditory signal to the first force
onset threshold; the front block time (FBT), defined as the pushing time on the front block
sub-phase; the rear block time (RBT), defined as the pushing time on the rear block sub-phase
and the total time block (TBT), defined as the pushing time on the total pushing phase. The
following kinetic variables obtained from the instrumented blocks data during the pushing
phase were also measured: the front peak force (FPF), defined as the maximum resultant front
force value; the rear peak force (RPF), defined as the maximum resultant rear force value; the
horizontal and the vertical front peak force (H_FPF and V_FPF); the horizontal and the verti-
cal rear peak force (H_RPF and V_RPF); the average total force (ATF). The front force impulse
(FFimpulse), the rear force impulse (RFimpulse) and the total force impulse (Total Fimpulse) were
computed according to Otsuka and colleagues [15]. All the kinetic variables were normalized
to the body mass of the sprinters expressed in kg. In addition, the following variables were
computed: the ratio of horizontal to resultant force impulse of both legs (Ratio_front and
Ratio_rear) [37]; the horizontal block velocity (H_BV) measured as the sum between the hori-
zontal impulse on the front block plus the horizontal impulse on the rear block (both expressed
in Ns) divided by the body mass of the sprinter expressed in kg; the normalized average hori-
zontal external block power (NAHEP) calculated according to the procedures by Bezodis and
colleagues [2].
Fig 2. Experimental set-up.
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For each participant the video material of the 12 video clips (6 trials and 2 cameras) was
uploaded onto a PC and digitalized at full resolution with a zoom factor of 2.5 using freeware
motion-analysis software (Kinovea; version 0.8.15, available for download at: http://www.
kinovea.org). One operator (VC) blinded to condition (AS, US) manually digitalized the mark-
ers and quantified the joint angles and stride lengths at specific video frames on each video
(see details below). The analysis of the video material was carried out in two stages. Firstly,
each video clip was rewound frame by frame and frozen at the set position to directly estimate
the angles in the sagittal plane with the digital goniometer built into the Kinovea software. The
operator visually digitalized the markers through the “cross marker” function and placed the
digital goniometers. The videos from Camera 1 (i.e., with the front block side view) were used
to estimate the hip, knee and ankle joint angles on the front leg while the videos from Camera
2 (i.e., with the rear block side view) were used to measure the hip, knee and ankle joint angles
on the rear leg (Fig 3). The joint angles were measured to the nearest 1 degree. Secondly, in
order to measure the length of the first stride, each video clip from Camera 1 was stopped at
the instant of the first foot strike. Stride was estimated at the first frame of the video clip where
the sprinter’s foot made contact with the track surface. The length of the inferior side of the
cube positioned to the rear of the blocks in the frame was used as a reference to calibrate all
other line lengths. The “line drawing tool” function was used to assess the horizontal distance
between the front block and the toe of the rear foot at the first foot strike (first stride length
[SL1]). Thirdly, in order to measure the length of the second stride, each video clip from Cam-
era 2 was stopped at the instant of the second foot strike. The “line drawing tool” function was
used to assess the horizontal distance to the nearest 0.1 cm between the rear foot at the first toe
off and toe of the front foot at the first foot strike (second stride length [SL2]). SL1 and SL2
were normalized to leg length to account for differences among subjects and labelled as
NorSL1 and NorSL2, respectively.
In order to limit any technical errors involved in 2D videography as much as possible, the
procedure adopted to quantify the joint angles and stride lengths was repeated in three sepa-
rate sessions, with a minimum interval of 7 days between sessions and the mean value was
recorded only when the coefficient of variation was <0.05. Furthermore, the operator was
familiar with the use of high-speed video as a tool to quantify joint angles in sprint running
and in sprint starts. It has been noted that the markers, despite being properly positioned dur-
ing data collection, can move in relation to the skin throughout the range of motion [38].
Accordingly, in line with Bradshaw and colleagues [39], the operator paid close attention dur-
ing data analysis to this fact and visually adjusted for skin movement by only using the markers
as a guide.
Fig 3. Two-dimensional functional representation of the joint angles on the front (Panel A) and rear blocks (Panel B).
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In this study, errors (i.e. parallax and lens distortion errors) in the measurement of the first
and second stride lengths has to be taken into account. A typical error (%Error) was estimated
starting from the calibration cube (50 cm) positioned behind the blocks and then every 50 cm
until the end of the field of view. The %Error was calculated according to the following formula:
%Error ¼ jE were found for the sitting height and the lower limb length (F = 13.238 and F = 14.495, respec-
tively; P<0.001 for both). Post-hoc analysis with Bonferroni’s correction revealed that the bra-
chycormic group had significantly lower sitting height and lower limb length values in
comparison with both the metricormic (P = 0.002 for both) and the macrocormic (P<0.001
for both) groups (Table 1). The mean values (±SD) of the anteroposterior block distances and
the kinematic and kinetic data in the US and AS conditions in the whole sample and in the
three Cormic Index groups are reported in Table 2.
