Content uploaded by Oribi Bruno Oponjuru
Author content
All content in this area was uploaded by Oribi Bruno Oponjuru on Jul 01, 2018
Content may be subject to copyright.
Vol.:(0123456789)
Sports Medicine
https://doi.org/10.1007/s40279-018-0947-8
SYSTEMATIC REVIEW
The Eectiveness ofResisted Sled Training (RST) forSprint
Performance: ASystematic Review andMeta‑analysis
PedroE.Alcaraz1,2· JorgeCarlos‑Vivas1· BrunoO.Oponjuru1· AlejandroMartínez‑Rodríguez3
© Springer International Publishing AG, part of Springer Nature 2018
Abstract
Background Sprinting is key in the development and final results of competitions in a range of sport disciplines, both indi-
vidual (e.g., athletics) and team sports. Resisted sled training (RST) might provide an effective training method to improve
sprinting, in both the acceleration and the maximum-velocity phases. However, substantial discrepancies exist in the lit-
erature regarding the influence of training status and sled load prescription in relation to the specific components of sprint
performance to be developed and the phase of sprint.
Objectives Our objectives were to review the state of the current literature on intervention studies that have analyzed the
effects of RST on sprint performance in both the acceleration and the maximum-velocity phases in healthy athletes and to
establish which RST load characteristics produce the largest improvements in sprint performance.
Methods We performed a literature search in PubMed, SPORTDiscus, and Web of Science up to and including 9 January
2018. Peer-reviewed studies were included if they met all the following eligibility criteria: (1) published in a scientific jour-
nal; (2) original experimental and longitudinal study; (3) participants were at least recreationally active and towed or pulled
the sled while running at maximum intensity; (4) RST was one of the main training methods used; (5) studies identified the
load of the sled, distance covered, and sprint time and/or sprint velocity for both baseline and post-training results; (6) sprint
performance was measured using timing gates, radar gun, or stopwatch; (7) published in the English language; and (8) had
a quality assessment score > 6 points.
Results A total of 2376 articles were found. After filtering procedures, only 13 studies were included in this meta-analysis.
In the included studies, 32 RST groups and 15 control groups were analyzed for sprint time in the different phases and full
sprint. Significant improvements were found between baseline and post-training in sprint performance in the acceleration
phase (effect size [ES] 0.61; p = 0.0001; standardized mean difference [SMD] 0.57; 95% confidence interval [CI] − 0.85 to
− 0.28) and full sprint (ES 0.36; p = 0.009; SMD 0.38; 95% CI − 0.67 to − 0.10). However, non-significant improvements
were observed between pre- and post-test in sprint time in the maximum-velocity phase (ES 0.27; p = 0.25; SMD 0.18; 95%
CI − 0.49 to 0.13). Furthermore, studies that included a control group found a non-significant improvement in participants
in the RST group compared with the control group, independent of the analyzed phase.
Conclusions RST is an effective method to improve sprint performance, specifically in the early acceleration phase. However,
it cannot be said that this method is more effective than the same training without overload. The effect of RST is greatest in
recreationally active or trained men who practice team sports such as football or rugby. Moreover, the intensity (load) is not
a determinant of sprint performance improvement, but the recommended volume is > 160m per session, and approximately
2680m per week, with a training frequency of two to three times per week, for at least 6weeks. Finally, rigid surfaces appear
to enhance the effect of RST on sprint performance.
* Pedro E. Alcaraz
pedro.e.alcaraz@gmail.com
* Alejandro Martínez-Rodríguez
amartinezrodriguez@ua.es
Extended author information available on the last page of the article
P.E.Alcaraz et al.
Key Points
Resisted sled training (RST) is an effective training
method for the development of sprint performance,
specifically in the early acceleration phase (≤ 10m),
independent of participant and load characteristics.
However, the effects are larger in male, trained, and
team sports athletes. Conversely, this method is not more
effective than the unresisted sprint in improving sprint
performance.
RST has a small effect on performance in the maximum-
velocity phase (≥ 15-m flying sprints at maximum
intensity using a run-in distance of ≥ 10m) and/or when
performing sprints ≥ 20m.
There is no optimal load for RST, and the load should
be adapted according to the desired objective. However,
when replicating the demands of sprinting (i.e., the
movement pattern, load, and movement velocity) using
sled towing with a slight overload, the load must never
be > 20% of body mass.
1 Introduction
Sprinting is recognized as the fastest mode of unaided
human locomotion. It is an important action that humans
have employed since prehistoric times, not only as a determi-
nant of survival but also as a key activity in the development
and final results of competitions in a range of sport disci-
plines, both individual (e.g., athletics) and team sports (e.g.,
soccer, rugby, American football, basketball, futsal, or field
hockey). For example, straight sprinting is the most frequent
action in goal situations in professional soccer [1]. In addi-
tion, professional soccer players, for whom sprinting is key,
have become faster over time [2, 3], independent of sex and/
or age [4]. However, the maximum expression of a sprint is
represented in the 100-m dash final in the Olympic games,
a sporting event with some of the largest social media and
sporting repercussions worldwide. Therefore, sprinting has
been extensively studied from both a biomechanical and a
physiologic point of view [5].
In a 100-m race, for instance, as in many other sports
in which speed is of crucial importance, there are several
clearly defined phases, but these can be summarized in two:
acceleration and maximum-velocity phases. The accelera-
tion phase is characterized by the athlete starting the sprint
from a semi-static position and increasing their speed rapidly
in a short period of time; in the maximum-velocity phase,
the athlete moves at high speed that is maintained without
any apparent acceleration. It is of utmost importance to
emphasize that, in some cases, these phases are not related,
since different factors affect performance in each phase; in
addition, not all sports include both phases [6]. Therefore,
training protocols to develop each of these phases must also
differ. For example, the main muscle groups involved in the
acceleration phase are the ankle, knee, and hip extensors [7].
Given the limited time available to produce force during a
sprint, the main manifestation of force is explosive, defined
as the development of maximal force in minimal time, or
rate of force development (RFD) [8]. An athlete’s position,
with a slight body lean, relates to the horizontal net ground
reaction force (GRF), which is paramount to accelerate the
body forward [9], with higher contact times (CTs) [9, 10]
and ratio of forces (horizontal:vertical GRF), when com-
pared with the maximum-velocity phase [9]. In contrast,
the main muscle groups involved in the maximum-velocity
phase are the hip and ankle extensors, which contribute to
greater vertical GRF (vGRF) [11]. Weyand and colleagues
[12, 13] stated that top speed was mechanically limited by
maximal vGRF, presenting a strong positive relationship
between top speed and the average vGRF applied during
the first half of the stance period [14]. Therefore, it seems
that, together with RFD, maximum (relative) strength may
play an important role in this phase. It should be noted that
the maximal-velocity phase includes an asymmetrical pro-
duction of force and the RFD is very high [15] as a result of
much shorter ground CT than observed in the acceleration
phase [9, 16, 17]. In addition, the erect stance-phase posture
that sprinters adopt in this phase likely contributes to the
stiffness required to decelerate the limb and body relatively
quickly after the instant of foot–ground impact [14], all in
order to produce the maximum possible mechanical power
that generates a high horizontal velocity. Notably, neuro-
muscular function is vital to sprint performance, because
the activity and the interaction of the central nervous system
with the muscles ultimately influence muscle RFD, given
that the stretch–shortening cycle (SSC) actions are par-
ticularly prevalent in sports involving sprinting [15]. Thus,
efficient usage of the SSC can recover approximately 60%
of the total mechanical energy, with a higher contribution
of non-metabolic energy sources with increases in running
speed [18, 19].
For sprint training, given the above-mentioned factors,
it is typical to recommend different classifications of train-
ing methods, such as that based on the specificity of the
method and its similitude with the sprint’s technique [20].
MacDougall and Sale [21] suggested that training should
be specific with regards to movement pattern, contrac-
tion velocity, muscle activation type, and applied force.
In fact, a recent study showed that chronic performance
and biomechanical adaptations are associated with ver-
tically and horizontally oriented conditioning regimens
[22]. Plisk [20] established primary methods that simu-
late the sprint movement pattern (sprint-technique drills,
Effectiveness of RST for Sprint Performance
stride length and frequency exercises, and sprints of vary-
ing distances and intensities); secondary methods that
simulate the sprint action but with a slight overload or
degree of assistance (resisted or assisted methods, respec-
tively); and tertiary methods, characterized by non-specific
sprint development (resistance training, plyometric train-
ing, complex training, stretching, etc.) [23–25]. It is also
typical to classify sprint training methods according to the
force–velocity (F–V) relationship of muscle shortening,
described by Hill and colleagues [26, 27] many years ago.
The F–V relationship describes a characteristic property
of the muscle that dictates its power-production capacities
[28]. Because mechanical power is the expression of both
force and velocity, it is generally accepted that improving
force-production potential and/or velocity of movement is
effective when seeking to improve short-distance sprint-
ing [29]. Based on contemporary scientific knowledge, it
is evident that maximal (relative) strength, the RFD, and
peak power-generating capacity are all important attributes
that need to be developed when implementing strength
and conditioning programs [30] to increase sprint perfor-
mance during the entire season. Haff and Nimphius [30]
suggested a mixed-methods approach in which a variety
of loads and exercise types are used in a periodized fash-
ion to optimize power output. In this context, resisted and
assisted sprint training protocols play a key role [30].
One of the most traditional secondary methods to improve
sprint performance is resisted sled training (RST), mainly
due to its greater effect on horizontal forces [31, 32] when
compared with tertiary methods, which have a greater ver-
tical orientation of resistance forces [29]. RST has been
applied in sports for decades, evolving from the pull of a
wheel to current electromechanical devices that regulate
the load to produce the loss of speed desired by the athlete
(i.e., 1080 Motion™). Traditionally, and mainly address-
ing the principle of specificity, the most popular manuals
and training guides [33, 34] have recommended that normal
unresisted (UR) sprint biomechanics should be maintained
when RST is used. Hence, loads should be chosen based
on the sport and the athlete’s physical status. For example,
track and field sprinters may use loads that do not decrease
running velocity by more than 10–12% of body mass (BM)
[35–37]. In contrast, field sport athletes who overcome
external resistance while blocking and tackling can use loads
20–30% of BM to improve early acceleration [38, 39]. This
hypothesis has been widely accepted, since it is believed that
the production of mechanical power when the load increases
is significantly reduced [40]. This reduction of mechanical
power is associated with an improper configuration of the
athlete’s levers (involving different motor units or even mus-
cle groups), an increase in the CT, and no possibility of
adequate use of the SSC. Thus, recent studies have tried
to elucidate the load that maximizes mechanical power in
RST, with some resulting controversy. Monte etal. [40] indi-
cated that the maximum power produced when using RST
occurs with loads close to 20% BM, without inducing sig-
nificant changes in the sprint technique when this load was
used, whereas Cross etal. [41] indicated that the maximum
power output is achieved with loads near 80% BM. However,
this latter study [41] has the limitation of not having meas-
ured the effect on kinematic parameters and measuring the
horizontal power when the athletes achieved the maximum
velocity of sprint, given that the maximum power output in
sprinting is known to usually occur in the first steps. Moreo-
ver, the horizontal force and power decreased by 82.0% and
62.5%, respectively, from the first to the last step during
the 20-m sprint with sled towing [40]. Interestingly, both
studies have used the method developed by Samozino etal.
