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Agility performance in athletes of different sport specializations

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  • Comenius University in Bratislava, Faculty of Physical Education and Sports

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Background: Data on agility skills in different populations using pre-planned, change of direction speed tests have previously been reported. However, there are no available data on the agility times of athletes specializing in different sports obtained from Reactive agility tests. Objective: The study compares agility time in groups of athletes of different sports where agility is one of the limiting factors of performance. Methods: Altogether 282 athletes of 14 sport specializations performed the Agility test. Their task was to touch, as fast as possible, with either the left or the right foot, one of four mats located outside each of the four corners of a 0.8 m square. The mats had to be touched in accordance with the location of a stimulus in one of the corners of a screen. The test consisted of 60 visual stimuli with random generation of their location on the screen and a time of generation of 500 to 2,500 ms. The result was a sum of the 32 best agility times. Results: The Agility test has been found to be sensitive in distinguishing groups of athletes of different sport specializations. Table tennis players, badminton players, fencers, tae-kwon-do competitors and karate competitors showed the best agility times (< 350 ms), followed by ice-hockey, tennis, soccer, volleyball, basketball, and hockeyball players (350-400 ms), then aikidoists (400-450 ms), and finally judoists and wrestlers (450-500 ms). Conclusions: The best agility times are in athletes of racquet sports, followed by competitors of combat sports with reactions to visual stimuli, then players of ball sports, and finally competitors of combat sports with reactions to tactile stimuli. Since this is the first study testing agility skills using the Reactive agility test in athletes of different sport specializations, data obtained can be used for comparison of athletes within particular sports.
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Agility performance in athletes of different sport specializations
Erika Zemková* and Dušan Hamar
Faculty of Physical Education and Sports, Comenius University, Bratislava, Slovak Republic
Copyright: © 2014 E. Zemková and D. Hamar. This is an open access article licensed under the Creative Commons Attribution License
(http://creativecommons.org/licenses/by/4.0/).
Background: Data on agility skills in different populations using pre-planned, change of direction speed tests have
previously been reported. However, there are no available data on the agility times of athletes specializing in different
sports obtained from Reactive agility tests. Objective: The study compares agility time in groups of athletes of differ-
ent sports where agility is one of the limiting factors of performance. Methods: Altogether 282 athletes of 14sport
specializations performed the Agility test. Their task was to touch, as fast as possible, with either the left or the right
foot, one of four mats located outside each of the four corners of a 0.8 m square. The mats had to be touched in
accordance with the location of a stimulus in one of the corners of a screen. The test consisted of 60 visual stimuli
with random generation of their location on the screen and a time of generation of 500 to 2,500 ms. The result was
a sum of the 32 best agility times. Results: The Agility test has been found to be sensitive in distinguishing groups of
athletes of different sport specializations. Table tennis players, badminton players, fencers, tae-kwon-do competitors
and karate competitors showed the best agility times (< 350 ms), followed by ice-hockey, tennis, soccer, volleyball,
basketball, and hockeyball players (350–400 ms), then aikidoists (400–450 ms), and finally judoists and wrestlers
(450–500 ms). Conclusions: The best agility times are in athletes of racquet sports, followed by competitors of com-
bat sports with reactions to visual stimuli, then players of ball sports, and finally competitors of combat sports with
reactions to tactile stimuli. Since this is the first study testing agility skills using the Reactive agility test in athletes of
different sport specializations, data obtained can be used for comparison of athletes within particular sports.
Keywords: agility test, agility time, combat sports, sports games
performance. However, many sports (soccer, basket-
ball, tennis, ice hockey, badminton, racquetball/squash,
volleyball, baseball/softball, lacrosse, american foot-
ball, wrestling, boxing, fencing) which are ranked high-
est for agility require changes of direction in response
to a stimulus (e.g., movement of the ball or a player).
Another general feature of field and court sports is that
actions are performed alongside the offensive player’s
movements; thus they involve some sort of competi-
tion. Therefore, testing and training conditions should
mimic these sport-specific demands.
Recently, agility has been defined as a rapid whole-
body movement with a change of velocity or direction
in response to a stimulus (Sheppard & Young, 2006).
The use of tests of agility that combine changes of
direction and/or speed with cognitive measures is
encouraged in practice. Such new Reactive agility tests
also include anticipation and decision-making compo-
nents in response to the movements of a tester. Shep-
pard, Young, Doyle, Sheppard, and Newton (2006)
have found that the Reactive agility test distinguishes
between players of different performance levels in
Australian football, while traditional closed skill sprint
Introduction
For many years, agility has been considered to be
the ability to execute fast movements and to stop
and restart rapidly. As a result, the majority of agility
research has been devoted to pre-planned, change of
direction speed tests. These tests (Illinois Agility Run,
Shuttle Run test, Zig Zag Test, 505 Agility test, Hexa-
gon test, Quadrant Jump Test, T-Test, 10 meter shuttle,
Quick Feet Test, Side-step Test, 20 Yard Shuttle, Agility
Cone Drill, 3-Cone Drill, Box Drill, AFL Agility Test,
Arrowhead Drill, 20 Yard Agility, Balsom Agility Run,
Lane Agility Drill, Shuttle Cross Pick-Up, etc.) have
been proposed to measure speed and agility. Although
there is great variation among the tests used, most of
them do not involve reactions to stimuli, and therefore
do not evaluate the cognitive component of agility
* Address for correspondence: Erika Zemková, Depart-
ment of Sports Kinanthropology, Faculty of Physical Educa-
tion and Sports, Comenius University in Bratislava, Nábr.
arm. gen. L. Svobodu 9, 814 69 Bratislava, Slovak Republic.