One-way ANOVA showed that in the US condition, the front block/starting line distance
was significantly different within the three groups (F = 9.500, P<0.001), but the inter-block
distance was not. Post-hoc analysis with Bonferroni’s correction revealed a significantly lower
front block/starting line distance in the brachycormic group vs. the metricormic group (-5.9
cm, P = 0.001) and macrocormic group (-6.1 cm, P = 0.002). One-way ANOVA also indicated
that all of the measured sprint start kinematic and kinetic variables were similar in the US con-
dition in the three Cormic Index groups with the exclusion of the TBT (F = 3.369, P = 0.045).
However, post-hoc analysis with Bonferroni’s correction, revealed no significant group-group
difference in the TBT.
A mixed-design ANOVA with three groups (brachycormic, metricormic, macrocormic)
and two block setting conditions (US and AS) with repeated measures on the second factor
showed a significant main effect of condition for both anteroposterior block distances and for
several kinematic and kinetic measurements (Tables 2 and 3).
The front block/starting line distance was significantly lower (-3.2 cm) in the AS vs. the US
whereas the inter-block distance was significantly greater (+9.2 cm). Furthermore, at the set
position, the rear hip and the rear knee joint angles were significantly greater in the AS vs. the
US (+6 and +5 degrees, respectively) while the opposite was found at the front hip and knee
joint angles (-4 and -3 degrees, respectively). The rear ankle joint angle was significantly lower
in the AS vs. the US (-2 degrees); no significant difference was found for the front ankle joint
angle. Results also showed that, during the pushing phase, several kinematic and kinetic vari-
ables were significantly greater in the AS vs. the US namely, the FBT (+0.02 s), the RPF (+1.63
N/kg), the H_RPF (+0.43 N/kg), the RFimpulse (+0.10 Ns/kg), the Total Fimpulse (+0.17 Ns/kg),
the Ratio_rear (+0.01), H_BV (+0.14 m/s), and the NAHEP (+0.03). No significant differences
were found for the other variables during the pushing phase. In the acceleration phase, the times
at 5 m and 10 m were significantly lower in the AS vs. the US (-0.05 and -0.04 s, respectively).
Table 1. Characteristics of the participants in the whole sample and the three Cormic Index groups. Data are means ± SD.
Whole sample
(n = 42)
Brachycormic
(n = 12)
Metricormic
(n = 19)
Macrocormic
(n = 11)
Age (y)
19.52 ± 2.14
19.75 ± 2.38
19.63 ± 2.41
19.09 ± 1.38
Sprinting experience (y)
4.76 ± 2.67
5.83 ± 3.04
3.95 ± 2.27
5.00 ± 2.65
Body mass (kg)
61.6 ± 10.2
59.6 ± 9.9
63.7 ± 10.4
60.3 ± 10.4
Height (cm)
171.3 ±7.9
167.6 ± 8.1
172. 4 ± 6.8
173.6 ± 8.8
BMI (kg/m2)
20.89 ± 2.19
21.10 ± 1.98
21.33 ± 2.44
19.89 ± 1.76
Sitting height (cm)
89.6 ± 5
84.9 ± 5
90.4 ± 3
93.33 ± 4.6
Lower limb length (cm)
81.8 ± 5
77.1 ± 5
82.5 ± 2.8
85.8 ± 4.2
Thigh circumference (cm)
49.04 ± 3.27
49.57 ± 3.97
49.32 ± 3.38
47.98 ± 2.09
Calf circumference (cm)
34.72 ± 2.56
34.73 ± 3.08
35.01 ± 2.41
34.22 ± 2.35
SLJ-relative
2.8 ± 0.2
2.7 ± 0.2
2.9 ± 0.3
2.7 ± 0.2
BMI, body mass index; SLJ-relative, performance in the standing long jump test expressed relative to the leg length.
, significantly different (P<0.05; Bonferroni’s post-hoc) vs. metricormic and macrocormic.
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Table 2. Block distances, and kinematic and kinetic data in the sprint start for the whole sample as well as for the three Cormic Index groups in their usual block
setting condition (US) and an anthropometry-driven block setting (AS) condition. Data are means ± SD.