[42] to calculate the horizontal power production but in dif-
ferent disciplines (sprinters vs. soccer players) and in differ-
ent phases. These authors indirectly estimated the anterio-
posterior (horizontal) force of a sprint from spatio-temporal
parameters and, consequently, calculated the horizontal
power production during the sprint.
From a kinematic point of view, cross-sectional studies
have focused on the effects of RST on different variables
such as stride length (SL), CT, flight times (FT), and joint
angles. For example, Alcaraz etal. [31] showed a decrease
in SL and running velocity with an RST load of 16% BM but
observed no significant changes in running technique (i.e.,
by analyzing the joint angles). In addition, various studies
[37, 40, 43, 44] showed a decrement in FT and SL, and an
increase in CT as a function of sled load. From a kinetic
point of view, Martínez-Valencia etal. [45] found an acute,
significant RFD increase when added loads were 15–20%
BM compared with an UR sprint. In addition, other authors
have concluded that RST, mainly with high loads (30% BM),
increases relative net horizontal and propulsive impulse
production compared with UR sprinting by directing force
production more horizontally and by allowing longer time
to apply force against the ground [32], which could be trans-
ferred to a better application of horizontal GRF. However,
the same research team compared the short-term effect
(8weeks) of using RST with low loads (~ 13% BM) versus
higher loads (~ 43% BM) [39] and did not find significant
differences between the groups, either for improvement of
performance or horizontal GRFs. Therefore, there is no
agreement on whether low or high loads are more benefi-
cial from both a kinetic and a kinematic point of view when
increases in performance in the short and medium term are
sought.
In sprinting with RST, the additional resistance expe-
rienced by the athlete arises mainly from the frictional
force between the base of the sled and the running surface.
This frictional force is approximately proportional to the
total weight of the sled, and the coach may manipulate the
P.E.Alcaraz et al.
resistance experienced by the athlete by changing the weight
placed on the sled. The greater the added weight, the greater
the friction, and hence the slower the athlete’s acceleration
and the lower the maximum speed achieved by the athlete.
The coefficient of friction between the sled and the running
surface is determined by the type and surface roughness of
the materials used in the base of the sled and running sur-
face. For this reason, the use of different surfaces (grass vs.
athletics track) can produce different stimuli with the same
load [46, 47]. Another factor that can alter friction is the
inertia of the sled, which is higher when the sled moves at
low speed.
Finally, a recent systematic review by Petrakos etal.
[47] described in detail the training recommendations in
the existing literature. However, the authors concluded that
performance benefits of RST over UR training remain to be
conclusively demonstrated. Between-study comparisons are
limited, primarily due to discrepancies in participant training
status and level and sled load prescription, indicating that
future work is required to define the optimal training load
for RST, depending on the specific components of sprint
performance to be enhanced.
In an effort to clarify discrepancies in the literature, the
following questions should be addressed: (1) does RST
improve sprint performance; (2) will the effect be greater
when RST is used for the different phases of sprint; (3) is
RST more effective than UR sprinting; (4) what is the opti-
mal load when applying RST for obtaining higher sprint
adaptations; (5) should the load be different for the different
phases of sprint; (6) does RST have a different effect on
athletes depending on age; (7) will the effect be greater if
the athlete is highly trained; (8) how many days per week
should RST be applied; (9) for how many weeks should RST
be applied; and (10) can the surface affect the performance
adaptations?
Therefore, and in response to the questions raised by the
current literature, the objective of this systematic review
with meta-analysis is twofold: (1) to review the state of the
current literature on intervention studies that have analyzed
the effects of RST on sprint performance both in the accel-
eration and the maximum-velocity phase in healthy athletes
and (2) to establish which RST load characteristics are asso-
ciated with the greatest improvements in sprint performance.
2 Methods
We followed the Preferred Reporting Items for Systematic
review and Meta-Analyses (PRISMA) guidelines [48] for
search procedures, study selection, data collection, and
analysis.
2.1 Literature Research andData Sources
The search was performed by two independent reviewers
(AM and BO) using the following databases to identify
studies for this review: PubMed,SPORTDiscus, and Web
of Science. The search results were limited to studies pub-
lished up to and including 9 January 2018. Reviewers used a
computerized and manual library search with the following
Boolean search phrases in all of the mentioned databases:
(“Sprint” OR “Pulling” OR “Towing” OR “Training”) AND
(“Sled” OR “Resisted”). Figure1 shows the flow diagrams
for the entire search process for both variables.
2.2 Inclusion Criteria
The following inclusion criteria had to be met for a study
to be considered for this review: (1) type of publication:
the current research only considered articles published in
scientific journals; (2) type of study: original experimental
and longitudinal studies were considered; (3) participants:
the study participants were at least recreationally active who
towed or pulled the sled while running at maximum inten-
sity; (4) intervention: sled towing and sprinting must have
been one of the training methods used; (5) outcome meas-
ures: studies must have identified the load of the sled used,
distance tested up to a maximum of 100m in at least one
of sprint time and/or sprint velocity, pre-test and post-test
results, and test used; (6) tests must have been measured by
an automated electronic machine, such as timing gates or a
radar gun, or by a manual method such as a stopwatch; (7)
only studies in English were considered; (8) quality assess-
ment: a score > 6 points on the Physiotherapy Evidence
Database scale (PEDro) for systematic review [49–51].
All studies that included the time used to cover a maxi-
mum distance of 10m were utilized for the subgroup analy-
sis of the acceleration phase. All studies that measured the
time used to cover a distance of at least 15m at maximum
intensity using a run-in distance of ≥ 10m before recording
time were used for the subgroup analysis of the maximum-
velocity phase. All studies that included the time used to
cover a distance of at least 20m were used for the subgroup
analysis of the full sprint. For studies that did not include the
time but showed the average speed and the covered distance,
the time was calculated as time = distance/average speed.
Likewise, for the studies that included the sprint time and
presented the acceleration phase and the full sprint data, or
the acceleration phase and the maximum-velocity phase, the
time was calculated as the subtraction or summation (based
on the conditions, respectively) of the known mean data.
Effectiveness of RST for Sprint Performance
2.3 Study Selection
Two reviewers (AM and BO) independently evaluated the
titles and abstracts of the studies that resulted from the
search. Disagreements between the two reviewers were
resolved by discussion; if necessary, a third reviewer (PA)
was consulted to reach a consensus.
For this review, only studies that met the eligibility cri-
teria were selected. Reviewers independently assessed the
methodological quality of the eligible studies using the
PEDro scale [49–51].
2.4 Data Extraction andAnalysis
One reviewer (AM) extracted the following information
from each full-text article, and a second reviewer (BO) con-
firmed the extraction. Disparities in data abstraction were
resolved by a third reviewer (PA).
Review Manager Software (RevMan 5.2; Cochrane Col-
laboration, Oxford, UK) and Comprehensive Meta-analysis
software (Version 2; Biostat, Englewood, NJ, USA) were
used for meta-analysis. A randomized effect model was used.
Heterogeneity among studies was assessed using I2 statistics.
Excluded based on abstract/title screening (n = 633)
•Notresisted sled training (n = 546)
•Notathletes (n = 6)
•NotEnglish language (n = 6)
•Acute studies (n = 37)
•Towing but not running (n = 1)
•Nottowing on ground (n = 18)
•Theoreticalreview paper (n = 14)
•Mathematical model (n = 1)
•Not journal articles (n = 4)
Articles included in meta-analysis
(n = 13)
Records identified from PubMed,
SPORTDiscus and Web of Science
(n = 2376)
Records after duplicates removed
(n = 659)
Additional records identified
through reference search (n = 0)
Excluded after full-text screening (n = 13)
•No outcome measure of sprint (n = 13)
Articles selected for full-text
retrieval (n = 26)
Fig. 1 Flow diagram of the process of study selection
P.E.Alcaraz et al.
Subgroup analyses were performed to evaluate the poten-
tial moderating factors or variables. For continuous variables
comparison, the cut-off values based on medians from the
full sprint analysis were used. However, in specific cases, the
cut-off was established in an arbitrary way (i.e., load). Pub-
lication bias was evaluated using the estimating funnel plot
asymmetry test. A p value of < 0.05 was considered statisti-
cally significant. The standard deviation (SD) was calculated
as the square root of the summation of the squared SDs of
the mean time in the known conditions. Cohen’s d was used
to calculate the effect size (ES, 95% confidence limit) of
each study using the following equation [52]:
where Mpre is the mean value before the CT intervention,
Mpost is the mean value after the intervention, n is the sam-
ple size of the CT group, and Spre is the SD pre-intervention.
Threshold values for Cohen’s ES statistics were > 0.2
(small), > 0.6 (moderate), and > 1.2 (large) [53].
2.5 Risk ofBias
Methodological quality and risk of bias were independently
assessed via visual interpretation of the funnel plot by two
authors (AM, BO), with disagreements resolved by a third
party evaluator (PA), in accordance with Cochrane Collabo-
ration guidelines [54].
3 Results
3.1 Characteristics ofIncluded Studies
A total of 2376 studies were found following the study
selection procedures, and 659 studies remained after dupli-
cates were removed. Finally, 13 studies [39, 55–66] were
included in this meta-analysis (Table1). All included stud-
ies had an RST group that accounted for a total of 32 sub-
groups analyzed for sprint time. However, only ten studies
[55–62, 64, 66] had control groups, which represented a
total of 15 subgroups analyzed.
The quality (internal validity) of the trials, according to
a PEDro scale [51], was high. The mean score was eight of
a possible ten points.
3.2 Characteristics oftheInterventions
Table2 shows the characteristics of the different RST inter-
vention groups. The sled-towing exercise load performed
ranged from 5 to 80% of BM. The interventions ranged from
4 to 10weeks in duration, with a frequency of one to three
ES
=
Mpre
−
Mpost
Spre
(1−3
4
n−
5)
sessions·week−1. The distance covered in sprint assessment
ranged from 10 to 50m. Regarding the sprint time assess-
ment, nine studies used photoelectric cells [39, 55, 57, 58,
61–65], three studies used a stopwatch [56, 59, 60], and only
one study used an indirect method [66] that was recently val-
idated by Samozino etal. [42] to record sprint performance.
3.3 Acceleration Phase
The effect of RST on sprint time was measured in 144 par-
ticipants. The results of the overall effects on sprint time
showed a significant and moderate improvement between
pre- and post-test on the sprint performance (ES 0.61;
p = 0.0001; standardized mean difference [SMD] 0.57; 95%
confidence interval [CI] − 0.85 to − 0.28), with an average
heterogeneity of I2 = 28% (Fig.2) [39, 55–57, 59–66]. Fur-
thermore, in the studies that included a control group, a non-
significant improvement was found in participants belonging
to the RST group compared with the control group (ES 0.09;
p = 0.64; SMD 0.07; 95% CI − 0.37 to 0.23), with an average
heterogeneity of I2 = 0% (Fig.3) [55–57, 59–62, 64, 66].
