Key words
power - sprint speed - soccer - concurrent training - vertical jump - team-sports
Introduction
Soccer is a tactical game; therefore, player behavior on the field is often
constrained by tactical tasks [1][2][3]. To perform these tasks successfully, players need
to be competent in several fitness attributes [3][4]. It is well established that some of these
qualities, which play significant roles in soccer performance, are maximal strength
and power [4][5][6][7][8][9], being considered key physical components for
professional soccer players [10]. Usually, maximal
strength is described in terms of one-repetition maximum (1RM), assessed in
traditional resistance exercises (e.g., squat). Power is defined as the product of
force and movement velocity; that is, the ability to perform as much work as
possible in the shortest time possible [6]. Although
technical-tactical training along with different soccer drills (e.g., small-sided
games) seem to act as useful methods for improving endurance-related capacities and
game skills, the development of strength and power in elite soccer players requires
focused interventions in order to provide sufficient and effective stimuli to elicit
significant adaptations [11][12].
The strength demands of soccer are complex and multifaceted. Overall, players must
be
able to effectively accelerate, decelerate, change direction, and jump [8][11][13][14][15]. On average, an elite player performs about
150–250 high-intensity activities during a soccer game [16]. Different training approaches have been suggested
to enhance neuromuscular [8][9][10][11][17][18][19][20][21][22][23][24][25] and recovery adaptations in soccer players [26]. It has now become apparent that strength and power
training requires maximal efforts and optimal intensities to yield best effects
[21]. Nevertheless, this scenario is not common in
professional soccer training routines [17]. At the
professional level, coaches are often concerned about the “side
effects” from intensive training periods (e.g., muscle injuries, perceived
muscle pain, and chronic fatigue), added to which, their training and recovery
practices are extremely affected by congested match schedules [18][21][27]. As a consequence, almost all interventions which
investigated the potential effects of strength-power training on soccer players were
conducted with semi-professional or amateur soccer teams [21]. At the professional level, considerably less information is
available about the training approaches used to improve or maintain optimal strength
levels. Thus, it remains to be established whether more traditional strength
training programs really provide significant benefits to professional soccer
players.
The ultimate goal of professional soccer players is to maximize performance during
competition [28], where the ability to produce high
levels of muscle power is considered of fundamental importance [29]. To date, coaches and researchers have provided
some practical recommendations to properly assess power output in soccer players
[6][30]. In fact, it is not possible to determine a
single gold-standard measurement since the neuromuscular demands of soccer are
multifactorial. The force-vector theory, for example, states that the direction of
the force vector applied during resistance exercises (e.g., half-squat or
hip-thrust) may play a key role in the development of strength-and power-related
abilities [31]. Likewise, during strength-power
training sessions, athletes usually execute different types of ballistic exercises,
in an attempt to improve their vertical and horizontal-based performance (e.g.,
vertical jumps and maximum acceleration efforts) [10][11][23][24]. In this regard, by examining changes in
counter-movement jump (i.e., [CMJ]; related to vertical force application) and
short-sprint abilities (i.e., 10 m time, [T10 m]; related to
horizontal force application), we can indirectly evaluate the influence of strength
training on the physical performance of professional soccer players [30]. These simple and applied physical tests are
considered valid and reliable measures of power and speed [17][24][32], and have been shown to be strongly correlated
with a number of strength-and power-related variables [29][33].
We consider that a systematic review of studies conducted with professional soccer
players playing in the first division leagues is necessary, especially for guiding
practitioners working with this population [21]. This
could help coaches to draw more consistent conclusions regarding the actual effects
of strength training on the physical qualities of soccer players and, more
importantly, to select the best training strategies for their players. Therefore,
the aim of this meta-analysis was to determine the effects of different strength
training programs on short-sprint and vertical jump performance of professional
soccer players who play in the first division leagues of their countries.
