RESEARCH ARTICLE
Similarities and differences among half-
marathon runners according to their
performance level
Ana Ogueta-Alday1*, Juan Carlos Morante1, Josue´ Go´mez-Molina2, Juan Garcı´a-Lo´pez1,3
1 Department of Physical Education and Sports, Institute of Biomedicine (IBIOMED), Faculty of Physical
Activity and Sports Sciences (FCAFD), University of Leo´n, Leo´n, Spain, 2 Department of Physical Education
and Sports, Faculty of Education and Sport, University of the Basque Country, UPV/EHU, Spain, 3 High
Sport Performance Centre of Leo´n (CAR-Leo´n), Spanish Council of Sports (CSD), Leo´n, Spain
* aogua@unileon.es
Abstract
This study aimed to identify the similarities and differences among half-marathon runners in
relation to their performance level. Forty-eight male runners were classified into 4 groups
according to their performance level in a half-marathon (min): Group 1 (n = 11, < 70 min),
Group 2 (n = 13, < 80 min), Group 3 (n = 13, < 90 min), Group 4 (n = 11, < 105 min). In two
separate sessions, training-related, anthropometric, physiological, foot strike pattern and
spatio-temporal variables were recorded. Significant differences (p<0.05) between groups
(ES = 0.55–3.16) and correlations with performance were obtained (r = 0.34–0.92) in train-
ing-related (experience and running distance per week), anthropometric (mass, body mass
index and sum of 6 skinfolds), physiological (VO2max, RCT and running economy), foot strike
pattern and spatio-temporal variables (contact time, step rate and length). At standardized
submaximal speeds (11, 13 and 15 kmh-1), no significant differences between groups were
observed in step rate and length, neither in contact time when foot strike pattern was taken
into account. In conclusion, apart from training-related, anthropometric and physiological
variables, foot strike pattern and step length were the only biomechanical variables sensitive
to half-marathon performance, which are essential to achieve high running speeds. How-
ever, when foot strike pattern and running speeds were controlled (submaximal test), the
spatio-temporal variables were similar. This indicates that foot strike pattern and running
speed are responsible for spatio-temporal differences among runners of different perfor-
mance level.
Introduction
The participation in long-distance running events has grown significantly in the last decade.
In races between 5 km and the marathon, the total number of finishers in the USA in 2015 was
about 17,114,800 runners [1]. The half-marathon was the favorite distance for male runners
between 25 and 44 years of age, and finishers’ average time was around 123 min [1]. This
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January 24, 2018
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OPEN ACCESS
Citation: Ogueta-Alday A, Morante JC, Go´mez-
Molina J, Garcı´a-Lo´pez J (2018) Similarities and
differences among half-marathon runners
according to their performance level. PLoS ONE 13
(1): e0191688. https://doi.org/10.1371/journal.
pone.0191688
Editor: Alena Grabowski, University of Colorado
Boulder, UNITED STATES
Received: September 11, 2017
Accepted: January 9, 2018
Published: January 24, 2018
Copyright: © 2018 Ogueta-Alday 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 by the Spanish
Sports Council (CSD) under the project 157/
UPB10/12, by a grant of the High Sport
Performance Centre of Leo´n (CAR-Leo´n); and by
the Basque Country Government, under a
predoctoral grant number reference
PRE_2013_1_1109 (J.G.). The funders had no role
in study design, data collection and analysis,
indicates that not only elite runners take part in these events, but so do amateur runners. It is
important to understand the demands and characteristics of all types of runners (i.e. recrea-
tional, moderately-trained, highly-trained), and the scientific community is interested in
addressing the discipline of running from different performance-related perspectives (e.g.
anthropometry, training, physiology and biomechanics).
The relationship between physiological variables and running performance has been deeply
investigated. A high VO2max, respiratory compensation threshold and a good running econ-
omy are highly related to performance in long-distance races [2]. Some anthropometric vari-
ables are also important for good running performance, as they can affect the aforementioned
physiological variables [3–5]. A lower body mass [4,5], body mass index [3,5] and sum of skin-
folds [5] implies a lower muscular effort to support and accelerate the body and the legs,
requiring less energy expenditure [4], lower heat production and higher heat dissipation [6],
and therefore allowing a better long-distance running performance.