E-mail: zemkova@fsport.uniba.sk
Acta Gymnica, vol. 44, no. 3, 2014, 133–140
doi: 10.5507/ag.2014.013
134 E. Zemková and D. Hamar
and sprint with direction change tests do not. Simi-
larly, Farrow, Young, and Bruce (2005) showed that
the highly-skilled group was significantly faster in both
the reactive and planned test conditions relative to the
lesser-skilled group, while the moderately-skilled group
was significantly faster than the lesser-skilled group in
the reactive test condition only.
Indeed, agility skills that involve three information-
processing stages (i.e., stimulus perception, response
selection, and movement execution) represent a crucial
part of performance in many sports. Therefore, their
assessment should be considered an integral part of
functional testing in young beginners and professional
athletes alike.
In practice, Reactive agility tests that can be carried
out in the playing field or gym are preferred. A com-
puter-based portable system consisting of four contact
switch mats connected by means of an interface to the
computer can be used for this purpose. The system gen-
erates stimuli and measures total agility time (AT) and
AT in each direction of movement. There are a number
of test settings varying in the time of generation (con-
stant or random), the number of stimuli, their forms
and colors, as well as the color of the background.
The task of the subject is to touch, as fast as pos-
sible, with either the left or right lower limb, one of the
four mats located outside the four corners of a 0.8 m
square. Mats have to be touched in accordance with
the location of the stimulus in one of the corners of the
screen. Besides reacting from a position in the middle
of the square, subjects may respond from the location
of the last stimulus.
This test has been found to be sensitive in distin-
guishing subjects of different ages (Zemková, 2007;
Zemková & Hamar, 2014). However, its ability to
discriminate subjects of different performance levels
has not yet been determined. It may be assumed that
agility time differs significantly between athletes with
different demands on agility skills, and is specific to
those responding to visual stimuli. Verification of
this hypothesis was accomplished by comparison of
agility times in groups of athletes of different sport
specializations.
Methods
Participants
Altogether 282 (male and female) athletes of different
sport specializations volunteered to participate in the
study (Table 1). They were required to be active in a par-
ticular sport. Only participants who met the inclusion
criteria were included in the study. They were asked to
avoid any strenuous exercises during the study. All of
them were informed of the procedures and the main
purpose of the study. The procedures presented were
in accordance with the ethical standards on human
experimentation as stated in the Helsinki Declaration.
Procedure
Prior to the study, participants attended a familiariza-
tion session during which the testing conditions were
explained and trial sets carried out. Afterwards they
performed the Agility test (Figure 1). Their task was
to touch, as fast as possible, with either the left or the
Table 1
Characteristics of groups of athletes (mean ± SD)
Group nAge (years) Height (cm) Weight (kg)
Wrestlers 13 26.2 ± 3.1 175.0 ± 4.8 85.7 ± 7.8
Judo competitors 14 24.1 ± 3.8 173.9 ± 5.6 80.2 ± 8.8
Hockeyball players 22 22.7 ± 2.8 177.1 ± 5.4 76.7 ± 6.5
Aikido competitors 18 25.3 ± 4.1 173.8 ± 4.5 73.9 ± 5.5
Basketball players 32 20.4 ± 1.8 187.5 ± 6.1 78.9 ± 7.7
Volleyball players 21 21.3 ± 2.6 186.9 ± 6.2 74.0 ± 5.4
Soccer players 26 22.7 ± 2.9 179.7 ± 4.7 70.8 ± 4.9
Tennis players 17 20.7 ± 3.2 175.4 ± 5.1 71.1 ± 5.1
Ice-hockey players 16 22.9 ± 3.7 177.0 ± 5.4 77.8 ± 6.4
Karate competitors 27 23.9 ± 3.7 175.9 ± 5.7 68.4 ± 7.2
Tae-kwon-do competitors 23 21.9 ± 2.6 172.8 ± 3.8 68.7 ± 6.5
Fencers 11 20.8 ± 2.4 175.4 ± 4.1 65.1 ± 6.6
Badminton players 15 21.8 ± 2.0 176.5 ± 3.8 64.7 ± 5.7
Table tennis players 27 24.6 ± 4.5 172.8 ± 2.9 64.1 ± 5.4
135
Agility performance in athletes of different sport specializations
right foot, one of four mats located outside the four
corners of a 0.8 m square. The mats had to be touched
in accordance with the location of a stimulus in one of
the corners of a screen. The test consisted of 60 visual
stimuli with random generation of their location on the
screen and the time of generation of 500 to 2,500 ms.
The result was a sum of the 32 best agility times.
Agility testing
Agility time was measured by means of the computer
based FiTRO Agility check system (FiTRONiC s.r.o.,
Bratislava, Slovak Republic). The reliability of the test
procedure had been verified previously, and the test-
ing protocol had been standardized by the examination
of 196 participants (Zemková & Hamar, 1998a). The
analysis of repeated measurements showed a measure-
ment error of 7.1%, which is within a range comparable
to common motor tests. The mean of the best 8 agility
times in each direction has been found to be the most
reliable parameter of the test consisting of 3 sets of 60
stimuli (15 in each direction) with random generation
of their location. However, when the same protocol
(i.e., the same location of stimuli in each trial) was
used repeatedly, agility time significantly decreased
after each trial. Participants were most likely able to
remember the position of the initial stimuli, which
contributed to better results in successive trials. There-
fore, the result of the Agility test is a sum of the 32
best multi-choice agility times in four directions as a
response to stimuli generated by the computer in one
of the corners of the screen.