Variable
Whole sample
(n = 42)
Brachycormic
(n = 12)
Metricormic
(n = 19)
Macrocormic
(n = 11)
Block distances
US
AS
US
AS
US
AS
US
AS
FB/SL distance (cm)
52.3 ± 4.8
49.1 ± 3.0
48.0 ± 3.6
46.3 ± 3.1
53. 9 ± 4.3
49.5 ± 1.7
54.2 ± 3.9
51.5 ± 2.5
I-B distance (cm)^
27.6 ± 2.4
36.8 ± 2.3
27.3 ± 2.5
34.7 ± 2.3#
27.2 ± 2.2
37.1 ± 1.3#
28.6 ± 2.5
38.6 ± 1.9#
Set position
Front hip (˚)
47 ± 6
43 ± 6
44 ± 6
41 ± 7
49 ± 4
43 ± 4
47 ± 9
44 ± 8
Rear hip (˚)
77 ± 8
84 ± 8
75 ± 8
80 ± 10
79 ± 7
85 ± 5
77 ± 11
85 ± 10
Front knee (˚)
92 ± 9
90 ± 8
94 ± 7
93 ± 5
92 ± 9
88 ± 8
92 ± 9
90 ± 9
Rear knee (˚)
112 ± 11
117 ± 11
115 ± 7
119 ±8
111 ± 12
115±11
112 ± 12
118 ± 15
Front ankle (˚)
92 ± 6
93 ± 7
94 ± 4
95 ± 3
92 ± 7
93 ± 7
92 ± 6
92 ± 8
Rear ankle (˚)
87 ± 6
85 ± 7
88 ± 5
86 ± 6
88 ± 6
86 ± 8
85 ± 6
84 ± 7
Pushing phase
RT (s)
0.185 ± 0.035
0.189 ± 0.035
0.195 ± 0.026
0.192 ± 0.029
0.184 ± 0.040
0.189 ± 0.032
0.175 ± 0.035
0.186 ± 0.047
FBT (s)
0.402 ± 0.041
0.416 ± 0.064
0.402 ± 0.051
0.402 ± 0.044
0.394 ± 0.036
0.419 ± 0.086
0.419 ± 0.036
0.424 ± 0.027
RBT (s)
0.211 ± 0.041
0.212 ± 0.041
0.220 ± 0.052
0.225 ± 0.059
0.203 ± 0.038
0.210 ± 0.035
0.215 ± 0.031
0.202 ± 0.025
TBT (s)
0.421 ± 0.047
0.427 ± 0.038
0.411 ± 0.035
0.415 ± 0.028
0.409 ± 0.035
0.424 ± 0.036
0.451 ± 0.066
0.448 ± 0.045
FPF (N/kg)
16.50 ± 2.27
16.60 ± 2.09
15.18 ± 2.16
15.31 ± 1.80
17.13 ± 2.20
17.16 ± 2.29
16.85 ± 2.04
17.03 ± 1.44
RPF (N/kg)^
11.44 ± 2.48
13.07 ± 3.37
10.83 ± 3.10
12.74 ± 3.10#
11.76 ± 2.03
14.08 ± 2.76#
11.55 ± 2.58
11.68 ± 4.24
H_FPF (N/kg)
6.02 ± 0.71
5.91 ± 0.65
5.65 ± 0.74
5.62 ± 0.67
6.25 ± 0.70
6.02 ± 0.71
6.02 ± 0.56
6.06 ± 0.45
V_FPF (N/kg)^
6.13 ± 0.92
6.12 ± 0.90
6.01 ± 0.98
5.91 ± 1.20
6.25 ± 0.87
5.99 ± 0.74
6.06 ± 0.98
6.58 ± 0.68#
H_RPF (N/kg)^
4.52 ± 1.09
4.95 ± 1.34
4.13 ± 1.17
4.58 ± 1.21#
4.70 ± 0.97
5.41 ± 1.00#
4.63 ± 1.20
4.55 ± 1.78
V_RPF (N/kg)^
3.78 ± 1.12
3.96 ± 1.20
3.36 ± 1.04
3.55 ± 1.07
3.76 ± 1.08
4.23 ± 1.00#
4.28 ± 1.16
3.94 ± 1.58
ATF (N/kg)
11.37 ± 1.19
11.55 ± 1.12
11.12 ± 1.58
11.22 ± 1.51
11.63 ± 0.91
11.83 ± 0.87
11.21 ± 1.14
11.44 ± 0.96
FFimpulse (Ns/kg)
3.48 ± 0.50
3.56 ± 0.55
3.32 ± 0.61
3.32 ± 0.62
3.52 ± 0.48
3.57 ± 0.58
3.60 ± 0.38
3.79 ± 0.33
RFimpulse (Ns/kg)^
1.29 ± 0.40
1.39 ± 0.42
1.25 ± 0.47
1.34 ± 0.40
1.25 ± 0.30
1.48 ± 0.34#
1.40 ± 0.47
1.31 ± 0.56
Total Fimpulse (Ns/kg)
4.76 ± 0.55
4.93 ± 0.56
4.56 ± 0.69
4.64 ± 0.65
4.75 ± 0.45
5.01 ± 0.54
5.01 ± 0.51
5.10 ± 0.38
Ratio_front
0.69 ± 0.05
0.69 ± 0.05
0.68 ± 0.05
0.69 ± 0.06
0.70 ± 0.05
0.70 ± 0.05
0.70 ± 0.05