Table3 presents the subgroup analysis assessing poten-
tial moderating factors for sprint time on the acceleration
phase of sprint. Regarding the population characteris-
tics, significant (p ≤ 0.05) improvements were found for
age, sex, and level. Moderate ESs were obtained for age
(ES < 21 = 0.60; ≥ 21 = 0.62), male sex (ES 0.73), recrea-
tionally active (ES 0.75), and trained (ES 0.84). However,
non-significant improvements were found for female sex (ES
0.14) and highly trained (ES 0.30). Additionally, between-
subgroup analyses revealed significant (p ≤ 0.05) differences
for sex and level.
Concerning the exercise characteristics, significant
(p ≤ 0.05) improvements were found for lower loads (< 20%
BM)(Fig.4), training frequency, training period duration,
session volume, total training volume, and rigid and grass
surfaces. A large ES was obtained for a frequency over twice
a week (ES 1.85) [55], and moderate ESs were found for
lower loads (ES 0.61) [39, 55–57, 59–65], > 6-week train-
ing periods (ES 0.63) [39, 55, 56, 60, 63–66], session vol-
ume > 160m (ES 0.92) [55, 56, 59, 60, 64], total weekly
training volume > 2680m (ES 0.83) [55, 59, 60, 64], and
rigid surface (ES 0.69) [39, 56, 61, 64]. Small ESs were
also found for a training frequency equal to or fewer than
two trainings per week (ES 0.52) [39, 56, 57, 59–66], a
total weekly training volume < 2680m (ES 0.53) [39, 56,
57, 61–63, 65, 66], and grass surface (ES 0.47) [59, 60, 65,
66]. However, non-significant improvements were found for
higher loads (≥ 20% BM; ES 0.63) [39, 63, 66], a train-
ing period ≤ 6weeks (ES 0.55) [57, 59, 61, 62], and track
surface (ES 0.64) [55, 57, 62, 63]. Additionally, significant
(p ≤ 0.05) differences were found for frequency of train-
ing between subgroups; however, it should be taken into
Effectiveness of RST for Sprint Performance
consideration that only one study evaluated a training fre-
quency of more than twice a week.
3.4 Maximum‑Velocity Phase
The effect of RST on sprint time in the maximum-veloc-
ity phase was measured in 81 participants. The results of
the overall effects on sprint time showed a non-significant
improvement between pre- and post-test on the sprint time
(ES 0.27; p = 0.25; SMD 0.18; 95% CI − 0.49 to 0.13), with
an average heterogeneity of I2 = 0% (Fig.5) [55, 58, 61–65].
Furthermore, the studies with a control group found a non-
significant improvement in the RST group compared with
the control group (ES 0.29; p = 0.23; SMD 0.26; 95% CI
− 0.16 to 0.68), with an average heterogeneity of I2 = 5%
(Fig.6) [55, 58, 61, 62, 64].
Subgroup analysis assessing potential moderating factors
for sprint time on the maximum-velocity phase of sprint is
presented in Table4. Both for population and exercise char-
acteristics, the ESs were small or trivial (ES 0.00–0.43) in
the maximum-velocity phase(Fig.7).
Table 1 Main characteristicsa of studies included in the meta-analysis
Data are mean, mean ± standard deviation, or n
A acceleration phase distance, B maximum-velocity phase distance, C full sprint distance, CG control group, HL high load, LL low load, ML
medium load, NA not available, RST resisted sled training exercise-group
a All characteristics refer to the RST group
Study Type NFemales (%) Age (years) Weight Height Level
CG RST
Alcaraz etal. [62] A: 0–15m 11 11 45 21.5 ± 2.2 69.8 ± 14.7 173.0 ± 10.5 Highly trained
B: 15–50m
C: 0–50m
Bachero-Mena etal. [63] LL–A: 0–20m – 7 0 21.9 ± 2.3 75.8 ± 10.7 180.9 ± 6.8 Recreationally active
LL–B: 20–40m
LL–C: 0–40m
ML–A: 0–20m – 6 0 20.8 ± 2.1 66.8 ± 8.5 173.8 ± 4.6
ML–B: 20–40m
ML–C: 0–40m
HL–A: 0–20m – 6 0 19.8 ± 1.6 70.2 ± 11.9 175.4 ± 6.8
HL–B: 20–40m
HL–C: 0–40m
Clark etal. [58] B: 18.3–54.9m 7 7 0 19.7 ± 1.0 87.9 ± 17.3 181.15 ± 6.8 Trained
De Hoyo etal. [65] A: 0–20m – 13 0 17.0 ± 1.0 73.1 ± 2.56 178.24 ± 1.3 Highly trained
B: 20–50m
C: 0–50m
Harrison and Bourke [57] A: 0–10m 7 8 0 20.5 ± 2.8 87.0 ± 10.5 NA Highly trained
Kawamori etal. [39] LL: 0–10m – 11 0 22.3 ± 5.2 82.5 ± 9.0 183.0 ± 0.07 Trained and recreationally
active
HL: 0–10m 10 0 22.8 ± 3.3 77.5 ± 7.3 179.0 ± 0.08
Lockie etal. [59] A: 0–10m 9 9 0 23.1 ± 4.2 83.1 ± 8.6 182.0 ± 0.1 Trained
Luteberget etal. [64] A: 0–10m 8 10 100 20.4 ± 3.1 74.6 ± 5.9 170.3 ± 5.3 Highly trained
B: 10–30m
C: 0–30m
Makaruk etal. [60] A: 0–20m 12 12 100 22.0 ± 0.9 61.5 ± 4.7 167.0 ± 0.1 Recreationally active
Morin etal. [66] A: 0–20m 6 10 0 26.3 ± 4.0 74.5 ± 5.3 177.0 ± 0.1 Trained
Spinks etal. [56] A:0–15m 10 10 0 21.8 ± 4.2 83.3 ± 8.7 181.9 ± 6.2 Trained
West etal. [61] A: 0–10m 10 10 0 26.8 ± 3.0 90.2 ± 10.3 186.0 ± 8.0 Highly trained
B: 10–30m
C: 0–30m
Zafeiridis etal. [55]A: 0–20m 11 11 0 20.1 ± 1.9 73.1 ± 2.4 178.0 ± 7.0 Recreationally active
B: 20–50m
C: 0–50m
P.E.Alcaraz et al.
3.5 Full Sprint
The effect of RST on sprint time in the full sprint was meas-
ured in 96 participants. The results of the overall effects
on sprint time showed a significant (p ≤ 0.05) improvement
between pre- and post-test in sprint performance (ES 0.36;
p = 0.009; SMD 0.38; 95% CI − 0.67 to − 0.10), with an
average heterogeneity of I2 = 0% (Fig.8) [55, 60–66]. How-
ever, the studies with a control group found a non-significant
improvement in the RST groups compared with the con-
trol groups (ES 0.05; p = 0.89; SMD 0.03; 95% CI − 0.40
to 0.47), with an average heterogeneity of I2 = 0% (Fig.9)
[55, 61, 62, 64].
Table 2 Characteristics of the resisted sled training interventions and sprint time assessment of the studies included in the meta-analysis
Data are mean or range
BM body mass
Study Fre-
quency
(week−1)
Session volume (m) Total train-
ing volume
(m)
Duration
(weeks)
Surface Load (% BM) Sprint time assessment
Instrument Total
distance
(m)
Alcaraz etal. [62] 2 90–180 1080 4 Track ~ 8 to 9 Photoelectric cells 50
Bachero-Mena etal.
[63]
2 100–210 2115 7 Track 5 Photoelectric cells 40
12.5
20
Clark etal. [58] 2 240–400 4060 7 Rigid 10.2 Photoelectric cells 36.6
De Hoyo etal. [65] 1–2 120–200 2680 8 Grass 12.6 Photoelectric cells 50
Harrison and Bourke
[57]
2 120 1440 6 Track ~ 13 Photoelectric cells 10
Kawamori etal. [39] 2 90–140 1740 8 Rigid ~ 13 Photoelectric cells 10
~ 43
Lockie etal. [59] 2 195–320 3100 6 Grass 12.6 Velocimeter with
stopwatch
10
Luteberget etal. [64] 2 240–280 5200 10 Rigid 12.4 Photoelectric cells 30
Makaruk etal. [60] 2 180–360 6210 9 Grass 7.5–10 Stopwatch 20
Morin etal. [66] 2 100 1600 8 Grass 80 Indirect method 20
Spinks etal. [56] 2 215–340 4090 8 Rigid 12.6 Stopwatch 15
West etal. [61] 2 60 720 6 Rigid 12.6 Photoelectric cells 30
Zafeiridis etal. [55] 3 280 6720 8 Track ~ 6.8 Photoelectric cells 50
Fig. 2 SMD between post and pre-interventionfor sprint time in the
acceleration phase. Squares represent the SMD for each trial. Dia-
monds represent the pooled SMD across trials. A acceleration phase,
CI confidence interval, HL high load, IV independent variable, LL
low load, ML moderate load, SD standard deviation, SMD standard-
ized mean difference
Effectiveness of RST for Sprint Performance
Table5 presents the subgroup analysis assessing poten-
tial moderating factors for sprint time on the full sprint.
Small ESs (0.24–0.53) were found for both population and
exercise characteristics. Furthermore, significant (p ≤ 0.05)
improvements with small ESs were found for younger ath-
letes (aged < 21years; ES 0.37) [55, 63–65], male sex (ES
0.34) [55, 61, 63, 65, 66], team-sports athletes (ES 0.42) [60,
61, 64–66], using a load < 20% BM (ES 0.35)(Fig.10) [55,
60–65], a training frequency equal to or less than twice a
week (ES 0.35) [60–66], a period of training > 6weeks (ES
0.39) [55, 60, 63–66], a session volume > 160m (ES = 0.53)
[55, 60, 64], and total training volume > 2680m (ES 0.53)
[55, 60, 64].
3.6 Evaluation ofPotential Bias
Visual interpretation of the funnel plot was performed to
evaluate potential bias. SMD between pre- and post-inter-
vention sprint time in RST participants was considered nota-
bly symmetrical, suggesting the absence of a significant pub-
lication bias. Similar results were obtained for the evaluation
of potential bias of the SMD in post-intervention sprint time
between RST and control group athletes.
4 Discussion
RST has been used extensively to improve sprint perfor-
mance. However, because there are many variables to
manipulate (load, distance, friction, etc.) with this type of
device, substantial controversy has been generated, both in
the scientific community and in the field of training, regard-
ing the optimal training protocol. The main objective of
this systematic review with meta-analysis was to determine
whether RST effectively improves sprint performance, in
both its acceleration and maximum-velocity phases. Second,
we intended to establish which variables are associated with
the largest RST-induced improvements. The main finding
of the present analysis is that RST improves sprint perfor-
mance, mainly in its early acceleration phase. However, its
effect is trivial or low in the maximum-velocity phase or in
sprints of ≥ 20m. Also, no additional benefit was observed
when RST was compared with UR conditions. Furthermore,
it was determined that the magnitude of its effect on sprint
performance is related to the selected population and/or
training characteristics.
