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RELIABILITY OF THE MAXIMAL RESISTED SPRINT
LOAD TEST AND RELATIONSHIPS WITH
PERFORMANCE MEASURES AND ANTHROPOMETRIC
PROFILE IN FEMALE FIELD SPORT ATHLETES
GEORGE PETRAKOS,
1,2
NICOLA C. TYNAN,
1
ADAM M. VALLELY-FARRELL,
1
CILLIAN KIELY,
1
ABDELHAK BOUDHAR,
1
AND BRENDAN EGAN
1,3
1
School of Public Health, Physiotherapy and Sport Science, Institute for Sport and Health, University College Dublin, Belfield,
Dublin, Ireland;
2
Glasgow Warriors, Scotstoun Stadium, Glasgow, United Kingdom; and
3
School of Health and Human
Performance, Dublin City University, Glasnevin, Dublin, Ireland
ABSTRACT
Petrakos,G,Tynan,NC,Vallely-Farrell,AM,Kiely,C,
Boudhar, A, and Egan, B. Reliability of the maximal resisted
sprint load test and relationships with performance meas-
ures and anthropometric profile in female field sport athletes.
J Strength Cond Res 33(6): 1703–1713, 2019—Resisted
sled sprint (RSS) training is an effective modality for the
improvement of linear sprint speed. Previous methods of
RSS load prescription, e.g., an absolute load or as a percent-
age of body mass (%BM), do not account for interindividual
differences in strength, power, or speed characteristics,
although the “maximum resisted sled load” (MRSL) method
of RSS load prescription may provide a solution. Maximum
resisted sled load is defined as the final RSS load before an
athlete can no longer accelerate between 2 phases (10–15
and 15–20 m) of a 20-m linear sprint. However, the MRSL
test has not been analyzed for reliability. In addition, MRSL
performance has not been compared with the outcome of
other performance tests. The primary aim of this study was
to investigate the reliability of the MRSL testing protocol in
female field sport athletes. Participants (age, 20.8 61.9
years; body mass, 64.3 68.4 kg; height, 1.66 60.65 m)
tested for anthropometric measurements, strength and
power performance testing, and twice for MRSL. Maximum
resisted sled load values ranged from 20.7 to 58.9% BM.
Maximum resisted sled load test-retest reliability intraclass
correlation coefficient, confidence intervals, and coefficient
of variations were 0.95, 0.85–0.98, and 7.6%, respectively.
Maximum resisted sled load was“moderately” and “strongly”
correlated with a number of anthropometric and perfor-
mance tests (p#0.05), including percentage fat free mass,
countermovement jump, loaded countermovement jump,
rate of force development, horizontal jump, and horizontal
bound performance. Maximum resisted sled load is a reliable
measure for determining the RSS load at which an individual
can no longer accelerate during a single RSS effort over 0–
20 m. Maximum resisted sled load also accounts for inter-
individual variation in body composition, power, and speed
characteristics of female field sport players.
KEY WORDS sled sprinting, speed training, sport performance,
correlation
INTRODUCTION
Resisted sled sprint (RSS) training is a form of
resistance exercise involving a set number of lin-
ear sprints while towing a sled device. Resistance
is provided by a combination of sled mass and the
coefficient of friction between the sled and running surface
(29,30). Resisted sled sprint training is an effective tool for
the improvement of linear sprint performance
(2,5,22,28,31,33,34,49,55,61,62). After RSS training, improve-
ments in sprint performance have been observed in males
(2,5,28,31,55,61,62) and females (33,34,62), including both
trained (2,22,28,31,33,55,61) and untrained adults (5,34,62).
From 11 RSS training studies, 3 different methods of sled
load prescription were used (49). Resisted sled sprint load is
prescribed by either (a) a targeted percentage decrement in
unresisted sprint (URS) velocity (%V
dec
) (2,11,28,31,34,55),
(b) a percentage of the individual’s body mass (%BM)
(5,22,33,61), or (c) an absolute mass of the sled (62). Differ-
ences in the method of sled load prescription affect the
validity of between-study comparisons for practical applica-
tions by strength and conditioning coaches. In addition, the
aforementioned methods may not be optimal for sled load
Address correspondence to George Petrakos, George.petrakos@
glasgowwarriors.org.
33(6)/1703–1713
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Ó2019 National Strength and Conditioning Association
VOLUME 33 | NUMBER 6 | JUNE 2019 | 1703
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prescription because they do not account for interindividual
variation in strength, power, or speed characteristics.
A greater power-to-body mass (BM) ratio is related to
faster acceleration in RSS performance (29). In addition,
as sled load increases, the rate of increase in sprint time
is inversely correlated to countermovement jump (CMJ)
height (r=20.73), CMJ relative peak power (CMJP) (r=
0.81), and squat jump relative peak power (r=0.80)in
male sprinters (35). Therefore, several authors have called
for methods of RSS load prescription to account for an
athlete’s power-to-BM ratio, as individual variation in
muscular power or sprint performance is unaccounted
forwhensledloadisprescribedbyanabsolutemassor
%BM (27,35,46). The %V
dec
method accounts for individ-
ual variation in sprint performance. However, a recent
systematic review found between-study differences in
the method of %V
dec
sled load prescription, with varying
sprint distances used to provide a measurement of velocity
decrement (49). Between-study variation in sled load pre-
scription methods does not allow a clear comparison of
training studies and therefore reduces the external validity
of the methodology. Furthermore, the %V
dec
method does
not provide a maximal value, such as a 1 repetition max-
imum (1RM), from which to periodize and program RSS
training from. Given the issues with the 3 current methods
of RSS load prescription, a contemporary approach is
required.
A 1RM test is often used as a reference for strength and
conditioning coaches to program resistance exercise
intensity (6,8,13,38,56). A comparable method for RSS
acceleration performance has been proposed (36). The
“maximum resisted sled load” (MRSL) test is based on
findings that the rate of decrease in sprint velocity is influ-
enced independently by both sled load and sprint distance
(36). Simply, the heavier the sled, or longer the sprint
distance, the greater the decline in sprint acceleration
(29). Maximum resisted sled load is defined as the final
RSS load before an athlete can no longer accelerate
between 2 phases (10–15 and 15–20 m) of a 20-m linear
sprint. Therefore, the MRSL protocol quantifies the mag-
nitude of linear RSS acceleration through the final 10 m of
a 22-m sprint (36). Maximum resisted sled load should
account for interindividual differences in muscular power
as the greater an athlete’s power-to-BM ratio, the lower
the rate of decrease in RSS velocity with increasing sled
mass (29). Significant relationships exist between MRSL
and relative Smith machine half squat 1RM (r=0.71)and
20 m URS time (r=20.71) (36). The strong relationships
between MRSL and the specific performance tests indi-
cate that prescribing RSS load from the MRSL may
account for interindividual variation in vertical force pro-
duction and sprint performance. It is unknown whether
MRSL correlates with other performance tests spanning
a range of force-velocity demands.