0.67 ± 0.04
Ratio_rear
0.75 ± 0.05
0.76 ± 0.05
0.75 ± 0.06
0.76 ± 0.06
0.76 ± 0.05
0.77 ± 0.04
0.71 ± 0.03
0.73 ± 0.05
Ratio_total
0.71 ± 0.04
0.72 ± 0.04
0.71 ± 0.05
0.71 ± 0.05
0.72 ± 0.05
0.73 ± 0.04
0.70 ± 0.03
0.69 ± 0.04
H_BV (m/s)
3.36 ± 0.35
3.50 ± 0.39
3.18 ± 0.41
3.27 ± 0.36
3.40 ± 0.28
3.62 ± 0.38
3.48 ± 0.35
3.52 ± 0.34
NAHEP
0.47 ± 0.90
0.50 ± 0.10
0.44 ± 0.10
0.46 ± 0.09
0.49 ± 0.08
0.54 ± 0.10
0.46 ± 0.08
0.47 ± 0.08
Acceleration Phase
5 m (s)
1.34 ± 0.10
1.29 ± 0.09
1.36 ± 0.10
1.31 ± 0.12
1.33 ± 0.10
1.28 ± 0.09
1.33 ± 0.09
1.29 ± 0.06
10 m (s)
2.07 ± 0.13
2.03 ± 0.13
2.12 ± 0.14
2.09 ± 0.16
2.05 ± 0.15
2.00 ± 0.12
2.06 ± 0.10
2.01 ± 0.07
NorSL1
1.09 ± 0.11
1.12 ± 0.12
1.06 ± 0.09
1.12 ± 0.12
1.11 ± 0.14
1.14 ± 0.15
1.07 ± 0.09
1.07 ± 0.07
NorSL2
1.15 ± 0.14
1.19 ± 0.12
1.12 ± 0.15
1.16 ± 0.11
1.18 ± 0.15
1.12 ± 0.13
1.14 ± 0.10
1.15 ± 0.10
FB/SL, front block/starting line; I-B, inter-block; RT, reaction time; FBT, front block time; RBT, rear block time; TBT, total block time; FPF, front peak force; RPF, rear
peak force; H_FPF, horizontal front peak force; V_FPF, vertical front peak force; H_RPF, horizontal rear peak force; V_RPF, vertical rear peak force; ATF, average total
force; FFimpulse, front force impulse; RFimpulse, rear force impulse; Total Fimpulse, total force impulse; Ratio_front, Ratio of horizontal to resultant force impulse of front
leg; Ratio_rear, Ratio of horizontal to resultant force impulse of rear leg; NAHEP, normalized average horizontal external power; H_BV, horizontal block velocity; 5 m,
time at 5 meters; 10 m, time at 10 meters; NorSL1, first stride length normalized to leg length; NorSL2, second stride length normalized to leg length.
, statistically significant (P<0.05) difference between the AS and US conditions
^, statistically significant (P<0.05) difference of the AS vs. the US effect across the three Cormic Index groups
#, statistically significant difference between the AS and US conditions (post-hoc analysis with Bonferroni’s correction).
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NorSL1, and NorSL2 were significantly larger in the AS vs. the US (+0.03 and +0.04, respectively).
The effect size was large (>0.14) for all the significantly different variables except for FBT,
NorSL1, and NorSL2 where the effect size was medium (>0.10 effect size <0.12).
Table 3. Results of the mixed-design ANOVA to quantify the effect of condition and effect of group by condition interaction on block distances, and kinematic and
kinetic data.