4.1 Acceleration Phase
As mentioned in Sect.1, training with sled towing is an
appropriate method for improving the early acceleration
phase of the sprint (here defined as 0–10m), with a moderate
and significant effect. However, it is no more effective than
performing the same sprint training without overload. The
explanation for these results is that most studies use loads
close to a subject’s BM, making the differences in load very
small. This fact has led some researchers [41, 66] to think
that higher loads may have to be used for the improvements
to be significantly greater than when lower loads are used.
However, given the low number of studies using loads > 20%
BM, the effect is similar (0.61 vs. 0.63, respectively), and the
effect pre-post is not significant with high loads. This finding
may be explained by some of the main characteristics that
make the human being run at great speed, such as muscular
mechanical properties (i.e., the capacity for adequate use of
the elastic elements, both in series and in parallel), consid-
ering here the SSC, RFD, as well as the H reflex. It is clear
that the SSC and H reflex can be developed insituations
Fig. 3 SMD in post-intervention sprint time between intervention and
control athletes for sprint time in the acceleration phase. Squares rep-
resent the SMD for each trial. Diamonds represent the pooled SMD
across trials. A acceleration phase, CI confidence interval, IV inde-
pendent variable, SD standard deviation, SMD standardized mean dif-
ference
P.E.Alcaraz et al.
Table 3 Subgroup analysis assessing potential moderating factors for sprint time in the acceleration phase in the studies included in the meta-
analysis
Population characteristics Studies Resisted sled training
NumberaReferences SMD (95% CI) ES I2 (%) p pDifference
Age (~ 17 to 27years)
< 21y.o. 7 Bachero-Mena etal. [63]: LL-A, ML-A,
HL-A
de Hoyo etal. [65]: A
Harrison and Bourke [57]
Luteberget etal. [64]: A
Zafeiridis etal. [55]: A
− 0.53 (− 1.01 to − 0.04) 0.60 40 0.03 0.81
≥ 21y.o. 8 Alcaraz etal. [62]: A
Kawamori etal. [39]: LL, HL
Lockie etal. [59]
Makaruk etal. [60]
Morin etal. [66]
Spinks etal. [56]
West etal. [61]: A
− 0.60 (− 0.97 to − 0.23) 0.62 25 0.001
Sex
Female ≥ 45% sample 3 Alcaraz etal. [62]: A
Luteberget etal. [64]: A
Makaruk etal. [60]
− 0.12 (− 0.60 to 0.37) 0.14 0 0.64 0.05
Male 12 Bachero-Mena etal. [63]: LL-A, ML-A,
HL-A
de Hoyo etal. [65]: A
Harrison and Bourke [57]
Kawamori etal. [39]: LL, HL
Lockie etal. [59]
Morin etal. [66]
Spinks etal. [56]
West etal. [61]: A
Zafeiridis etal. [55]: A
− 0.70 (− 1.01 to − 0.39) 0.73 20 < 0.001
Level
Recreationally active 7 Bachero-Mena etal. [63]: LL-A, ML-A,
HL-A
Kawamori etal. [39]: LL, HL
Makaruk etal. [60]
Zafeiridis etal. [55]: A
− 0.79 (− 1.24 to − 0.34) 0.75 29 < 0.001 0.04
Trained 5 Kawamori etal. [39]: LL, HL
Lockie etal. [59]
Morin etal. [66]
Spinks etal. [56]
− 0.85 (− 1.27 to − 0.43) 0.84 0 < 0.001
Highly trained 5 Alcaraz etal. [62]: A
de Hoyo etal. [65]: A
Harrison and Bourke [57]
Luteberget etal. [64]: A
West etal. [61]: A
− 0.17 (− 0.56 to 0.22) 0.30 0 0.39
Sport characteristics
Team sports 9 de Hoyo etal. [65]: A
Harrison and Bourke [57]
Kawamori etal. [39]: LL, HL
Lockie etal. [59]
Luteberget etal. [64]: A
Morin etal. [66]
Spinks etal. [56]
West etal. [61]: A
− 0.58 (− 0.91 to − 0.26) 0.66 11 < 0.001 0.07
Individual sports 1 Alcaraz etal. [62]: A 0.23 (− 0.61 to 1.07) 0.23 NA 0.59
Effectiveness of RST for Sprint Performance
Table 3 (continued)
Population characteristics Studies Resisted sled training
NumberaReferences SMD (95% CI) ES I2 (%) p pDifference
Exercise characteristics
Load (5–80% BM)
< 20% BM 12 Alcaraz etal. [62]: A
Bachero-Mena etal. [63]: LL-A, ML-A
de Hoyo etal. [65]: A
Harrison and Bourke [57]
Kawamori etal. [39]: LL
Lockie etal. [59]
Luteberget etal. [64]: A
Makaruk etal. [60]
Spinks etal. [56]
West etal. [61]: A
Zafeiridis etal. [55]: A
− 0.61 (− 0.97 to − 0.25) 0.61 43 < 0.001 0.63
≥ 20% BM 3 Bachero-Mena etal. [63]: HL-A
Kawamori etal. [39]: HL
Morin etal. [66]
− 0.45 (− 0.99 to 0.10) 0.63 0 0.11
Frequency (1–3week−1)
≤ 2week−1 14 Alcaraz etal. [62]: A
Bachero-Mena etal. [63]: LL-A, ML-A,
HL-A
de Hoyo etal. [65]: A
Harrison and Bourke [57]
Kawamori etal. [39]: LL, HL
Lockie etal. [59]
Luteberget etal. [64]: A
Makaruk etal. [60]
Morin etal. [66]
Spinks etal. [56]
West etal. [61]: A
− 0.47 (− 0.72 to − 0.22) 0.52 0 < 0.001 0.008
> 2week−1 1 Zafeiridis etal. [55]: A − 1.92 (− 2.97 to − 0.88) 1.85 NA < 0.001
Duration (4–10weeks)
≤ 6weeks 4 Alcaraz etal. [62]: A
Harrison and Bourke [57]
Lockie etal. [59]
West etal. [61]: A
− 0.38 (− 0.87 to 0.11) 0.55 12 0.13 0.41
> 6weeks 11 Bachero-Mena etal. [63]: LL-A, ML-A,
HL-A
de Hoyo etal. [65]: A
Kawamori etal. [39]: LL, HL
Luteberget etal. [64]: A
Makaruk etal. [60]
Morin etal. [66]
Spinks etal. [56]
Zafeiridis etal. [55]: A
− 0.64 (− 0.99 to − 0.28) 0.63 35 < 0.001
Session volume (60–360m)
≤ 160m 10 Alcaraz etal. [62]: A
Bachero-Mena etal. [63]: LL-A, ML-A,
HL-A
de Hoyo etal. [65]: A
Harrison and Bourke [57]
Kawamori etal. [39]: LL, HL
Morin etal. [66]
West etal. [61]: A
− 0.40 (− 0.70 to − 0.11) 0.46 0 0.008 0.18
P.E.Alcaraz et al.
where specific patterns of movement are replicated and load
specificity occurs [67]. Therefore, an excess load may limit
the development of the SSC, and—to a lesser degree—the
coupling of the H reflex, despite the athlete’s attempts to
maintain the movement pattern. On the other hand, the mus-
cle has been observed to work quasi-isometrically when
sprinting [68, 69], allowing for greater tendon lengthening
as load intensity increases [70] and for the tendon to act as
a power amplifier as it recoils at high velocities [71, 72].
Therefore, if we take into account that the tendon demands
are dependent on the movement velocity, the adaptations
induced will also be velocity dependent. This appears to also
explain why RST is much more effective in the acceleration
phase than in the maximum-velocity phase, where the move-
ment velocity, the SSC, and H reflex are critical [67]. That
is, in the acceleration phase, CT is greater than during the
maximum-velocity phase, as is the involvement of horizontal
force and the larger H:V force ratio. Moreover, it has been
suggested that increases in maximal strength are more likely
to increase short-distance (5-m) sprint performance [73].
One of the most analyzed variables that has consequently
generated the greatest discrepancy among the scientific com-
munity in recent years, is the load that should be used when
performing sled towing. Some authors [40] have shown that
the maximum power production when using these methods
occurs with loads around 20% BM, whereas others have
Table 3 (continued)
Population characteristics Studies Resisted sled training
NumberaReferences SMD (95% CI) ES I2 (%) p pDifference
> 160m 5 Lockie etal. [59]
Luteberget etal. [64]: A
Makaruk etal. [60]
Spinks etal. [56]
Zafeiridis etal. [55]: A
− 0.89 (− 1.53 to − 0.25) 0.92 57 0.006
Total training volume (720–6720m)
≤ 2680m 11 Alcaraz etal. [62]: A
Bachero-Mena etal. [63]: LL-A, ML-A,
HL-A
de Hoyo etal. [65]: A
Harrison and Bourke [57]
Kawamori etal. [39]: LL, HL
Morin etal. [66]
Spinks etal. [56]
West etal. [61]: A
− 0.49 (− 0.79 to − 0.19) 0.53 9 0.001 0.48
> 2680m 4 Lockie etal. [59]
Luteberget etal. [64]: A
Makaruk etal. [60]
Zafeiridis etal. [55]: A
− 0.78 (− 1.52 to − 0.03) 0.83 62 0.04
Surface
Rigid 5 Kawamori etal. [39]: LL, HL
Luteberget etal. [64]: A
Spinks etal. [56]
West etal. [61]: A
− 0.71 (− 1.24 to − 0.18) 0.69 40 0.009 0.70
Track 6 Alcaraz etal. [62]: A
Bachero-Mena etal. [63]: LL-A; ML-A;
HL-A
Harrison and Bourke [57]
Zafeiridis etal. [55]: A
− 0.57 (− 1.19 to 0.05) 0.64 54 0.07
Grass 4 de Hoyo etal. [65]: A
Lockie etal. [59]
Makaruk etal. [60]
Morin etal. [66]
− 0.42 (− 0.84 to 0.01) 0.47 0 0.05
Subgroup analyses were performed on SMD between post and pre-intervention sprint time. Median values of continuous variables were used as
cut-off values for grouping studies. Changes in moderating factors were calculated as post-intervention minus pre-intervention values
A acceleration phase, B maximum-velocity phase, BM body mass, C full sprint, CI confidence interval, ES Cohen´s d effect size, HL high load,
I2 heterogeneity, LL low load, ML medium load, NA not available, p test for overall effect, pDifference test for subgroup differences, SMD standard-
ized mean difference
a Number of intervention groups in the studies. Some enrolled studies were not included because the value used for subgroup analysis was not
reported
Effectiveness of RST for Sprint Performance
suggested that the maximum power output can be achieved
with 69–96% BM [41]. It should be noted that Monte etal.
[40] calculated and examined the load that maximizes power
output with sprinters and for the full sprint (20m) and ana-
lyzed the effect on the kinematics of the joints and segments.
However, Cross etal. [41] calculated the maximum power
output at the moment when participants (team-sports ath-
letes) reached maximum sprint speed and did not calculate
effect on sprint technique. In any case, it is not clear for this
training method that training with the load that produces
the maximum power output is the most effective method
for improving sprint performance. Hence, more research is
needed in this regard.
