ArticlePDF Available

Abstract and Figures

Most change of direction (COD) tests use total time to evaluate COD performance. This makes it difficult to identify COD ability, since the majority of time is a function of linear running. The COD deficit has been proposed as a practical measure to isolate COD ability independent of sprint speed. This study evaluated relationships between sprint time, 505 time and COD deficit, and whether the COD deficit identified a different and more isolated measure of COD ability compared to 505 time. Seventeen cricketers performed the 505 for both left and right sides, and 30 m sprint tests (with 10 m split time). The COD deficit for both sides was calculated as the difference between average 505 and 10 m time. Correlations were calculated between all variables (p < 0.05). To compare 505 time and COD deficit, z-scores were calculated; the difference in these scores were evaluated for each subject. The COD deficit correlated to 505 (r = 0.74-0.81) but not sprint time (r = -0.11-0.10). In contrast, 505 time did correlate with sprint time (r = 0.52-0.70). Five of seventeen subjects were classified differently for COD ability when comparing standardized scores for 505 time versus COD deficit. The majority of subjects (88-94%) had a meaningful difference between 505 time and COD deficit. Using 505 time to determine COD ability may result in a large amount of replication to linear speed assessments. The COD deficit may be a practical tool to better isolate and identify an athlete's ability to change direction.
Content may be subject to copyright.
Centre for Exercise and Sport Science, School of Exercise and Health Sciences, Edith Cowan University, Joondalup, Australia;
School of Health Sciences, The Notre Dame University Australia, Fremantle, Australia;
Department of Kinesiology, California
State University, Northridge, California; and
Hurley Surfing Australia High Performance Centre, Casuarina, Australia
Nimphius, S, Callaghan, SJ, Spiteri, T, and Lockie, RG. Change
of direction deficit: A more isolated measure of change of
direction performance than total 505 time. J Strength Cond
Res 30 (11): 3024–3032, 2016—Most change of direction
(COD) tests use total time to evaluate COD performance. This
makes it difficult to identify COD ability because the majority of
time is a function of linear running. The COD deficit has been
proposed as a practical measure to isolate COD ability inde-
pendent of sprint speed. This study evaluated relationships
between sprint time, 505 time, and COD deficit, and whether
the COD deficit identified a different and more isolated mea-
sure of COD ability compared with 505 time. Seventeen crick-
eters performed the 505 for both left and right sides and 30-m
sprint tests (with 10-m split time). The COD deficit for both
sides was calculated as the difference between average 505
and 10-m time. Correlations were calculated between all vari-
ables (p#0.05). To compare 505 time and COD deficit,
z-scores were calculated; the difference in these scores was
evaluated for each subject. The COD deficit correlated to 505
(r= 0.74–0.81) but not sprint time (r=20.11 to 0.10). In
contrast, 505 time did correlate with sprint time (r= 0.52–
0.70). Five of 17 subjects were classified differently for COD
ability when comparing standardized scores for 505 time vs.
COD deficit. Most subjects (88–94%) had a meaningful differ-
ence between 505 time and COD deficit. Using 505 time to
determine COD ability may result in a large amount of replica-
tion to linear speed assessments. The COD deficit may be
a practical tool to better isolate and identify an athlete’s ability
to change direction.
KEY WORDS agility, linear speed, athletic testing, cricket,
Change of direction (COD) speed forms the phys-
ical foundation for agility, as it incorporates the
mechanics associated with agility performance
(i.e., the deceleration, directional change, and
acceleration) (36) while allowing for progression from lower
joint loading received in the preplanned movements before
training the higher joint loadings that must be handled dur-
ing agility (2). Because of the importance of using COD
movements to build the physical platform before performing
agility, many field and court sport athletes, strength and
conditioning coaches seek to use appropriate tests to accu-
rately isolate and measure the physical quality of changing
direction. A variety of assessments have been adopted by
coaches to assess COD ability (3,35,36). Some examples
include the proagility shuttle (27,31,37,42,43), 3-cone drill
or L-run (11,31,37), T-test (16,30,33), and Illinois agility test
(IAT) (16,22,43,44). It would be assumed that these COD
tests intend to provide a valid assessment, specifically, the
assessment of one’s ability to both decelerate and reacceler-
ate for a given directional change. The inclusion of any addi-
tional components to those mentioned above begin to assess
other physical qualities (e.g., acceleration and maximal
velocity), removing the emphasis from COD ability.
Therefore, the aforementioned tests are not without their
limitations. First, the inherent movement patterns during
certain assessments contain actions that are not necessarily
specific to the COD patterns within particular sports. For
example, the proagility test has been adopted for football
(27,31,37) and soccer (42,43), yet the movements within the
assessment (3 side-to-side runs within a 10-yard distance) do
not match the CODs typically performed in each sport. This
is also true for the 3-cone drill (5 CODs while running in the
shape of an “L”), which is also popular for American football
(31,37), and has been used in rugby league (11). In addition to
this, if a COD test is too long in duration, then, there is less
emphasis on COD ability and more on anaerobic capacity
and linear sprinting ability (43). For example, the 3-cone drill
can have a duration of approximately 7–8 seconds when com-
pleted by collegiate football players (37). The T-test can last
Address correspondence to Sophia Nimphius,
Journal of Strength and Conditioning Research
Ó2016 National Strength and Conditioning Association
Journal of Strength and Conditioning Research
Copyright © National Strength and Conditioning Association Unauthorized reproduction of this article is prohibited.
up to 10–12 seconds (21,30,33), whereas the IAT is typically
completed in 14–18 seconds (16,22,43,44) by athletic popula-
tions. Potentially, this could result in metabolic limitations
influencing the performance of these tests (43), without the
provision of appropriate information about COD ability.
A test that restricts many of these limitations is the 505,
which is another popular assessment of COD ability (40). The
505 traditionally involves a 10-m sprint past a timing gate,
a further 5-m sprint to a turning line where 1 leg needs to
reach and plant at this line, before the athlete completes a 1808
turn and sprints back through the timing gate (Figure 1). The
action of the 1808COD is physically demanding, and can
isolate horizontal plane COD ability (6), and has been identi-
fied as a reliable test (11,34,40). The 505 can also be used to
investigate as the COD ability for each leg (17,18,28,29), which
is an important consideration for athletes, as most athletes
strive toward achieving a balance between the legs in
power-based activities (17). Consequently, this test has been
administered for a range of athletes from sports, such as rugby
league (11), soccer (24), netball (9), basketball (41), softball
(28,29), and cricket (18). The use of the 505 with cricketers
is notable. The action of running between the wickets in this
sport involves a 1808turn (7,15,18,23). As evidence of the
importance of this COD, when batsmen score 100 runs during
a match, they will be required to complete approximately
forty 1808turns during their innings (7). For this population,
the 505 is very specific to actions they would produce during
a match (18,38).
The duration of the 505 is relatively short (approximately
2–3 seconds) (17,18,28,29,34), which means that it should
place a greater emphasis on COD ability. However, using
the time as a measure from a test such as the 505 may not
necessarily represent the COD ability of an athlete (34).
Nimphius et al. (27) originally stated that because of the
design of the 505 test, approximately 31% of the time is spent
actually changing direction. Therefore, a majority of the total
time to complete the test can be explained by an athlete’s
acceleration ability (27). Simply stated, an athlete who is fast
linearly may still perform well in a COD test, as their sprint-
ing ability could mask any deficiencies in COD ability. This
concept is supported by research that has found large
correlations between linear and COD speed tests
(11,22,30,34,43), although it is widely acknowledged that
they are different skills (32,43,45). Rather than measuring
time in the traditional manner within the 505, (34) suggested
that COD speed should be measured over shorter distances,
such as within the first meter after the COD. However, there
are practical issues with using this approach. If a coach is
using timing gates in the field over such short distance (i.e.,
1 m or less), the light beam may be broken purely because of
the athlete’s forward lean within the COD. In addition to
this, the reliability of times measured in a COD speed de-
creases when the distances are reduced (34), which influen-
ces how the data can be interpreted by a coach. Therefore, it
would be useful for strength and conditioning coaches to be
able to use the time measured during the traditional 505, but
be able to interpret them in such a way that better isolates
COD ability.
One such solution is the COD deficit that is a procedure
proposed by Nimphius et al. (27). The COD deficit docu-
ments the effect or additional time that one directional
change requires when compared with a pure linear sprint
over an equivalent distance. This measure was initially inves-
tigated in Division IA collegiate football players, whereby
COD deficit was calculated as the difference between the
10-yard split time during a 40-yard sprint, and the 10-yard
split with a 1808cut that was measured within the first half of
the proagility shuttle (27). Nimphius et al. (27) proposed that
the average COD deficit time (0.72 60.08 seconds) calcu-
lated from the first half of the proagility shuttle (2.29 60.17
seconds) was the duration required to add a single COD
within a 10-yard distance. In addition to this, although the
Figure 1. Structure and dimensions of the 505 change of direction test.