Condition
Group by condition
Variable
F value
P value
ηp
2
F value
P value
ηp
2
Block distances
FB/SL distance
29.232
<0.001
0.428
2.308
0.113
0.106
I-B distance
545.112
<0.001
0.933
4.494
0.018
0.187
Set position
Front hip
46.494
<0.001
0.544
2.392
0.105
0.109
Rear hip
60.857
<0.001
0.609
1.520
0.231
0.072
Front knee
11.569
0.002
0.229
1.224
0.305
0.059
Rear knee
10.482
0.002
0.212
1.643
0.531
0.032
Front ankle
3.830
0.058
0.089
0.213
0.809
0.011
Rear ankle
7.485
0.009
0.161
0.150
0.861
0.008
Pushing phase
RT
0.925
0.342
0.023
0.621
0.543
0.031
FBT
4.261
0.046
0.098
1.201
0.312
0.058
RBT
0.031
0.862
0.001
2.661
0.083
0.120
TBT
1.647
0.207
0.041
1.770
0.184
0.083
FPF
0.356
0.554
0.009
0.066
0.937
0.003
RPF
25.821
<0.001
0.398
5.402
0.008
0.217
H_FPF
1.969
0.168
0.048
2.247
0.119
0.103
V_FPF
0.274
0.603
0.007
4.935
0.012
0.202
H_RPF
10.706
0.002
0.215
4.436
0.018
0.185
V_RPF
1.299
0.261
0.032
6.770
0.003
0.258
ATF
2.237
0.143
0.054
0.165
0.848
0.008
FFimpulse
1.950
0.171
0.048
0.815
0.450
0.040
RFimpulse
6.821
0.013
0.149
10.191
<0.001
0.343
Total Fimpulse
11.838
0.001
0.233
2.255
0.118
0.104
Ratio_front
1.321
0.257
0.033
3.241
0.050
0.143
Ratio_rear
9.244
0.004
0.192
0.829
0.444
0.041
Ratio_total
0.008
0.930
0.000
1.803
0.178
0.085
H_BV
11.946
0.001
0.234
3.107
0.056
0.137
NAHEP
6.815
0.013
0.149
1.446
0.248
0.069
Acceleration phase
5 m
27.802
<0.001
0.416
0.273
0.762
0.014
10 m
19.531
<0.001
0.334
0.219
0.804
0.011
NorSL1
12.041
0.001
0.236
3.002
0.061
0.133
NorSL2
12.732
0.001
0.246
1.241
0.300
0.060
US, usual sprinter’s block setting; AS, anthropometry-driven block setting; ηp
2, partial eta squared; FB/SL, front block/starting line; I-B, inter-block; RT, reaction time;
FBT, front block time; RBT, rear block time; TBT, total block time; FPF, front peak force; RPF, rear peak force; H_FPF, horizontal front peak force; V_FPF, vertical front
peak force; H_RPF, horizontal rear peak force; V_RPF, vertical rear peak force; ATF, average total force; FFimpulse, front force impulse; RFimpulse, rear force impulse;
Total Fimpulse, total force impulse; Ratio_front, Ratio of horizontal to resultant force impulse of front leg; Ratio_rear, Ratio of horizontal to resultant force impulse of rear
leg; NAHEP, normalized average horizontal external power; H_BV, horizontal block velocity; 5 m, time at 5 meters; 10 m, time at 10 meters; NorSL1, first stride length
normalized to leg length; NorSL2, second stride length normalized to leg length.
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As shown in Table 3, the results of the mixed-design ANOVA (group by condition)
revealed a significant main effect for condition (US and AS) by group (brachycormic, metri-
cormic and macrocormic) interaction for a number of variables. The effect size for all the sig-
nificantly different variables was large (>0.14). Post hoc analysis showed significantly greater
mean inter-block distance in the AS vs. the US in the brachycormic, metricormic and macro-
cormic groups by respectively +7.4 cm, +9.9 cm and +10.0 cm (P<0.001 for all); in the AS con-
dition, RPF was significantly greater in the brachycormic and the metricormic group (+1.91
N/kg, P = 0.001 and +2.32 N/kg, P<0.001, respectively), but not in the macrocormic group.
H_RPF was significantly greater for brachicormic group (+0.45 N/kg, P = 0.031) and the
metricormic group (+0.71 N/kg, P<0.001). In the AS V_RPF was significantly greater in the
metricormic group vs. the US (+0.47 N/kg, P = 0.001) and the V_FPF was significantly higher
in the macrocormic group (+0.52 N/kg, P = 0.013). RFimpulse was also significantly greater in
the metricormic group (+0.23 Ns/kg, P<0.001) in the AS vs. the US.
The estimation of a regression model for each performance variable using the difference
(Delta) in the anteroposterior block distances between the two conditions (US and AS) as pre-
dictors and the Delta in the performance variable as dependent variable, evidenced some sta-
tistically significant relationships which were summarized in Table 4.
Discussion
The first aim of this study was to investigate the effect of two different block setting conditions
(US and AS) on kinematic and kinetic performance outcomes during the sprint start in well-
trained sprinters focusing on block phases (set position and pushing-phase), and the early
acceleration phase (times at 5 m and 10 m, first and second stride lengths). Results showed
that an anthropometry-driven block setting condition (AS) based on the sprinter’s leg length
[11] is associated with several statistically significant changes in postural parameters at the set
position, as well as in kinetic and kinematic variables at the pushing and acceleration phases in
comparison with the sprinter’s usual block setting, leading to improved performance.
When using the US condition, which was based on the individual sprinter’s preferences, all
participants in the sample adopted an inter-block distance (27.6 ± 2.4 cm) classifiable as a
bunched start, suggesting that sprinters prefer a low anteroposterior distance between the
front and rear foot. This is in agreement with recent studies [15,18] showing that sprinters
with different ability levels chose an anteroposterior inter-block distance from 25 cm to 30 cm
Table 4. Multiple linear regression model estimated using the difference (Delta) in the anteroposterior block dis-
tances between the two conditions (US and AS) as predictors and the delta in the performance variable as the
dependent variable.