However, the influence of some biomechanical variables on long-distance running perfor-
mance is quite unclear. Some studies identified the foot strike pattern (i.e. midfoot/forefoot vs
rearfoot) as a key factor of performance, and found a higher percentage of midfoot/forefoot
runners in the top place finishers of high-level half-marathon and marathon races [7,8]. In
contrast, in low-level races this tendency was not observed [9]. On the other hand, some stud-
ies have associated a shorter contact time with better performance or running economy
[7,10,11], while others have not [10,12]. These discrepancies could be due to the dependence
of contact time on both running speed and foot strike pattern [13]. In regards to step rate and
length, some studies observed a higher step rate in highly-trained runners compared to well-
trained and non-trained ones [14,15]. This seems to be a natural adaptation to obtain an ener-
getically more optimal step rate [10]. However, at similar running speeds, step rate and length
have not been associated with performance [12].
Therefore, the main purpose of the present study was to analyze the similarities and differ-
ences between training-related, anthropometric, physiological, foot strike pattern and spatio-
temporal variables in half-marathon trained runners, according to their performance level.
The hypothesis was that there would be differences among runners of different level in train-
ing-related, anthropometric and physiological variables, as well as in foot strike pattern, but
not in spatio-temporal variables if running speed and foot strike patterns are controlled.
Materials and methods
Experimental design
The study was approved by the University of Leo´n Ethics Committee. Forty-eight half-mara-
thon runners with different performance level (from 63 to 101 min) were analyzed. Runners
reported to the laboratory on two different days, with an interval of at least one week. On the
first day, training-related and anthropometric characteristics were recorded, and an incremen-
tal treadmill test was performed. On the second day, a submaximal test at different running
speeds was performed. The submaximal running speeds were set at 11, 13 and 15 kmh-1 to
assure that low- and high-level runners were between 60–90% of VO2max in one of these
speeds, and therefore obtain their running economy [16]. During both tests, foot strike pat-
tern, physiological (VO2, RER and HR) and spatio-temporal variables (i.e. contact and flight
times, step rate and length) were simultaneously registered.
Subjects
Runners were recruited from national and local track and field clubs, as well as from recrea-
tional running training groups. Finally, forty-eight long-distance male runners participated
Comparison of different level runners
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decision to publish, or preparation of the
manuscript.
Competing interests: The authors have declared
that no competing interests exist.
according to the following inclusion criteria: 1- runners had to be Caucasian from 20 to 50
years-old, 2- they must have participated in at least one self-selected half-marathon during the
six-week period prior to the study, 3- their performance level must be better than 105 min,
determined by the “chip time” (time from the start to the finish line after 21,097 m). Runners
were divided into four groups according to their performance level: Group 1 (n = 11, < 70
min), Group 2 (n = 13, between 70 and < 80 min), Group 3 (n = 13, between 80 and < 90
min) and Group 4 (n = 11, between 90 and < 105 min). Additionally, following the criteria of
Hasegawa et al. [8], runners were divided into two groups according to their foot strike pat-
tern: rearfoot or midfoot/forefoot strikers, in order to 1- analyze the influence of foot strike
pattern in long-distance running performance and 2- avoid the influence of foot strike pattern
on spatio-temporal parameters. Written consent was obtained from the subjects and the study
was approved by the University Ethics Committee.
Procedures
All testing sessions were conducted at the same time of day (between 10 a.m. and 1 p.m.)
under similar environmental conditions (~ 800 m altitude, 20–25 ˚C, 20–35% relative humid-
ity). During these days, a correct intake of carbohydrate (~ 400 gr) was recommended [17].
Participants fasted for 2 h before the submaximal test and during the tests, but they were able
to drink water ad libitum to avoid dehydration. Both running tests were preceded by a stan-
dardized warm-up (treadmill running at 10–12 kmh-1 for 10 min followed by 5 min of free
stretching). All runners wore the same running shoes in every testing session (250–300 gr
weight for each shoe) to prevent this variable from affecting running economy [18].