As mentioned, the present meta-analysis observed that
the effect on performance improvement was moderate when
comparing loads < 20% BM and loads ≥ 20% BM, with no
significant improvements achieved with loads ≥ 20% BM.
It should be noted that only three groups [39, 63, 66] used
loads ≥ 20% BM and that these three groups were composed
of team-sports athletes. Therefore, it cannot be inferred that
the use of high loads is more effective than the use of low
loads. In fact, the only study to use very high loads (80%
Fig. 4 SMD between post and pre-intervention for sprint time in
the acceleration phase based on different load (subgroup analysis).
Squares represent the SMD for each trial. Diamonds represent the
pooled SMD across trials. A acceleration phase, HL high load, ML
moderate load, LL low load, BM body mass, CI confidence interval,
IV independent variable, SD standard deviation, SMD standardized
mean difference
Fig. 5 SMD between post and pre-intervention for sprint time in the
maximum-velocity phase. Squares represent the SMD for each trial.
Diamonds represent the pooled SMD across trials. B maximum-
velocity phase, CI confidence interval, HL high load, IV independ-
ent variable, LL low load, ML moderate load, SD standard deviation,
SMD standardized mean difference
P.E.Alcaraz et al.
Table 4 Subgroup analysis assessing potential moderating factors for sprint time in the maximum-velocity phase in the studies included in the
meta-analysis
Population characteristics Studies SMD (95% CI) Resisted sled training
NumberaReferences ES I2 (%) p pDifference
Age (~ 17 to 27years)
< 21y.o. 7 Bachero-Mena etal. [63]: LL-B, ML-B, HL-B
Clark etal. [58]
de Hoyo etal. [65]: B
Luteberget etal. [64]: B
Zafeiridis etal. [55]: B
− 0.17 (− 0.53 to 0.19) 0.26 0 0.35 0.92
≥ 21y.o. 2 Alcaraz etal. [62]: B
West etal. [61]: B
− 0.21 (− 0.81 to 0.40) 0.28 0 0.50
Sex
Female ≥ 45% simple 2 Alcaraz etal. [62]: B
Luteberget etal. [64]: B
− 0.38 (− 0.99 to 0.24) 0.18 0 0.23 0.47
Male 7 Bachero-Mena etal. [63]: LL-B, ML-B, HL-B
Clark etal. [58]
de Hoyo etal. [65]: B
West etal. [61]: B
Zafeiridis etal. [55]: B
− 0.11 (− 0.47 to 0.25) 0.23 0 0.54
Level
Recreationally active 4 Bachero-Mena etal. [63]: LL-B, ML-B, HL-B
Zafeiridis etal. [55]: B
− 0.04 (− 0.54 to 0.47) 0.21 0 0.89 0.67
Trained 1 Clark etal. [58] 0.00 (− 1.05 to 1.05) 0.00 NA 1
Highly trained 4 Alcaraz etal. [62]: B
de Hoyo etal. [65]: B
Luteberget etal. [64]: B
West etal. [61]: B
− 0.31 (− 0.73 to 0.11) 0.39 0 0.15
Sport characteristics
Team sports 4 Clark etal. [58]
de Hoyo etal. [65]: B
Luteberget etal. [64]: B
West etal. [61]: B
− 0.29 (− 0.73 to 0.15) 0.34 0 0.20 0.84
Individual sports 1 Alcaraz etal. [62]: B − 0.19 (− 1.03 to 0.65) 0.20 NA 0.65
Exercise characteristics
Load (5–20% BM)
< 20% BM 8 Alcaraz etal. [62]: B
Bachero-Mena etal. [63]: LL-B, ML-B
Clark etal. [58]
de Hoyo etal. [65]: B
Luteberget etal. [64]: B
West etal. [61]: B
Zafeiridis etal. [55]: B
− 0.18 (− 0.50 to 0.14) 0.26 0 0.28 0.97
≥ 20% BM 1 Bachero-Mena etal. [63]: HL-B − 0.20 (− 1.34 to 0.93) 0.28 NA 0.73
Frequency (1–3week−1)
≤ 2week−1 8 Alcaraz etal. [62]: B
Bachero-Mena etal. [63]: LL-B, ML-B, HL-B
Clark etal. [58]
de Hoyo etal. [65]: B
Luteberget etal. [64]: B
West etal. [61]: B
− 0.23 (− 0.57 to 0.10) 0.25 0 0.17 0.41
> 2week−1 1 Zafeiridis etal. [55]: B 0.15 (− 0.69 to 0.98) 0.13 NA 0.73
Duration (4–8weeks)
≤ 6weeks 2 Alcaraz etal. [62]: B
West etal. [61]: B
− 0.21 (− 0.81 to 0.40) 0.28 0 0.50 0.92
Effectiveness of RST for Sprint Performance
Fig. 6 SMD in post-intervention sprint time between intervention
and control athletes for sprint time in the maximum-velocity phase.
Squares represent the SMD for each trial. Diamonds represent the
pooled SMD across trials. B maximum-velocity phase, CI confidence
interval, IV independent variable, SD standard deviation, SMD stand-
ardized mean difference
Table 4 (continued)
Population characteristics Studies SMD (95% CI) Resisted sled training
NumberaReferences ES I2 (%) p pDifference
> 6weeks 7 Bachero-Mena etal. [63]: LL-B, ML-B, HL-B
Clark etal. [58]
de Hoyo etal. [65]: B
Luteberget etal. [64]: B
Zafeiridis etal. [55]: B
− 0.17 (− 0.53 to 0.19) 0.26 0 0.35
Session volume (60–400m)
≤ 160m 6 Alcaraz etal. [62]: B
Bachero-Mena etal. [63]: LL-B, ML-B, HL-B
De Hoyo etal. [65]: B
West etal. [61]: B
− 0.20 (− 0.58 to 0.18) 0.32 0 0.31 0.87
> 160m 3 Clark etal. [58]
Luteberget [64]: B
Zafeiridis etal. [55]: B
− 0.15 (− 0.67 to 0.38) 0.15 0 0.59
Total training volume (720–6720m)
≤ 2680m 6 Alcaraz etal. [62]: B
Bachero-Mena etal. [63]: LL-B, ML-B, HL-B
De Hoyo etal. [65]: B
West etal. [61]: B
− 0.20 (− 0.58 to 0.18) 0.32 0 0.31 0.87
> 2680m 3 Clark etal. [58]
Luteberget etal. [64]: B
Zafeiridis etal. [55]: B
− 0.15 (− 0.67 to 0.38) 0.15 0 0.59
Surface
Rigid 3 Clark etal. [58]
Luteberget etal. [64]: B
West etal. [61]: B
− 0.30 (− 0.84 to 0.24) 0.31 0 0.28 0.80
Track 5 Alcaraz etal. [62]: B
Bachero-Mena etal. [63]: LL-B, ML-B, HL-B
Zafeiridis etal. [55]: B
− 0.08 (− 0.51 to 0.36) 0.20 0 0.73
Grass 1 de Hoyo etal. [65]: B − 0.27 (− 1.04 to 0.50) 0.43 NA 0.49
Subgroup analyses were performed on SMD between post and pre-intervention sprint time. Median values of continuous variables were used as
cut-off values for grouping studies. Changes in moderating factors were calculated as post-intervention minus pre-intervention values
A acceleration phase, B maximum-velocity phase, BM body mass, C full sprint, CI confidence interval, ES Cohen´s d effect size, HL high load,
I2 heterogeneity, LL low load, ML medium load, NA not available data, p test for overall effect, pDifference test for subgroup differences, SMD
standardized mean difference
a Number of intervention groups in the studies. Some enrolled studies were not included because the value used for subgroup analysis was not
reported
P.E.Alcaraz et al.
BM) [66] found a small and trivial effect on performance
of the 5- and 20-m sprint, respectively, which is similar
to those found in the control group with the same training
but without overload. Thus, Morin etal. [66] found only
a moderate effect on the F0, (i.e., the force at velocity 0),
or what would be equivalent to the maximum theoretical
force of the participants, but not on V0 (i.e., which would
be the equivalent of the maximum theoretical velocity of
the players), according to the model proposed by the same
authors [42]. As a consequence, the proposal of using RST
with very heavy loads would only be justified as a tertiary
method, which would affect the improvement of the force
at low or null velocities “simulating” the movement pattern
(and only in athletes who can maintain it). However, it is
far from the load and velocity specificity, which are both
decisive in the training of maximum power production, as
explained by Cormie etal. [28] in their narrative review on
maximal power production training. Another problem that
can occur when using excessively high loads is that neither
the SSC nor the H reflex are properly activated. In fact, train-
ing activities aimed at improving SSC performance should
fulfill two criteria [15, 74–77]: (1) they should involve skill-
ful, multi-joint movements that transmit forces through the
kinetic chain and exploit elastic–reflexive mechanisms; and
(2) they should be structured around brief work bouts or
clusters separated by frequent rest periods to manage fatigue
and emphasize work quality and technique.
Another point to consider is that chronic exposure to
movements eliciting the SSC can increase muscle stiffness,
which is a potential physiological advantage for sprint ability
[78]. An optimal development of mechanical stiffness in the
human leg has a major positive influence on various athletic
variables, including RFD, elastic energy storage and utiliza-
tion, and therefore the SSC, and sprint kinematics (i.e., CT
and FT, and SL and frequency) [79]. However, only Alcaraz
etal. [62] analyzed the effects of sled towing on stiffness, and
they found a slight non-significant reduction after a training
period of 4weeks (with low loads). However, this study
observed that the group training without a sled experienced
an improvement in stiffness that approached significance,
suggesting that training that respects the principle of speci-
ficity can have a positive effect on one of the most important
variables in sprinting (i.e., stiffness), whereas increasing the
load can have the opposite effect. Given these findings and
the recommendations based on a mixed-methods approach
in which a variety of loads and exercise types are used in a
periodized fashion to optimize power output, training with
high loads could be an alternative to traditional resistance
training. Thereby, using high-load RST to improve maxi-
mum strength, athletes train—to some extent—replicating
the movement patterns of the sprint. However, when the aim
is to work in the area of the force-velocity curve close to
the demands of the competition, the RST must be carried
out with low loads to develop all the mechanisms involved
in this situation, such as the RFD, SSC, H reflex, and leg
stiffness.
Regarding the characteristics of the population, statisti-
cally significant differences were observed only between lev-
els of participants, with the effect being moderate for both
recreationally active (ES 0.75) and trained participants (ES
0.84) but small for highly trained participants (ES 0.30).