Materials and Methods
Procedures
In this investigation a meta-analysis of 13 studies with a total of 29 effect
sizes was performed to determine the effects of different strength training
programs on jumping and sprinting abilities of professional soccer players who
play in the first division of their countries. This study meets the IJSM ethical
standards [34]. The following inclusion criteria
were employed for the analysis: a) randomized controlled studies, 2) instruments
with high validity and reliability, 3) published in a high-quality peer-review
journal, 4) professional soccer players playing in the first division of their
countries, 5) studies where the strength training was fully described, and 6)
studies where CMJ and T10m were measured pre- and post-training.
To evaluate the chronic effects of different strength training protocols on
jumping and sprinting performance of professional soccer players, a
meta-analysis was conducted. Literature searches were electronically conducted
to identify investigations which examined the effects of different strength
training protocols applied to professional soccer players on CMJ and T10m. The
research assessed the ADONIS, ERIC, SPORTDiscus, EBSCOhost, Google Scholar,
Medline, and PubMed electronic databases between December 2020 and January 2021
and was updated in February 2021. Moreover, manual searches were performed in
relevant sport science journals. The references of identified articles were
examined to identify additional studies eligible for the review. The search
included studies published in English and studies in any language for which the
abstract was available in English. Key words used included “strength
training”, “resistance training”, “power
training”, “professional”,
“top-professional”, “elite”,
“soccer”, and “football”. No age or sex
restrictions were imposed at the search stage.
For the study selection, three steps were followed: 1) the article titles were
read, 2) the abstracts were read, and 3) the entire articles were read. In this
review, only full primary research papers (i.e. not conference abstracts, letter
to the editors, and thesis, or reviews) were eligible for inclusion.
Studies were included if they met the following criteria based on the
recommendations by Campbell and Stanley [35]: 1)
randomized controlled studies, 2) instruments with high validity and
reliability, 3) published in a high quality peer-review journal, 4) professional
soccer players playing in the first division of their countries, 5) studies
where the strength training was fully described, and 6) studies where CMJ ([Table 1]) and T10m ([Table 2]) were measured pre- and post-training. Following this search
process, 13 articles were included in the analysis ([Fig. 1]).
Table 1 Summary of characteristics of all studies meeting the
inclusion criteria. CMJ.
|
Authors
|
Year
|
L
|
PoS
|
Gr
|
n
|
Age
|
Bm
|
H
|
Wk
|
FWS
|
TS
|
DF
|
Nexe
|
Nset
|
Nrs
|
TNr
|
IR
|
Iex
|
VC
|
% CMJ
|
ES
|
|
Koundourakis et al.
|
2014
|
Gre
|
P-I
|
E
|
23
|
25.5
|
79
|
182
|
24
|
1.5
|
36
|
V
|
3
|
4
|
10
|
4320
|
4
|
70-80 RM
|
No
|
7.23
|
0.87
|
|
Koundourakis et al.
|
2014
|
Gre
|
P-I
|
E
|
22
|
24.7
|
80
|
181
|
24
|
1
|
24
|
OKC
|
4
|
4
|
5-6
|
1920
|
4
|
90 RM
|
No
|
7.48
|
1.08
|
|
Koundourakis et al.
|
2014
|
Gre
|
In
|
E
|
23
|
25.5
|
79
|
182
|
18
|
1.5
|
27
|
V
|
3
|
4
|
10
|
2160
|
4
|
70-80 RM
|
No
|
4.03
|
0.41
|
|
Koundourakis et al.
|
2014
|
Gre
|
In
|
E
|
22
|
24.7
|
80
|
181
|
18
|
1
|
18
|
OKC
|
4
|
4
|
5-6
|
1440
|
4
|
90 RM
|
No
|
-0.21
|
-0.02
|
|
Helgerud et al.
|
2011
|
Cha
|
Pre
|
E
|
21
|
25
|
78
|
184
|
8
|
2
|
16
|
V
|
1
|
4
|
4
|
256
|
3
|
90 RM
|
Yes
|
5.24
|
0.64
|
|
Rønnestad et al.
|
2008
|
Nor
|
Pre
|
E
|
6
|
23
|
74
|
180
|
7
|
2
|
14
|
V
|
2
|
3-5
|
4-6
|
272
|
–
|
85-90 RM
|
Yes
|
4.95
|
2.00
|
|
Rønnestad et al.