Although the original MRSL protocol represents a for-
ward step in sled load prescription, the method has not been
tested for reliability. A measurement tool cannot be valid if
lacking sufficient reliability (16).
The primary aim of this study was to determine the
reliability of a MRSL protocol in female field sport athletes.
If reliable, the secondary aim of the study was to determine
whether various performance tests can determine or predict
or estimate a female field sport athlete’s MRSL (MRSL
est
).
METHODS
Experimental Approach to the Problem
The cross-sectional study design consisted of 5 sessions
(Figure 1). Familiarization sessions were designed to account
for a possible learning effect. Each performance test was
practiced with coaching provided by a qualified strength
and conditioning coach. Most participants regularly used
RSS methods as part of their resistance training programs.
Those participants who required RSS practice undertook
RSS familiarization sessions after physical testing on days 2
and 3. Participants were required to maintain their routine
physical activity and diet throughout the testing period,
Figure 1. Experimental approach. RSS = resisted sled sprinting; MRSL = resisted sprint acceleration maximum; CMJ = countermovement jump; IMCP
= isometric midthigh clean pull; URS = unresisted sprint; DJ = drop jump; 5RB = 5-repeated bound; CMJ50 = hexagonal bar countermovement jump
loaded at 50% body mass.
Reliability of the Maximum Resisted Sled Load Test
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refraining from high-intensity physical activity 48 hours
before each testing day.
Subjects
Twenty-one female participants (mean 6SD: age, 20.8 61.9
years; range 18-26 years; body mass, 64.3 68.4 kg; height,
1.66 60.65 m) volunteered to take part in this study. After
the first MRSL trial, 4 participants withdrew because of
European field hockey commitments. Therefore, 17 women
(mean 6SD: age, 20.5 62.0 years; body mass, 64.8 68.7 kg;
height, 1.68 60.65 m) completed the second MRSL trial,
and their data were used for the reliability analysis. All par-
ticipants played a field-based team sport of field hockey (n=
16), soccer (n= 2) or Gaelic football (n= 3). Playing stand-
ards ranged from senior, junior, and university international-
ists to amateur club-level competitors. All participants were
free from musculoskeletal pain or injuries from the past 6
months. Participants were informed of the benefits and risks
of the investigation before providing written informed con-
sent, with ethical approval obtained from the local research
ethics committee at University College Dublin.
Procedures
Body Composition and Anthropometry. The test battery and
testing variables performed in this study and their accom-
panying abbreviations used throughout the text are found in
Table 1. Participant height (Ht) and BM were measured
using, respectively, a stadiometer (Leicester Height Mea-
surer, Birmingham, United Kingdom) to the nearest 0.01 m
and mechanical column scales (SECA 756; SECA UK, Bir-
mingham, United Kingdom) to nearest 0.1 kg. Body compo-
sition was measured with dual-energy x-ray absorptiometry
(DXA) (Lunar iDXA; GE Healthcare, Madison, WI, USA)
and Lunar iDXA enCore 2008 computer software (version
12.30.008; GE Healthcare). Participants were instructed to
attend the DXA scan after a 12-hour fast. Participants wore
underwear or tight-fitting minimal clothing. All DXA scans
were administered and analyzed by the same technician.
Measurements were taken for whole body fat percentage
(BF), relative fat-free mass (FFM) as a percentage of total
BM, and relative lower limb fat-free mass (LLFFM) as a per-
centage of total BM. All body composition variables have
TABLE 1. Test battery and abbreviations.
Test name
Test
abbreviation Independent variable
Variable
abbreviation
Dual-energy x-ray
absorptiometry
DXA Whole body fat percentage (%) BF
Relative fat-free mass as a percentage of total body mass (%) FFM
Lower limb fat-free as a percentage of
total body mass (%)
LLFFM
Countermovement jump CMJ Countermovement jump height (cm) CMJHt
Countermovement jump peak power output relative to body
mass (W$kg BM
21
)
CMJP
Countermovement jump
loaded with 50% of body
mass
CMJ50 Countermovement jump loaded with 50% of body mass peak
power output relative to body mass (W$kg BM
21
)
CMJ50P
Drop jump DJ Reactive strength index (mm$ms
21
) RSI
Horizontal jump HJ Horizontal jump distance (m) HJ distance
Horizontal jump distance relative to
standing height (m$mHt
21
)
HJ
rel
5-repeated alternate-leg
bound
5RB 5-repeated alternate-leg bound distance (m) 5RB
5-repeated alternate-leg bound distance relative to
standing height (m$mHt
21
)
5RB
rel
Isometric midthigh clean pull IMCP Isometric peak force relative to body mass (N$kg BM
21
) IPF
Rate of force development from 0 to 100 ms relative
to body mass (N$kg BM
21
)
RFD100
Rate of force development from 0 to 200 ms relative to body
mass (N$kg BM
21
)
RFD200
Peak rate of force development over a 20 ms period
relative to body mass
RFDpeak
Unresisted sprint time URS 0–10 m sprint time (s) URS10
0–20 m sprint time (s) URS20
Maximal resisted sled load MRSL Maximal resisted sled load (%BM) MRSL
Velocity decrement from an unresisted sprint (%) V
dec
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previously shown adequate reliability through intraclass cor-
relation coefficient (ICC) and coefficient of variation (ICC =
0.99, CV = 0.4–5.0%) (10,47).
Warm-up. Day 2 was initiated with a standardized warm-up
consisting of 4 minutes of continuous cycling on a stationary
bike at 90–100 W, 10 forward leg swings per limb, 10 deep
bodyweight squats, and 5 bodyweight CMJs of which pro-
gressed from 50 to 90% of perceived maximal effort. The day
3 warm-up differed only where 10 ankle bounces replaced
the CMJs from day 2. After cessation of each test, partici-
pants were provided 5 minutes of rest before the warm-up of
the following performance test.
Countermovement Jump. The day 2 warm-up was completed
immediately before CMJ testing. Participants were instructed
to stand on a portable force platform (HUR Labs, Tampere,
Finland) with their feet shoulder-width apart. The CMJ
involves an eccentric countermovement at a self-selected
depth and speed, immediately followed by a maximal
concentric vertical jump. Instructions were provided to jump
“as high as possible” and “land back on the force platform.”
Hands remained on hips for the duration of the movement.
Participants had just 3 maximal repetitions with 2 minutes
rest between efforts. The force platform collected vertical
ground reaction force data at 2,000 Hz. The independent
variables were CMJ height (CMJHt) and CMJ relative peak
power output (CMJP). Countermovement jump height and
absolute peak power output were derived by Force Platform
Software Suite v.2.65.4 (HUR Labs) with previously
described methods (18). Countermovement jump relative
peak power was calculated by dividing absolute peak power
output by participant BM. All independent variables have
previously shown adequate reliability (ICC = 0.98, CV =
2.3–5.0%) (12,26).