Journal of Strength and Conditioning Research
VOLUME 30 | NUMBER 11 | NOVEMBER 2016 | 3025
Copyright © National Strength and Conditioning Association Unauthorized reproduction of this article is prohibited.
COD deficit correlated with the modified proagility test
times (first 10-yard split and total time), the explained vari-
ance was low (29–37%). Conversely, when these variables
were assessed through a partial correlation with sprint time
over 10 yards as the controlled variable, the explained vari-
ance was much higher (89%). These data suggest that COD
deficit potentially provides a measure of COD ability inde-
pendent of linear speed. Given the nature of the 505, the
COD deficit could be directly applied to this test. However,
the value of doing so, and whether this provides a different
magnitude of COD ability rather than just 505 time alone,
must be confirmed.
Therefore, this study investigated the COD deficit in an
athletic population. Experienced cricketers were selected
because of the importance of 1808direction changes in
their sport and thus a necessity for them to be proficient
in this action (7,15,18,23). There were 2 purposes for this
research. The first purpose was to evaluate the relation-
ship between measures of linear speed (10- and 30-m
sprint times), COD time measured by the 505, and COD
deficit. Second, this study sought to determine whether
the COD deficit identified a different magnitude of COD
ability of individuals in comparison with the traditional
total time for completion of the 505 COD test. It was
hypothesized that the correlations and explained variance
would illustrate that the COD deficit provided a different
measure of COD ability. Furthermore, analysis of stan-
dardized scores would document that the COD deficit
identified a different magnitude of COD ability when
compared with total 505 test time for both the preferred
and nonpreferred sides.
Experimental Approach to the Problem
The study investigated the COD deficit as measured by the
505 in experienced cricketers. A cross-sectional analysis was
conducted, and Pearson’s correlations were used to determine
the relationship between the 505 times and COD deficits for
each side and 10- and 30-m sprint times. Standardized
(z-score) 505 times and COD deficits for each side were used
to determine whether scores for each subject were meaning-
fully different from the group mean.
Seventeen experienced male cricketers (age = 24.4 65.0
years; height = 1.84 60.1 m; mass = 86.9 613.9 kg), who
currently played first grade cricket in a regional competi-
tion in Australia, were recruited for this study. This subject
number is similar to previous research that analyzed linear
and COD speed in cricketers (5,15,18,23), and the sample
size of 16 estimated using G*Power (alpha = 0.05; beta =
0.80) (10) to find similar explained variance in previous
research between a COD test and COD deficit (27). Sub-
jects were recruited if they: were currently playing first
grade cricket in the regional competition; had at least 5
years of experience playing cricket; had a general cricket
training history ($2times$wk
) extending over the pre-
vious 12 months; were currently training for cricket ($3
); and did not have any existing medical conditions
that would compromise participation in the study. The
methodology and procedures used in this study were
approved by the institutional ethics committee. All sub-
jects received a clear explanation of the study, including
the risks and benefits of participation, and written
informed consent and assent (if required) was provided
before testing.
One testing session was used in this study, whereby
subjects completed 30-m sprints and 505 trials, turning off
both the left and right foot. All subjects were familiar with
the tests used in this study. Testing was conducted in the
biomechanics laboratory, with a textured concrete surface,
at the university. Testing was conducted during the middle
of the cricket season, and sessions were scheduled in the
afternoon or early evening. Subjects did not eat for 2–3
hours before the testing session, and refrained from inten-
sive exercise, and abstained from caffeine or any form of
stimulant in the 24-hour period before testing. Subjects
were permitted to consume water ad libitum throughout
the session. Before data collection, the subject’s age, height,
and body mass were recorded. Height was measured using
a stadiometer (Seca 213; Ecomed Trading, Seven Hills,
Australia) and recorded to the nearest 0.1 cm. Body mass
was recorded using electronic digital scales (BF-522; Tanita
Corporation, Japan) to the nearest 0.1 kg. A standardized
warm-up was conducted before the testing session consist-
ing of 5 minutes of jogging on a treadmill at a self-selected
running velocity, followed by 10 minutes of dynamic
stretching of the lower limbs, and progressive speed runs
over the testing distances.
30-m Sprint
The 30-m sprint has been previously used to assess linear
speed in cricketers (18). Time was recorded using a timing
lights system (Smartspeed; Fusion Sports, Sumner, Austral-
ia). Gates were placed at 0, 10, and 30 m, at a height of
1.2 m and width of 1.5 m, to measure the 0–10 m and 0–
30 m intervals. These intervals provided a measure of accel-
eration (20) and maximum velocity (8) for the correlation
analysis. Subjects began each sprint 30 cm behind the start
line, to trigger the first gate (18). A standing start was used,
and subjects were free to choose their front leg in this
stance, which was the same for all trials. Subjects were
instructed to drive off from the starting line and sprint
through all sets of timing gates. Three trials were com-
pleted, with 3 minutes of recovery between efforts. If the
subject rocked backward or forward before starting, the
trial was disregarded and repeated after the requisite recov-
ery period. Time for each distance was recorded to the
nearest 0.001 seconds, and the averages were used for
Change of Direction Deficit in Cricket Players
Journal of Strength and Conditioning Research
Copyright © National Strength and Conditioning Association Unauthorized reproduction of this article is prohibited.
analysis. The mean 0- to 10-m split time was used to cal-
culate the COD deficit, the process of which will be
detailed later.
505 Change of Direction Test
The methodology for the 505 was used as per established
methods (6) with the setup is shown in Figure 1. Subjects
used a standing start with the same body position as per the
30-m sprint, with their front foot 30 cm behind the start line.
The subjects sprinted through the timing gate to the turning
line, indicated by a line marked on the laboratory floor and
markers. Subjects were to place either the left or right foot,
depending on the trial, on or behind the turning line, before
sprinting back through the gate. Three trials were recorded
for turns off the left and right side, the order of which was
randomized among the subjects, with 3 minutes recovery
provided between trials. A researcher was positioned at
the turning line, and if the subject changed direction before
hitting the turning point, or turned off the incorrect foot, the
trial was disregarded and reattempted after the recovery
period. Time for each distance
was recorded to the nearest
0.001 seconds. The mean for
the 3 trials for the 505 for each
leg was used for analysis. The
side with the fastest time was
defined as the preferred side,
whereas the other was the non-
preferred side (19). The COD
deficit for the 505 for each leg
was calculated by the formula:
mean 505 time 2mean 10-m
time (27). As stated, the mean
10-m time was taken from the
30-m sprint.
Statistical Analyses
Mean and SDs, in addition to
95% confidence intervals, were calculated for each variable.
Trial-to-trial reliability of sprint and COD times were as-
sessed through intraclass correlation coefficients (ICCs) cal-
culated from a 2-way mixed method consistency model for
average measures. An ICC equal to or above 0.70 was con-
sidered acceptable (1,14,18). The Levene’s statistic was used
to determine homogeneity of variance of the data. Pearson’s
product-moment correlation (2-way) was conducted to
determine the relationships between 505 times, COD deficit,
and 10- and 30-m sprint times. The preferred and nonpre-
ferred sides were examined separately. An alpha level of p#
0.05 was the criterion for significance. The strength of the
correlation coefficient (r) was described as per Hopkins (12).
An rvalue between 0 to 0.3, and 0 to 20.3, was considered
small; 0.31–0.49, and 20.31 to 20.49, moderate; 0.5–0.69,
and 20.5 to 20.69, large; 0.7–0.89, and 20.7 to 20.89, very
large; and 0.9–1, and 20.9 to 21, near perfect for predicting
The second part of the analysis determined whether the
505 time and COD deficit provided a different assessment of
TABLE 1. Descriptive data (mean 6SD; 95% CIs) for 10, 30 m, and 505 times
for the preferred and nonpreferred sides, and COD deficit for the preferred and
nonpreferred sides in experienced male cricketers (n= 17).*
Test Mean 6SD 95% CI
10 m 1.826 60.060 1.795–1.857
30 m 4.417 60.166 4.331–4.502
Preferred 505 2.443 60.089 2.397–2.489
Nonpreferred 505 2.496 60.102 2.443–2.548
Preferred COD deficit 0.617 60.073 0.580–0.655
Nonpreferred COD deficit 0.670 60.087 0.625–0.715
*COD = change of direction.
All variables measured in seconds.
TABLE 2. Correlations for the preferred side between 505 time, COD deficit, and 10- and 30-m sprint times in
experienced male cricketers (n= 17).*
505 time vs.
COD deficit
505 time vs.
10-m sprint
505 time vs.
30-m sprint
COD deficit vs.
10-m sprint
COD deficit vs.
30-m sprint
r0.740.58z0.70§ 20.11 0.097
95% CI 0.41 to 0.90 0.14 to 0.83 0.32 to 0.88 20.56 to 0.39 20.40 to 0.55
0.55 0.34 0.48 0.013 0.0095
p(2 tailed) 0.001 0.014 0.002 0.667 0.710
*COD = change of direction; r= Pearson’s correlation coefficient; R
= explained variance; p= significance.