Statistical analysis
Data analysis was performed using the SPSS statistical
program for Windows (Version 18; SPSS, Inc., Chicago,
IL, USA). The calculation of the sample size was car-
ried out with α = 0.05 (5% chance of type I error) and
1 – β = .80 (power 80%) and using the results from our
preliminary studies that showed differences in agility
time between athletes of different sports (Zemková &
Hamar, 1998b; Zemková & Hamar, 1998c; Zemková
& Hamar, 1999). This provides a sample size of 16
subjects for this study. However, the sample size in
four groups was below this limit (from 11 to 15) as the
inclusion criteria required participants to be active in
a particular sport. Therefore, the statistical power for a
group of size n ranged from .76 to .85.
A series of one-factor ANOVA with a Bonferroni
post hoc test was used to determine differences in agil-
ity time between groups of athletes of different sport
specializations. The criterion level for significance was
set at p .05. Sex data, determined to be normally dis-
tributed, were analyzed in previous studies using the
independent samples t-test and showed no significant
differences in agility time between men and women
(Zemková & Hamar, 1998b; Zemková & Hamar,
1998c; Zemková & Hamar, 1999). Data on agility time
for all examined groups are presented as the mean ±
the standard deviation.
Results
The Agility test has been found to be sensitive in
distinguishing groups of athletes of different sport
specializations and has shown that some differences
do exist among the mean values for the examined
groups at p ≤ .05. The mean values of agility time and
the standard deviations for each group of athletes
a
b
Figure 1. The Agility test (a), summary report of the test (b)
136 E. Zemková and D. Hamar
Table 2
Agility time (mean±SD) and interdifference matrix between agility times of examined groups of athletes of different sport specializations
Sport Agility time (ms) Wrestling Judo Aikido Hockeyball Basketball Volleyball Soccer Tennis Ice-hockey Karate Tae-kwon-do Fencing Badminton
Wrestling 497.6 ± 44.4
Judo 454.6 ± 44.9 .039
Aikido 409.1 ± 38.0 .008 .036
Hockeyball 392.4 ± 36.1 .007 .024 .091
Basketball 380.6 ± 35.4 .006 .021 .066 .098
Volleyball 369.3 ± 29.9 .005 .008 .042 .072 .099
Soccer 364.0 ± 34.7 .004 .008 .036 .066 .091 .119
Tennis 362.2 ± 27.0 .004 .008 .034 .063 .088 .114 .129
Ice-hockey 352.1 ± 29.4 .003 .007 .029 .042 .066 .090 .098 .105
Karate 339.4 ± 25.6 .002 .006 .009 .030 .041 .065 .070 .074 .096
Tae-kwon-do 338.7 ± 23.9 .002 .006 .009 .031 .040 .063 .068 .072 .095 .131
Fencing 336.6 ± 26.1 .002 .006 .009 .028 .038 .061 .067 .069 .092 .124 .126
Badminton 314.8 ± 23.9 .001 .004 .008 .009 .026 .031 .033 .034 .055 .070 .071 .075
Table tennis 306.1 ± 22.2 < .001 .003 .007 .009 .009 .026 .029 .028 .035 .060 .061 .063 .111
137
Agility performance in athletes of different sport specializations
are presented in Table 2. In addition, the variability
among subjects showed high F values for agility time
(F1,280 = 34.48, p < .001) indicating that the subjects
differed significantly in their performance.
As shown in Figure 2, the best agility times have
been found in table tennis players, badminton players,
fencers, tae-kwon-do competitors and karate com-
petitors (< 350 ms), followed by ice-hockey, tennis,
soccer, volleyball, basketball, and hockeyball players
(350–400 ms), then aikidoists (400–450 ms), and
finally judoists and wrestlers (450–500 ms).
Accordingly, these sports were divided into four
basic categories (Figure 3) that can be used for the
comparison of individual athlete data and changes in
the data during training.
0
50
100
150
200
250
300
350
400
450
500
550
Table tennis
Badminton
Fencing
Tae-kwon-do
Karate
Ice hockey
Tennis
Socce
r
Volleyball
Basketball
Hockeyball
A
ikido
Judo
Wrestling
A
gility time (ms)
Figure 2. Agility time in groups of athletes of different sport specializations
Figure 3. Agility time (± SD) in different sports divided in four basic categories
138 E. Zemková and D. Hamar
Discussion
The study showed that the Agility test discriminates
between groups of athletes with different demands on
their agility skills. The results are in agreement with
preliminary findings which showed better agility times
in athletes responding to visual rather than tactile
stimuli (Zemková & Hamar, 1998b, 1998c, 1999).
Moreover, differences in agility time have reflected
the actual ranking of athletes, for instance, at different
playing positions (center, forward, guard) in basketball
players (Zemková & Hamar, 2013), between hockey-
ball players and hockeyball goalkeepers (Divald, 2012),
in different corners of the hockey goal in ice-hockey
goalkeepers (Tóth et al., 2010), and in different move-
ment directions in badminton players (Štefániková &
Zemková, 2011). The data obtained in these studies
form the basis for the design of training programs spe-
cifically focused on the improvement of agility skills in
a particular movement direction.
Similar to strength and speed abilities, assessment
of agility also requires a sport-specific approach. In
order to obtain parameters of agility skills relevant to a
particular sport, the test closest to the one used during
training or competition should be preferred. In recent
years, several sport-specific versions of the Agility test
have been developed. These tests vary in: a) number
of contact mats (2 or 4), b) the distance between mats
and subject (0.4 m, 0.8 m, 1.6 m or 3.2 m), c) their
alignment (square or semi-circular), d) positioning
(underfoot or at the height of the thorax), and e) size
(6.5 × 6.5 cm or 35 × 35 cm) (Zemková & Hamar,
2009). The number of stimuli, their time of generation
and their colour have also been modified according to
the requirements of particular sports. The most used
versions of the Agility test are as follows: a) using two
mats for forehand and backhand movements in tennis
players, b) moving shorter distances for karate com-
petitors and longer distances for basketball players, c)
responding to the same stimulus located in four corners
for ice-hockey players and to stimuli of different forms
or colors located in a semi-circle for ice-hockey goalies,
d) touching the mats with the lower limbs for soccer
players and with upper limbs for basketball players, and
e) using a smaller target for karate competitors and big-
ger target for basketball players (Zemková & Hamar,
2013). Another example is the test for goalkeepers con-
sisting of two stimuli for the upper limbs and two stim-
uli for the lower limbs. Experience has shown that the
assessment of agility performance under sport-specific
conditions represents a more appropriate alternative
than the original version of the Agility test.
