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Timeless evolution of walking and pace strategy of women’s race walking

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Background and Study Aim. The purpose of this research was to study the timeline evolution of walking, as well as the Pacing Strategy Profiles of high-level women in the 20 km of race walking. Material: The practical example of applying the theoretical basis was made during the Women’s Greek Championship (Megara 2016), in which 12 athletes aged 19 to 40 participated (28.50 ± 7.20). Material and Methods. The certified distance of the 20km route was divided into 10 sections of 2 km each. The same happened with the times (intermediate, final) corresponding to the individual sections (2 km) of the route. The athletes were divided into 4 groups: the first 3, those who finished 15% slower than the first, those who finished 15% - 30% slower, and those who finished more than 30% slower than the winner. Finally became comparison of the first 6 and last 6 athletes’ groups. Results. The individual pace strategies that describe the tactics of the athletes in this race have been calculated. It was found that the winners of the race used Even Pacing Strategy, maintaining a steady speed on most of the route. As the level of women athletes became lower, Variable Pacing Strategy was used, while the athletes who finished last did not seem to be able to maintain any particular pacing strategy. Conclusions. It is suggested that athletes should follow Even Pacing Strategy during the race in order to improve their performance.
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278
of Physical Culture
and Sports
PEDAGOGY
Timeless evolution of walking and pace strategy of women’s
race walking
Panagiotα FitiliABCDE, Vasilios GiovanisABCDE
National and Kapodistrian University of Athens, Greece
Authors’ Contribution: A – Study design; B – Data collection; C – Statistical analysis; D – Manuscript Preparation;
E – Funds Collection.
Abstract
Purpose: The purpose of this research was to study the timeline evolution of walking, as well as the Pacing Strategy
Proles of high-level women in the 20 km of race walking.
Material: The practical example of applying the theoretical basis was made during the Womens Greek
Championship (Megara 2016), in which 12 athletes aged 19 to 40 participated (28.50 ± 7.20). The certied
distance of the 20km route was divided into 10 sections of 2 km each. The same happened with the
times (intermediate, nal) corresponding to the individual sections (2 km) of the route. The athletes were
divided into 4 groups: the rst 3, those who nished 15% slower than the rst, those who nished 15% -
30% slower, and those who nished more than 30% slower than the winner. Finally became comparison
of the rst 6 and last 6 athletes’ groups.
Results: The individual pace strategies that describe the tactics of the athletes in this race have been calculated.
It was found that the winners of the race used Even Pacing Strategy, maintaining a steady speed on most
of the route. As the level of women athletes became lower, Variable Pacing Strategy was used, while the
athletes who nished last did not seem to be able to maintain any particular pacing strategy.
Conclusions: It is suggested that athletes should follow Even Pacing Strategy during the race in order to improve their
performance.
Keywords: race walking, even pacing strategy, variable pacing strategy, performance.
Introduction1
Various activities that are repeated on a daily basis put
the human body on a motor alert, whether it is for social,
working or sporting purposes. Beginning of walking from
stillness is considered to be one of the most common
activities of a person in its daily living. Depending on the
purpose and the method, we can divide it as follows:
1) Simple walk or walk is considered as the natural
way of moving the human body into space from its
infancy [1].
2) The healing walk, which is the acceptance of
exercise as a practical form of rehabilitation, promotion
and preservation of health, as it was known by Byzantine
medicine [2].
3) Recreational walk or walk as a recreation. Mannel &
Reid, [3] and Sylvester, [4] dene three dimensions based
on: (a) Leisure as free time, (b) Leisure as an experience,
(c) Leisure as an activity. It is therefore understood,
that recreation is a broader concept that involves active
activity, whereas entertainment involves passive activity
[5].
4) Nordic walking is walking with specially designed
walking sticks, to improve tness [6].
5) Race walking is a part of the classical athletics and
one of the Olympic Games, in which athletes move as fast
as possible without running in routes of 20 km and 50 km.