Significant p,0.0001.
zSignificant p#0.05.
§Significant p,0.01.
Journal of Strength and Conditioning Research
VOLUME 30 | NUMBER 11 | NOVEMBER 2016 | 3027
Copyright © National Strength and Conditioning Association Unauthorized reproduction of this article is prohibited.
COD ability. To compare variables with different mean and
SDs, a transformation to a normalized score is recommended
(26). Therefore, to compare the relative performance of each
athlete for COD deficit and 505 time, the values were
normalized. To do this, 505 time and COD deficit for the
preferred and nonpreferred legs were converted to z-scores,
by the formula: z-score = (subject’s test score 2mean score
from the sample)/SD. As for the correlation analysis, pre-
ferred and nonpreferred sides
were analyzed separately. The
difference in z-scores (505 def-
icit 2505 time) was deter-
mined and compared with the
smallest worthwhile change
(SWC) for the sample. The
SWC is equal to the between-
subject SD multiplied by 0.2,
which is the typical small effect
(13). As these were standard-
ized scores, the SD is 1.0 and
therefore, the SWC is simply
0.2. Those subjects that had
a z-score ($0.2) difference ex-
ceeded the SWC and were
deemed to have a meaningful
difference in the COD ability
assessment provided by the
505 time and COD deficit.
Therefore, a positive difference
in z-scores indicated an overes-
timate of COD ability, and
a negative difference in z-scores
indicated an underestimate of
COD ability.
Descriptive data for all the tests
are shown in Table 1. The trial-
to-trial reliability for the 10 m
(ICC: 0.91), 30 m (ICC: 0.98),
and preferred (ICC: 0.84) and
nonpreferred (ICC: 0.78) 505
TABLE 3. Correlations for the nonpreferred side between 505 time, COD deficit, and 10- and 30-m sprint times in
experienced male cricketers (n= 17).*
505 time vs.
COD deficit
505 time vs.
10-m sprint
505 time vs.
30-m sprint
COD deficit vs.
10-m sprint
COD deficit vs.
30-m sprint
r0.810.52z0.63§ 20.082 0.097
95% CI 0.54 to 0.93 0.051 to 0.80 0.22 to 0.85 20.54 to 0.41 20.40 to 0.55
0.65 0.27 0.40 0.0068 0.0095
p(2 tailed) ,0.0001 0.033 0.006 0.754 0.710
*COD = change of direction; r= Pearson’s correlation coefficient; R
= explained variance; p= significance.
Significant p,0.0001.
zSignificant p#0.05.
§Significant p,0.01.
Figure 2. Z-score of the COD time and COD deficit for each subject of the (A) preferred side results and (B)
nonpreferred side results. The * represents subjects where opposite COD abilities were indicated by the 505 time
vs. the 505 deficit. COD, change of direction.
Change of Direction Deficit in Cricket Players
Journal of Strength and Conditioning Research
Copyright © National Strength and Conditioning Association Unauthorized reproduction of this article is prohibited.
times, were all considered acceptable. The correlation
between 10- and 30-m sprint times was significant and con-
sidered near perfect (r= 0.91; 95% CI [0.77–0.97]; p#
0.0001). The correlation data with 95% CI for the preferred
side are shown in Table 2, and for the nonpreferred side in
Table 3. With regard to the preferred side, the 505 time had
a significant and very large correlation with the COD deficit
and a large to very large correlations with 10- and 30-m
sprint time, respectively. A similar trend was found for the
nonpreferred side, with a very large, significant relationship
between 505 time and COD deficit and 505 time had large
significant relationships with the 10- and 30-m sprint times.
However, the COD deficit did not significantly correlate
with the 10- or 30-m sprint times for both the preferred
and nonpreferred sides. All significant relationships were
positive, which meant subjects that had a lower time in
one measure, also had a lower time in the other measure.
Figure 2 displays the z-scores for the 505 total time and
COD deficit for the preferred and nonpreferred side for each
subject. For the preferred side, both the 505 time and COD
deficit for all subjects provided directionally similar indica-
tions of COD ability. However, for the nonpreferred side, 5
of 17 subjects (29%) had a 505
time and COD deficit that sug-
gested opposite COD abilities.
For 3 subjects, the 505 indi-
cated better than average
COD performance, while the
COD deficit suggested it was
less than average, whereas for
the other 2 subjects, the oppo-
site was true.
Figure 3 displays the differ-
ences in the z-scores (COD
deficit 2505 time) for the pre-
ferred and nonpreferred sides.
With regard to the preferred
side, there was a worthwhile
difference for 16 of 17 subjects
(94%). This suggested that 7
subjects had their COD ability
overestimated by the 505 time,
whereas 9 subjects had their
COD ability underestimated.
The trend was similar for the
nonpreferred side, with 15 sub-
jects (88%) having a worthwhile
difference in the standardized
z-scores. The 505 time overesti-
mated the COD ability of 8 sub-
jects and underestimated the
ability of 7 subjects.
The challenge in assessing
COD ability is isolating that physical quality in a simple
metric for strength and conditioning coaches. Historically,
the time taken to perform various COD tests was used to
measure an athlete’s capacity to change direction. It is pos-
sible that in many COD tests, an athlete’s ability to actually
change direction may be “masked” by other physical quali-
ties needed within the test (e.g., linear sprinting ability,
anaerobic capacity, and movement specificity for the test)
(27,34,43). As a result, it would be pertinent for strength
and conditioning coaches to be able to use an assessment
that more clearly identifies COD ability. This study investi-
gated the COD deficit, assessed during the 505 in comparison
with one’s 10-m sprint time, to determine whether it provided
a more specific measure of COD ability. The results of this
study suggested that this was the case. The practical relevance
of these findings is strength and conditioning coaches could
potentially use the COD deficit to assess COD ability in their
athletes, without the requirement of additional equipment or
adoption of new field tests. Although this study investigated
cricketers, this research has potential for crossover into other
athletic populations simply trying to evaluate the physical
capacity to change direction.
Figure 3. Difference in standardized scores (COD deficit 2505 time) of the (A) preferred side results and (B)
nonpreferred side results. The bars indicate subjects where the difference in the z-scores was greater than an
SWC or difference in performance. The SWC is indicated by the horizontal dotted lines. As the scores are
presented in z-scores, the SD = 1.0, therefore the SWC (0.2 31.0) is simply 0.2. COD, change of direction;
SWC, smallest worthwhile change.
Journal of Strength and Conditioning Research
VOLUME 30 | NUMBER 11 | NOVEMBER 2016 | 3029
Copyright © National Strength and Conditioning Association Unauthorized reproduction of this article is prohibited.
An issue with many COD tests is that because of the
relatively large volume of linear sprinting, an athlete with
superior straight-line running ability could use this physical
quality to mask any COD deficiencies that were previously
expected to be assessed within a test (34). This overlap
between linear sprint ability and apparent COD ability
(determined by tests with primarily linear running volume)
is supported by the significant relationships between COD
and linear speed tests (11,22,30,34,43), which was also the
case in this study with 505, 10-, and 30-m sprint times (Table
2). The 505 involves a 15-m sprint (although only the last
5 m is timed) before the subject reaches the turning line (6)
and completes an additional 5 m, which indicates why there
were relationships with linear speed in this study. As dis-
cussed previously by Nimphius et al. (27), the relationship
between total time in a COD test and linear sprint times can
be explained by the small large amount of time spent run-
ning linearly (69%) vs. the time spent “actually changing
direction” (31%). This is partly why (34) recommended mea-
suring the time in the first meter after a COD to limit the
influence of linear running speed. The value of restricting the
measurement of COD ability to the action itself is supported
by Spiteri et al. (39), who in an analysis of stronger (who
were faster) and weaker (who were slower) recreational ath-
letes, found that the poststride velocity (velocity of the first
step out) after a 458COD, and not total time to complete the
test, was one of the key kinematic variables that distin-
guished the groups. However, as previously acknowledged,
measuring an athlete’s exit velocity after a COD is difficult to
do in the field. Therefore, the COD deficit was designed as
a practical way to isolate the measurement of an athlete
changing direction (27).
The correlation analysis indicated very large relationships
between the 505 and COD deficit for both legs (Table 2),
which would be expected if both are reported to measure
COD ability. However, although there were significant rela-
tionships between the 505 time for both legs and linear
speed, this was not the case for the COD deficit (Table 2).
The COD deficit calculated from the 505 provides a measure
of the time required to add 1 1808COD to a 10-m sprint
(27). Thus the larger the deficit, the less effective the direc-
tion change or the lower the ability of an athlete to change
direction relative to their physical capability for linear speed.