Measurements of simple and multi-choice reaction
times and of movement time may provide additional
information on the components of agility performance.
In the Reaction test, the participant may respond to
either one (simple reaction time) or more stimuli of
different forms or colors (multi-choice reaction time).
Decision time has a strong influence on total agility
time and therefore perceptual skill should be addressed
in agility testing and training. Young and Willey (2009)
found that of the three components that make up the
total time, decision time had the highest correlation
(r = .77, p < .001) with the total time. This correlation
with total time was greater than for response move-
ment time (r = .59) or tester time (r = .37), indicating
that decision time was the most influential of the test
components for explaining the variability in total time.
The decision time component within the reactive test
condition also revealed that the highly-skilled players
made significantly faster decisions than the lesser-
skilled players (Farrow, Young, & Bruce, 2005). The
results of Gabbett and Benton (2009) also demonstrate
that the decision and movement times on the Reactive
agility test were faster in higher-skilled players, with-
out compromising response accuracy. It is therefore of
practical significance to assess the perceptual compo-
nents of agility performance.
A new approach in the functional assessment of
athletes is the testing of agility skills under simulated
competitive conditions. It has been found that agility
time is better when the Agility test is performed in sim-
ulated competitive (Agility dual), rather than non-com-
petitive (Agility single) conditions (Zemková, Vilman,
Kováčiková, & Hamar, 2013). An Agility test in the
form of simulated competition should be preferred for
children and young athletes in order to enhance their
arousal level and motivation. Such an exercise may also
represent an appropriate means for agility training, par-
ticularly in young athletes (Zemková, 2012).
Recently, Kováčiko (2012) evaluated the changes
in reaction and speed abilities after 8 weeks of agility
training under simulated competitive and non-compet-
itive conditions. A group of 22 fit young men, divided
into two experimental groups, underwent the same agil-
ity training (two times a week for 30 minutes). How-
ever, while experimental group 1 performed the train-
ing in the form of simulated competition (i.e., either in
pairs or in a group), experimental group 2 performed
the same training under non-competitive conditions.
Prior to and after the training, agility times in the tests
of Agility single and Agility dual were measured. Addi-
tionally, simple reaction time, multi-choice reaction
time, maximal velocity of step initiation, frequency of
movement of the lower limbs, power in the concentric
phase of take off in a 10 second test of repeated jumps,
jump height, and contact time after drop jump were
measured. After 8 weeks of agility training, a more
139
Agility performance in athletes of different sport specializations
pronounced improvement of agility time was found in
the test of Agility dual in the group trained in the form
of simulated competition than in the group that carried
out the same training, but without competitive compo-
nents (18% and –0.6%, respectively). However, there
were no significant differences in the changes of other
parameters of reaction and speed abilities after train-
ing under simulated competitive and non-competitive
conditions. These findings indicate that agility training
performed in the form of simulated competition rep-
resents a more effective means for the improvement
of agility skills than the same training under non-com-
petitive conditions. However, such a training does not
contribute to more pronounced improvement of other
reaction or speed abilities.
Since agility skills represent a crucial part of per-
formance in many sports, their assessment should be
considered an integral part of the functional testing of
athletes. Data on agility skills in different populations
using pre-planned, change-of-direction speed tests have
been reported. However, there were no available data
on agility times in different sports obtained from Reac-
tive agility tests. This is the first study that provides
data on the agility time in the Reactive agility test of
athletes of different sport specializations.
Conclusions
The Agility test discriminates between groups of ath-
letes with different demands on their agility skills. The
best agility times have been found in athletes of racquet
sports, followed by competitors of combat sports with
reactions to visual stimuli, then players of ball sports,
and finally competitors of combat sports with reactions
to tactile stimuli. These data on agility times in different
sports can be used for the decision making process in
related sports, enabling comparisons to be made with
individual athlete data and changes in the data during
training. Taking into account significantly better agility
time in athletes responding to visual rather than tactile
stimuli, the Agility test may be recommended primar-
ily for athletes used to responding to various forms of
visual stimuli (e.g., the ball).
Acknowledgment
This study was supported through a Scientific Grant
Agency of the Ministry of Education of Slovak Republic
and the Slovak Academy of Sciences (No. 1/0373/14).
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competitive and non-competitive conditions. Journal of
Strength and Conditioning Research, 27, 3445–3449.
... Yakın zamanda yapılan geniş örneklemli bir çalışma, 553 katılımcı üzerinde bir uyarana karşı yanıt olarak reaksiyon süresini farklı yaş gruplarında gözlemlemiştir. 23 Katılımcılar, bilgisayar ekranı tarafından oluşturulan görsel uyaranlara (arka sağ veya sol ve ön sağ veya sol) göre 0,55 m 2 lik bir karenin köşelerine yerleştirilmiş 4 adet mata dokundukları bir antrenman protokolü uygulamışlardır. Bu çalışmada, 7-14 yaşları arasındaki sporcularda, daha büyük yaştaki sporculara kıyasla daha büyük gelişmeler gözlemlemiştir. ...
