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CHANGE OF DIRECTION DEFICIT:AMORE ISOLATED
MEASURE OF CHANGE OF DIRECTION PERFORMANCE
THAN TOTAL 505 TIME
SOPHIA NIMPHIUS,
1,4
SAMUEL J. CALLAGHAN,
1
TANIA SPITERI,
2
AND ROBERT G. LOCKIE
3
1
Centre for Exercise and Sport Science, School of Exercise and Health Sciences, Edith Cowan University, Joondalup, Australia;
2
School of Health Sciences, The Notre Dame University Australia, Fremantle, Australia;
3
Department of Kinesiology, California
State University, Northridge, California; and
4
Hurley Surfing Australia High Performance Centre, Casuarina, Australia
ABSTRACT
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,
cutting
INTRODUCTION
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, s.nimphius@ecu.edu.au.
30(11)/3024–3032
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Ó2016 National Strength and Conditioning Association
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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.
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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.
METHODS
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.
Subjects
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
21
) extending over the pre-
vious 12 months; were currently training for cricket ($3
h$wk
21
); 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.
Procedures
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
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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
relationships.
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
r0.74†0.58z0.70§ 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
R
2
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
2
= explained variance; p= significance.
†Significant p,0.0001.
zSignificant p#0.05.
§Significant p,0.01.
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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.
RESULTS
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
r0.81†0.52z0.63§ 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
R
2
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
2
= 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
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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.
DISCUSSION
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.
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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
3030
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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.
PRACTICAL APPLICATIONS
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.
ACKNOWLEDGMENTS
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.
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