It is important to note that the COD deficit is a measure that
provides information on COD ability relative to one’s speed
sprint speed instead of being inclusive of one’s sprint speed
as would be the case for total time. If an athlete improves
their linear speed but does not improve their COD ability,
the total 505 time may decline (perceived COD improve-
ment), whereas the COD deficit would either remain the
same or potentially become worse if they can not handle
their new speed capacity when entering a COD. Given that
the COD deficit did not relate to linear speed, yet did relate
to the 505 times, provides some evidence that this test mea-
sured COD performance without the influence of linear
speed in cricketers. Potentially, the COD deficit provides
a practical way to restrict the measurement of COD perfor-
mance to the action itself while separating COD ability from
the physical capacity of sprint speed.
An important concern for strength and conditioning
coaches is that they are able to correctly identify strengths
and weaknesses for their athletes from performance test
results (25). This relates to the validity of a test, in that, the
test data accurately reflect the physical quality those are
supposed to measure. A further issue for the coach is that
valid tests that are determined in the controlled, laboratory
environment need to have a practical equivalent, while still
maintaining acceptable reliability. The results from this study
indicated that the measurement of 505 time, although reli-
able (11,34,40), exhibited some of the problems noted by
(34). When comparing the z-scores, there were 4 subjects
who had 505 time and COD deficit results that indicated
opposing COD abilities (i.e., a faster 505 time, but worse
COD deficit, or vice versa) (Figure 2). This is a concern, as
coaches can often use test results to inform the decisions
they make with regard to training and team selection (25).
A further note is that the conflicts between 505 time and
COD deficit only occurred for the nonpreferred side. This is
a particular issue for cricketers, as coaching practice outlines
that batsmen should complete the turn when running
between the wickets while facing the location of the ball
(4). As a result, they must be proficient turning from each
side. Given most athletes generally attempt to have a balance
between the legs for multidirectional movements (17), 505
time may not properly indicate COD ability in experienced
athletes, and this may be specific to the side that is tested.
There were also worthwhile differences between the 505
time and COD deficit for almost all subjects on the preferred
(94%) and nonpreferred (88%) sides, whether it was an
overestimation or underestimation of COD ability (Figure 3).
Taken together with the correlations from this study (Tables
2 and 3), the z-score comparison (Figure 2) and the findings
of (34) 505 time may not provide the best indication of COD
ability because of the linear sprinting that still features in this
test result. In contrast, the COD deficit eliminates the con-
tribution of linear speed (Tables 2 and 3), and thus seemed to
provide a more isolated measure of COD performance for
the cricketers in this study. This is very noteworthy for the
strength and conditioning coach. If test time alone does not
always provide an accurate and valid measure of how effec-
tively an athlete changes direction (34), then the COD def-
icit could provide this information for a coach. In support of
research that has documented the importance of measuring
COD performance over short distances in the laboratory
(34,39), the COD deficit potentially provides a practical
way to measure this in the field. This information can then
be used to drive coaches training practice, as they will have
potentially more valid information as to which of their ath-
letes need to improve their COD ability, as defined by their
COD deficit.
Change of Direction Deficit in Cricket Players
Journal of Strength and Conditioning Research
Copyright © National Strength and Conditioning Association Unauthorized reproduction of this article is prohibited.
There are limitations for this study that should be
acknowledged. Cricketers were the only athletes analyzed
in this study, so the COD deficit may differ across different
athletes. Nonetheless, because of the importance of the 1808
COD to cricket (7,15,18,23), the sample was appropriate for
this study, as the subjects were experienced with the move-
ment. In addition to this, only a 1808COD was investigated
in this study. A COD deficit may be specific to the angle of
the direction change. Future research should investigate the
COD deficit as measured from the 505 for athletes from
different sports and for different angles of direction changes.
This study also did not include technical analysis for COD
ability, as all testing was field based. Laboratory-based stud-
ies can provided more detailed technical information (34,39),
and future research should investigate relationships between
the COD deficit and entry and exit velocities when changing
direction in athletes. However, the focus of this study was to
provide practical information that a coach could directly use
in testing and training, which adds value to the study findings.
Because of the importance of poststride velocity and the tech-
nique of a direction change (39), future research should also
investigate how technique influences the COD deficit.
Nevertheless, there is practical value in the results from
this study. The COD deficit seems to provide a more isolated
measure of physical performance than 505 test time alone, as
it reduces the effect of linear sprinting speed within a COD
test. Strength and conditioning coaches should consider
incorporating the COD deficit into their athlete testing
protocols. Further research, however, is required to confirm
the validity of the COD deficit, through the assessment of
different athletic populations. Finally, consideration of the
COD deficit in conjunction with video analysis or other
practical measures of isolating COD performance may help
better identify the strengths and weaknesses of an athlete in
COD performance, and thus allow for better prescription
and athlete development.
The COD deficit and 505 time seem to provide different
assessments of the physical capacity of COD ability. Strength
and conditioning coaches who use the 505 should also
calculate the COD deficit to provide a potentially more specific
measure of COD ability. Because many coaches will also
measure 10-m sprint performance in their assessments in linear
speed, it should not take too much extraeffort to calculate the
COD deficit for a squad of athletes, especially if this can
elucidate useful information. Coaches who do not use the 505
should consider adding this assessment to their protocols, so
that they could use the COD deficit, as it seems to better isolate
the ability to change direction. There are also several avenues
for research investigating the COD deficit (e.g., validation of
the COD deficit in different athletic populations, relationships
between COD deficit and technique, and effects of training on
the COD deficit), which provides practical application for
researchers and sport science practitioners as well.
The authors would like to acknowledge their subjects for
their contribution to the study. Thanks also to Matthew
Jeffriess for assisting with data collection. This research
project received no external financial assistance. None of the
authors have any conflict of interest.
1. Baumgartner, TA and Chung, H. Confidence limits for intraclass
reliability coefficients. Meas Phys Educ Exerc Sci 5: 179–188, 2001.
2. Besier, TF, Lloyd, DG, Ackland, TR, and Cochrane, JL.
Anticipatory effects on knee joint loading during running and
cutting maneuvers. Med Sci Sports Exerc 33: 1176–1181, 2001.
3. Brughelli, M, Cronin, J, Levin, G, and Chaouachi, A. Understanding
change of direction ability in sport. Sports Med 38: 1045–1063, 2008.
4. Buckley, M. Australian Cricket Coach: Your Complete Guide to Coaching
Cricket. Melbourne, Victoria: Cricket Australia, 2013.
5. Callaghan, S J, Lockie, RG, and Jeffriess, MD. The acceleration
kinematics of cricket-specific starts when completing a quick single.
Sports Tech 7: 39–51, 2014.
6. Draper, JA and Lancaster, MG. The 505 test: A test for agility in the
horizontal plane. Aust J Sci Med Sport 17: 15–18, 1985.
7. Duffield, R and Drinkwater, EJ. Time-motion analysis of test and
one-day international cricket centuries. J Sports Sci 26: 457–464,
8. Duthie, G M, Pyne, DB, Marsh, DJ, and Hooper, SL. Sprint patterns
in rugby union players during competition. J Strength Cond Res 20:
208–214, 2006.
9. Farrow, D, Young, W, and Bruce, L. The development of a test of
reactive agility for netball: A new methodology. J Sci Med Sport 8:
52–60, 2005.
10. Faul, F, Erdfelder, E, Buchner, A, and Lang, A-G. Statistical power
analyses using g*power 3.1: Tests for correlation and regression
analyses. Behav Res Methods 41: 1149–1160, 2009.
11. Gabbett, TJ, Kelly, JN, and Sheppard, JM. Speed, change of direction
speed, and reactive agility of rugby league players. J Strength Cond
Res 22: 174–181, 2008.
12. Hopkins, WG. A scale of magnitudes for effect statistics A new view
of statistics from,
2002. Accessed October 6, 2011.
13. Hopkins, WG. How to interpret changes in an athletic performance
test. Sportscience 8: 1–7, 2004.
14. Hori, N, Newton, RU, Kawamori, N, McGuigan, MR, Kraemer, WJ,
and Nosaka, K. Reliability of performance measurements derived
from ground reaction force data during countermovement jump and
the influence of sampling frequency. J Strength Cond Res 23: 874–
882, 2009.
15. Houghton, LA. Running between the wickets in cricket: What is the
fastest technique? Int J Sports Sci Coach 5: 101–107, 2010.
16. Jarvis, S, Sullivan, LO, Davies, B, Wiltshire, H, and Baker, JS.
Interrelationships between measured running intensities and agility
performance in subelite rugby union players. Res Sports Med 17 : 2 17
230, 2009.
17. Lockie, RG, Callaghan, SJ, Berry, SP, Cooke, ER, Jordan, CA,
Luczo, TM, and Jeffriess, MD. Relationship between unilateral
jumping ability and asymmetry on multidirectional speed in team-
sport athletes. J Strength Cond Res 28: 3557–3566, 2014.