Running tests were performed on a treadmill (HP Cosmos Pulsar, HP Cosmos Sports &
Medical GMBH, Nussdorf-Traunstein, Germany) with a 1% slope in an attempt to mimic the
effects of air resistance on the metabolic cost of flat outdoor running [19]. Two fans with a
wind speed between 4–8 kmh-1 (according to the preference of each runner) were placed
around the treadmill (~ 50–100 cm) to cool the subjects during running [17]. Respiratory
gases (Medisoft Ergocard, Medisoft Group, Sorinnes, Belgium) and heart rate (HR) (Polar
Team, Polar Electro Oy, Kempele, Finland) were monitored throughout the tests. Running
spatio-temporal parameters (i.e. contact and flight times, step rate and length) were recorded
with a contact laser platform installed in the treadmill (SportJUMP System PRO1, DSD Inc.,
Leo´n, Spain) and connected to a specific software (Sport-Bio Running, DSD Inc., Leo´n,
Spain). The spatio-temporal variables computed from this system were previously validated
[20]. A minimum recording time of 20 s was set at each running speed to obtain at least 32
consecutive steps and thus reduce the effect of intra-individual step variability [13]. Runners’
foot strike pattern was determined using a high-speed video camera (240 Hz) (Casio Exilim
Pro EX-F1, CASIO Europe GMBH, Norderstedt, Germany) placed on the right side of the
treadmill (~ 1 m), perpendicular to the sagittal plane at a height of 40 cm from the ground. All
runners were analyzed by the same observer, who identified their foot strike pattern (i.e. rear-
foot or midfoot/forefoot) at their competitive running speed during the incremental treadmill
test. This running speed was calculated from the time needed to complete the half-marathon
(e.g. 18 kmh-1 for a runner with a performance of 70 min).
Anthropometry
Subject’s body mass, height and 6 skinfold measurements (triceps, subscapular, supra-iliac,
abdominal, anterior thigh and medial calf) were recorded using standard equipment (HSB-BI,
British Indicators LTD, West Sussex, UK). The total leg and lower leg (shank) lengths were
also obtained (Harpender anthropometer, CMS instruments, London, UK), taking into
Comparison of different level runners
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account the distance from the floor to the femur (greater trochanter) and to the tibia (superior
point on the lateral border of the head of the tibia), respectively. Maximal thigh and shank cir-
cumferences as well as minimum ankle circumference were measured (Holtain LTD, Cry-
mych, UK). All measurements were made by the same researcher following the international
guidelines for anthropometry [21] and the criteria of previous studies [17].
Incremental test
The test started at 6 kmh-1 and treadmill speed was increased 1 kmh-1 every 1-min until voli-
tional exhaustion. VO2max and HRmax were recorded as the highest values obtained in the 30 s
before exhaustion [13]. The ventilatory threshold (VT) and the respiratory compensation
threshold (RCT) were identified according to the criteria of Davis [22]. Spatio-temporal
parameters were recorded in the last 20 s of each running speed, from 10 kmh-1 (i.e. when
runners started to have flight time) until peak speed [13].
Submaximal test
Subjects performed 6-min running at 11, 13 and 15 kmh-1 with a 5-min rest in between. VO2
and HR were continuously recorded during the test, considering the average of the last 3-min
period of each set as representative data [17]. Running economy was determined as the VO2
cost at a given running speed, expressed in mlkg-1km-1 and mlkg-0.75km-1. This last unit was
chosen to avoid the possible influence of body mass in running economy [23]. The best value
between 60–90% of VO2max was chosen as running economy representative value [16]. Spatio-
temporal parameters were recorded for a minimum of 20 s during the 5th minute of each set.
Statistical analysis
The results are expressed as mean ± SD. The Kolmogorov-Smirnov test was applied to ensure
a Gaussian distribution of all results. A one-way Analysis of Variance (ANOVA) was used to
analyze the differences between the four groups of runners. Additionally, the Analysis of
Covariance (ANCOVA) was used to analyze the differences between the four groups of run-
ners in biomechanical variables, taking into account as covariates runners’ foot strike pattern
(i.e. midfoot/forefoot and rearfoot) and running speeds where physiological variables were
obtained (i.e. peak, RCT and VT speeds). When a significant F value was found, the Newman-
Keuls post hoc analysis was used to establish statistical differences between means. Effect sizes
(ES) (Cohen’s d) were also calculated [20]. The magnitude of the difference was considered to
be trivial (ES < 0.2), small (0.2  ES < 0.5), moderate (0.5  ES < 0.8) and large (ES  0.8).