Countermovement Jump Loaded With 50% of Body Mass. A
hexagonal bar (hex bar) CMJ was used as a measure of
vertical strength-speed. The hex bar jump squat exhibits
a greater force and power output in comparison to the
barbell jump squat (57). In addition, peak power output with
the hex bar jump squat demonstrates strong inverse relation-
ships with 10-m (r=20.70) and 20-m (r=20.75) URS
performance (59). The measurement protocol differed only
from the standard CMJ
test with a change in
arm position to hold the
hex bar. In addition, par-
ticipants were instructed
not to alter bar displace-
ment through elbow
flexion during any phase
of the jump. Participants
performed just 3 repeti-
tions separated by 2 mi-
nutes of rest. The independent variable was CMJ loaded
with 50% of body mass (CMJ50) relative peak power output
(CMJ50P). CMJ50P was calculated by dividing CMJ50 abso-
lute peak power output by participant BM. Peak power out-
put in the loaded hex bar CMJ has previously shown
adequate reliability (ICC = 0.98, CV = 0.5–8.0) (58).
Drop Jump Reactive Strength. Participants completed the day
3 warm-up and 1 submaximal drop jump (DJ) effort before
their first maximal repetition. The DJ test used the force
platform (HUR Labs) and a starting box 30 cm higher than
the force platform surface. Participants stepped off the box
and performed a bilateral DJ on to the force platform. The
DJ requires a fast eccentric contraction followed by a fast
maximal concentric vertical jump. The DJ instructions
included: “spend as little time on the floor for as much jump
height as possible” and “be like a spring.” Participants kept
hands on hips for the entirety of the movement and per-
formed just 3 repetitions separated by 2 minutes of passive
rest. The independent variable taken from the DJ was the
reactive strength index (RSI). The RSI describes the ability
to change quickly from an eccentric to concentric contrac-
tion and is calculated as flight time divided by force plat-
form contact time (mm$ms
21
) (19). Reactive strength
index is correlated with URS performance in female ath-
letes (43). The RSI, as previously described (19), was mea-
sured as jump height divided by force platform contact time
(mm$ms
21
). The RSI has previously shown adequate
reliability (ICC = 0.97, CV not measured in adult popula-
tions) (19).
Figure 2. Schematic illustration of the maximum resisted sled load test.
Figure 3. The sled towing device.
Reliability of the Maximum Resisted Sled Load Test
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Horizontal Jump. The horizontal jump (HJ) is positively
correlated with URS performance in female athletes (1,42).
Participants warmed-up for the test with 5 progressive repe-
titions from 50 to 90% of perceived maximal effort. The inde-
pendent variables were HJ distance and HJ distance relative to
standing height (HJ
rel
). Participants stood with feet shoulder-
width apart and directly behind a starting line at 0 cm. To
provide augmented motivation, investigators repeatedly
placed a target marker beyond the individual’s best HJ dis-
tance from previous efforts. Participants performed a counter-
movement of self-selected depth and speed immediately
followed by a maximal concentric jump for distance. Partic-
ipants were allowed to use arm swing during all phases of the
movement (ICC = 0.95, CV = 2.4%) (7). Verbal cues were
limited to: “jump as far as you can” and “beat your previous
best mark.” For a valid effort, participants had to stick the
landing with no extra step or fall backwards. Measurements
were taken from 0 cm to the big-toe of the back-most foot
from landing. Participants performed just 3 repetitions sepa-
rated by 2 minutes of passive rest.
Five-Repeated Alternate-Leg Bound. Alternate single-leg
repeated bounding is positively correlated with URS perfor-
mance in female athletes (1). Participants warmed-up for the
test with 1 repetition at 80% of perceived maximal effort.
Participants initiated the activity with their favored starting
leg at 0 cm. The favored leg was self-selected and deter-
mined during the familiarization session. The 5-repeated
alternate-leg bound (5RB) test requires 5 maximal, continu-
ous single-leg bounds. The single-leg bounds are performed
with alternate legs (e.g., left, right, left, etc). Participants
landed in a bilateral position. Participants performed 3 rep-
etitions separated by a 2-minute rest. The independent var-
iables were 5RB distance and distance relative to standing
height (5RB
rel
). The 5RB distance was measured from 0 cm
to the big-toe of the back-most leg. The 5RB distance has
previously show adequate reliability (CV = 2.7%, ICC has
not been previously investigated) (43).
Isometric Midthigh Clean Pull. Relative maximum strength
measured by a 1RM half squat is strongly correlated (r=
0.71) with MRSL (36). However, not all participants in the
current study were familiar with the same high-force com-
pound exercise (e.g., back squat). Therefore, the isometric
midthigh clean pull (IMCP) was used to measure maximal
force production. Participants warmed-up with 3-second
IMCPs at 50 and 80% of perceived maximal effort. The test
required the force platform directly underneath an immov-
able barbell at midthigh height. Participants stepped onto
the force platform, gripped the barbell, and flexed their
ankle, knee, and hip joints to assume the starting position.
Hip (134–1408) and knee angles (137–1438) were measured
with a handheld goniometer (14). Lifting straps placed
around the wrist and palm were used to aid grip strength.
Participants performed a maximal concentric contraction for
5 seconds by pulling upwards on the immovable barbell.
Maximal isometric force was created from attempted triple
extension of the ankle, knee, and hip joints against the force
platform. Verbal instructions included: “from the word go,
pull as hard and fast as you can” and “keep pulling as hard as
possible until asked to stop.” Participants were restricted
from elbow flexion during the pull. In addition, any efforts
that included an eccentric countermovement before the pull
were discarded. Participants performed 2 maximal efforts
separated by 3 minutes of passive rest. All data points were
exported to a custom-made spreadsheet (Microsoft Excel,
WA, USA) for calculation of independent variables. The
absolute measures were isometric peak force (IPF), rate of
force development (RFD) from 0 to 100 ms, 0 to 200 ms and
peak RFD over a 20-ms period. Isometric peak force was
taken as the highest force recorded during the 5-second pull.
RFD100, RFD200, and RFDpeak were calculated manually.
All absolute measures
were made relative by
dividing by participant
BM. Therefore, the inde-
pendent variables were
IPF relative to BM
(IPF), relative RFD from
0 to 100 ms (RFD100),
0 to 200 ms (RFD200),
and relative peak RFD
over a 20 ms period
(RFDpeak). All IMCP
TABLE 2. Test-retest reliability of the MRSL test
(n= 17).*
ICC 95% CI SEM CV (%)
MRSL 0.95†0.85–0.98 3.29 7.6
*MRSL = maximal resisted sled load; ICC = intra-
class correlation coefficient; CI = confidence interval;
SEM = standard error of measurement; CV = coeffi-
cient of variation.
†p,0.001.