The explanation for these results lies in the fact that highly
Fig. 7 SMD between post and pre-interventionfor sprint time in the
maximum-velocity phase based on different load (subgroup analy-
sis). Squares represent the SMD for each trial. Diamonds represent
the pooled SMD across trials. B maximum-velocity phase, BM body
mass, CI confidence interval, HL high load, LL low load, ML moder-
ate load, IV independent variable, SD standard deviation, SMD stand-
ardized mean difference
Effectiveness of RST for Sprint Performance
Table 5 Subgroup analysis assessing potential moderating factors for sprint time during full sprint in the studies included in the meta-analysis
Population characteristics Studies Resisted sled training
NumberaReferences SMD (95% CI) ES I2 (%) p pDifference
Age (~ 17 to 27years)
< 21y.o. 6 Bachero-Mena etal. [63]: LL-C, ML-C, HL-C
De Hoyo etal. [65]: C
Luteberget etal. [64]: C
Zafeiridis etal. [55]: C
− 0.41 (− 0.80 to − 0.02) 0.37 0 0.04 0.83
≥ 21y.o. 4 Alcaraz etal. [62]: C
Makaruk etal. [60]
Morin etal. [66]
West etal. [61]: C
− 0.35 (− 0.78 to 0.08) 0.35 0 0.11
Sex
Female ≥ 45% sample 3 Alcaraz etal. [62]: C
Luteberget etal. [64]: C
Makaruk etal. [60]
− 0.42 (− 0.91 to 0.07) 0.41 0 0.09 0.84
Male 7 Bachero-Mena etal. [63]: LL-C, ML-C, HL-C
De Hoyo etal. [65]: C
Morin etal. [66]
West etal. [61]: C
Zafeiridis etal. [55]: C
− 0.36 (− 0.71 to − 0.01) 0.34 0 0.04
Level
Recreationally active 4 Bachero-Mena etal. [63]:LL-C, ML-C, HL-C
Zafeiridis etal. [55]: C
− 0.38 (− 0.90 to 0.13) 0.35 0 0.14 0.91
Trained 0 – – – – –
Highly trained 4 Alcaraz etal. [62]: C
De Hoyo etal. [65]: C
Luteberget etal. [64]: C
West etal. [61]: C
− 0.35 (− 0.77 to 0.08) 0.32 0 0.11
Sport characteristics
Team sports 5 De Hoyo etal. [65]: C
Luteberget etal. [64]: C
Makaruk etal. [60]
Morin etal. [66]
West etal. [61]: C
− 0.43 (− 0.81 to − 0.06) 0.42 0 0.02 0.51
Individual sports 1 Alcaraz etal. [62]: C − 0.12 (− 0.96 to 0.71) 0.12 NA 0.77
Exercise characteristics
Load (5–80% BM)
< 20% BM 8 Alcaraz etal. [62]: C
Bachero-Mena etal. [63]: LL-C, ML-C
De Hoyo etal. [65]: C
Luteberget etal. [64]: C
Makaruk etal. [60]
West etal. [61]: C
Zafeiridis etal. [55]: C
− 0.38 (− 0.70 to − 0.07) 0.35 0 0.02 0.99
≥ 20% BM 2 Bachero-Mena etal. [63]: HL-C
Morin etal. [66]
− 0.39 (− 1.09 to 0.32) 0.42 0 0.28
Frequency (1–3week−1)
≤ 2week−1 9 Alcaraz etal. [62]: C
Bachero-Mena etal. [63]: LL-C, ML-C, HL-C
de Hoyo etal. [65]: C
Luteberget etal. [64]: C
Makaruk etal. [60]
Morin etal. [66]
West etal. [61]: C
− 0.37 (− 0.67 to − 0.06) 0.35 0 0.02 0.76
> 2week−1 1 Zafeiridis etal. [55]: C − 0.51 (− 1.36 to 0.35) 0.46 NA 0.24
P.E.Alcaraz et al.
trained athletes have a lower margin of improvement than
recreationally active or trained athletes when any training
protocol is applied [80]. On the other hand, it has been
observed that, when an RST is applied to improve accel-
eration capacity, the effect is moderate in team sports (ES
0.66) but small in individual sports (athletics) (ES 0.23). It
is necessary to consider, in this case, that only one study was
included [60] that analyzed the effects of RST on national
level sprinters and jumpers. Thus, more studies are needed
in this type of population, since RST is used regularly in the
design of training plans in athletics, specifically in force-
velocity disciplines (such as sprints, jumps, and hurdles),
and understanding is needed on the effects of RST on sprint
performance in both trained and highly trained athletes for
proper programming during the season. The effect shown
for team sports is also statistically significant. Therefore, the
RST is clearly recommended for the improvement of early
acceleration in sports such as soccer or rugby, particularly
Table 5 (continued)
Population characteristics Studies Resisted sled training
NumberaReferences SMD (95% CI) ES I2 (%) p pDifference
Duration (4–10weeks)
≤ 6weeks 2 Alcaraz etal. [62]: C
West etal. [61]: C
− 0.24 (− 0.85 to 0.37) 0.24 0 0.44 0.61
> 6weeks 8 Bachero-Mena etal. [63]: LL-C, ML-C, HL-C
De Hoyo etal. [65]: C
Luteberget etal. [64]: C
Makaruk etal. [60]
Morin etal. [66]
Zafeiridis etal. [55]: C
− 0.42 (− 0.75 to − 0.10) 0.39 0 0.01
Session volume (60–360m)
≤ 160m 7 Alcaraz etal. [62]: C
Bachero-Mena etal. [63]: LL-C, ML-C, HL-C
De Hoyo etal. [65]: C
Morin etal. [66]
West etal. [61]: C
− 0.29 (− 0.65 to 0.06) 0.29 0 0.10 0.40
> 160m 3 Luteberget etal. [64]: C
Makaruk etal. [60]
Zafeiridis etal. [55]: C
− 0.56 (− 1.05 to − 0.06) 0.53 0 0.03
Total training volume (720–6720m)
≤ 2680m 7 Alcaraz etal. [62]: C
Bachero-Mena etal. [63]: LL-C, ML-C, HL-C
De Hoyo etal. [65]: C
Morin etal. [66]
West etal. [61]: C
− 0.29 (− 0.65 to 0.06) 0.29 0 0.10 0.40
> 2680m 3 Luteberget etal. [64]: C
Makaruk etal. [60]
Zafeiridis etal. [55]: C
− 0.56 (− 1.05 to − 0.06) 0.53 0 0.03
Surface
Rigid 2 Luteberget etal. [64]: C
West etal. [61]:C
− 0.49 (− 1.12 to 0.14) 0.42 0 0.13 0.90
Track 5 Alcaraz etal. [62]: C
Bachero-Mena etal. [63]: LL-C, ML-C, HL-C
Zafeiridis etal. [55]: C
− 0.31 (− 0.75 to 0.12) 0.31 0 0.16
Grass 3 De Hoyo etal. [65]: C
Makaruk etal. [60]
Morin etal. [66]
− 0.40 (− 0.88 to 0.07) 0.42 0 0.10
Subgroup analyses were performed on SMD between post and pre-intervention sprint time. Median values of continuous variables were used as
cut-off values for grouping studies. Changes in moderating factors were calculated as post-intervention minus pre-intervention values
A acceleration phase, B maximum-velocity phase, BM body mass, C full sprint, CI confidence interval, ES Cohen´s d effect size, HL high load,
I2 heterogeneity, LL low load, ML medium load, NA not available data, p test for overall effect, pDifference test for subgroup differences, SMD
standardized mean difference
a Number of intervention groups in the studies. Some enrolled studies were not included because the value used for subgroup analysis was not
reported
Effectiveness of RST for Sprint Performance
since sprinting is the most frequent physical action for scor-
ing and assisting players before goals [1], and total sprint
distance and number of sprints undertaken during games
have increased significantly in different European league
players in the last decade [81].
Regarding the characteristics of training, weekly train-
ing frequencies > 2days were observed to produce a sig-
nificantly greater effect than frequencies ≤ 2 (ES 1.85 vs.
0.52). However, these data must be taken with caution since
only one study was included [53] that had applied > 2days
(3days·week−1) of training. In addition, this study was con-
ducted with physical education students, who had a lower
level of sprint performance and, a priori, higher potential
for improvement than those who are highly trained, as
noted in Sect.3.3. Therefore, training frequencies between
2–3days·week−1 can be optimal for the development of
acceleration capacity when using RST. With respect to the
duration of the program, four groups [57, 59, 61, 62] had
a duration of 4–6weeks, with a small and non-significant
effect, whereas 11 groups [39, 55, 56, 60, 63–66] used dura-
tions of 6–10weeks, with a significant (p < 0.001) moderate
effect (ES 0.63). The explanation for this finding may be
that shorter durations do not produce sufficient neuromus-
cular and mechanical adaptations to have a positive effect
on sprint performance [82]. Consequently, when designing a
program for the development of sprint performance through
RST, based on the results of the present meta-analysis, we
recommend a minimum duration of > 6weeks.
Another variable that should be considered when design-
ing training programs with RST is volume, both for each
session and for the microcycle. The volume per session var-
ied widely, from 60 to 360m. Although most (ten) groups
included volumes < 160m, volumes between 160 and 360m
(five groups) produced greater effects than lower volumes
(ES 0.92 vs. 0.46, respectively). Similarly, when weekly
volumes were compared, higher volumes (> 2680m) pro-
duced a moderate effect (ES 0.83) compared with volumes
720–2680m (ES 0.53), although the effects were statistically
significant for both volume per session and weekly volume.
Therefore, we can infer that slightly higher volumes, both
per session and microcycle, have a greater effect; however,
whether volume is as important as other variables that have
been previously analyzed is unclear.
Finally, with respect to the early acceleration phase, it has
been observed that the effect differs according to the surface
used. For example, rigid surfaces or athletic tracks have a
moderate effect (ES 0.69 and 0.64, respectively) and grass
produces a small effect. These results can be explained by
the high variability in friction related to the different types
of surfaces (natural vs. artificial turf). Since the coefficient of
Fig. 8 SMD between post and pre-interventionfor sprint time during
full sprint. Squares represent the SMD for each trial. Diamonds repre-
sent the pooled SMD across trials. C full sprint, CI confidence inter-
val, HL high load, IV independent variable, LL low load, ML moder-
ate load, SD standard deviation, SMD standardized mean difference
Fig. 9 SMD in post-intervention sprint time between intervention and
control athletes for sprint time during full sprint. Squares represent
the SMD for each trial. Diamonds represent the pooled SMD across
trials. C full sprint, CI confidence interval, IV independent variable,
SD standard deviation, SMD standardized mean difference
P.E.Alcaraz et al.
friction differs greatly between surfaces, this largely affects
resistance when using RST, as suggested by Linthorne and
Cooper [46]. These authors concluded that different sprint
surfaces would elicit varying degrees of coefficient of friction.
4.2 Maximum‑Velocity Phase andFull Sprint
Unlike the findings for the acceleration phase, RST has a
small effect on performance in the maximum-velocity phase
(ES 0.27) and/or when performing sprints ≥ 20m (ES 0.36);
however, in the latter case, the effect was significant. These
findings can be explained by the fact that resistance coming
from the friction between the surface of the sled and the
contact surface (track, grass, etc.) when the sprint is per-
formed with a sled will be different if the sled is stopped
or in motion because of the inertia of the system. There-
fore, when the maximum power output is calculated, the
maximum power output in sprinting usually occurs in the
first steps, and the horizontal force and power are decreased
by 82% and 63%, respectively, from the first to the last
step when using 20-m RST [40]. Therefore, if the aim is
to develop maximum power production in the maximum-
velocity phase, training strategies other than sled towing
may be needed, since vertical forces are predominant in this
phase [9, 16, 17]. Perhaps plyometric training or another
type of resisted training, such as the weighted vest, could
produce a greater effect in these phases.