Delta FB/SL distance
Delta I-B distance
Adj. R2
Delta RPF
r = -0.35; P = 0.024
r = -0.26; P = 0.102
0.11
Delta H_RPF
r = -0.31; P = 0.047
r = -0.21; P = 0.175
0.07
Delta V_RPF
r = -0.37; P = 0.017
r = -0.19; P = 0.246
0.10
Delta RFimpulse
r = -0.34; P = 0.027
r = -0.03; P = 0.836
0.08
Delta Total Fimpulse
r = -0.50; P < 0.001
r = -0.10; P = 0.545
0.25
Delta Rear hip
r = 0.33; P = 0.036
r = 0.62; P < 0.001
0.36
US, usual sprinter’s block setting; AS, anthropometry-driven block setting; FB/SL, front block/starting line; I-B, inter-
block; Adj. R2, adjusted coefficient of determination; r, partial correlation coefficient; RPF, rear peak force; H_RPF,
horizontal rear peak force; V_RPF, vertical rear peak force; RFimpulse, rear force impulse; Total Fimpulse, total force
impulse.
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on the basis of their sensations. Nevertheless, the bunched start has been demonstrated to be
the least efficient from a biomechanical perspective because less force is exerted on the starting
blocks with a reduction in block velocity [12,21,42].
Several studies (2,7,11,14,18,21,22,25–27) highlighted that the increase in inter-block dis-
tance is associated with improved performance in several kinetic and kinematic variables
linked to the sprint start (i.e., a greater contribution of total force generation and force impulse
from the rear leg and higher block clearing velocities). On the other hand, in the AS condition,
which was based on the individual sprinter’s leg length, sprinters decreased the front block/
starting line distance (-6.56%) and increased the inter-block distance (+25.02%). Such varia-
tions in the anteroposterior block distances in the AS condition lead to a postural adaptation
at the set position resulting in a decrease in the front hip, front knee and rear ankle joint angles
and an increase in the rear hip and rear knee joint angles (Table 3). Based on the literature
[3,4,17,43,44], it is reasonable to assume that these postural changes at the set position in the
AS condition compared to the US condition could be associated with an improvement in per-
formance in the subsequent pushing phase such as greater RPF, H_RPF, RFI, Ratio_rear, Total
Fimpulse and NAHEP. In fact, the resulting joint angles (front/rear) in the AS condition were
similar to those reported in sprinters with ability levels ranging from national-level to world-
class [3,4,17]. Consistently, scientific data also showed that the front hip and knee as well as
the ankle joint angles were found to be smaller in faster than slower sprinters, allowing for the
stretch-reflex of the hip extensor and the soleus muscles and the greatest velocity when leaving
the blocks [43,44].
A recent study identified an important role of the rear hip joint angle to assist the genera-
tion of NAHEP during the block phase [3]. This is supported by results of regression analysis
in the current study showing that the difference between the US and AS conditions in the ante-
roposterior front/starting line and inter-block distances predicted the difference between the
two conditions in the rear hip angle (R2 = 0.39 for both distances). This suggests that the action
of the rear hip extensor can be enhanced by adjusting the anteroposterior block distances. This
finding is supported by a study by Slawinski and colleagues [12] reporting changes in the rear
and front hip angular velocity among three different inter-block distances (bunched, medium
and elongated). What is more, in the AS condition, the more flexed front hip, front knee and
rear ankle joint angles as well as the shorter front block/starting line distance led sprinters to
assume a lower crouched set position, (i.e., the centre of mass is closer to the ground). In the
literature it is reported that a crouched set position is able to generate greater H_ BV [7,18].
From a biomechanical point view, the ability to leave the blocks at a high velocity depends
on the horizontal force impulse on the blocks during the pushing phase [7]. In accordance
with classic mechanical physics, impulse is equal to the product of force and time. Conse-
quently, a higher block velocity could either be due to an increase in the net propulsion force
generated or to the push duration. In our sample, no significant difference in the duration of
the applied force (TBT) was found between the two starting conditions, thus the increase asso-
ciated with the AS in H_BV (+4%) was due to an increased force production, not to an
increase in the duration of the push against the blocks. The H_BV is a commonly measured
variable when evaluating sprint start performance [6,10,11,22]. However, we agree with the
statement of Bezodis and colleagues [2] that the NAHEP best describes the sprint start perfor-
mance because it summarizes in a single parameter how much a sprinter is able to increase
their velocity and the amount of time duration to achieve this. In our study, results showed a
greater NAHEP (+6%) in the AS vs. the US indicating that anthropometry-driven anteropos-
terior block distances may assist sprinters in translating their centre of mass in the horizontal
direction.
Starting block performance in sprinters
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In line with previous studies underlining the importance of the rear leg [1,3,7,16,18] in the
sprint start, another important result in the current study was the significant increase observed
in the AS condition for several kinetic parameters in the rear block such as the RPF, RFimpulse
and the Ratio_rear by respectively +12.47%, +7.19%, and +1.32%. It is likely that the greater
force generated by the rear leg allowed sprinters to achieve significantly greater H_BV.