The great schools of race walking were created after
the war. First the Soviet School, later the Italian, the Spain,
the Mexican, the Poland, the German and last the Chinese.
© Panagiotα Fitili, Vasilios Giovanis, 2020
doi:10.15561/26649837.2020.0601
ORIGINAL ARTICLE
The most important athlete of race walking was the Polish
Robert Korzeniowski. He has had gain four gold Olympic
medals (3 in 50 km and 1 in 20 km), and four medals in
World Championships (3 gold and 1 bronze, all in 50 km).
The basic rules of race walking:
Race walking is carried out on at public roads.
Athletes walk 20 km, repeating 10 times routes of 2 km,
or 4 times routes of 5 km. There are rules that differentiate
walking from running and athletes of race walking have
to know them and follow them. According to Regulations,
article 230 IAAF Track and Field Regulations 2012-13
“Race walking is a sequence of steps. The race walker
contacts the ground in a way that, no visible (in the human
eye) loss occurs.
The forward leg should be stretched (not bent at the
knee) from the point of rst contact with the ground to the
vertical upright position”. Judges of race walking watch
the athletes during the race and exclude them, if their
foot is not stretched on the ground or, if they both lose
contact with it. When the judge nds an infringement, he
makes his rst remark. If the offense is repeated, then the
athlete’s warning exclusion is placed on a sign visible to
all participants in the race. If three different judges charge
the athlete in violation, then exclusion follows.
Pace strategy in race walking
The observation that athletes’ speed during a race
varies caused interest as far as the pace strategy they
should follow is concerning. This strategy is a key
factor in the success of athletes in sports events [7]. Pace
strategy is the ability to regulate the speed of an athlete’s
movement in order to reach the end of the race in a shorter
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time [8, 9]. The tempo or pace strategy relates to racing:
(a) up to 40 sec (sprint), (b)from 40 sec up to a few
minutes (short distance), (c) medium and long distance
and overtime, which last for hours [10]. Aschenbrenner,
Erdmann, Giovanis, & Lipinska, [11] had investigated the
tactics and technique of race walking at the 2004 Athens
Olympics. Ruchlewicz et al., [12] studied the tactic of
race walking, based on measurements made in athletes on
a oor meter. It is well known that athletes should not run
at high speed early in their race. Often the elite athletes
run the second part of a distance faster than the rst part
[13, 14].
Hypothesis
The following research questions will be investigated
in the present study:
a. Will analysing the strategy of the race help coaches
and athletes?
b. Do athletes or groups of athletes differ in terms of
pace strategy?
Purpose
The purpose of this research was to study the timeless
evolution of walking, as well as the Pacing Strategy
Proles of high-level women in the 20 km of race walking.
The importance of the research was signicant as follows:
the above information would be able to extend theoretical
knowledge, so that the methodology of analysing the data
of races, that have been or will be conducted in the future,
is applied in practice.
Material and Methods
Participants
The practical example of applying the theoretical
basis was made during the Women’s Greek Championship
(Megara 2016), in which 12 athletes of race walking
aged 19 to 40 participated (28.50 ± 7.20). Athletes
had experience in endurance training in race walking
for at least 5 years [15, 16]. A prerequisite for their
participation in the study was their ability to have reached
the qualifying thresholds for the Race Walking National
Championships. Which means that these athletes had
a high level of training experience and endurance [17].
The race course was certied and measured by SEGAS at
20km. Took place on the Megara beach on a public road,
and consisted of a 2km circular route, which athletes were
required to walk 10 times.
The present study was a targeted review work with a
practical example of applying the theoretical basis.
Independent variables: High-level women athletes in
the 20 km race track, initially divided into 4 groups. The
rst 3, those who nished 15% slower than the rst, those
who nished 15% - 30% slower and, nally, those who
nished more than 30% slower than the winner. Then,
they are splitted into two groups: those nishing in the
top 6 and bottom 6. Also, the predened distances of the
sections of the route.