When analyzing both the characteristics of the population
and the training method for the maximum-velocity phase,
the effects were small or trivial and not significant in all
cases. However, sub-analysis for the full sprint (≥ 20m)
indicated that, although the effects were still trivial or small
in some cases, some were significant. For example, regard-
ing the population characteristics, the effect was small but
significant for age < 21years (ES 0.37; p = 0.04), men (ES
0.34; p = 0.04), and team sports (ES 0.42; p = 0.02). With
respect to the training characteristics, the effect was small
in all cases and significant with loads < 20% BM (ES 0.35;
p = 0.02), weekly training frequencies of ≤ 2days (ES 0.35;
p = 0.02), for duration >6weeks (ES 0.39; p = 0.01), vol-
umes per session > 160m (ES 0.53; p = 0.03), and weekly
values > 2680m (ES 0.53; p = 0.03).
Although this meta-analysis answers many of the ques-
tions from the scientific literature, there is still a significant
lack of research that focuses on highly trained athletes in
individual sports such as athletics, in both males and females
of different ages.
5 Conclusions
RST has been used extensively in both team and individual
sports to improve sprint performance. However, to date,
there has been no consensus on whether this training method
actually improves sprint performance, in either the accelera-
tion or the maximum-velocity phases. Furthermore, whether
the effects differ according to population characteristics is
unclear, as is the optimal training load (intensity, volume,
etc.) for adaptations to be optimised. Based on the present
systematic review with meta-analysis, it can be affirmed that
RST is an effective method to improve sprint performance,
Fig. 10 SMD between post and pre-interventionfor sprint time dur-
ing full sprint based on different load (subgroup analysis). Squares
represent the SMD for each trial. Diamonds represent the pooled
SMD across trials. BM body mass, C full sprint, CI confidence inter-
val, HL high load, IV independent variable, LL low load, ML moder-
ate load, SD standard deviation, SMD standardized mean difference
Effectiveness of RST for Sprint Performance
mainly via improvement of the early acceleration phase.
However, it cannot be said that this method is more effec-
tive than the same training without overload. Regarding the
population characteristics, the effect is greater in men, rec-
reationally active or trained, but is small in highly trained
individuals who practice team sports such as football (soc-
cer) or rugby. Finally, with regards to the training charac-
teristics, the intensity (load) is not a determinant of sprint
performance improvement, but the recommended volume
is > 160m per session, and approximately 2680m per week,
with a training frequency of 2–3 times per week, for at least
6weeks. Finally, rigid surfaces appear to enhance the effect
of RST on sprint performance.
Based on these findings and given the limitations of this
meta-analysis, we provide the following answers to the
questions posed by coaches and the scientific community
in Sect.1:
1. Does RST improve sprint performance? Yes, but the
improvements will depend on the training phase.
2. Will the effect be greater when RST is used for the dif-
ferent phases of sprint? Yes. For the early acceleration
phase (≤ 10m), there will be a reduction in the average
sprint time of 2.3%; for the maximum-velocity phase
(≥ 15-m flying sprints at maximum intensity using a
run-in distance of ≥ 10m), the time will be reduced
by 1.7%; and for the full sprint (≥ 20m), the reduction
will be 1.5%. The effect is moderate and significant
only for the early acceleration phase.
3. Is RST more effective than UR sprinting? No; no dif-
ference was observed between groups with sleds and
controls (same training without sled). Therefore, RST
or UR will produce a similar level of adaptation.
4. What is the optimal load to use when applying RST for
obtaining higher sprint adaptations? There is no opti-
mal load for RST, since it will depend on the desired
objective. However, when training with sled towing as
a secondary method (i.e., replicating sprint demands in
terms of movement pattern, load, and movement veloc-
ity) but with a slight overload, the load must never
be > 20% BM. Conversely, when the aim is to improve
maximum strength, “respecting” the movement pat-
tern, loads > 20% BM could be suitable, as long as the
athlete does not substantially modify his/her running
technique. Loads > 20% BM should not be used with
low-level or inexperienced athletes with sled towing.
5. Should the load be different for the different phases
of sprint? Yes, keeping in mind that the main effect
of RST occurs in the early acceleration phase. For the
maximum-velocity phase, instead of using a different
load, perhaps another sprint training method with a
more vertical resistance component, like weighted
vests, could be used.
6. Does RST have a different effect on athletes depend-
ing on age? This is not clear. Therefore, more studies
comparing the effects of RST on different age groups
are necessary to determine whether the effect will dif-
fer.
7. Will the effect be greater if the athlete is highly
trained? No, in fact, for the acceleration phase, the
effect is significantly greater in recreationally active
and trained athletes than in highly trained athletes.
8. How many days per week should RST be applied?
These methods should be applied between 2 and 3days
per week, depending on the sprint demands of the sport
in which the athlete is working.
9. How many weeks should RST be applied? The effect
is significantly greater when the training is > 6weeks.
10. Can the surface affect the performance adaptations?
Yes, the effect is greater for rigid surfaces than for
grass, probably due to the lower friction that exists
with the same load on this surface.
Compliance with Ethical Standards
Funding No sources of funding were used to assist in the preparation
of this article.
Conflict of interest Pedro E. Alcaraz, Jorge Carlos-Vivas, Bruno O.
Oponjuru, and Alejandro Martínez-Rodríguez have no conflicts of in-
terest relevant to the content of this review.
References
1. Faude O, Koch T, Meyer T. Straight sprinting is the most fre-
quent action in goal situations in professional football. J Sports
Sci. 2012;30(7):625–31.
2. Haugen TA, Tønnessen E, Seiler S. Speed and countermove-
ment-jump characteristics of elite female soccer players, 1995–
2010. Int J Sports Physiol Perform. 2012;7(4):340–9.
3. Haugen TA, Tønnessen E, Seiler S. Anaerobic performance
testing of professional soccer players 1995–2010. Int J Sports
Physiol Perform. 2013;8(2):148–56.
4. Vescovi JD. Impact of maximum speed on sprint performance
during high-level youth female field hockey matches: Female
Athletes in Motion (FAiM) study. Int J Sports Physiol Perform.
2014;9(4):621–6.
5. Mann RA, Hagy J. Biomechanics of walking, running, and
sprinting. Am J Sports Med. 1980;8(5):345–50.
6. Young W, Benton D, Duthie G, Pryor J. Resistance training
for short sprints and maximum-speed sprints. Strength Cond J.
2001;23(2):7–13.
7. Mero A, Komi P, Gregor R. Biomechanics of sprint running. A
review. Sports Med. 1992;13(6):376–92.
8. Alexander RM. Mechanics of skeleton and tendons. Hand-
book of physiology—the nervous system. Am Physiol Soc.
1981;2:17–42.
9. Rabita G, Dorel S, Slawinski J, Saez-de-Villarreal E, Couturier
A, Samozino P, etal. Sprint mechanics in world-class athletes: a
P.E.Alcaraz et al.
new insight into the limits of human locomotion. Scand J Med Sci
Sports. 2015;25(5):583–94.
10. Mero A, Komi PV. Force-, EMG-, and elasticity-velocity rela-
tionships at submaximal, maximal and supramaximal run-
ning speeds in sprinters. Eur J Appl Physiol Occup Physiol.
1986;55(5):553–61.
11. Delecluse C. Influence of strength training on sprint running per-
formance. Sports Med. 1997;24(3):147–56.
12. Weyand PG, Sandell RF, Prime DNL, Bundle MW. The biological
limits to running speed are imposed from the ground up. J Appl
Physiol. 2010;108(4):950–61.
13. Weyand PG, Sternlight DB, Bellizzi MJ, Wright S. Faster top
running speeds are achieved with greater ground forces not more
rapid leg movements. J Appl Physiol. 2000;89(5):1991–9.
14. Clark KP, Weyand PG. Are running speeds maximized
with simple-spring stance mechanics? J Appl Physiol.
2014;117(6):604–15.
15. DeWeese BH, Bellon C, Magrum E, Taber CB, Suchomel TJ.
Strengthening the springs: improving sprint performance via
strength training. Track Tech. 2016;9(3):8–20.
16. Nagahara R, Mizutani M, Matsuo A, Kanehisa H, Fukunaga T.
Step-to-step spatiotemporal variables and ground reaction forces
of intra-individual fastest sprinting in a single session. J Sports
Sci. 2017;36(12):1392–401.
17. Nagahara R, Mizutani M, Matsuo A, Kanehisa H, Fukunaga T.
Association of sprint performance with ground reaction forces
during acceleration and maximal speed phases in a single sprint.
J Appl Biomech. 2017;34:104–10.
18. Dalleau G, Belli A, Bourdin M, Lacour J-R. The spring-mass
model and the energy cost of treadmill running. Eur J Appl Phys-
iol Occup Physiol. 1998;77(3):257–63.
19. Voigt M, Bojsen-Møller F, Simonsen EB, Dyhre-Poulsen P. The
influence of tendon Youngs modulus, dimensions and instantane-
ous moment arms on the efficiency of human movement. J Bio-
mech. 1995;28(3):281–91.
20. Plisk SS. Speed, agility, and speed-endurance development. In:
Baechle TR, Earle RW, editors. National strength and conditioning
association: essentials of strength training & conditioning. 2nd ed.
Champaign IL: Human Kinetics; 2000. p. 471–91.
21. MacDougall D, Sale D. Continuous vs. interval training:
a review for the athlete and the coach. Can J Appl Sport Sci.
1981;6(2):93–7.
22. Iacono AD, Martone D, Milic M, Padulo J. Vertical-vs. hori-
zontal-oriented drop jump training: Chronic effects on explosive
performances of elite handball players. J Strength Cond Res.
2017;31(4):921–31.
23. Rumpf MC, Lockie RG, Cronin JB, Jalilvand F. Effect of different
sprint training methods on sprint performance over various dis-
tances: a brief review. J Strength Cond Res. 2016;30(6):1767–85.
24. Freitas TT, Martinez-Rodriguez A, Calleja-González J, Alcaraz
PE. Short-term adaptations following complex training in team-
sports: a meta-analysis. PLoS One. 2017;12(6):e0180223.
25. Seitz LB, Reyes A, Tran TT, de Villarreal ES, Haff GG.
Increases in lower-body strength transfer positively to sprint
performance: a systematic review with meta-analysis. Sports
Med. 2014;44(12):1693–702.
26. Hill A. The heat of shortening and the dynamic constants of
muscle. Proc R Soc Lond B Biol Sci. 1938;126(843):136–95.
27. Hill A, Long C, Lupton H. The effect of fatigue on the relation
between work and speed, in contraction of human arm muscles.
J Physiol. 1924;58(4–5):334–7.
28. Cormie P, McGuigan MR, Newton RU. Developing maxi-
mal neuromuscular power part 2-training considerations
for improving maximal power production. Sports Med.
2011;41(2):125–46.
29. Randell AD, Cronin JB, Keogh JWL, Gill ND. Transference of
strength and power adaptation to sports performance-horizontal
and vertical force production. Strength Cond J. 2010;32(4):100–6.