According to Slawinski et al. [7], the ability of faster sprinters to leave the blocks at a higher
velocity depends on the rear block total force and the rate of force development.
When considering the peak force components on the front and rear blocks, we found sig-
nificantly higher horizontal and vertical peak forces at the rear block in the AS vs. the US
(+8.68% and +4.54%, respectively. However, the difference in the mean value on peak force
between the front and the rear blocks was -3.53 N/kg (-21.26%) and -5.06 N/kg (-30.66%) in
the AS and US conditions, respectively. A similar pattern was observed for the Total Fimpulse
which was -2.17 Ns/kg (-60.95%) and -2.19 Ns/kg (-62.93%) in the AS and US conditions,
respectively. The finding of a smaller force difference between the rear and front legs in the AS
condition suggests that sprinters are able to get a more balanced force generation between the
rear and front legs. Although results showed that sprinters generated higher FPF than RPF in
both conditions, in the AS condition the RPF was greater than in the US condition. Recent
studies have reported that the generation of greater forces against the rear block was the stron-
gest predictor of sprint start performance, suggesting that forces at the rear block need to be
maximised to increase performance [16,19].
In our study, the results of the regression analysis showed that the difference in the front
block/starting line distance between the AS and US conditions is able to predict the difference
between the two conditions in RPF, the horizontal and vertical components of RPF, as well as
RFI (Table 4). These findings suggest that the front block/starting line distance is an important
predictor of the ability to generate greater rear block force. On the other hand, results of the
present study showed that the difference between the AS and US conditions in the front block/
starting line distance is not able to predict the difference between the two conditions in the
Ratio_rear. This suggests that the reduction of the front block/starting line distance does not
increase the ability to direct the forces in a more horizontal direction. This is in line with a
recent study [16] highlighting that the ratio of horizontal to resultant impulse against the rear
block was less important in predicting sprint start performance because of its low correlation
with block phase performance (standardized regression coefficient = 0.010).
The changes of the lower limb joint angles at the set position showed in the AS condition
and subsequent improvement in several kinetic and kinematic parameters measured in the
pushing phase, might explain the significant differences between the two conditions in the
acceleration phase. In fact, several studies underpinned the importance of the block phase in
the subsequent sprinting times at 5 m and 10 m as well as in the first two step lengths
[6,7,9,12]. In our sample, the AS condition was associated with a decrease in the times at 5 m
and 10 m (-3.59% and -2.32%, respectively) and an increase of the first and second stride
lengths (+2.67% and +3,36%, respectively) vs. the US condition. This is in agreement with pre-
vious studies showing that the contributions of the hip and ankle joints to force production
play an important role in the acceleration phase of the sprint start [3,6,15,45–47].
The findings of our study expand on previous findings by showing that a number of pos-
tural, kinematic and kinetic parameters of the sprint start change when setting the starting
blocks according to anthropometry causing sprinters to adopt a medium start. In addition, the
findings highlight the importance of the front/starting line distance as predictor of certain
kinetic and kinematic variables. However, further studies are needed to better understand how
the kinetic and kinematic parameters are related to this block distance. Interestingly enough,
modifying the anteroposterior block distances, allowed for an immediate improvement of
Starting block performance in sprinters
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performance in the sprinters with no period of familiarization. However, achieving an optimal
automatized movement is a long-term process. Accordingly, further studies should investigate
the retention of improvement of performance after at least 24/48 hours.
The second aim of the present study was to assess whether an interaction exists between the
two block setting conditions (US and AS) and the body proportionality of the sprinters (bra-
chycormic, metricormic and macrocormic) affecting the kinematic and kinetic parameters of
sprint start. In other words, the present study tested if the kinematic and kinetic parameters of
the sprint start were different between the US and AS conditions depending on the body pro-
portionality of the sprinters.
It is important to underline that the three Cormic Index groups were similar in age, sprint-
ing experience, several anthropometric parameters (e.g. BMI, lower limb circumferences),
SLJ-relative (Table 1). All of the measured kinematic and kinetic parameters in the US condi-
tion were similar as well (Table 2). This suggests that the three groups were largely comparable.
In the US condition the three groups adopted a similar inter-block distance whereas the front
block/starting line distance was lower in the metricormic and macrocormic groups in compar-
ison with the brachycormic group (Table 2). Actually, the front block/starting line distance
increased with the mean trunk length (sitting height) of the sprinters (Tables 1 and 2). Taken
together, these findings suggest that body proportionality has some effect on the front block/
starting line distance when the sprinter adopts a block setting on the basis of personal
sensation.
When considering the interaction effect between the three Cormic Index groups over the
two block setting conditions, a significant effect was found for the inter-block distance but not
for the front block/starting line distance. This may be explained by the following: first, the
finding of a significantly lower limb length in the brachycormic vs. metricormic and macro-
cormic groups in the presence of similar stature (Table 1); second, the lower limb length was
the parameter used to calculate the anteroposterior block distances in the AS condition; third,
in the US condition the three Cormic Index groups chose similar inter-block distances, while
the front block/starting line distance increased together with the trunk length (Tables 2 and 3).