Pearson correlation coefficient (r) was used to obtain relationships between variables. SPSS
+ version 17.0 statistical software (SPSS, Inc., Chicago, IL, USA) was used. Values of p<0.05
were considered statistically significant.
Results
Anthropometry, training-related and physiological parameters
The four groups of runners (n = 48) were not different in age (32.0 ± 7.0 years), height
(176.0 ± 5.0 m), total leg length (90.0 ± 4.0 cm), lower leg (shank) length (44.0 ± 2.0 cm), and
maximal thigh, shank and ankle circumferences (51.1 ± 3.1, 36.0 ± 1.0 and 22.0 ± 1.0 cm,
respectively). Table 1 shows that running experience (ES = 1.62), weekly training volume
(ES = 1.65), body mass (ES = 0.55), body mass index (ES = 1.42), sum of skinfolds (ES = 2.08),
peak speed (ES = 3.27), VO2max expressed in mlkg-1min-1 (ES = 1.31) and mlkg-0.75min-1
(ES = 1.24), speed in both VT (ES = 1.80) and RCT (ES = 3.16), and running economy
Comparison of different level runners
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expressed in mlkg-1km-1 (ES = 1.06) and mlkg-0.75km-1 (ES = 1.12) had a significant effect
on performance level (p<0.01), and were related to running performance (p<0.05) (Table 1).
Foot strike pattern
Fig 1 shows that performance level had a moderate effect on foot strike pattern distribution
among groups (ES = 0.72, p<0.01). The percentage of midfoot/forefoot strikers was higher in
Group 1 with respect to Groups 2, 3 and 4 (73, 31, 15 and 9%, respectively).
Spatio-temporal parameters during the incremental test (comparison at
the same relative physiological intensities)
Table 2 shows that, during the incremental test at different running speeds (i.e. peak, RCT and
VT speeds), there were significant differences between groups of runners in contact time and step
length (p<0.01), but not in step rate. Besides, significant correlations (p<0.05) between half-mar-
athon performance (i.e. time spent) and contact time (r  0.50), step rate (r  -0.38) and length
(r  -0.62) were observed. These differences and correlations disappeared taking into account the
runners’ foot strike pattern and the running speed where these variables were obtained.
Spatio-temporal parameters during the submaximal test (comparison at
standardized running speeds)
Table 3 shows that, at standardized submaximal speeds (11, 13 and 15 kmh-1), no significant
differences between groups were observed in step rate and length. On the contrary, contact
Table 1. Mean (± SD) training-related, anthropometric and physiological variables of the different groups of runners. Correlation (r) with running performance
(time to complete a half-marathon).
G1
(n = 11)
G2
(n = 13)
G3
(n = 13)
G4
(n = 11)
r
Running performance (min)
66.0±2.3†#
73.0±3.4†#
85.2±2.5#
96.0±3.2
---
Running experience (years)
16.5±5.6†#
11.0±3.7†#
4.5±3.3
3.6±4.2
-0.75
Training volume (kmweek-1)
118.6±30.3†#
85.8±23.3†#
51.7±21.3
43.3±15.4
-0.80
Mass (kg)
66.5±5.3†#
68.1±5.0†
73.0±5.6
73.0±8.9
0.45
Body mass index (kgm-2)
21.4±1.4†#
21.1±0.9†#
23.3±1.3
24.1±2.4
0.64
∑ of 6 skinfolds (mm)
37.4±9.1†#
40.4±6.3†#
58.6±13.8#
70.3±15.9
0.78
Peak speed (kmh-1)
22.1±0.8†#
20.6±1.0†#
18.8±0.4#
17.4±0.9
-0.92
VO2max (mlkg-1min-1)
69.2±5.0†#
64.4±5.7†#
56.9±4.5
55.9±6.2
-0.76
VO2max (mlkg-0.75min-1)
197.4±13.8†#
184.9±14.1†#
166.1±13.2
163.1±16.0
-0.67
RCT speed (kmh-1)
18.6±1.2†#
17.4±1.2†#
15.5±0.8#
13.8±1.1
-0.92
RCT—% VO2max
87.8±4.8
90.2±3.7
87.6±5.0
84.4±5.3
-0.33
VT speed (kmh-1)
12.7±1.2†#
11.8±1.3†#
10.2±0.5
9.8±1.3
-0.76
VT—% VO2max
58.9±4.5
61.1±7.1
59.7±6.4
62.7±7.4
0.11
RE (mlkg-1km-1)
196.1±18.8#
205.5±12.1
205.2±12.9
219.5±18.4
0.39
RE (mlkg-0.75km-1)
559.7±55.1#
590.0±35.6
600.0±41.8
640.4±52.8
0.50
RER (VCO2VO2
-1)
0.79±05#
0.83±0.06
0.84±0.06
0.89±0.05
0.51
Note: G1, G2, G3, G4, groups of runners of different performance level (< 70, < 80, < 90 and < 105 min, respectively). ∑ of 6 skinfolds, sum of six skinfolds. VO2max,
maximun oxygen uptake. RCT, respiratory compensation threshold. VT, ventilatory threshold. RE, running economy. RER, Respiratory Exchange Ratio.