... Bu çalışmada, 7-14 yaşları arasındaki sporcularda, daha büyük yaştaki sporculara kıyasla daha büyük gelişmeler gözlemlemiştir. 23 Sonuç olarak yazarlar, genel algısal bileşenlere dayalı reaksiyon becerilerinin puberte öncesi dönemde etkili bir şekilde eğitilebilir olacağını belirtmişlerdir. Sekiz haftalık SÇÇ antrenman protokolümüzde, ayna ve gölge çalışmalarına yer vermemizin, çeviklik performansını ölçme amaçlı RÇT'yi tercih etmemizin sebebi; sporcuların reaksiyon, algısal bileşenler ile karar verme becerilerini geliştirmek ve ölçmek, branşın ihtiyaçlarını karşılamaktır. ...
... Age-appropriate speed-agility training recommendations are largely speculative due to the low amount of literature in this area (Jeffreys, 2019). Data from several different studies suggest that agility performance naturally improves with age (in addition to training), but especially from childhood to adolescence according to (Zemková & Hamar, 2014). Adaptation of training to improve speed & agility is not attributed only to the influences of exposed training stimuli but also to the natural processes of development of young athletes according to the authors (Harrison & McGuigan, 2019). ...
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It is known that children of the same chronological age show differences in biological growth. For better results, it is important for coaches and sports scientists to understand how age influences physical and physiological performance in sports. Methodology; this systematic search was used to conduct on the influence of age on the development of speed and agility components in 10-14-year-old male soccer and basketball players. Identification of study sources: Academic databases such as PubMed, Google Scholar and SPORT Discus were used to search for relevant articles in the last 10 years. Keywords and phrases included "age and sports performance," "speed and agility development," "youth". Results; in total, 60 studies or scientific articles that fit the inclusion criteria in our study were reviewed. Data were collected and organized into thematic sections, including motor skills, body shape, injury risk, and training programs. Within each section, studies were grouped based on focus and key findings. Conclusions Following this systematic methodology, this literature review aims to provide a broad and evidence-based assessment of how age affects the development of speed and agility skills in 10 - 14 year old male players. This literature review highlights the importance of age-appropriate training.
... Different sports prioritize different aspects of conditioning programme, but it remains a fundamental factor for improved athletic performance (Lee et al., 2020). Sports that require rapid directional changes, such as American football and basketball, place a high emphasis on agility (Zemková & Hamar, 2014). Moreover, optimum motor fitness in youth can foster lifelong physical activity habits, reducing the risks associated with sedentary lifestyles (Lubans et al., 2010). ...
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Background. Motor fitness is one of the keys to athletes’ success and is the initial factor mixed with game-specific technique and tactics that has an impact on game performance. All athletes should incorporate these elements into their sport and game actions. Study purpose. The aim of this study was to evaluate differences in motor fitness metrics among university-level male athletes participating in various sports. Materials and methods. Sixty (60) male athletes, ranging in age from 18 to 25 years, were selected from six different sports: Athletics, Basketball, Cricket, Football, Handball, and Volleyball. Each group consisted of 10 athletes who had competed at the inter-university level. The research focused on six key fitness metrics: agility, speed, power, arm strength, abdominal muscle strength, and cardiovascular endurance. Appropriate testing methods and instruments were used to measure these parameters. Statistical analysis, including one-way ANOVA and post hoc LSD tests, was performed to identify significant differences between the groups. A significance level of 0.05 was set for the study. Results. The results showed statistically significant differences among the groups in agility (F(5,54) = 4.776, p<0.001), speed (F(5,54) = 5.602, p<0.000), and cardiovascular endurance (F(5,54) = 3.578, p<0.007). However, no significant differences were observed for power (F(5,54) = 2.079, p>0.082), arm strength (F(5,54) = 1.368, p>0.251), and abdominal muscle strength (F(5,54) = 1.947, p>0.102). According to the post hoc (LSD) test findings, each group’s agility, speed, and cardiovascular endurance parameters were compared to each other to check the significance level. Conclusions. In summary, the study has revealed that agility, speed, and cardiovascular endurance were significantly different among athletes in various sports, whereas power, arm strength, and abdominal muscle strength were not. The findings suggest that athletes and coaches should prioritize sport-specific fitness components to improve game performance.
... Speed, or the ability to move quickly, is one of the most important bio-motor skills needed in sports from a mechanical perspective; speed is defined as the ratio of space to time [11] . Agility abilities that require three stages of information processing-stimulus perception, response choice, and movement execution-are crucial to success in many sports [12] . The crucial motor skills needed in every game to enhance performances are speed and agility. ...
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The purpose of the present study was to compare the selected physical fitness components among team game players. The age range of the 40 male subjects for the current study was 18 to 25 years. 20 football and 20 handball players were chosen as subjects from the Murshidabad district in West Bengal, India. The variables chosen for this study were agility and speed. The information was gathered by administering the tests for agility (10x4 meter shuttle run) and speed (50-meter dash). Descriptive analysis and an independent t-test with a significance level of 0.05 were used to compare the means of the physical fitness components. According to the findings of this study, there were no significant differences found in speed and agility between football and handball players. Based on the results, it was determined that football and handball players have almost the same fitness capacity for speed and agility.