Intriguingly, it was found that sprinters modified the joint angles at the set position in the US
and AS conditions irrespective of their body proportionality. In fact, the changes in the front
and rear lower limb joint angles were consistent across the brachycormic, metricormic and
macrocormic groups.
A statistically significant group by condition interaction was also found in a number of per-
formance outcomes (Tables 2 and 3). In particular, the metricormic group showed an increase
in the AS condition for the RPF, (+16.52%), the H_RPF and the V_RPF (+13.12% and 11.11%,
respectively), the RFimpulse, (+15.54%) (all significant at P<0.05); a significant increase was
also found in the brachycormic group for the RPF (+14.99%) and the H_RPF (+9.82%); a sig-
nificant increase in the V_FPF in the macrocormic group (+7.90%). These findings show that
the AS condition is able to drive important improvements in kinetic variables measured in the
pushing phase only for the metricormic and in the brachycormic groups. These findings are
not attributable to differences in lower limbs muscle mass or strength, because thigh and calf
girth as well as performance in the standing long jump expressed relative to the leg length were
similar in the three Cormic Index groups (Table 1). Taken together, the above findings suggest
that the anthropometry-driven condition used in this study is not best suited for macrocormic
sprinters, while the sprinters with an intermediate proportionality between the trunk and the
lower limbs (i.e. the metricormic sprinters) are those who are more likely to receive extensive
benefits in the kinetics of the rear leg from a block setting based on their lower limb length.
A limitation of this study is the relatively small size of the three Cormic Index groups, mak-
ing it difficult to generalize our findings to performance outcomes associated with trunk and
Starting block performance in sprinters
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lower limb proportionality. Moreover, 2D kinematic measurement was used, which is well
suited to data acquisition in a number of settings [48]. However, accurate analysis of joint
angles and the two first stride lengths would have benefit from 3D acquisition [49]. Accord-
ingly, the values of the stride lengths and joint angles presented herein should be interpreted
with caution as per the presence of the parallax error and the lens distortion error which have
occurred in our set-up using a 2D kinematic measurement. Despite these limitations and uti-
lizing instrumented starting blocks, the current data provides important biomechanical evi-
dence to further understand the influence of the set position on sprint start performance and
on the importance of the rear leg action.
Taken together, the findings presented in this study show that a block setting position, cal-
culated on the basis of a proportion of the leg length allows sprinters to improve performance
in both the block phase and early acceleration, thereby confirming the hypothesis that consid-
ering the athlete’s body dimensions when calculating block setting is beneficial to the sprint
start. In view of these results, future research is needed to adjust the anthropometry-driven
condition investigated in this study in relation to the body proportionality of the sprinter to
find the optimal anteroposterior block distances.
Conclusion
In conclusion, the current study confirmed the role played by an anthropometry-driven block
setting on the starting block performance and underpins the relevance of body proportionality
in calculating personalized anteroposterior block distances. The results obtained in the present
study provide new relevant information that may represent the starting point for future studies
aimed to develop new guidelines for helping coaches and athletes to identify the ideal personal
anteroposterior block distances. From a practical standpoint, the results of this study should
encourage coaches to pay more attention to the anthropometric characteristics of their athletes
when searching for a more effective block start position. It would seem that a good starting
point for further exploration of this field of research would be the inclusion of the Cormic
Index in the identification of an individual block settings. Moreover, current findings showed
that a key kinetic and kinematic determinant of the rear block performance is the front block/
starting line distance. Therefore, further research is required to elucidate the effect of this dis-
tance with kinetic and kinematic parameters to more completely understand its influence on
sprint start performance.
Supporting information
S1 File. Database.
(XLSX)
Acknowledgments
The authors thank all the participants for kind cooperation. This study was supported by a
grant from the University of Verona (Joint Projects 2009) to CM.
Author Contributions
Conceptualization: Valentina Cavedon, Chiara Milanese.
Data curation: Valentina Cavedon, Marco Sandri, Mariola Pirlo, Nicola Petrone, Chiara
Milanese.
Formal analysis: Marco Sandri.
Starting block performance in sprinters
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Investigation: Mariola Pirlo.
Supervision: Valentina Cavedon, Marco Sandri, Carlo Zancanaro, Chiara Milanese.
Validation: Valentina Cavedon, Nicola Petrone, Carlo Zancanaro, Chiara Milanese.
Writing – original draft: Valentina Cavedon, Chiara Milanese.
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Anthropometry-driven block setting improves starting block performance in sprinters.
Cavedon, Valentina,Sandri, Marco,Pirlo, Mariola,Petrone, Nicola,Zancanaro, Carlo,Milanese, Chiara