TABLE 3. Descriptive statistics for the MRSL test (n= 21).*
MRSL (%BM) No. of participants (%) within MRSL (%BM) range
Mean 6SD Range ,30% 30–40% 40–50% 50–60%
33.7 610.0 20.7–58.9 8 (38) 8 (38) 4 (19) 1 (5)
*MRSL = maximum resisted sled load; BM = body mass; SD = standard deviation.
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variables have previously shown adequate reliability (ICC =
0.90–0.99, CV = 1.7–12.9%) (21).
Unresisted Sprint. Infrared, single-beam speed gates (Fusion
Sport, Queensland, Australia) were placed at 0, 10, and 20 m.
The beam was set at a height of 1 m. Participants warmed-up
with submaximal 20-m sprint repetitions at 60, 80, and 90%
of perceived maximal velocity. Participants started 0.5 m
behind the first gate and were restricted from “rocking” into
the sprint start. A set of markers were placed at 22 m to act
as a finish line, ensuring that participants ran through the
final 20-m gate without dipping or decelerating. Verbal in-
structions included “sprint as fast as you can” and “sprint all
the way through the finish line.” Participants performed 3
repetitions separated by 2 minutes of passive rest. The inde-
pendent variables were 0–10 m (URS10) and 0–20 m
(URS20) URS time, measured in seconds. Single-beam
speed gates have previously shown adequate reliability for
the measurement of sprint performance (ICC = 0.87–0.96,
CV = 1.4%) (20,23).
Maximum Resisted Sled Load. Participants completed a stan-
dardized warm-up consisting of 4 minutes of continuous
cycling on a stationary bike at 90–100 W, 10 repetitions of
hip circling, walking lunges, butt-kicks and leg swings, three
20-m URS efforts at 60, 80, and 90% of perceived maximum
intensity and a RSS effort with a 15% BM load at 90% of
perceived maximum intensity. Speed gates (Fusion Sport)
were placed at 0, 10, 15, and 20 m (Figure 2). The beam
was set at a height of 1 m. Participants were attached to a 4-
kg sled (Figure 3) by a vest-harness and 3 m towing chord.
The same sled was used for all MRSL trials. The total tow-
ing mass consisted of the sled mass plus external load
(Olympic weightlifting plates; Eleiko, Halmstad, Sweden).
The coefficient of friction was measured as 0.64 mand was
calculated using previously stated methods (30). After a pilot
study (n= 8 female, field sport participants), 15% BM was
determined as the heaviest RSS load that was consistently
lighter than MRSL. Therefore, all participants began the
MRSL test with a RSS load of 15% BM. Participants started
0.5 m behind the first gate and were restricted from “rock-
ing” into the sprint start. A set of markers were placed at
22 m, which acted as the finish line, ensuring that partici-
pants ran through the final 20-m gate without dipping or
decelerating. Verbal instructions were identical to those from
the URS methods. After each sprint, the average velocity
measurements from section “A” and “B” were recorded (Fig-
ure 2). If section “B” velocity was greater than that of section
“A,” the sprint was considered successful. If section “B”
velocity was slower than that of section “A,” the sprint
was considered unsuccessful. Simply, a successful RSS effort
identifies acceleration from section “A” to “B.” An unsuccess-
ful effort identifies deceleration from section “A” to “B.” After
a successful effort, the external load was increased by a range
of 0.5–5 kg. The increase in sled load was subjectively based
on the magnitude of difference in velocity between sections
A and B. An unsuccessful sprint required the participant to
re-perform with the same external load as the unsuccessful
effort. Two consecutive unsuccessful sprints required the
participant to perform a final sprint with a sled load of
0.5–2.5 kg lighter than the previously unsuccessful effort.
Again, the decrement in load after 2 failed sprints was sub-
jectively determined by the tester based on the magnitude of
difference in velocity between sections A and B.
Three minutes of passive rest were provided between sprint
efforts. There were no limitations to the number of repeti-
tions required to find MRSL. The final MRSL was taken as
the heaviest “successful” effort. The independent variable
was MRSL recorded as %BM.
Statistical Analyses
The “best score” for each test was used for analysis. Maximum
resisted sled load reliability was tested on various levels. A
paired t-test assessed the systematic difference between 2
MRSL trials. An average-measures ICC examined the test-
retest reliability of the MRSL. An ICC model 2,1 (2-way ran-
dom effects) was used as all participants provided scores for all
trials, whereas a random-effects model enables the generaliza-
tion of results to practical scenarios with similar athlete cohorts
(60). There is currently no accepted determination of
Figure 4. Examples of (a) The relationship between RSS load and the
difference in average velocity between 15–20 m (B) and 10–15 m (A) in
a 0–20 m RSS effort and (b) The relationship between RSS load and %
V
dec
. RSS = resisted sled sprint; BM = body mass; %Vdec = % velocity
decrement from an unresisted sprint.
Reliability of the Maximum Resisted Sled Load Test
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magnitude of ICC (4,60). Within-subject variation was inter-
preted by the coefficient of variation as a percentage of the
mean difference between trials (CV%). The standard error of
measurement (SEM) was calculated as the square root of the
mean square error from a 2-way analysis of variance (60).
A paired t-test was used to identify differences between 10
and 20 m %V
dec
at MRSL. Pearson’s product moment cor-
relations (r) were used to determine whether there was a rela-
tionship between an individual’s “best” MRSL (%BM) and
anthropometric or performance task measurements. The
magnitude of correlation was interpreted from Hopkin’s
scale of effect sizes (25), where Pearson’s rvalues of
,0.1 = trivial, 0.1–0.3 = small, 0.3–0.5 = moderate, 0.5–0.7
= large, 0.7–0.9 = very large, and .0.9 = nearly perfect.
Multiple regression equations were calculated to determine
whether the performance tests could predict MRSL. A step-
wise approach used performance variables only if they held
a significant relationship with MRSL. The regression analy-
sis included a test to check for multicollinearity. Significance
was accepted at p#0.05 for all statistical tests.
RESULTS
There was no significant difference (p= 0.734, t(16) = 0.35)
between the MRSL trial 1 (30.7 611.0% BM) and trial 2
(31.1 69.6% BM).
A description of the ICC and confidence intervals for the
MRSL test are stated in Table 2. The within-subject variation is
described by a CV of 7.6%. Ten participants recorded their best
MRSL in the re-test trial, whereas 7 scored highest in the first trial.
The average number of sprint repetitions required for the
MRSL test was 8.7 63.3 with a range of 4–14 repetitions. The
descriptive statistics for the MRSL test are presented in Table 3.
The average %V
dec
for 10 and 20 m at MRSL was 27.4 6
6.9% (range = 16.2–42.5%) and 31.0 68.6% (range = 18.5–
53.5%), respectively. The 3.6 62.2% difference in V
dec
between 10 and 20 m was statistically significant (t(20) =
7.53, p,0.001). The relationship between RSS load and
(a) sprint acceleration and (b) %V
dec
is illustrated in Figure
4. The Pearson-product moment correlations between best
effort MRSL (%BM), body composition, and performance
tests revealed a number of positive and inverse correlations
(Tables 4–6). However, there were no “very large” correla-
tions found between MRSL and any measured variable.