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Successful performance in each sport requires high ability in various features, including motor and perceptual-cognitive skills. This study aimed to compare the balance and agility in athletes from several sports branches to find out how cognitive functions relate to these parameters. Seventy-three individuals aged 18-30 were included in this prospective-descriptive study. In the assessment of cognition, Montreal Cognitive Assessment Scale, d2 Test of Attention, and a Bassin Anticipation Timer Device were used. While Prokin-TecnoBody was used to measure the balance skills, Illinois Agility Test (IAT) was used for agility. IAT times showed positive weak correlations with both the absolute error-score (AES) at 8mph (r=0.260, p=0.040) and mediolateral balance score (ML)(r=0.255, p=0.043). While there was a negative weak correlation between AES at 3mph and anteroposterior score of balance (r=-0.267, p=0.035), we found positive weak correlation between AES at 8mph and ML of balance (r=0.253, p=0.046). It was found that the IAT scores of the sedentary group were significantly lower than athletes (p=0.000). According to AES at 3mph, there were significant differences between tennis players and both sedentary and volleyball players (p=0.008, p=0.002, respectively). When the AES at 8mph compared, the only statistically significant difference was between tennis players and sedentary (p=0.008). In conclusion, this study shows how cognitive functions, particularly coincidence anticipation timing (CAT), correlate with essential physical performance factors like agility and balance across different sport branches, suggesting that improving cognitive skills could enhance overall athletic performance and inform mental training strategies in sports. It is recommended that future sports science research focus on enhancing CAT through targeted training programs.
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This study aimed to analyze the relationships between weekly training frequency, changes in training duration, and maximal aerobic speed (MAS), maximum oxygen uptake (VO2max), and isokinetic strength over an 8-week period (pre-season 8 weeks). Eighteen hearing-impaired handball players (26.78±2.26 years old) were positioned in defense and offense based on their playing positions and were monitored for 8 weeks. The statistical analysis of the data was conducted using the SPSS 22.0 software package. Repeated Measures ANOVA test was performed for the pre-test and post-test comparisons of defense and offense players. The analysis results revealed a significant large positive difference in the agonist/antagonist ratio in the right extremity. Throughout the study, fluctuating changes in the numbers and durations of training sessions were observed to significantly increase and correlate with changes in the players' fitness status. However, the variability in the large positive difference in the agonist/antagonist ratio in the right extremity suggests that it cannot be solely explained by the number and duration of training sessions in terms of fitness level.
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Introduction: Nutrition is very important in any sport because it is the main source of energy required to perform the activity. The food eaten directly impacts strength, training, performance, and recovery. Also, fatigue can lead to poor performance and therefore appropriate nutrition can help in reducing fatigue. Hence basic understanding of nutrition is necessary to understand and apply the principles of sports nutrition. Athletes should have proper nutritional status with support of good physical fitness. Objective: To assess the Nutritional status, Physical fitness and Anthropometric parameters of judo players of Belagavi district. Methodology: 24 participants were enrolled in the study. Data to assess physical fitness, anthropometric parameters and nutritional status were obtained by using pre designed questionnaire. Data was analyzed using SPSS software and was tabulated using percent. Results: The study resulted that most of the players were normal weight which is most required in this area.. The nutritional evaluation of the players had shown that the diet was in adequate in nutrients for some players and excess for some players. Conclusion: In conclusion to the study conducted, it was observed that physical components were not discriminatory to success. The anthropometry had a minimal effect on the game.
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Bu araştırmanın amacı rekreatif bir etkinlik olarak tekerlekli patenin bireylerde denge ve çeviklik üzerine etkisinin incelenmesidir. Çalışmaya Manisa Celal Bayar Üniversitesi (MCBÜ), Spor Bilimleri Fakültesinde (SBF) birinci sınıfta okuyan ve daha önce hiç paten, tekerlekli paten kaykay deneyimi olmayan 17 erkek, 13 kadın olmak üzere toplam 30 üniversite öğrencisi katılmıştır. Katılımcıların 15’i deney grubu (7 erkek yaş ort.=19,14 ± 1,06, 8 kadın yaş ort.=18,75 ± 0,70) ve 15’i kontrol grubu (10 erkek yaş ort.=18,6 ± 0,69, 5 kadın yaş ort.= 18,6 ± 0,89) olarak ikiye ayrılmıştır. Kontrol grubu hiçbir aktiviteye katılmamış olup, deney grubu 8 hafta boyunca haftada 3 gün tekerlekli paten antrenmanı yapmıştır. 8 haftalık antrenman programı öncesi ve sonrasında katılımcılara boy, kilo ölçümü, Y denge testi ve T çeviklik testi uygulanmıştır. Ön ve son testte elde edilen veriler, istatistik paket programı ile değerlendirilmiş ve anlamlılık düzeyi p
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The purpose of this study was to examine the test-retest reliability, and convergent and discriminative validity of a new taekwondo-specific change-of-direction (COD) speed test with striking techniques (TST) in elite taekwondo athletes. Twenty (10 males and 10 females) elite (athletes who compete at national level) and top-elite (athletes who compete at national and international level) taekwondo athletes with an average training background of 8.9 ± 1.3 years of systematic taekwondo training participated in this study. During the two-week test-retest period, various generic performance tests measuring COD speed, balance, speed, and jump performance were carried out during the first week and as a retest during the second week. Three TST trials were conducted with each athlete and the best trial was used for further analyses. The relevant performance measure derived from the TST was the time with striking penalty (TST-TSP). TST-TSP performances amounted to 10.57 ± 1.08 s for males and 11.74 ± 1.34 s for females. The reliability analysis of the TST performance was conducted after logarithmic transformation, in order to address the problem of heteroscedasticity. In both groups, the TST demonstrated a high relative test-retest reliability (intraclass correlation coefficients and 90% compatibility limits were 0.80 and 0.47 to 0.93, respectively). For absolute reliability, the TST’s typical error of measurement (TEM), 90% compatibility limits, and magnitudes were 4.6%, 3.4 to 7.7, for males, and 5.4%, 3.9 to 9.0, for females. The homogeneous sample of taekwondo athletes meant that the TST’s TEM exceeded the usual smallest important change (SIC) with 0.2 effect size in the two groups. The new test showed mostly very large correlations with linear sprint speed (r = 0.71 to 0.85) and dynamic balance (r = −0.71 and −0.74), large correlations with COD speed (r = 0.57 to 0.60) and vertical jump performance (r = −0.50 to −0.65), and moderate correlations with horizontal jump performance (r = −0.34 to −0.45) and static balance (r = −0.39 to −0.44). Top-elite athletes showed better TST performances than elite counterparts. Receiver operating characteristic analysis indicated that the TST effectively discriminated between top-elite and elite taekwondo athletes. In conclusion, the TST is a valid, and sensitive test to evaluate the COD speed with taekwondo specific skills, and reliable when considering ICC and TEM. Although the usefulness of the TST is questioned to detect small performance changes in the present population, the TST can detect moderate changes in taekwondo-specific COD speed.