30. Haff GG, Nimphius S. Training principles for power. Strength
Cond J. 2012;34(6):2–12.
31. Alcaraz PE, Palao JM, Elvira JLL, Linthorne NP. Effects of three
types of resisted sprint training devices on the kinematics of sprint-
ing at maximum velocity. J Strength Cond Res. 2008;22(3):890–7.
32. Kawamori N, Newton R, Nosaka K. Effects of weighted sled
towing on ground reaction force during the acceleration phase of
sprint running. J Sports Sci. 2014;32(12):1139–45.
33. Brown SC, Craik FI. Encoding and retrieval of information. In:
Tulving E, Craik FIM, editors. The Oxford handbook of memory.
2000. p. 93–107.
34. Haff GG, Stone MH. Methods of developing power with special
reference to football players. Strength Cond J. 2015;37(6):2–16.
35. Alcaraz PE, Palao JM, Elvira JL. Determining the optimal load
for resisted sprint training with sled towing. J Strength Cond Res.
2009;23(2):480–5.
36. Jakalski K. The pros and cons of using resisted and assisted train-
ing methods with high school sprinters: parachutes, tubing and
towing. Track Coach. 1998;144:4585–9.
37. Lockie RG, Murphy AJ, Spinks CD. Effects of resisted sled tow-
ing on sprint kinematics in field-sport athletes. J Strength Cond
Res. 2003;17(4):760–7.
38. Cottle CA, Carlson LA, Lawrence MA. Effects of sled towing on
sprint starts. J Strength Cond Res. 2014;28(5):1241–5.
39. Kawamori N, Newton RU, Hori N, Nosaka K. Effects of weighted
sled towing with heavy versus light load on sprint acceleration
ability. J Strength Cond Res. 2014;28(10):2738–45.
40. Monte A, Nardello F, Zamparo P. Sled towing: the optimal over-
load for peak power production. Int J Sports Physiol Perform.
2016;12(8):1052–8.
41. Cross MR, Brughelli M, Samozino P, Brown SR, Morin J-B. Opti-
mal loading for maximising power during sled-resisted sprinting.
Int J Sports Physiol Perform. 2017;12(8):1069–77.
42. Samozino P, Rabita G, Dorel S, Slawinski J, Peyrot N, Saez de
Villarreal E, etal. A simple method for measuring power, force,
velocity properties, and mechanical effectiveness in sprint run-
ning. Scand J Med Sci Sports. 2016;26(6):648–58.
43. Cronin JB, Hansen K, Kawamori N, McNair P. Effects of weighted
vests and sled towing on sprint kinematics. Sports Biomech.
2008;7(2):160–72.
44. Maulder PS, Bradshaw EJ, Keogh JWL. Kinematic altera-
tions due to different loading schemes in early acceleration
sprint performance from starting blocks. J Strength Cond Res.
2008;22(6):1992–2002.
45. Martinez-Valencia MA, Romero-Arenas S, Elvira JLL, Gon-
zalez-Rave JM, Navarro-Valdivielso F, Alcaraz PE. Effects of
sled towing on peak force, the rate of force development and
sprint performance during the acceleration phase. J Hum Kinet.
2015;46(1):139–48.
46. Linthorne NP, Cooper JE. Effect of the coefficient of friction of
a running surface on sprint time in a sled-towing exercise. Sports
Biomech. 2013;12(2):175–85.
47. Petrakos G, Morin JB, Egan B. Resisted sled sprint training to
improve sprint performance: A systematic review. Sports Med.
2016;46(3):381–400.
48. Moher D, Liberati A, Tetzlaff J, Altman DG, Prisma G. Preferred
reporting items for systematic reviews and meta-analyses: the
PRISMA statement. PLoS Med. 2009;6(7):e1000097.
49. Bhogal SK, Teasell RW, Foley NC, Speechley MR. The PEDro
scale provides a more comprehensive measure of methodological
quality than the Jadad scale in stroke rehabilitation literature. J
Clin Epidemiol. 2005;58(7):668–73.
Effectiveness of RST for Sprint Performance
50. de Morton NA. The PEDro scale is a valid measure of the meth-
odological quality of clinical trials: a demographic study. Aust J
Physiother. 2009;55(2):129–33.
51. Maher CG, Sherrington C, Herbert RD, Moseley AM, Elkins M.
Reliability of the PEDro scale for rating quality of randomized
controlled trials. Phys Ther. 2003;83(8):713–21.
52. Cohen J. Statistical power analysis for the behavioral sciences
(revised ed.). New York: Academic; 1977.
53. Hopkins W, Marshall S, Batterham A, Hanin J. Progressive statis-
tics for studies in sports medicine and exercise science. Med Sci
Sports Exerc. 2009;41(1):3.
54. Higgins JP, Green S. Cochrane handbook for systematic reviews
of interventions. New York: Wiley; 2011.
55. Zafeiridis A, Saraslanidis P, Manou V, Ioakimidis P, Dipla K,
Kellis S. The effects of resisted sled-pulling sprint training on
acceleration and maximum speed performance. J Sports Med Phys
Fit. 2005;45(3):284–90.
56. Spinks CD, Murphy AJ, Spinks WL, Lockie RG. The effects
of resisted sprint training on acceleration performance and kin-
ematics in soccer, rugby union, and Australian football players. J
Strength Cond Res. 2007;21(1):77–85.
57. Harrison AJ, Bourke G. The effect of resisted sprint training on
speed and strength performance in male rugby players. J Strength
Cond Res. 2009;23(1):275–83.
58. Clark KP, Stearne DJ, Walts CT, Miller AD. The longitudinal
effects of resisted sprint training using weighted sleds vs weighted
vests. J Strength Cond Res. 2010;24(12):3287–95.
59. Lockie RG, Murphy AJ, Schultz AB, Knight TJ, de Jonge XAKJ.
The effects of different speed training protocols on sprint accel-
eration kinematics and muscle strength and power in field sport
athletes. J Strength Cond Res. 2012;26(6):1539–50.
60. Makaruk B, Sozański H, Makaruk H, Sacewicz T. The effects of
resisted sprint training on speed performance in women. Hum
Mov Sci. 2013;14(2):116–22.
61. West DJ, Cunningham DJ, Bracken RM, Bevan HR, Crewther
BT, Cook CJ, etal. Effects of resisted training on accelera-
tion in professional rugby union players. J Strength Cond Res.
2013;27(4):1014–8.
62. Alcaraz PE, Elvira JLL, Palao JM. Kinematic, strength, and stiff-
ness adaptations after a short-term sled towing training in athletes.
Scand J Med Sci Sports. 2014;24(2):279–90.
63. Bachero-Mena B, Gonzalez-Badillo JJ. Effects of resisted sprint
training on acceleration with three different loads account-
ing for 5, 12.5, and 20% of body mass. J Strength Cond Res.
2014;28(10):2954–60.
64. Luteberget LS, Raastad T, Seynnes O, Spencer M. Effect of tra-
ditional and resisted sprint training in highly trained female team
handball players. Int J Sports Physiol Perform. 2015;10(5):642–7.
65. de Hoyo M, Gonzalo-Skok O, Sañudo B, Carrascal C, Plaza-
Armas JR, Camacho-Candil F, etal. Comparative effects of in-
season full-back squat, resisted sprint training, and plyometric
training on explosive performance in U-19 elite soccer players. J
Strength Cond Res. 2016;30(2):368–77.
66. Morin JB, Petrakos G, Jimenez-Reyes P, Brown SR, Samozino
P, Cross MR. Very-heavy sled training for improving horizon-
tal force output in soccer players. Int J Sports Physiol Perform.
2016;12(6):840–4.
67. Ross A, Leveritt M, Riek S. Neural influences on sprint running.
Sports Med. 2001;31(6):409–25.
68. Van Hooren B, Bosch F. Is there really an eccentric action of
the hamstrings during the swing phase of high-speed run-
ning? part I: a critical review of the literature. J Sports Sci.
2017;35(23):2313–21.
69. Van Hooren B, Bosch F. Is there really an eccentric action of the
hamstrings during the swing phase of high-speed running? Part
II: implications for exercise. J Sports Sci. 2017;35(23):2322–33.
70. Reeves ND, Narici MV. Behavior of human muscle fascicles
during shortening and lengthening contractions invivo. J Appl
Physiol. 2003;95(3):1090–6.
71. Ettema G. Mechanical efficiency and efficiency of storage and
release of series elastic energy in skeletal muscle during stretch-
shorten cycles. J Exp Biol. 1996;199(9):1983–97.
72. Nagano A, Komura T, Fukashiro S. Effects of the length ratio
between the contractile element and the series elastic element
on an explosive muscular performance. J Electromyogr Kinesiol.
2004;14(2):197–203.
73. Comfort P, Bullock N, Pearson SJ. A comparison of maximal
squat strength and 5-, 10-, and 20-meter sprint times, in ath-
letes and recreationally trained men. J Strength Cond Res.
2012;26(4):937–40.
74. McLean B. Biomechanics of running. In: Hawley JA, editor.
Handbook of sports medicine and science: running. John Wiley
& Sons; 2008. p. 28–43.
75. Schmidtbleicher D. Strength training: part 2: structural analysis of
motor strength qualities and its application to training. Sci Period
Res Tech Sport. 1985;4:1–10.
76. Schmidtbleicher D. Strength training: part 1: structural analysis of
motor strength qualities and its application to training. Sci Period
Res Tech Sport. 1985;4:1–12.
77. Siff M, Verkhoshansky Y. Supertraining. Denver: Supertraining
Institute; 2003.
78. Farley CT, Gonzalez O. Leg stiffness and stride frequency in
human running. J Biomech. 1996;29(2):181–6.
79. Brughelli M, Cronin J. A review of research on the mechanical
stiffness in running and jumping: methodology and implications.
Scand J Med Sci Sports. 2008;18(4):417–26.
80. Kraemer WJ, Adams K, Cafarelli E, Dudley GA, Dooly C, Feigen-
baum MS, American College of Sports Medicine position stand,
etal. Progression models in resistance training for healthy adults.
Med Sci Sports Exerc. 2002;34(2):364–80.
81. Barnes C, Archer D, Hogg B, Bush M, Bradley P. The evolution
of physical and technical performance parameters in the English
Premier League. Int J Sports Med. 2014;35(13):1095–100.
82. Bolger R, Lyons M, Harrison AJ, Kenny IC. Sprinting perfor-
mance and resistance-based training interventions: a systematic
review. J Strength Cond Res. 2015;29(4):1146–56.
Aliations
PedroE.Alcaraz1,2· JorgeCarlos‑Vivas1· BrunoO.Oponjuru1· AlejandroMartínez‑Rodríguez3
1 UCAM Research Center forHigh Performance Sport,
Catholic University ofMurcia, Murcia, Spain
2 Faculty ofSport Sciences, UCAM, Catholic University
ofMurcia, Murcia, Spain
3 Department ofAnalytical Chemistry, Nutrition andFood
Sciences, Faculty ofSciences, University ofAlicante,
Alicante, Spain
- A preview of this full-text is provided by Springer Nature.
- Learn more
Preview content only
Content available from Sports Medicine
This content is subject to copyright. Terms and conditions apply.