“Large” correlations were found between the best MRSL
result and BF, FFM, LLFFM, HJ, HJ
rel
,5RB
rel
, URS10,
URS20, CMJHt, CMJP, and CMJ50P. “Moderate” correla-
tions were found between MRSL and 5RB, CMJ50Ht, RSI,
and RFD200
rel
.
A multiple regression analysis revealed the best
predictive models for MRSL. Prediction model 1 used
RSI (b=0.412,p= 0.021) and CMJ50P (b=0.548,
p= 0.003), explaining 53.5% of the variance in MRSL
(r= 0.731, standard error of the estimate (SEE) = 7.20,
p,0.001).
MRSLest ¼29:444 þ14:5193RSI þ0:3983CMJ50P
(1)
Tests to check the data met the assumption of collinearity
indicated no concern of multicollinearity (RSI, Tolerance =
0.98 variance inflation factor (VIF) = 1.02; CMJ50P, Toler-
ance = 0.98, VIF = 1.02).
Prediction model 2 used HJ
rel
(b= 0.412, p= 0.040) and
CMJ50P (b= 0.419, p= 0.037), explaining 50.4% of the
variance in MRSL (r= 0.710, SEE = 7.44, p= 0.002).
MRSLest ¼226:466 þ34:6483HJrel þ0:3043CMJ50P
(2)
Tests to check the data met the assumption of collin-
earity indicated no concern of multicollinearity (HJ
rel
,
Tolerance = 0.79, VIF = 1.26; CMJ50P, Tolerance = 0.79,
VIF = 1.26).
DISCUSSION
The MRSL test (36) proposes to determine the maximal sled
load that allows an athlete to maintain acceleration from phase
“A” (10–15 m) to phase “B” (15–20 m) in a 20-m RSS. Deter-
mining such a parameter would allow for the prescription of
RSS training load on an individual basis analogous to the %
1RM in standard strength training. The reliability of the MRSL
and the relationships of MRSL performance to other tests of
athletic performance have not been established and therefore,
were the focus of this study. Our data suggest that the MRSL
test is reliable (ICC = 0.95, CV = 7.6%), and MRSL performance
is related to the outcome of various anthropometric and perfor-
mance tests. Moreover,
the initial load for an
MRSL test can be esti-
mated from 2 differ-
ent predictive equations
derived from the present
data involving specific per-
formance tests. The pre-
dictive equations may
provide the practitioner
with an estimate of MRSL
from which the initial load
TABLE 4. Relationships between body composition variables and MRSL
performance (n= 15).*
BM (kg) Ht (cm) BF (%) FFM (%) LLFFM (%)
MRSL (%BM) 20.277 20.165 20.599†0.593†0.631†
*MRSL = maximum resisted sled load; BM = body mass; Ht = standing height; BF = body fat;
FFM = fat-free mass; LLFFM = lower limb fat-free mass.
†p#0.05.
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(the first repetition) of the MRSL can be decided on.
In this study, the MRSL test was performed with a slight
modification such that we did not use standardized
increases in sled load after each successful repetition.
Standard increases in sled load were previously used when
the MRSL protocol was first established, although MRSL
test-retest reliability was not reported (36). However, in-
line with previous research on general 1RM testing
(39,40,53), future MRSL protocols should analyze test-
retest reliability using standardized increases in RSS load.
That notwithstanding, the test-retest reliability of the
MRSL test reported herein (ICC = 0.95) is comparable to
that of 1RM squat (ICC = 0.97) (53), URS10 (ICC = 0.87)
(41) and single-leg HJ performance (ICC = 0.95) (41) in
females. The within-subject variation is described by a CV
of 7.6%. The within-subject variation is greater than pre-
viously investigated 10-m sprint time (CV = 1.9%) (41),
single-leg HJ performance (CV = 2.7%) (41), and loaded
jump squat peak power output (CV = 2.1–3.9%) (48) in
female athletes. One previous study has investigated the
reliability of RSS performance (37). Interrepetition 10-m
sprint time with RSS loads of 10 and 20% BM produced
a CVof 1.7–5.8% (37). Athletes in the current study, compared
with the RSS reliability
study (37), sprinted with
heavier loads (.20.7%
BM vs. 10–20% BM)
and over longer distances
(20 vs. 10 m). Heavier re-
sistances and longer dis-
tances may have
accounted for the higher
within-subject variation
in the current study.
The current study
used an initial sled load
of 15% BM for the first
MRSL effort. There was
an interindividual range
of 4–14 RSS repetitions
required to determine
MRSL. However, for repeated sprint activities, variation in
the number of sprint repetitions may significantly alter the
relative energy system contribution and metabolic demand
of the exercise (54) and could introduce variation between
participants if fatigue ensues. Ideally, the between-participant
variation in number of RSS repetitions should be within
a narrow range to minimize the contribution of fatigue to
the MRSL test, but an individual’s “fatigue resistance” is
likely related to maximum strength and specific training
experience (17,24,52). Therefore, there will be an element
of fatigue with repeated efforts, and there will be variations
between participants in the number of efforts performed.
Moreover, the current protocol allows for 3 minutes of rest
between repetitions so that the influence of fatigue from the
previous repetition is minimized. Currently, no research has
compared the acute physiological responses with variations
in the number of RSS repetitions. However, the range of
MRSL values (20.7–58.9% BM) clearly demonstrates that
there is significant interindividual variation within a cohort
of female field sport athletes. The interindividual variation in
acceleration ability under a range of loads provides further
evidence that sled load prescribed by %BM will not provide
the same training stimulus to a team of individuals in field
sport setting. The rela-
tionship between accel-
eration and sled load is
generally inverse and lin-
ear (Figure 4) i.e., as sled
load increases, the differ-
ence in average sprint
velocity between phase
“A” (15–20 m) and phase
“B” (10–15 m) decreases.
An inverse linear rela-
tionship validates the
fundamental require-
ment of the MRSL test
TABLE 6. Relationships between horizontal performance tests and MRSL (n= 21).*
HJ (m) HJ
rel
(m$mHt
21
) 5RB (cm) 5RB
rel
(m$mHt
21
) URS10 (s) URS20 (s)
MRSL 0.587z0.604z0.465†0.520†20.511†0.563z
*MRSL = maximum resisted sled load; HJ = horizontal jump distance; HJ
rel
= horizontal jump
distance relative to standing height; Ht = standing height; 5RB = 5-repeated bound distance;
5RB
rel
= 5-repeated bound distance relative to standing height; URS10 = unresisted sprint
time from 0 to 10 m; URS20 = unresisted sprint time from 0 to 20 m.