, significant differences with Group 2.
†, significant differences with Group 3.
#, significant differences with Group 4.
r, significant correlations (p<0.05) in bold type.
https://doi.org/10.1371/journal.pone.0191688.t001
Comparison of different level runners
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time was significantly shorter (p<0.01) in higher level runners (ES = 0.72, 0.74 and 0.88,
respectively). These differences disappeared when the runners’ foot strike pattern was taken
into account.
Discussion
The main outcome of this study was that there were no differences in spatio-temporal parame-
ters (i.e. contact time, step rate and length) among half-marathon runners of different perfor-
mance level (from 63 to 101 min) when the same foot strike pattern is used and they are
running at equal submaximal speed. However, high-level runners’ group exhibited the highest
percentage of midfoot/forefoot strikers (~ 73%) compared to the other three groups (~
9–31%) (Fig 1), and therefore they showed lower contact times than rearfoot strikers (i.e. low-
level runners).
Anthropometry, training-related and physiological parameters
Strong relationships between performance and training-related variables were found
(Table 1). This is in line with previous studies that considered the excellence in long-distance
running as the combination of genetic, environmental (i.e. socio-demographic) and training-
related factors (i.e. deliberate practice theory) [24]. In the present study, in line with previous
ones [3,4,5], higher level runners were lighter, had lower body mass index and lower fat/sum
of skinfolds. In contrast, linear anthropometric variables (i.e. height, lengths or circumfer-
ences) had no influence on running performance, which is in agreement with some previous
studies [3,4,5]. However, other studies found the contrary, which could be due to the different
ethnicities compared (e.g. Caucasian vs African) and not to the performance level itself
[17,25].
Additionally, as expected, VO2max, peak speed, and speed in both VT and RCT were
strongly related to half-marathon performance (Table 1), in the same line with previous
Fig 1. Foot strike pattern distribution (midfoot/forefoot and rearfoot) in each group of runners. G1, G2, G3, G4,
groups of runners of different performance level (< 70, < 80, < 90 and < 105 min, respectively). , significant
differences with Group 1.
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findings [2,11,16,26,27]. It is noteworthy the weak relationship between performance and run-
ning economy (r  0.50), coinciding with studies that did not observe any influence of this
variable [12, 28]. This could be because: 1- running economy is just one factor explaining per-
formance and it can be compensated by other factors [28]; 2- both economical and uneconom-
ical runners have been identified at all levels of performance [29]; 3- the dependence of
running economy on training status [2], as all runners in this study were well-trained; and 4-
the higher percentage of midfoot/forefoot strikers in the Group 1 (Fig 1), being less economi-
cal runners than rearfoot strikers [13,30].
Table 2. Mean (± SD) spatio-temporal variables of the different groups of runners during the incremental tests. Correlation (r) with running performance (time to
complete a half-marathon).