18. Lockie, RG, Callaghan, SJ, and Jeffriess, MD. Analysis of specific
speed testing for cricketers. J Strength Cond Res 27: 2981–2988, 2013.
19. Lockie, RG, Callaghan, SJ, McGann, TS, and Jeffriess, MD. Ankle
muscle function during preferred and non-preferred 458directional
cutting in semi-professional basketball players. Int J Perform Anal
Sport 14: 574–593, 2014.
Journal of Strength and Conditioning Research
VOLUME 30 | NUMBER 11 | NOVEMBER 2016 | 3031
Copyright © National Strength and Conditioning Association Unauthorized reproduction of this article is prohibited.
20. Lockie, RG, Murphy, AJ, Knight, TJ, and Janse de Jonge, XAK.
Factors that differentiate acceleration ability in field sport athletes.
J Strength Cond Res 25: 2704–2714, 2011.
21. Lockie, RG, Schultz, AB, Callaghan, SJ, and Jeffriess, MD. The
effects of traditional and enforced stopping speed and agility training
on multidirectional speed and athletic performance. J Strength Cond
Res 28: 1538–1551, 2014.
22. Lockie, RG, Schultz, AB, Callaghan, SJ, Jeffriess, MD, and Berry, SP.
Reliability and validity of a new test of change-of-direction speed for
field-based sports: The change-of-direction and acceleration test
(CODAT). J Sports Sci Med 12: 88–96, 2013.
23. Loock, N, Du Toit, DE, Ventner, DJ, and Stretch, RA. Effect of
different types of cricket batting pads on the running and turning
speed in cricket batting. Sports Biomech 5: 15–22, 2006.
24. Maio Alves, JM, Rebelo, AN, Abrantes, C, and Sampaio, J. Short-
term effects of complex and contrast training in soccer players’
vertical jump, sprint, and agility abilities. J Strength Cond Res 24:
936–941, 2010.
25. McGuigan, MR, Cormack, SJ, and Gill, ND. Strength and power
profiling of athletes: Selecting tests and how to use the information
for program design. Strength Cond J 35: 7–14, 2013.
26. Newton, RU and Dugan, E. Application of strength diagnosis.
Strength Cond J 24: 50, 2002.
27. Nimphius, S, Geib, G, Spiteri, T, and Carlisle, D. “Change of
direction” deficit measurement in division I american football
players. J Aust Strength Cond 21: 115–117, 2013.
28. Nimphius, S, McGuigan, MR, and Newton, RU. Relationship
between strength, power, speed, and change of direction performance
of female softball players. J Strength Cond Res 24: 885–895, 2010.
29. Nimphius, S, McGuigan, MR, and Newton, RU. Changes in muscle
architecture and performance during a competitive season in female
softball players. J Strength Cond Res 26: 2655–2666, 2012.
30. Pauole, K, Madole, K, Garhammer, J, Lacourse, M, and Rozenek, R.
Reliability and validity of the t-test as a measure of agility, leg power,
and leg speed in college-aged men and women. J Strength Cond Res
14: 443–450, 2000.
31. Robbins, DW. The national football league (nfl) combine: Does
normalized data better predict performance in the nfl draft? J
Strength Cond Res 24: 2888–2899, 2010.
32. Salaj, S and Markovic, G. Specificity of jumping, sprinting, and quick
change-of-direction motor abilities. J Strength Cond Res 25: 1249–
1255, 2011.
33. Sassi, RH, Dardouri, W, Yahmed, MH, Gmada, N,
Mahfoudhi, ME, and Gharbi, Z. Relative and absolute reliability
of a modified agility t-test and its relationship with vertical
jump and straight sprint. JStrengthCondRes23: 1644–1651,
34. Sayers, MG. The influence of test distance on change of direction
speed test results. J Strength Cond Res 29: 2412–2416, 2015.
35. Sheppard, JM, Dawes, JJ, Jeffreys, I, Spiteri, T, and Nimphius, S.
Broadening the view of agility: A scientific review of the literature.
J Aust Strength Cond 22: 6–25, 2014.
36. Sheppard, JM and Young, WB. Agility literature review:
Classifications, training and testing. J Sports Sci 24: 919–932, 2006.
37. Sierer, SP, Battaglini, CL, Mihalik, JP, Shields, EW, and
Tomasini, NT. The national football league combine: Performance
differences between drafted and nondrafted players entering the
2004 and 2005 drafts. J Strength Cond Res 22: 6–12, 2008.
38. Smith, RG, Harley, RA, and Stockill, NP. Cricket. In: Sport and
Exercise Physiology Testing Guidelines: The British Association of Sport
and Exercise Sciences Guide. EM Winter, AM Jones, RCR Davison,
PD Bromley, and TH Mercer, eds. London, United Kingdom:
Routledge, 2007. pp. 225–231.
39. Spiteri, T, Cochrane, J L, Hart, NH, Haff, GG, and Nimphius, S.
Effect of strength on plant foot kinetics and kinematics during
a change of direction task. Eur J Sport Sci 13: 646–652, 2013.
40. Stewart, PF, Turner, AN, and Miller, SC. Reliability, factorial
validity, and interrelationships of five commonly used change
of direction speed tests. Scand J Med Sci Sports 24: 500–506,
41. Van Gelder, LH and Bartz, SD. The effect of acute stretching on
agility performance. J Strength Cond Res 25: 3014–3021, 2011.
42. Vescovi, JD, Brown, TD, and Murray, TM. Positional characteristics
of physical performance in division I college female soccer players.
J Sports Med Phys Fitness 46: 221–226, 2006.
43. Vescovi, JD and McGuigan, MR. Relationships between sprinting,
agility, and jump ability in female athletes. J Sports Sci 26: 97–107,
44. Wilkinson, M, Leedale-Brown, D, and Winter, EM. Validity of
a squash-specific test of change-of-direction speed. Int J Sports
Physiol Perform 4: 176–185, 2009.
45. Young, WB, McDowell, MH, and Scarlett, BJ. Specificity of sprint
and agility training methods. J Strength Cond Res 15: 315–319,
Change of Direction Deficit in Cricket Players
Journal of Strength and Conditioning Research
Copyright © National Strength and Conditioning Association Unauthorized reproduction of this article is prohibited.
... The COD time performance test was registered with a photocell beam connected to a computer (Chronojump BoscoSystem, Barcelona, Spain) in seconds. All COD tests were performed with the players starting in a standing position, with their preferred foot forward and 0.5 m behind the first timing gate [27]. For the COD measurements, the subjects were instructed to run as fast as possible for five meters and then turn 90 • or 135 • , and a final 5-m sprint ( Figure 1). ...
... The COD time performance test was registered with a photocell beam connected to a computer (Chronojump BoscoSystem, Barcelona, Spain) in seconds. All COD tests were performed with the players starting in a standing position, with their preferred foot forward and 0.5 m behind the first timing gate [27]. For the COD measurements, the subjects were instructed to run as fast as possible for five meters and then turn 90° or 135°, and a final 5-m sprint ( Figure 1). ...
... The Highest Performing Limb (HPL) was defined as the side with the higher value for each task, while the Lowest Performing Limb (LPL) was defined as the side with the lower value for each task. To calculate COD deficit time, the 10 m sprint time was subtracted from the COD time in each direction and for each leg [27]: Table 1 shows descriptive statistics for both limb data, the percentage of asymmetry for each task, and reliability measures for all assessments. Most assessments had excellent within-session ICC values (≥0.9). ...
Full-text available
The purposes of this study were to quantify inter-limb asymmetries from unilateral jumps, change of direction (COD) speed, and flywheel resistance skill tests and to examine their relationship with physical performance in a sample of elite youth female basketball players. Eleven female basketball players (age = 17.56 ± 0.60 y; body mass = 75.13 ± 12.37 kg; height = 1.83 ± 0.08 m; BMI = 22.42 ± 2.28; sports experience = 6.31 ± 1.73 y; years post-peak height velocity = 4.79 ± 0.68 y) performed a battery of fitness tests in the post-season consisting of the Single Leg Countermovement Jump in vertical (SLCJ-V), horizontal (SLCJ-H), and lateral (SLCJ-L) directions, 135° and 90° COD tests, and four skills (acceleration step, deceleration step, sidestep, and crossover step) with an flywheel resistance device. The results showed significant differences between the higher performing and lower performing limbs across all tasks (p < 0.05). The mean asymmetry index values ranged from 1.26% (COD 135°) to 11.75% (SLC-V). Inter-limb asymmetries were greatest during the flywheel resistance skills. Spearman’s correlations (ρ) for all tests were only significant for inter-limb asymmetries during the sidestep test and reduced performance in SLCJ-L (ρ = −0.61; p = 0.046) and all COD deficits (ρ range = −0.72 to −0.81). The findings of the present study showed that inter-limb asymmetries are task-specific in female youth basketball players and suggest that the use of flywheel devices can be included in the battery of tests to detect inter-limb asymmetry.