†p#0.05.
zp,0.01.
TABLE 5. Relationships between vertical performance tests and MRSL (n= 21).*
CMJHt
(cm)
CMJP
(W$kg
BM
21
)
CMJ50P
(W$kg
BM
21
)
RSI
(cm$ms
21
)
IPF
(N$kg
BM
21
)
RFD100
(N$kg
BM
21
$s
21
)
RFD200
(N$kg
BM
21
$s
21
)
RFDpeak
(N$kg
BM
21
$s
21
)
MRSL 0.589z0.555z0.607z0.490†0.306 0.351 0.455†0.381
*MRSL = maximum resisted sled load; CMJHt = countermovement jump height; CMJP = coun-
termovement jump relative peak power output; BM = body mass; CMJ50P = loaded hexagonal bar
countermovement jump with 50% body mass relative peak power output; RSI = reactive strength
index; IPF = isometric peak force; RFD100 = rate of force development from 0 to 100 ms relative to
body mass; RFD200 = rate of force development from 0 to 200 ms relative to body mass;
RFDpeak = peak rate of force development over 20 ms relative to body mass.
†p#0.05.
zp,0.01.
Reliability of the Maximum Resisted Sled Load Test
1710
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to identify a sled load that progressively reduces acceleration
between 10 and 20 m in a 0–20 m RSS sprint.
The MRSL is correlated with body composition (BF,
FFM, LLFFM), linear sprint speed (0–10 and 0–20 m
URS time), vertical jump performance (CMJHt), vertical
power output (CMJP, CMJ50P), vertical reactive strength
(RSI), vertical RFD (RFD200), HJ performance (HJ,
HJ
rel
), and horizontal bound performance (5RB, 5RB
rel
).
These relationships indicate the MRSL test as a method
of RSS load prescription that accounts for individual
variation of body composition, power, and speed char-
acteristics in female field sport athletes. A previous
investigation correlated MRSL to linear sprint speed and
maximum vertical force production (36). URS20 time and
“Smith machine” back squat 1RM relative to BM were,
respectively, 50 and 51% predictive of MRSL (36). Con-
versely, the current study did not observe a relationship
between IPF and MRSL. The discrepancy between study
findings may be explained by differences in the measure-
ment and representation of maximum force production.
Isometric midthigh clean pull measures isometric force,
whereas sprinting is a dynamic movement, requiring
eccentric and concentric force production. An isometric
vertical movement such as the IMCP holds far less spec-
ificity to sprinting compared with a dynamic and explo-
sive vertical movement such as a back squat. This
discrepancy in specificity may be why IPF did not hold
a relationship with MRSL performance. The current
study used the IMCP as opposed to a back squat (36). A
history of strength training was not a prerequisite to
participate in the current study, only participation in field
sport training with a competitive team. Participants in the
previous MRSL study were males with a “Smith machine”
half back squat of 159.7 kg or 2.3 kg per kg BM (36).
Therefore, future research should use strength-trained
males and females to investigate if maximum muscle
strength or concentric force production are related to
MRSL.
Vertical performance tests (CMJHt, CMJP, CMJ50P, RSI,
and RFD200) were moderately to strongly correlated with
MRSL. Athletes with greater general concentric power and
RFD are likely able to produce greater forces at higher
velocities and therefore greater RSS acceleration with
heavier loads when compared with a less-powerful athlete.
Horizontal performance tests (URS10, URS20, HJ, HJ
rel
,
5RB, and 5RB
rel
) were moderately to strongly correlated
with MRSL. When sprinting at heavier RSS loads, there is
a requirement for a greater horizontal orientation of force
when compared with lighter sled loads (27). The technical
ability to apply force at a greater horizontal orientation is
a mechanical determinant of URS acceleration performance
(9,44,45,50) and is speculated to be one of the elements of
RSS training resulting in a transfer to improvements in sprint
performance (2,15,27,32,55,62). However, correlation does
not explain causation (48). The large correlation between
URS performance and MRSL do not infer that longitudinal
improvements in MRSL will improve URS10 or 20. The
MRSL test cannot presently be described as a marker of
URS performance, rather as a tool for prescription of load
for RSS training.
A recent systematic review suggested that RSS loads up to
43% BM or 30% V
dec
are effective in the improvement of
sprint performance after RSS training (49). However, the %
BM method does not account for individual sprint ability or
physical performance attributes, whereas the %V
dec
method
does not provide a “maximal” value from which to program
and periodize sled load (49). The MRSL moves sled load
prescription beyond the limitations of these 2 methods.
However, it remains to be established if training at a given
percentage of MRSL will provide uniform adaptation in
sprint performance, kinetics, or kinematics after a period of
RSS training. This study has provided 2 possible predictive
equations for MRSL
est
in female field sport athletes, specif-
ically with the aim of decreasing the time and number of
repetitions required for MRSL testing. To reduce the num-
ber of MRSL repetitions, the initial load can be increased to
a value close to MRSL
est
, i.e., 80–90% of MRSL
est
. Using an
estimated maximal load to strategize a testing protocol is
a method commonly used in 1RM testing for traditional
maximum strength exercises (3,51) and may improve the
practicality of using the MRSL test in a team sport environ-
ment by reducing the time-cost of the testing protocol and
allowing grouping of individuals by similar abilities. How-
ever, necessary equipment (force plate, hexagonal bar) and
time constraints (time to familiarize tests, time to perform
tests) may be barriers in many training environments. There-
fore, the prediction equations are likely most useful in the
research setting and may have limited utility for strength and
conditioning coaches. In this case, we suggest to simply
perform the MRSL test without pre-testing protocols, but
with the initial sled load at 15% of BM for a female field sport
athlete. Future research should challenge the 15% of BM
recommendation, but for now this starting point represents
a load that is unlikely to be greater than the MRSL for
a female field sport athlete.
PRACTICAL APPLICATIONS
The MRSL protocol is a reliable assessment tool of resisted
sprint sled load for female field sport athletes. Prescription of
training load for RSS training based on a percentage of
MRSL may allow a practitioner to account for interindivid-
ual differences in body composition, power, and sprint speed
characteristics of athletes, and thereby personalizing the RSS
training stimulus, something that is currently lacking in
practice. MRSL
est
is predicted by 2 different equations using
measures from standard performance testing. Strength and
conditioning coaches may wish to refine the MRSL protocol
by starting the test at a given percentage of MRSL
est
. Future
work should focus investigating the longitudinal effects of
RSS training at various percentages of MRSL.
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VOLUME 33 | NUMBER 6 | JUNE 2019 | 1711
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ACKNOWLEDGMENTS
The authors received no funding for this study. The results of
this study do not constitute endorsement of any product by
authors or the NSCA.
REFERENCES
1. Agar-Newman, DJ and Klimstra, MD. Efficacy of horizontal
jumping tasks as a method for talent identification of female rugby
players. J Strength Cond Res 29: 737–743, 2015.