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The study deals with a variety of sport-specific testing of agility performance. Altogether, 178 young, fit subjects performed an agility test under various conditions. Their task was to touch as fast as possible, with either the left or the right lower limb, one of the four mats located in four corners outside of 0.8 m square. Mats had to be touched in accordance with the location of the stimulus in one of the corners of the screen. The original version of the test consisted of 60 visual stimuli with random generation of their location on the screen and time generation from 500 to 2500 ms. The result was total agility time (AT) measured by a PC-based system FiTRO Agility Check. The modified versions of the agility test varied in a) number of contact mats (2, and 4), b) distance between mats and subject (0.4, 0.8, 1.6, and 3.2 m), c) their alignment (square, and semi-arch), d) positioning (underfoot, and aloft of thorax), and e) size (6.5 x 6.5 cm, and 35 x 35 cm). Also number of stimuli, their time of generation, and color were modified according to a particular sport. It has been shown that assessment of agility performance in many sports requires a specific approach. The most used versions of the agility test are as follows: a) using two mats for forehand and backhand movements of tennis players, b) moving shorter distances for karate competitors and longer distances for basketball players, c) responding to the same stimulus located in four corners for ice-hockey players and to stimuli of different forms or colors located in semi-arch for ice-hockey goalies, d) touching the mats with lower limbs for soccer players and with upper limbs for basketball players, e) using small size of the target for karate competitors and bigger target for basketball players. Another example is the test for goalkeepers consisting of two stimuli for upper and two stimuli for lower limbs. Experience showed that assessment of agility performance under sport-specific conditions represents a more appropriate alternative than the original version of the agility test.
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The study evaluates a reaction time in the Agility Test under simulated competitive and non-competitive conditions. A group of 16 fit men performed, in random order, two versions of the Agility Test: non-competitive Agility Single and Agility Dual in form of simulated competition. In both cases, subjects had to touch, as fast as possible, with either the left or the right foot one of four mats located in four corners outside of a 80 cm square. Mats had to be touched in accordance with the location of the stimulus in one of the corners of the screen. The test consisted of 20 visual stimuli with random generation of their location on the screen and time generation from 500 to 2500 ms. The result was total reaction time (RT) for all 20 reactions measured by a PC based system FiTRO Agility Check. Results showed significantly (p < 0.01) better RT in the Agility Dual than in the Agility Single Test (690.6 ± 83.8 ms and 805.8 ± 101.1 ms, respectively). Further comparisons of RT under non-competitive and simulated competitive conditions for the best eight subjects proceeded in the second match showed a decrease from 781.3 ± 111.2 ms to 693.6 ± 97.8 ms in the 1 match and to 637.0 ± 53.0 ms in the 2 match. It may be concluded that reaction time is better when the Agility Test is performed in simulated competitive than non-competitive conditions. The Agility Test in form of competition may be used for children and young athletes in order to enhance their attention level and motivation.
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The purpose of this study was to evaluate the reliability and validity of a new test of agility, the reactive agility test (RAT), which included anticipation and decision-making components in response to the movements of a tester. Thirty-eight Australian football players took part in the study, categorized into either a higher performance group (HPG) (n=24) or lower performance group (LPG) (n=14) based on playing level from the previous season. All participants undertook testing of a 10m straight sprint (10mSS), a 8-9m change of direction speed test (CODST), and the RAT. Test-retest and inter-tester reliability testing measures were conducted with the LPG. The intra-class correlation (ICC) of the RAT was 0.870, with no significant (p<0.05) difference between the test results obtained on the first and second test sessions using a t-test. A dependent samples t-test revealed no significant (p<0.05) difference between the test results of two different testers with the same population. The HPG were significantly (p=0.001) superior to those of the LPG on the RAT, with no differences observed on any other variable. The RAT is an acceptably reliable test when considering both test-retest reliability, as well as inter-rater reliability. In addition, the test was valid in distinguishing between players of differing performance level in Australian football, while the 10mSS and CODST were not. This result suggests that traditional closed skill sprint and sprint with direction change tests may not adequately distinguish between players of different levels of competition in Australian football.
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At present, no agreement on a precise definition of agility within the sports science community exists. The term is applied to a broad range of sport contexts, but with such great inconsistency, it further complicates our understanding of what trainable components may enhance agility. A new definition of agility is proposed: "a rapid whole-body movement with change of velocity or direction in response to a stimulus". Agility has relationships with trainable physical qualities such as strength, power and technique, as well as cognitive components such as visual-scanning techniques, visual-scanning speed and anticipation. Agility testing is generally confined to tests of physical components such as change of direction speed, or cognitive components such as anticipation and pattern recognition. New tests of agility that combine physical and cognitive measures are encouraged.