... A measure that helps in assessing the isolated COD capacity is the COD deficit. The COD deficit corresponds to the difference in speed between the linear sprint and the task of an equal distance with a COD [10,11]. The influence of various variables on the COD efficiency was analyzed, e.g., jump height, lower body power, and strength [4,12,13]. ...
... However, the authors showed a statistically significant positive correlation between the 10 and 20 m linear sprint and the COD deficit in the Zigzag test [3]. Furthermore, Nimphius et al. [11] showed a positive relationship between the 100° COD deficit and the 505 test. On the other hand, Pereira et al. [10] found a positive correlation between the 100° COD tests and mean propulsive power output (obtained in the squat jump and the countermovement jump) in female and male handball teams. ...
Introduction: Although soccer matches require players to perform repetitive power-related abilities, the impact of lower-body strength and power asymmetry on sprint and change of direction (COD) performance receives little attention. Therefore, this study aimed to establish the relationship between lower limb power, sprint, and change of direction (COD) performance. In addition, the relationship between lower limb power asymmetry and the above mentioned running tests was determined. Material and Methods: Twenty-four male soccer players from First Polish League (age = 24.8 ±8.2 years, body mass = 77.4 ±16.9kg, body height=179.5 ±14.5cm, soccer training experience = 10 ± 1.5years) took part in the study. To examine the relationship between linear sprint, lower limb muscle power, and COD performance (time and deficit), the following tests were performed: 5-and 20-m linear sprint, leg press exercise, and two 20-m COD sprints (“COD90” and “L” test). Result: Pearson correlation coefficients didn’t show any statistically significant relationship between lower limb power and linear sprint speed as well as COD performance. The results indicate that the considered variables are independent physical characteristics. Conclusion: Relative lower limb-power output and low level of mean inter-limb asymmetry in power output does not affect 5- and 20-m linear sprint time and COD performance with 90° turn.
... The modified 505 agility test (COD). Each participant was instructed to run to a mark situated 5 m from the starting line, perform a 180° COD using the right or left leg to push off, and return to the starting line, covering a total of 10 m [27]. The participants were asked to pass the line indicated on the ground with their entire foot at each turn. ...
... The lower limb asymmetry index (ASI) was determined using the following formula [28]: ASI = 100/Max Value (right and left)*Min Value (right and left)* − 1 + 100. The COD deficit (CODD) for the double 180° COD test for each leg was calculated via the following formula: mean double modified 505 agility test time-mean 10 m time [27]. ...
Full-text available
The differential learning approach, which includes fluctuations that occur without movement repetitions and without corrections has received growing interest in the skill acquisition field. This study aimed to determine the effects of a 9-week training intervention involving differential repeated sprint training on a series of physical tests in youth basketball players. A total of 29 participants with different maturity statuses (pre-peak height velocity (PHV), n = 7; mid-PHV, n = 6; post-PHV, n = 16) completed 2 sessions per week of differential repeated sprint training for a period of 9 weeks. Sessions consisted of 2 × 10 repetitions sprints of 20-m whereby participants were instructed to perform various additional fluctuations for each repetition. Before and after the training intervention , participants completed jumping tests (countermovement jump (CMJ), single-leg CMJs, the modified 505 agility test, and straight sprinting tests (0-10 splits time), and maturity status was evaluated as well. Within-group analysis showed improvement in CMJ asymmetries and changes in direction asymmetries and 10-m sprint performance for the pre-, mid-, and post-PHV groups, respectively (p < 0.05), with large to very large effects. Analysis of covariance demonstrated that changes in sprint time in post-PHV players were greater than in the pre-and mid-PHV groups (p < 0.05), with moderate effect. Adding random fluctuations during repeated sprint training appear to be a suitable and feasible training strategy for maintaining and enhancing physical performance in youth basketball players, irrespective of maturity status. Furthermore, the present findings encourage practitioners to implement the present approach in youth athletes to improve their physical performance, but they should be aware that training response can vary according to maturity status.
... The COD deficit was used by subtracting the COD time by the linear speed time at 10-m. 28 The ICC for the test was 0.81. ...
... 20 However, since COD time in 5-0-5 is perfectly related with a linear speed test of 10-m, 43 it is not possible to describe that COD ability was improved. In fact, COD deficit, a better measure of COD ability, 28 was not significantly improved in both groups. In fact, only in the group combining RST it was observed a significant improvement of the COD deficit. ...
Full-text available
Most of the research combining small-sided games (SSGs) with high-intensity interval training (HIIT) is using the short or long forms of HIIT. However, other types of HIIT as repeated sprint training (RST) could enhance different stimuli. The purpose of the current research was to analyze the within-and between-group variations of physical fitness and body composition of two combined training interventions: (i) SSGs combined with a short high intensity interval training (sHIIT); and (ii) SSGs combined with a RST. This study followed a randomized parallel study design. Twenty-eight youth soccer players (age: 17.3 ± 0.5) belong to the same team were assigned equally to two intervention groups: SSG + sHIIT versus SSG + RST. Training intervention lasted 4 weeks, with a 2-session/week frequency. The players were tested twice, once before and after the intervention with the following tests: skinfolds (fat mass); Sargent jump test (SJT); standing long jump; sprinting time at 10-, 20-, or 30-m; 5-0-5 for time and deficit; 30-15 intermittent fitness test (30-15IFT) based on the final velocity, and repeated sprint ability (RAST) for peak, minimum, average power, and fatigue index. A mixed analysis of variance was conducted to considering factor × time effect. Between-group analysis revealed no significant differences at baseline and post-intervention period for fat mass, sprinting time at 10-, 20-, and 30-m, change-of-direction (COD) time and deficit, SJT and standing long jump, final velocity at 30-15IFT and RAST peak, average power, and fatigue index (p > 0.05). Within-group analysis revealed that both groups significantly reduced fat mass (p ≤ 0.001), SJT (p ≤ 0.001), standing long jump (p ≤ 0.001), sprint time at 10-and 20-m (p ≤ 0.001), 30-m (p = 0.002), COD time (p ≤ 0.001) and deficit (p < 0.05), RAST average (p < 0.05), and final velocity 30-15IFT (p ≤ 0.001). Only SSG + RST had significant improvements on COD deficit and peak Reviewers: Beat Knechtle, University of Zürich, Switzerland/home/spo power (p < 0.05). The result of the current research suggests that either SSG + sHIIT or SSG + RST are effective for improving physical fitness in youth soccer players, with a multiple beneficial effect on locomotor profile, speed and COD, jumping performance and repeated sprint ability.
... Regarding between-age group analysis, only significant differences were found in 505 COD test (best results in older). Since COD time in 505 COD test is predominantly explained by acceleration 36 and considering that greater force and sprint are observed in latest stage of youth period 37 , it is expectable to observe the results observed in this test. This also highlight that besides typical field-based training, physical qualities related with COD tests must be oriented to improve the skill across the time. ...
Full-text available
The present study aimed to examine the influence of leg dominance on the change of direction (COD) performance. In this study participated 94 healthy young highly trained male soccer players belonging from two categories (n = 27 vs. n = 67; 14.81 ± 0.40 vs. 16.64 ± 1.25 years of age; 170.61 ± 5.61 vs. 173.73 ± 7.19 cm of height; 64.74 ± 8.44 vs. 66.70 ± 7.95 kg of weight, for U16 and U18, respectively). Fitness assessments were performed two times in a period of three months, and included: (1) anthropometry measures, (2) 30–15 IFT, (3) 10-m sprint test, (4) 505-COD test, 90° COD test and cross-over hop test. A paired sample t-test was performed to evaluate the asymmetries at the intragroup level in each of the COD’s tests. A symmetry index was used to analyse the asymmetries between categories, and an independent sample t-test was used to compare the variability between the two categories in each of the three tests performed. The effect size was also evaluated. Analysis demonstrated that evidence a trend for a better performance with the preferred leg in the cross-over hop and 505-COD tests, and with the non-dominant leg in the 90° COD. However, in the intragroup analysis, only the 505-COD test registered differences, and no differences were notice din the intergroup comparison. Only in the 505-COD test the percentage of variability (CV) was statistically significant (7.03 ± 4.18% vs. 4.03 ± 2.02% from U16 and U18, respectively). In sum, bilateral differences were noticed in the intragroup comparison, although only in 505-COD test the leg dominance showed to influence performance. In the intergroup analysis any difference was noticed between age categories.
... Specifically, it was possible by subtracting the 10 m sprint time from the average best performance time. As previously suggested, COD deficit has the potential to assess an actual COD ability unbiased toward linear sprint capacity [23,24]. ...