Dependent variables: The performance of top-level
women athletes in the race of 20 km. The individual times
of the athletes in the predetermined sections of the track,
as well as their pace strategy.
Research Design
Initially, the certied distance of the race track (St-
20km) divided into 10 sections of 2km each was recorded.
The same happened with the times (intermediate, nal)
corresponding to the individual sections (2 km) of the
route. Based on the data of the individual track distances
and the respective times of the athletes, the individual
pace strategies were found that describe the athletes’
tactics in this race.
The appliances that were used to perform the
measurements and to evaluate the data were:
a) One video camera (Sony, Full HD 1080, 50 Hz).
The camera’s resolution was 0.02s and it was rmly
positioned at the start-stop (where the athletes completed
the 2km cycle). The video recording of the athletes’ passes
at 2km and recording the electronic timer,
(b) The protocols in which the distances of the race
and the kinematic parameters were written.
Statistical Analysis
The analysis included:
1. Descriptive statistics: mean (M), standard deviation
(SD) and coefcient of variation (V).
2. Pace strategy analysis for the top 3 athletes, those
who nished 15% slower than the rst, those who nished
15% to 30% slower than that and, nally, those who
nished more than 30% slower than the winner [18].
3. Relation of the times (intermediate and nal) of the
12 athletes, as well as the rst 6 and last 6 athletes, in
relation to the distances of the sections of the track.
4. After a detailed explanation of all the terms used for
the statistical processing of the work, follows a reference
to the t-test. The t - test method investigates the difference
between the mean values of a variable at two time points.
In other words, it examines whether the difference of
two averages is due to random factors. A prerequisite for
the above hypothesis to be valid is that the index t to be
greater than or equal to the criterion (tc) value of the t-test.
The criterion value is derived from the special t-student
price table by selecting any level of signicance and any
degrees of freedom. In this work the t - test calculations
were performed with 5% statistical signicance and two
-sided control, with degrees of freedom N - 1, where N is
the sample population.
Results
The following results expand the theoretical
knowledge of women’s pace strategy in 20km of race
walking. So that the methodology of analysing the data of
races that have been or will be conducted in the future is
applied in practice.
Figure 1 shows the time course of the athletes in the
predetermined intermediate sections of the 20km route of
the race, in relation to their ranking. The Table 1 shows the
nish times (t) of the leader in each group of athletes of
20 km of race walking, and their relationship (r) with the
distance travelled (s) in individual sections of the route.
For the rst athlete (Figure 2) we can see that, there
are no signicant uctuations in the intermediate times
between her passes. In other words, it is observed that
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she follows Even Pacing Strategy, which concerns the
uniform distribution of the expenditure of her forces
during the struggle [19].
Table 1. Finish times (t) of the leader in each group of
athletes of 20 km of the race walking and their relation
(r) with the distance travelled (s) in individual sections of
the route.
Athletes Time(M)
r = distance
(s) - time (t)
Winner 1.29.35 0,44
Group< 15% 1.37.14 0,50
Group 15 - 30% 1.43.36 0,49
Group 30% 1.59.54 0,47
Group 100% (12) 1.47.83 0,55
In other words, the rst winner tried to keep constant
the time in the individual passes, throughout the race, in
order to run at the same pace.
The athletes, who nished in times up to 15% slower
than the 1st winner (Figure 3), had uctuations in the
intensity of their effort or rhythm during the race. In the
team that nished in times up to 15-30% slower than
the 1st winner (Figure 4) you can see that the fatigue
comes much faster than in the previous group. In other
words, their intermediate times, along the route, vary
from passage to passage, either increasing or decreasing
signicantly. These athletes display Variable Pacing
Strategy [19, 7].