G1
(n = 11)
G2
(n = 13)
G3
(n = 13)
G4
(n = 11)
r
PEAK
Contact time (ms)
177±15†#
193±17†#
215±17
222±14
0.76
Step rate (spm)
190.7±4.7
187.6±6.3
190.6±8.0
189.7±15.5
0.01
Step length (m)
1.86±0.09†#
1.80±0.12†#
1.61±0.13
1.54±0.16
-0.73
RCT
Contact time (ms)
198±23†#
219±19†#
241±19#
260±19
0.82
Step rate (spm)
181.7±6.9
177.4±7.3
178.5±8.9
172.7±9.6
-0.38
Step length (m)
1.66±0.09†#
1.58±0.11†#
1.42±0.09#
1.29±0.10
-0.87
VT
Contact time (ms)
246±22†#
282±34†#
304±21
313±33
0.66
Step rate (spm)
167.5±4.8
166.2±8.0
162.6±6.2
159.6±6.2
-0.43
Step length (m)
1.22±0.09†#
1.13±0.12†#
1.03±0.06
1.05±0.08
-0.62
Note: G1, G2, G3, G4, groups of runners of different performance level (< 70, < 80, < 90 and < 105 min, respectively). PEAK, peak speed reached during the
incremental test. RCT, respiratory compensation threshold. VT, ventilatory threshold. spm, steps per minute.
, significant differences with Group 2.
†, significant differences with Group 3.
#, significant differences with Group 4.
r, significant correlations (p<0.05) in bold type.
https://doi.org/10.1371/journal.pone.0191688.t002
Table 3. Mean (± SD) spatio-temporal variables of the different groups of runners during the submaximal tests. Correlation (r) with running performance (time to
complete a half-marathon).
G1
(n = 11)
G2
(n = 13)
G3
(n = 13)
G4
(n = 11)
r
11 kmh-1
Contact time (ms)
258±19†#
279±19
290±20
295±26
0.53
Step rate (spm)
165.1±3.7
165.5±7.3
164.4±7.8
163.1±11.6
0.52
Step length (m)
1.11±0.03
1.11±0.05
1.12±0.05
1.13±0.08
0.19
13 kmh-1
Contact time (ms)
236±16†#
253±19
264±16
263±11
0.51
Step rate (spm)
169.3±3.7
168.2±6.2
173.4±9.8
171.1±11.1
0.13
Step length (m)
1.28±0.03
1.29±0.05
1.25±0.07
1.27±0.08
-0.10
15 kmh-1
Contact time (ms)
219±16†#
233±16
242±15
242±11
0.50
Step rate (spm)
174.9±3.6
172.1±6.6
180.5±10.3
178.5±13.0
0.23
Step length (m)
1.43±0.03
1.46±0.06
1.39±0.08
1.41±0.10
-0.21
Note: G1, G2, G3, G4, groups of runners of different performance level (< 70, < 80, < 90 and < 105 min, respectively). spm, steps per minute.
, significant differences with Group 2.
†, significant differences with Group 3.
#, significant differences with Group 4.
r, significant correlations (p<0.05) in bold type.
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Foot strike pattern
Foot strike pattern distribution among groups found in this study is in line with previous stud-
ies that compared the foot strike patterns of top and bottom place finishers of high-level half-
marathon and marathon races [7,8]. Runners with a higher performance level tend to more
frequently use a midfoot/forefoot strike pattern, which allows them to shorten contact time by
10% at the same running speed than rearfoot strikers [7,13,20,30–32]. This could be beneficial
to reach high running speeds during training and competition (> 20 kmh-1) without
compromising step rate [13,32]. Table 1 showed that peak running speed in Groups 1 and 2
was higher than 20 kmh-1, and contact time was lower than 200 ms (10% shorter than in the
Groups 3 and 4), which highlights the importance of foot strike pattern to shorten contact
time to achieve those high running speeds.
Spatio-temporal parameters during the incremental test (comparison at
relative physiological intensities)
The differences in spatio-temporal variables (i.e. contact time, step rate and length) among
groups and the correlations with performance during the incremental test were reasonable
(Table 2). All these variables are highly dependent on running speed, and as it was previously
commented, contact time is also dependent on foot strike pattern. In fact, it was observed in a
previous study that an increase of 2 kmh-1 in running speed could mean an increase of ~ 7.4
steps per minute in step rate, ~ 0.284 m in step length and a decrease of ~ 20 ms in contact
time, independently of the type of foot strike pattern [13]. However, during the incremental
test, when foot strike pattern and running speed were considered as covariates (i.e. ANCOVA),
the differences in spatio-temporal variables disappeared. This finding suggests that foot strike
pattern and running speed are responsible for spatio-temporal differences between runners.