2. Alcaraz, PE, Elvira, JLL, and Palao, JM. Kinematic, strength, and
stiffness adaptations after a short-term sled towing training in
athletes. Scand J Med Sci Sports 24: 279–290, 2014.
3. Alemany, JA, Pandorf, CE, Montain, SJ, Castellani, JW, Tuckow, AP,
and Nindl, BC. Reliability assessment of ballistic jump squats and
bench throws. J Strength Cond Res 19: 33–38, 2005.
4. Atkinson, G and Nevill, AM. Statistical methods for assessing
measurement error (reliability) in variables relevant to sports
medicine. Sports Med 26: 217–238, 1998.
5. Bachero-Mena, B and Gonzalez-Badillo, JJ. Effects of resisted sprint
training on acceleration with three different loads accounting for 5,
12.5 and 20% of body mass. J Strength Cond Res 28: 2954–
2960, 2014.
6. Baechle, TR, Earle, RW, and Wathen, D. Resistance Training. In:
3rd, ed. Essentials of Strength Training and Conditioning. Champaign,
IL: Human Kinetics, 2008. p. 288.
7. Barr, MJ, Sheppard, JM, Agar-Newman, DJ, and Newton, RU.
Transfer effect of strength and power training to the sprinting
kinematics of international rugby players. J Strength Cond Res 28:
2585–2596, 2014.
8. Bompa, TO and Haff, GG. Strength and Power Development. In:
Periodization: Theory and Methodology of Training. Champaign, IL:
Human Kinetics, 2009. p. 274.
9. Buchheit, M, Samozino, P, Glynn, JA, Michael, BS, Al Haddad, H,
Mendez-Villanueva, A, and Morin, JB. Mechanical determinants of
acceleration and maximal sprinting speed in highly trained young
soccer players. J Sports Sci 32: 1906–1913, 2014.
10. Burkhart, TA, Arthurs, KL, and Andrews, DM. Manual
segmentation of DXA scan images results in reliable upper and
lower extremity soft and rigid tissue mass estimates. J Biomech 42:
1138–1142, 2009.
11. Clark, KP, Stearne, DJ, Walts, CT, and Miller, AD. The longitudinal
effects of resisted sprint training using weighted sleds vs. weighted
vests. J Strength Cond Res 24: 3287–3295, 2010.
12. Cormack, SJ, Newton, RU, McGuigan, MR, and Doyle, TL.
Reliability of measures obtained during single and repeated
countermovement jumps. Int J Sports Physiol Perform 3: 131–144, 2008.
13. Cormie, P, McCaulley, GO, and McBride, JM. Power versus
strength-power jump squat training: Influence on the load-power
relationship. Med Sci Sports Exerc 39: 996–1003, 2007.
14. Cormie, P, McGuigan, MR, and Newton, RU. Adaptations in
athletic performance after ballistic power versus strength training.
Med Sci Sports Exerc 42: 1582–1598, 2010.
15. Cronin, J, Hansen, K, Kawamori, N, and McNair, P. Effects of
weighted vests and sled towing on sprint kinematics. Sport Biomech
7: 160–172, 2008.
16. Currell, K and Jeukendrup, AE. Validity, reliability and sensitivity of
measures of sporting performance. Sports Med 38: 297–316, 2008.
17. Docherty, D and Hodgson, MJ. The application of postactivation
potentiation to elite sport. Int J Sports Physiol Perform 2: 439–
444, 2007.
18. Dugan, EL, Doyle, TL, Humphries, B, Hasson, CJ, and Newton, RU.
Determining the optimal load for jump squats: A review of methods
and calculations. J Strength Cond Res 18: 668–674, 2004.
19. Flanagan, EP, Ebben, WP, and Jensen, RL. Reliability of the reactive
strength index and time to stabilization during depth jumps. J
Strength Cond Res 22: 1677–1682, 2008.
20. 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.
21. Haff, GG, Ruben, RP, Lider, J, Twine, C, and Cormie, P. A
comparison of methods for determining the rate of force
development during isometric midthigh clean pulls. J Strength Cond
Res 29: 386–395, 2015.
22. Harrison, AJ and Bourke, G. The effect of resisted sprint training on
speed and strength performance in male rugby players. J Strength
Cond Res 23: 275–283, 2009.
23. Haugen, TA, Tonnessen, E, Svendsen, IS, and Seiler, S. Sprint time
differences between single- and dual-beam timing systems. J
Strength Cond Res 28: 2376–2379, 2014.
24. Hodgson, M, Docherty, D, and Robbins, D. Post-activation
potentiation: Underlying physiology and implications for motor
performance. Sports Med 35: 585–595, 2005.
25. Hopkins, WG. A scale of magnitudes for effect statistics. 2002.
Available at: http://www.sportsci.org/resource/stats/effectmag.
html. Accessed May 17, 2015.
26. 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.
27. Kawamori, N, Newton, R, and Nosaka, K. Effects of weighted sled
towing on ground reaction force during the acceleration phase of
sprint running. J Sports Sci 32: 1139–1145, 2014.
28. Kawamori, N, Newton, RU, Hori, N, and Nosaka, K. Effects of
weighted sled towing with heavy versus light load on sprint
acceleration ability. J Strength Cond Res 28: 2738–2745, 2014.
29. Linthorne, NP. A mathematical modelling study of an athlete’s
sprint time when towing a weighted sled. Sports Eng 16: 61–
70, 2013.
30. Linthorne, NP and Cooper, JE. Effect of the coefficient of friction of
a running surface on sprint time in a sled-towing exercise. Sports
Biomech 12: 175–185, 2013.
31. Lockie, RG, Murphy, AJ, Schultz, AB, Knight, TJ, and de Jonge,
XAKJ. The effects of different speed training protocols on sprint
acceleration kinematics and muscle strength and power in field
sport athletes. J Strength Cond Res 26: 1539–1550, 2012.
32. Lockie, RG, Murphy, AJ, and Spinks, CD. Effects of resisted sled
towing on sprint kinematics in field-sport athletes. J Strength Cond
Res 17: 760–767, 2003.
33. Luteberget, LS, Raastad, T, Seynnes, O, and Spencer, M. Effect of
traditional and resisted sprint training in highly trained female team
handball players. Int J Sports Physiol Perform 10: 642–647, 2015.
34. Makaruk, B, Sozanski, H, Makaruk, H, and Sacewicz, T. The effects
of resisted sprint training on speed performance in women. Hum
Mov 14: 116–122, 2013.
35. Martinez-Valencia, M, Linthorne, N, and Alcaraz, P. Effect of lower
body explosive power on sprint time in a sled-towing exercise. Sci
Sports 28: e175–e178, 2013.