Full-text available
Background: The present study aimed to determine the association of anthropometry-based characteristics with an aggregate score (AS) of physical performance in young elite soccer players. Methods: Sixteen under 15 elite players were enrolled. Among numerous anthropometrics variables, upper arm contracted (UACC) and relaxed circumference (UARC), corrected arm muscle area (AMAcorr), arm muscle circumference (AMC), thigh muscle circumference (TMC) and suprapatellar girths were also employed in this study. Players’ physical performance was assessed by the change of direction (COD), 10 m and 20 m sprint, countermovement jump (CMJ) test, sprint with 90∘ turns (with ball), and yo-yo intermittent recovery test level 1 (Yo-Yo IRT1). The AS was computed by Principal Components Analysis technique with one component on normalized performance results. A stepwise regression analysis was conducted to assess potential association between anthropometry-based variables and AS. Results: Large negative correlations (r < –0.68) of AS with UACC, UARC, AMAcorr, and AMC were detected. UACC and TMC permits to accurately estimate AS explaining 60% of the total variance (p < 0.001). Conclusions: These findings demonstrated the importance of including anthropometry-based measures of both upper and lower body to the physical performance potential expressed by AS in elite youth soccer.
... The best performance of the two tests was used for further analysis. The 30m sprint was previously used to estimate linear speed in a study by Nimphius, Callaghan, Spiteri, & Lockie (2016). ...
Full-text available
The purpose of this study was to present the physical performance of elite female soccer players and to analyze the relationship between jump performance, speed and COD ability. Sixteen elite female soccer players (age: 20.05±2.85; height: 166.47±4.83cm; body weight: 60.52±8.30kg, BMI 21.88±2.86) from a women's club who played the highest rank of the competition took part in this study. The jump, speed and COD abilities of each player were determined using: (1) the Squat jump (SJ), (2) Countermovement Jump (CMJ), countermovement jump with arm swing (CMJA), (2) running speed at 30-m with passing time at 10m and 20m, (3) the pro agility test (pro), (4) zigzag test (zig-zag), (5) 9-6-3-6-3 sprint (9-6-3-6-9). The results of Pearson's correlation indicated moderate significant relationships between the 10m running speed and pro agility test (r=0.59; p<0.01), as well as the zigzag test (r=0.55; p<0.01), and also between the 30m and all COD tests (pro agility r=0.66; p<0.01, zigzag r=0.59; p<0.01 and 9-6-3-6-9 r=0.58; p<0.05). A small correlation (r=0.49; p<0.03) was noticed between the 10m running test and 9-6-3-6-9 agility test, and also between the CMJA (r=0.45; p<0.05) and the 9-6-3-6-9 agility test. The findings of the present study indicated a significant correlation between speed and all of the COD tests, additionally between the CMJA and 9-6-3-6-9 COD test. Therefore, elite female soccer players with higher maximum acceleration rates and speed tend to perform better in change of direction tests. On the other hand, jump performance does not significantly correlate with COD ability.
Full-text available
RESUMEN El objetivo del presente estudio fue determinar el perfil morfológico y funcional por posición en jugadoras de fútbol femenino bogotanas. La muestra fue de 81 jugadoras con una edad promedio (15,58±0,85 años), talla (159,4±5,36 cm) y masa corporal (54,55±6,82 kg), seleccionadas en seis posiciones: portera (P, n:8), defensa central (DC, n:13), defensa lateral (DL, n:14), volante central (VC, n:18), volante lateral (VL, n:11) y delantera (DEL, n:17). Estudio de enfoque cuantitativo, diseño no experimental y tipo descriptivo con un muestreo no probabilístico, las pruebas empleadas fueron el test de campo yo-yo test de recuperación intermitente nivel uno, el test sprint Bangsbo, el test de velocidad 15 y 30 metros, mientras que, la fuerza se evaluó a través de plataformas uniaxiales. La determinación del somatotipo se realizó a partir del método Heath y Carter. El tratamiento estadístico fue realizado mediante el programa R versión 4.1.0. Los resultados evidencian que, entre las diversas posiciones existen diferencias significativas entre variables relacionadas con el peso (p=0.03), la masa libre de grasa (p=0.01), la fuerza neta en pierna derecha en 100 ms [N] (p=0.04), fuerza neta pierna derecha 150ms [N] (p=0.03), fuerza neta pierna derecha 200ms [N] (p=0.03), promedio de habilidad de sprint repetido (RSA) (p=0.00) y porcentaje de fatiga (p=0.00). Del estudio, se puede concluir que, si existen diferencias significativas vinculadas al rol por posición de juego que desempeña cada jugadora en competencia, por lo que, establecer el perfil neuromuscular de la deportista es un punto de partida para fortalecer la estructuración del proceso de entrenamiento en el fútbol femenino. Palabras clave: perfil morfofuncional, fútbol, deportistas, esfuerzo físico, fuerza muscular. ABSTRACT The aim of this study was to determine the morphological and functional profile by position in female soccer players from Bogota. The sample consisted of 81 players with an average age (15.58±0.85 years), height (159.4±5.36 cm) and body mass (54.55±6.82 kg), selected in six positions: goalkeeper (P, n:8), central defender (DC, n:13), lateral defender (DL, n:14), central midfielder (VC, n:18), lateral midfielder (VL, n:11) and forward (DEL, n:17). Quantitative approach study, non-experimental design and descriptive type with a non-probabilistic sampling, the tests used were the yo-yo field test intermittent recovery test level one, the Bangsbo sprint test, the speed test 15 and 30 meters, while, strength was evaluated through uniaxial platforms. The somatotype was determined using the Heath and Carter method. The statistical treatment was carried out using the R program version 4.1.0. The results show that, among the different positions, there are significant differences between variables related to weight (p=0.03), fat free mass (p=0.01), net strength in right leg at 100 ms [N] (p=0.04), net strength right leg 150ms [N]
Full-text available
The aims of this study were: a) to investigate the effects of a unilateral training program in reducing inter-limb asymmetry in male soccer players; b) to explore such effects on measures of physical performance and unilateral inter-limb asymmetry. Twenty-four soccer players, randomly assigned to a 6-week unilateral strength and power training (UNI) (n = 12) or a control group (CON) (n = 12), performed single leg countermovement jump (SLCMJ), single leg broad jump (SLBJ), and single leg drop jump (SLDJ), and 10-meter sprint and 505 change of direction (COD) speed test. Raw jump scores revealed small to large improvements in SLCMJ, SLBJ, and SLDJ reactive strength index (RSI) (g = 0.46 to 1.66) in the UNI group; whereas negligible changes were found in the CON group (g =-0.31 to 0.33). Asymmetry indexes showed a moderate significant reduction in the SLDJ (RSI) and in the SLDJ stiffness (K) (g = 1.00 to 1.11) in the UNI group. The between-group comparison indicated a significant change in the SLDJ (RSI) and in the SLDJ (K) (g = 1.01 to 1.07) in favour of the UNI group. Thus, a unilateral training program seems to be able to reduce between-limb imbalances and foster improvements in jump performance, without any detrimental effects on linear or COD speed times. Given the importance of these physical characteristics for soccer, it is suggested that unilateral strength and power training are incorporated into strength training routines for players of all abilities.
Besides examining upper and lower limb morphological and functional asymmetry magnitudes, this study examined the relationship between lean mass and functional asymmetry in terms of magnitude and direction in 41 youth tennis players versus 41 controls. Asymmetry magnitude was determined based on anthropometric measurements (circumferences, widths), bioelectrical impedance analysis (lean mass) and a test battery (handgrip strength, seated medicine ball throw, plate tapping, single leg countermovement jump, single leg forward hop test, 6 m single leg hop test, 505 change of direction). ANOVAs compared the dominant (overall highest/best value) against the non-dominant (highest/best value of opposing limb) result. Linear regressions explored the relationship between lean mass and functional asymmetry magnitudes. Kappa coefficients examined consistency in asymmetry direction between the limb displaying the highest lean mass value and the limb performing dominantly across tests. Significant asymmetry magnitudes (p<0.05) were found for all upper and lower limb morphological and functional outcome measures. No significant relationship was apparent between lean mass and functional asymmetry magnitude (r-value range=-0.283-0.262). Despite finding (almost) perfect consistency in asymmetry direction (k-value range=0.84-1.00) for the upper limb, poor to slight consistency (k-value range=-0.03-0.15) was found for the lower limb. Therefore, lean mass and functional asymmetry should be examined independently.
Full-text available
Change of direction (COD) ability is an important physical fitness capacity required in conjunction with cognitive-perceptual ability to perform effective and efficient agility manoeuvres in many sports (4). Although, the physical capacity to change direction is often measured by strength and conditioning professionals, the ability of these common COD tests (presented as time to complete a running task) to truly measure one’s ability to decelerate and subsequently reaccelerate in a new direction is often tangled within one’s ability to perform straight line running. This has been demonstrated with large to very large correlations found between COD tests and straight-line sprint speed in various studies (1, 3, 5). The reason for continuing to use these common COD tests, such as the T-test, 505 and pro-agility is often due to existing data to compare athlete performances and ease of data collection. Some researchers have used the velocity of the centre of mass as a true measure of COD ability (6). Although assessing COD ability by measuring athlete COM out of a COD step provides a direct measure of COD ability, the scope for strength and conditioning professionals to be able to use this type of assessment is small due to time and equipment constraints. A proposed method, termed “change of direction deficit”, to assess COD ability was calculated to assess if this measure could better isolate COD ability independent of one’s straight-line sprint ability.