As for the athletes who nished in times over 30%
slower than the rst winner (Figure 5), their common
tactics are obvious up to the 14th kilometre. But from then
on, with the effect of fatigue, we notice a big difference
in times of this group in the last kilometres. The athletes
don’t seem to have used a specic pace strategy; they just
tried to keep a steady pace all the way, which they didn’t
manage. The difference in capacity between this group
and the previous ones is obvious. Since we are talking
about athletes who nished in the last positions of the race
Figure 1. An intermediate me in the respecve secons (F.i) of women’s 20km of race walking in relaon to their
classicaon posion.
Figure 2. The individual mes per 2km of the winners in the 20km women’s race walking.
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Figure 3. The individual mes per 2km of the group<15% of the athletes in the 20km of race walking
Figure 4. The individual mes per 2km of the group 15-30%, of the athletes in the 20km of race walking.
Figure 5. The individual mes per 2km of the group> 30% of the athletes in the 20km of race walking.
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(Figure 6), and that was the reason that the fatigue came
earlier than the previous groups [19].
Correlation coefcients (r) in relation to the
performance of the women’s teams were signicant
(Table 2). The t-test between the team of the rst 6
athletes M1-6 (9.69 ± 0.48 min) and that of 6 last athletes
M7-12 (11.92 ± 0.97 min), with a correlation r = 0.97.
Showed the difference in performance between the two
groups of athletes (Figure 7) t = 6,255> tc = 2,179 with
bilateral control ( p <0.05). It was found that none of the
Figure 6. The individual mes per 2km of the four groups in the 20km women’s race walking.
Table 2. The correlation coefficients (r) in relation to the performance of the groups of walkers.
r The 3 winners <15% slower 15-30% slower >30% slower 12 athletes
The 3 winners Χ0,94 0,90 0,98 0,95
< 15% slower Χ0,97 0,92 0,98
15-30% slower Χ0,89 0,98
> 30% slower Χ0,95
12 athletes Χ
Figure 7. Comparison of the mean values (M) of the performance between the group of the rst 6 athletes M1-6
(9.69 ± 0.48) and the last 6 athletes M7-12 (11.92 ± 0.97), with correlaon r = 0.97 where the t-test showed the
dierence in performance between the two groups of athletes t = 6.25>tc = 2,179 with bilateral control (p <0.05).
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athletes who belonged to the rst group, who were the
winners, started the race faster than their personal record.
The athletes of the last group started the race faster than
their own performance [19].
The fact that a large percentage of athletes that did
not nish in the rst places, start faster than the ones that
followed. Leads us to the conclusion that, these athletes
started the race seduced by how relaxed they felt at that
moment, not having the perception of impending fatigue.
Discussion
As we can observe by studying the proles of the
pace strategy at 20km of race walking in the practical
example of application of the theoretical basis, there are
differences from athlete to athlete. The winners (the rst
three athletes) seem to follow the Even Pacing Strategy,
which deals with the uniform distribution of the cost
expenditure of their forces during the race. In other words,
these athletes tried to maintain a constant passage time, in
each circular route of 2km and a small difference of their
individual speeds between their passes [19]. The lower
this deviation, the better the performance of the athletes.
Leads us to the conclusion that, the optimal tactic at this
distance is the constant passes of the athletes at a speed
equal to the average speed.
After all, the tactics of walking, like all long-distance
roads, must be accompanied by specialized technique
and speed distribution [19]. These ndings are in line
with previous studies that have analysed the path of
athletes in the marathon. They found that the change
in speed was less for the best runners compared to the
slower athletes [20, 19]. Athletes, who nished up to 30%
slower than the winner, show Variable Pacing Strategy.
These athletes had greater uctuations in the intensity of
their effort, or rhythm, during the race. The pace strategy
in race walking, as in all long-distance roads, must be
accompanied by the specialized technique [19]. It was
found that, the optimal deviation of the speed from the
average speed improves the nal performance of the
athletes, which was expected according to previous
studies conducted in this subject [8, 9].