At similar physiological intensities, step length was different among the groups of runners,
while step rate was not (Table 2). This is in agreement with previous studies performed in vet-
eran marathon runners, where shorter step length was the cause of speed reduction with age
[33], possibly due to a loss of strength over the years [34]. Similarly, a strong relationship was
also established between strength training and the improvement in long-distance running per-
formance [35]. Nevertheless, to the best of our knowledge, none of these studies analyzed the
effect of strength training programs on running spatio-temporal variables, which could be a
future aim.
Spatio-temporal parameters during the submaximal test (comparison at
standardized running speeds)
When running speed was controlled (i.e. submaximal text, Table 3), there were no differences
among groups in step rate and length, in concordance with previous findings [13,20]. On the
contrary, a recent study performed in collaboration with our research group and following
similar experimental procedures showed differences in both step rate and length, but not in
contact time when trained and untrained runners were compared [15]. Trained runners
showed higher step rate and shorter step length at the same running speeds than untrained
ones. This condition (i.e. higher step rate and shorter length) could be a natural adaptive
mechanism to prevent some of the most common running-related injuries as it decreases the
magnitude of the center of mass vertical excursion, ground reaction force, impact shock, and
may ameliorate energy absorption at the hip, knee, and ankle joints impacts during running
[36]. However, when experienced runners of different performance level are compared, as the
present study showed, these differences in step rate and length are not observed, probably due
Comparison of different level runners
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January 24, 2018
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to the high training status of the runners (i.e. more than 40 kmweek-1 of running, more than 3
years of running experience and a RCT above the 84% of VO2max) regardless their perfor-
mance level.
Thereby, from the results of the present and previous studies [13,15], the association
between shorter contact times and better performance in long-distance runners [7,11] is quite
questionable, because it depends on both foot strike pattern and running speed. When both
variables are controlled, there are no differences in contact time among runners of different
performance level. In other words, contact time seems to be very consistent among highly-
trained runners of different performance level, which could constitute further investigation.
Conclusions
The present study demonstrated that runners from different performance level differed in
training-related (i.e. years of experience and weekly training volume), anthropometric (i.e.
body mass, body mass index and sum of skinfolds), physiological (i.e. VO2max, RCT and run-
ning economy), foot strike pattern and spatio-temporal variables (i.e. contact time, step rate
and length). However, when foot strike pattern and running speed were controlled (i.e. run-
ning at the same absolute speed), spatio-temporal variables were similar among them. Higher
level participants more frequently adopt midfoot/forefoot strike patterns and they run at
higher running speeds, which implies differences in spatio-temporal variables. Nonetheless,
future studies should analyze why spatio-temporal variables are so consistent when running
speed and foot strike pattern are similar.
Supporting information
S1 Dataset. Individual dataset of the runners.
(XLS)
Acknowledgments
The authors would like to thank the runners who participated in this study for their
collaboration.
Author Contributions
Conceptualization: Ana Ogueta-Alday, Josue´ Go´mez-Molina, Juan Garcı´a-Lo´pez.
Formal analysis: Ana Ogueta-Alday, Juan Garcı´a-Lo´pez.
Funding acquisition: Juan Garcı´a-Lo´pez.
Investigation: Ana Ogueta-Alday, Juan Carlos Morante, Juan Garcı´a-Lo´pez.
Methodology: Ana Ogueta-Alday, Juan Carlos Morante, Josue´ Go´mez-Molina, Juan Garcı´a-
Lo´pez.
Resources: Juan Carlos Morante, Josue´ Go´mez-Molina.
Software: Juan Carlos Morante, Juan Garcı´a-Lo´pez.
Supervision: Juan Carlos Morante, Juan Garcı´a-Lo´pez.
Validation: Juan Carlos Morante.
Writing – original draft: Ana Ogueta-Alday, Juan Carlos Morante, Josue´ Go´mez-Molina,
Juan Garcı´a-Lo´pez.
Comparison of different level runners
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Writing – review & editing: Ana Ogueta-Alday, Josue´ Go´mez-Molina, Juan Garcı´a-Lo´pez.
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Similarities and differences among half-marathon runners according to their performance level.
Ogueta-Alday, Ana,Morante, Juan Carlos,Gómez-Molina, Josué,García-López, Juan