36. Martinez-Valencia, MA, Gonzalez-Rave, JM, Santos-Garcia, DJ,
Alcaraz Ramon, PE, and Navarro-Valdivielso, F. Interrelationships
between different loads in resisted sprints, half-squat 1 RM and
kinematic variables in trained athletes. Eur J Sport Sci 14(Suppl 1):
S18–S24, 2014.
37. Maulder, PS, Bradshaw, EJ, and Keogh, JW. Kinematic alterations due to
different loading schemes in early acceleration sprint performance from
starting blocks. J Strength Cond Res 22: 1992–2002, 2008.
Reliability of the Maximum Resisted Sled Load Test
1712
Journal of Strength and Conditioning Research
the
TM
Copyright © 2019 National Strength and Conditioning Association. Unauthorized reproduction of this article is prohibited.
38. McBride, JM, Triplett-McBride, T, Davie, A, and Newton, RU.
The effect of heavy- vs. light-load jump squats on the
development of strength, power, and speed. J Strength Cond Res
16: 75–82, 2002.
39. McCurdy, K, Langford, G, Jenkerson, D, and Doscher, M. The
validity and reliability of the 1RM bench press using chain-loaded
resistance. J Strength Cond Res 22: 678–683, 2008.
40. McCurdy, K, Langford, GA, Cline, AL, Doscher, M, and Hoff, R.
The reliability of 1- and 3RM tests of unilateral strength in trained
and untrained men and women. J Sports Sci Med 3: 190–196, 2004.
41. Meylan, C, McMaster, T, Cronin, J, Mohammad, NI, Rogers, C, and
Deklerk, M. Single-leg lateral, horizontal, and vertical jump
assessment: Reliability, interrelationships, and ability to predict
sprint and change-of-direction performance. J Strength Cond Res 23:
1140–1147, 2009.
42. Meylan, CM, Cronin, J B, Oliver, JL, Hughes, MG, and McMaster,
DT. The reliability of jump kinematics and kinetics in children of
different maturity status. J Strength Cond Res 26: 1015–1026, 2012.
43. Michailidis, Y, Fatouros, IG, Primpa, E, Michailidis, C, Avloniti, A,
Chatzinikolaou, A, Barbero-Alvarez, JC, Tsoukas, D, Douroudos, II,
Draganidis, D, Leontsini, D, Margonis, K, Berberidou, F, and
Kambas, A. Plyometrics’ trainability in preadolescent soccer
athletes. J Strength Cond Res 27: 38–49, 2013.
44. Morin, JB, Bourdin, M, Edouard, P, Peyrot, N, Samozino, P, and
Lacour, JR. Mechanical determinants of 100-m sprint running
performance. Eur J Appl Physiol 112: 3921–3930, 2012.
45. Morin, JB, Edouard, P, and Samozino, P. Technical ability of force
application as a determinant factor of sprint performance. Med Sci
Sports Exerc 43: 1680–1688, 2011.
46. Murray, A, Aitchison, TC, Ross, G, Sutherland, K, Watt, I, McLean,
D, and Grant, S. The effect of towing a range of relative resistances
on sprint performance. J Sports Sci 23: 927–935, 2005.
47. Nana, A, Slater, GJ, Stewart, AD, and Burke, LM. Methodology
review: Using dual-energy x-ray absorptiometry (DXA) for the
assessment of body composition in athletes and active people. Int J
Sport Nutr Exerc Metab 25: 198–215, 2015.
48. Nimphius,S,McGuigan,MR,andNewton,RU.Relationshipbetween
strength, power, speed, and change of direction performance of female
softball players. J Strength Cond Res 24: 885–895, 2010.
49. Petrakos,G,Morin,J-B,andEgan,B.Resistedsledsprint
training to improve sprint performance: A systematic review.
Sports Med 46: 381–400, 2016.
50. Rabita, G, Dorel, S, Slawinski, J, Saez-de-Villarreal, E, Couturier, A,
Samozino, P, and Morin, JB. Sprint mechanics in world-class
athletes: A new insight into the limits of human locomotion. Scand J
Med Sci Sports 25: 583–594, 2015.
51. Ritti-Dias, RM, Avelar, A, Salvador, EP, and Cyrino, ES. Influence of
previous experience on resistance training on reliability of one-
repetition maximum test. J Strength Cond Res 25: 1418–1422, 2011.
52. Seitz, LB and Haff, GG. Factors modulating post-activation
potentiation of jump, sprint, throw, and upper-body ballistic
performances: A systematic review with meta-analysis. Sports Med
46: 231–240, 2016.
53. Seo, D, Kim, E, Fahs, CA, Rossow, L, Young, K, Ferguson, SL,
Thiebaud, R, Sherk, VD, Loenneke, JP, Kim, D, Lee, MK, Choi, KH,
Bemben, DA, Bemben, MG, and So, WY. Reliability of the one-
repetition maximum test based on muscle group and gender. J Sport
Sci Med 11: 221–225, 2012.
54. Spencer, M, Bishop, D, Dawson, B, and Goodman, C. Physiological
and metabolic responses of repeated-sprint activities: Specific to
field-based team sports. Sports Med 35: 1025–1044, 2005.
55. Spinks, CD, Murphy, AJ, Spinks, WL, and Lockie, RG. The effects
of resisted sprint training on acceleration performance and
kinematics in soccer, rugby union, and Australian football players. J
Strength Cond Res 21: 77–85, 2007.
56. Stone, MH, Stone, M, Sands, WA, and Sands, B. Adaptations and
Benefits of Resistance Training. In: Principles and Practice of
Resistance Training: Champaign, IL: Human Kinetics, 2007. pp. 167–
168.
57. Swinton, PA, Stewart, AD, Lloyd, R, Agouris, I, and Keogh, JW.
Effect of load positioning on the kinematics and kinetics of weighted
vertical jumps. J Strength Cond Res 26: 906–913, 2012.
58. Turner, TS, Tobin, DP, and Delahunt, E. Optimal loading range for
the development of peak power output in the hexagonal barbell
jump squat. J Strength Cond Res 29: 1627–32, 2014.
59. Turner, TS, Tobin, DP, and Delahunt, E. Peak power in the hexagonal
barbell jump squat and its relationship to jump performance and
acceleration in elite rugby union players. J Strength Cond Res 29: 1234–
1239, 2015.
60. Weir, JP. Quantifying test-retest reliability using the intraclass correlation
coefficient and the SEM. J Strength Cond Res 19: 231–240, 2005.
61. West, DJ, Cunningham, DJ, Bracken, RM, Bevan, HR, Crewther,
BT, Cook, CJ, and Kilduff, LP. Effects of resisted sprint training on
acceleration in professional rugby union players. J Strength Cond Res
27: 1014–1018, 2013.
62. Zafeiridis, A, Saraslanidis, P, Manou, V, Ioakimidis, P, Dipla, K, and
Kellis, S. The effects of resisted sled-pulling sprint training on
acceleration and maximum speed performance. J Sports Med Phys
Fitness 45: 284–290, 2005.
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