Full-text available
No research has analysed the influence of ankle muscle activity for joint mobility and stability on preferred directional cutting. Twelve basketballers completed the Y-shaped agility test, requiring 45° cuts to the left or right, to assess planned and reactive cutting. In planned conditions, participants knew the cutting direction. In reactive conditions, participants responded to a randomly illuminated gate. Legs were defined as the outside (furthest from target gate) or inside (closest to target gate) cut legs. The preferred outside cutting leg was determined from the fastest planned cut. Electromyography measured peak normalised (against 10-meter sprint performance) activity of the tibialis anterior, peroneus longus (PL), peroneus brevis (PB), and soleus. Paired t-tests (p Keywords: AGILITY; COURT SPORTS; DOMINANT LEG; ELECTROMYOGRAPHY; PERONEALS Document Type: Research Article Publication date: August 1, 2014 More about this publication? Editorial Board Information for Authors Subscribe to this Title Terms & Conditions ingentaconnect is not responsible for the content or availability of external websites $(document).ready(function() { var shortdescription = $(".originaldescription").text().replace(/\\&/g, '&').replace(/\\, '<').replace(/\\>/g, '>').replace(/\\t/g, ' ').replace(/\\n/g, ''); if (shortdescription.length > 350){ shortdescription = "" + shortdescription.substring(0,250) + "... more"; } $(".descriptionitem").prepend(shortdescription); $(".shortdescription a").click(function() { $(".shortdescription").hide(); $(".originaldescription").slideDown(); return false; }); }); Related content In this: publication By this: publisher In this Subject: Internal Medicine By this author: Lockie, Robert G. ; Jeffriess, Matthew D. ; McGann, Tye S. ; Callaghan, Samuel J. GA_googleFillSlot("Horizontal_banner_bottom");
Full-text available
The influence of unilateral jump performance, and between-leg asymmetries, on multidirectional speed have not been widely researched. This study analyzed how speed related to unilateral jumping. Multidirectional speed was measured by 20-m sprint (0-5, 0-10, 0-20 m intervals), left- and right-leg turn 505, and modified T-test performance. Unilateral jump performance, and between-leg asymmetries, was measured by vertical (VJ), standing broad (SBJ), and lateral (LJ) jumping. Thirty male team sport athletes (age = 22.60 3.86 years; height = 1.80 0.07 m; mass = 79.03 12.26 kilograms) were recruited. Pearson's correlations (r) determined speed and jump performance relationships; stepwise regression ascertained jump predictors of speed (p < 0.05). Subjects were divided into lesser and greater asymmetry groups from each jump condition. A one-way analysis of variance found between-group differences (p < 0.05). Left-leg VJ correlated with the 0-10 and 0-20 m intervals (r = -0.437 to -0.486). Right-leg VJ correlated with all sprint intervals and the T-test (r = -0.380 to -0.512). Left-leg SBJ and LJ correlated with all tests (r = -0.370 to -0.729). Right-leg SBJ and LJ related to all except the left-leg turn 505 (r = -0.415 to -0.650). Left-leg SBJ predicted the 20-m sprint. Left-leg LJ predicted the 505 and T-test. Regardless of the asymmetry used to form groups, no differences in speed were established. Horizontal and lateral jump performance related to multidirectional speed. Athletes with asymmetries similar to this study (VJ = ∼10%; SBJ = ∼3%; LJ = ∼5%) should not experience speed detriments.
Full-text available
The cricket quick single has received minimal scientific analysis. This study investigated the acceleration kinematics of the non-striking batsmen during a quick single. A total of 20 cricketers completed 17.68-m sprints following three starts: standard (no cricket-specific equipment), static cricket (side-on start, bat held on crease) and rolling cricket (walking start, bat dragged through crease). Timing gates recorded 0–5 m and 0–17.68 m time. Participants wore leg guards and carried a bat during cricket-specific sprints. Joint and step kinematics were investigated through the first and second steps via motion analysis. A repeated measures analysis of variance determined significant (p < 0.05) within-participant differences between conditions. The rolling cricket start resulted in faster 0–5 m and 0–17.68 m times, and a 12% longer first, and 8% longer second, step. For cricket-specific sprints, shoulder sagittal plane range of motion (ROM) and elbow extension decreased in the arm carrying the bat. In response to this reduced arm ROM, hip flexion decreased. There were no changes to hip extension. Shoulder and wrist frontal plane ROM, and wrist sagittal plane ROM, increased as a result of carrying the bat. The need for cricketers to use specialised equipment while completing a quick single resulted in specific acceleration kinematic alterations.
Full-text available
Abstract Understanding the magnitude of forces and lower body kinematics that occur during a change of direction (COD) task can provide information about the biomechanical demands required to improve performance. To compare the magnitude of force, impulse, lower body kinematics and post-COD stride velocity produced between athletes of different strength levels during a COD task, 12 stronger (8 males, 4 females) and 12 weaker (4 males, 8 females) recreational team sport athletes were recruited. Strength levels were determined by relative peak isometric force of the dominant and non-dominant leg. All athletes performed 10 pre-planned 45° changes of direction (5 left, 5 right) while three-dimensional motion and ground reaction force (GRF) data were collected. Differences in all variables for the dominant leg were examined using a one-way analysis of variance (ANOVA) with a level of significance set at p ≤0.05. The stronger group displayed significantly faster post-COD stride velocity and greater vertical and horizontal braking forces, vertical propulsive force, vertical braking impulse, horizontal propulsive impulse, angle of peak braking force application, hip abduction and knee flexion angle compared to the weaker group. The results suggest that individuals with greater relative lower body strength produced higher magnitude plant foot kinetics and modified lower body positioning while producing faster COD performances. Future investigations should determine if strength training to enable athletes to increase plant foot kinetics while maintaining or adopting a lower body position results in a concomitant increases in post-COD stride velocity.
Strength and power diagnosis can provide valuable insights into the different capacities of athletes. The strength and power tests chosen should be reliable and valid and take into account the requirements of the sport and what is a meaningful change in performance. The results of these tests need to be reported in a clear, meaningful, and timely manner for coaches if they are to have maximal impact on training programs. The practitioner can use this evidence-based information in conjunction with the art of coaching to maximize training program effectiveness.
In an attempt to develop a new measure of agility in the horizontal plane, this study examines several tests, including: the Illinois agility test, the 20m dash and two new tests - the Up and Back (UAB) and 505 tests, which both involve a short sprint and a reversal of direction. Eighteen subjects performed the tests in a randomised order. A strobe video and time were used to record the displacement data of the subjects, over set intervals, in the UAB and 505 tests. These data were then smoothed using a least-squares polynomial, and differentiated to produce a velocity and acceleration values. Times were recorded for the completion of the Illinois agility test and the 20m dash. The results for the four tests and the derived velocity and acceleration values were subjected to a correlation matrix. Significant correlations were found between the 505 test and acceleration values, but not with velocity values. The other tests correlated significantly with each other. It is concluded that the UAB test and Illinois Agility test are not purely agility tests because of their significant relationships with the 20m dash. The 505 test, however, has no significant correlation with velocity, but rather with acceleration. Therefore, the 505 test is seen as the test which best isolates agility in the horizontal plane.
This study assessed the relationships between linear running velocity and change of direction (CoD) ability, and how assessing CoD ability over distances ≤ 5 m influences test reliability. Participants (n=15) from amateur rugby league teams performed three trials of a 20 m sprint test (light gates at 5 m, 10 m and 20 m) and six trials of the 5-0-5 agility test. Twelve participants repeated the 5-0-5 test several weeks later. A three-dimensional motion capture system (250 Hz) was used to track the centre of mass at 0.3 m, 0.5 m and 1.0 m either side of the turn and identify specific CoD phase times. Pearson's correlations showed strong, significant relationships between the 5-0-5 time and 5 m (r=0.89, P<0.001); 10 m (r=0.91, P<0.001) and 20 m sprint times (r=0.93, P<0.001). However, the strength of these relationships decreased (r<0.65, P>0.05) when CoD ability was measured over distances less than 0.5 m. Analysis of coefficient of variation (CV%) data indicated that the 5-0-5 test had high intra (CV% = 2.8) and inter-test reliability(CV% = 1.3), with these data decreasing for distances less than 1 m (CV% = 3.5-6.9). Specific movement phase times were the least reliable measures of CoD ability (CV% 4.7-53.6). Results suggest a bias between high speed linear running ability and 5-0-5 time. However, an effective compromise can be found between test reliability and the external validity by assessing CoD ability over 1 m. Findings indicate that the current practice of assessing CoD ability over large distances in questionable.