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While studies have investigated change of direction speed in rugby league players, no study has investigated the reactive agility of these athletes. The purpose of this study was to investigate the reactive agility of rugby league players, to determine if this quality discriminated higher and lesser skilled players. Twenty-four elite (mean+/-S.D. age, 24.5+/-4.2 years) and 42 sub-elite (23.6+/-5.3 years) rugby league players completed a game-specific test of reactive agility. Elite players had better response accuracy (93.2+/-1.9% vs. 85.5+/-2.5%; p<0.05, effect size=0.58) and faster decision (89.5+/-5.8ms vs. 111.5+/-6.4ms; p<0.05, effect size=0.62) and movement times (2.35+/-0.03s vs. 2.56+/-0.03s; p<0.05, effect size=1.39) on the reactive agility test than sub-elite players. The reactive agility test was able to distinguish four distinct classifications. Specifically, players were classified as requiring either (1) decision-making and change of direction speed training to further consolidate good physical and perceptual abilities, (2) decision-making training to develop below average perceptual abilities, (3) change of direction speed training to develop below average physical attributes or (4) a combination of decision-making and change of direction speed training to develop below average physical and perceptual abilities. The results of this study demonstrate that a test of reactive agility discriminates higher and lesser skilled rugby league players. In addition, these findings highlight the important contribution of perceptual skill to agility in rugby league players.
Article
This study compares agility times in groups aged from 7 to 18 years. Altogether 553 subjects performed an agility test. Their task was to touch, as quickly as possible, with either the left or the right foot, one of four mats located in the four corners outside of a 0.55 m square. The mats had to be touched in accordance with the location of a stimulus in one of the corners of a screen. The result was a sum of 32 multi-choice agility times, in four directions, measured by means of the computer-based system FiTRO Agility Check. A decrease in agility time from childhood to adult age has been found. There was a rather steep decrease in agility time from 7 to 10 years of age (27.1%) and from 10 to 14 years of age (26.5%). Afterwards, there was a slow decrease during puberty, from age 14 to 18 (16.5%). It may be concluded that agility time decreases with increasing age up to early maturity. Since this is the first study testing agility skills by means of the Reactive Agility Test, the obtained data can be used as a set of reference values for comparison with subjects of particular ages.
Conference Paper
Agility skills are characterized by three information-processing stages: stimulus perception, response selection, and movement execution. These skills represent a crucial part of performance in many sports. Therefore, their assessment should be considered as an integral part of functional testing in young and professional athletes. For this purpose, the Agility test has been used. The task of the subjects is to touch as fast as possible, with either the left or the right lower limb, one of the four contact mats located in four corners of the square in accordance with the location of the stimulus in one of the corners of the screen. The result is total reaction time (RT) and RT in each direction of movement measured by the system FiTRO Agility Check (FiTRONiC s.r.o., SK). The system allows a number of test settings varying in time generation (constant or random), number of stimuli, their forms and colors, as well as background color. During the years of practice, several sport-specific versions of the Agility test have been created, including the variability with number of stimuli, distances between mats, number of mats, positioning of mats, foot and hand responses, sizes of the target, and so forth. Nevertheless, there seems to be also possibilities to include the Agility test into the testing batteries assessing physical performance of children and youth. In doing so, the reaction times in groups of subjects from 7 to 18 years have been provided. For children, the Agility test in form of competition should be preferred in order to enhance their arousal level and motivation. The talk will address the complexity of evaluating agility performance while providing a sport-specific approach under various testing conditions. It will also deals with a wide variety of practical examples and implications for teaching, learning, and performing agility skills. More information on assessing agility skills in sport practice and possibly also in physical education can be found in book ”Toward an understanding of agility performance” (Zemková & Hamar, 2009).
Book
The book addresses the complexity of evaluating agility performance while providing a sport-specific approach under various testing conditions. The book also offers a wide variety of practical examples and implications for teaching, learning, and performing agility skills.
Article
The purpose of this research was to evaluate a reactive agility test by determining the relationships between the total time recorded for the test and various components. A tester used side-step movements to provide a stimulus for the athlete to change direction. By using electronic timing and high speed video analysis of the test, three times were recorded. These were the time taken for the tester to display the stimulus to change direction (tester time), the time taken by the participant to respond to the stimulus (decision time), and the time taken by the participant to change direction and sprint to the left or right (response movement time). Thirty-one semi-professional Australian Rules football players were assessed by analysing the mean of eight trials of the reactive agility test. The greatest correlation with total time was r=0.77 for decision time (p=0.00), with movement time and tester time producing coefficients of 0.59 (p=0.00) and 0.37 (p=0.04), respectively. The coefficient of variation for the mean tester time was 5.1%. It was concluded that perceptual skill as measured by decision time is an important component of the reactive agility test and the tester time should be controlled by using high speed video recordings to isolate its influence.
Article
The purpose of this study was to present a new methodology for the measurement of agility for netball that is considered more ecologically valid than previous agility tests. Specifically, the agility performance of highly-skilled (n = 12), moderately-skilled (n = 12) and lesser-skilled players (n = 8) when responding to a life-size, interactive video display of a netball player initiating a pass was compared to a traditional, pre-planned agility movement where no external stimulus was present. The total movement times and decision times of the players were the primary dependent measures of interest. A second purpose of the research was to determine the test-retest reliability of the testing approach. Results revealed significant differences existed between the 2 test conditions demonstrating that they were measuring different types of agility. The highly-skilled group was significantly faster in both the reactive and planned test conditions relative to the lesser-skilled group, while the moderately-skilled group was significantly faster than the lesser-skilled group in the reactive test condition. The decision time component within the reactive test condition revealed that the highly-skilled players made significantly faster decisions than the lesser-skilled players. It is reasoned that it is this decision-making component of reactive agility that contributes to the significant differences between the two test conditions. The testing approach was shown to have good test-retest reliability with an intra-class correlation of r = .83.