Conclusions
With the help of this study, we obtained the following
important information: that the winners of the race used
Even Pace Strategy, maintaining a constant speed for
most of the route at the 20 km of race walking. We also
concluded that, the groups of athletes tested differ from
each other in terms of pace strategy. As the level of the
athletes decreases, the Variable Pace Strategy was used,
while the athletes, who nished in the last positions, do
not seem to have managed to maintain any particular pace
strategy.
It is therefore recommended that athletes should design
with their coaches the model of the pace strategy they wish
to follow. Not be carried away by the momentary latent
sense of relaxation, they have at the beginning of the race.
The application by the coaches of the relevant training
protocols to their athletes, will signicantly contribute to
the improvement of their nal performance.
Conict of interest
Authors declare no conict of interest.
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Information about the authors:
Vasilios Giovanis; (Corresponding Author); Ph.D.; http://orcid.org/0000-0003-2511-8286; vgiovan@phed.uoa.gr; School of
Physical Education and Sport Science, National and Kapodistrian University of Athens; 41 Ethnikis Antistassis Str., Daphne
17237, Athens, Greece.
Panagiotα Fitili; Msc ; https://orcid.org/0000-0001-5682-3047; fytili@hotmail.com; School of Physical Education and Sport
Science, National and Kapodistrian University of Athens; 41 Ethnikis Antistassis Str., Daphne 17237, Athens, Greece.
Cite this article as:
Fitili P, Giovanis V. Timeless evolution of walking and pace strategy of women’s race walking. Pedagogy of Physical Culture and
Sports, 2020;24(6):278-284.
https://doi.org/10.15561/26649837.2020.0601
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 work is properly cited
(http://creativecommons.org/licenses/by/4.0/deed.en).
Received: 01.05.2020
Accepted: 12.06.2020; Published: 30.12.2020
ResearchGate has not been able to resolve any citations for this publication.
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Race walking is the technical and athletic expression of fast walking and it can be considered as a type of endurance performance. The purpose of this study was to examine whether 12 weeks of a specially designed training program results in the further training enhancement of endurance performance and the related physiological parameters in already well-trained race walkers competing at the national and international level. The investigation protocol consisted of determining the maximal oxygen uptake (VO2peak) and related gas exchange values using an automated cardiopulmonary exercise system and of determining blood lactate variables (aerobic threshold - LTAer and the maximal lactate steady state - MLSS) during walking with proper technique at 8, 10, 12 and 14 km·h-1 for 4 minutes without rest in between. Thereafter, the speed on the treadmill was increased by 0.5 km·h-1 every two minutes until exhaustion to determine VO2peak. After 12 weeks of a specially designed endurance training, statistically significant increases in VO2peak (61.8±8.5 mL·kg-1·min-1 pre vs. 66.9±9.5 mL·kg-1·min-1 post training; p<0.05) and blood lactate variables (VO2-LTAer and VO2-MLSS; p<0.05) were noted. The obtained results suggest that the applied training program can improve endurance and race performance in previously well trained race walkers.
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Concepts of how athletes should expend their aerobic and anaerobic energetic reserves are generally based on results of tests where an "all out" strategy is imposed on/required from the athlete. We sought to determine how athletes spontaneously expend their energetic reserves when the only instruction was to finish the event in minimal time, as in competition. Well trained, and task habituated, road cyclists (N = 14) completed randomly ordered laboratory time trials of 500 m, 1000 m, 1500 m and 3000 m on a windload braked cycle ergometer. The pattern of aerobic and anaerobic energy use was calculated from total work accomplished and V.O (2) during the trials. The events were completed in 40.3 +/- 0.6 s, 87.4 +/- 4.1 s, 133.8 +/- 6.6 s and 296.0 +/- 7.2 s. The peak V.O (2) during the terminal 200 m of all events was similar (2.72 +/- 0.22, 3.01 +/- 0.34, 3.23 +/- 0.44 and 3.12 +/- 0.13 l x min (-1)). In all events, the initial power output and anaerobic energy use was high, and decreased to a more or less constant value over the remainder of the event. However, the subjects seemed to reserve some ability to expend energy anaerobically for a terminal acceleration which is contrary to predictions of an "all out" starting strategy. Although the total work accomplished increased with distance (23.14 +/- 4.24, 34.14 +/- 6.37, 43.54 +/- 6.12 and 78.22 +/- 8.28 kJ), the energy attributable to anaerobic sources was not significantly different between the rides (17.29 +/- 3.82, 18.68 +/- 8.51, 20.60 +/- 6.99 and 23.28 +/- 9.04 kJ). The results are consistent with the concept that athletes monitor their energetic resources and regulate their energetic output over time in a manner designed to optimize performance.
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It is widely recognized that an athlete's 'pacing strategy', or how an athlete distributes work and energy throughout an exercise task, can have a significant impact on performance. By applying mathematical modelling (i.e. power/velocity and force/time relationships) to athletic performances, coaches and researchers have observed a variety of pacing strategies. These include the negative, all-out, positive, even, parabolic-shaped and variable pacing strategies. Research suggests that extremely short-duration events (< or =30 seconds) may benefit from an explosive 'all-out' strategy, whereas during prolonged events (>2 minutes), performance times may be improved if athletes distribute their pace more evenly. Knowledge pertaining to optimal pacing strategies during middle-distance (1.5-2 minutes) and ultra-endurance (>4 hours) events is currently lacking. However, evidence suggests that during these events well trained athletes tend to adopt a positive pacing strategy, whereby after peak speed is reached, the athlete progressively slows. The underlying mechanisms influencing the regulation of pace during exercise are currently unclear. It has been suggested, however, that self-selected exercise intensity is regulated within the brain based on a complex algorithm involving peripheral sensory feedback and the anticipated workload remaining. Furthermore, it seems that the rate and capacity limitations of anaerobic and aerobic energy supply/utilization are particularly influential in dictating the optimal pacing strategy during exercise. This article outlines the various pacing profiles that have previously been observed and discusses possible factors influencing the self-selection of such strategies.
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Despite interest in competitive strategy by coaches and athletes, there are no systematically collected data regarding the effect of differences in pacing strategy on the outcome of middle distance (2-4 min duration) events. In this study different pacing strategies were evaluated using a 2-km time trial on a bicycle attached to a wind load simulator. Well-trained subjects (N = 9) performed five separate time trials with the pace during the first 50% of the trial experimentally constrained within the usual real world range from very slow (approximately 55% of best time) to very fast (approximately 48% of best time). Serial VO2 was measured to estimate the oxidative contributions to the trial and accumulated O2 deficit and postexercise blood lactate measured to estimate the anaerobic contribution to the trial. The evenly paced trial (first 1 km = 50.9% final time) produced the fastest total time. The starting pace to final time relationship was described by a U shaped second order polynomial curve with the nadir for final time at a starting pace of 51% of best total time. There were no systematic differences in serial VO2, accumulated O2 deficit, or postexercise lactate that could account for the pacing related variations in performance. The data support the concept of relatively even pacing in middle distance events with negative consequences for even small variations in this strategy.
Work and leisure. In: Leisure Studies, Prospects for the Twenty-first century
  • R Mannell
  • D Reid
Mannell R, Reid D. Work and leisure. In: Leisure Studies, Prospects for the Twenty-first century, 1999. P. 151-163.
Biomechanical parameters of race walking on the example of tests of an international champion class walkers
  • T Ruchlewicz
  • R Staszkiewicz
  • W Chwala
  • J Laska
Ruchlewicz,T, Staszkiewicz R, Chwala W, Laska J. Biomechanical parameters of race walking on the example of tests of an international champion class walkers. In: Urbanik Cz (ed.). Zagadnienia biomechaniki sportu -technika ruchu [Biomechanics of sport issues -movement technique]. Warsaw; 2003. P.46-57 (in Polish)