|
2008
|
Nor
|
Pre
|
E
|
8
|
22
|
80
|
186
|
7
|
2
|
14
|
V-H
|
5
|
2-5
|
4-10
|
928
|
–
|
0-90 RM
|
Yes
|
1.94
|
0.35
|
|
Rønnestad et al.
|
2008
|
Nor
|
Pre
|
C
|
7
|
24
|
81
|
186
|
7
|
–
|
–
|
–
|
–
|
–
|
–
|
–
|
–
|
–
|
–
|
-0.83
|
-0.33
|
|
Rønnestad et al.
|
2011
|
Nor
|
Pre
|
E
|
12
|
24
|
80
|
185
|
10
|
2
|
20
|
V
|
1
|
3
|
4-10
|
387
|
–
|
80-90 RM
|
Yes
|
4.58
|
1.13
|
|
Rønnestad et al.
|
2011
|
Nor
|
In
|
E
|
7
|
22
|
76
|
184
|
12
|
1
|
12
|
V
|
1
|
3
|
4-10
|
144
|
–
|
80-90 RM
|
Yes
|
-1.46
|
-0.15
|
|
Rønnestad et al.
|
2011
|
Nor
|
In
|
E
|
7
|
26
|
83
|
186
|
12
|
0.5
|
6
|
V
|
1
|
3
|
4-10
|
72
|
–
|
80-90 RM
|
Yes
|
-1.46
|
-0.14
|
|
Loturco et al.
|
2013
|
Bra
|
Pre
|
E
|
16
|
19.2
|
73
|
173
|
6
|
2
|
6
|
V
|
1
|
4
|
4-8
|
296
|
2
|
30-80 RM
|
Yes
|
6.70
|
0.62
|
|
Loturco et al.
|
2013
|
Bra
|
Pre
|
E
|
16
|
19.1
|
72
|
172
|
6
|
2
|
6
|
V
|
1
|
4
|
4-8
|
296
|
2
|
30-80 RM
|
Yes
|
6.90
|
0.62
|
|
McGawley et al.
|
2013
|
Swe
|
Pre
|
E
|
9
|
23
|
76
|
180
|
5
|
3
|
15
|
V-H
|
6
|
2-3
|
5-10
|
60
|
1-1.5
|
75-90 RM
|
Yes
|
7.00
|
0.83
|
|
McGawley et al.
|
2013
|
Swe
|
Pre
|
E
|
9
|
23
|
76
|
180
|
5
|
3
|
15
|
V-H
|
6
|
2-3
|
5-10
|
60
|
1-1.5
|
75-90 RM
|
Yes
|
1.90
|
0.19
|
|
Gil et al.
|
2018
|
Bra
|
Pre
|
E
|
9
|
22.8
|
78
|
179
|
6
|
1
|
6
|
V-H
|
3
|
2-6
|
4-6
|
348
|
1-3
|
60 BM
|
No
|
15.37
|
1.80
|
|
Gil et al.
|
2018
|
Bra
|
Pre
|
E
|
9
|
22
|
76
|
180
|
6
|
1
|
6
|
V-H
|
3
|
2-6
|
4
|
348
|
1-3
|
60 BM
|
No
|
15.44
|
1.80
|
|
Loturco et al.
|
2017
|
Bra
|
Pre
|
E
|
7
|
21.7
|
74
|
177
|
5
|
2.5
|
12
|
V-H
|
2
|
4-8
|
1
|
1152
|
–
|
20-60 BM
|
No
|
-2.87
|
-0.39
|
|
Loturco et al.
|
2017
|
Bra
|
Pre
|
E
|
11
|
22.2
|
76
|
179
|
5
|
2.5
|
12
|
V-H
|
2
|
4-6
|
4
|
1704
|
–
|
0-60 BM
|
No
|
2.05
|
0.20
|
|
Pareja-Blanco et al.
|
2017
|
Mor
|
In
|
E
|
10
|
23.8
|
76
|
174
|
6
|
3
|
18
|
V
|
1
|
2-3
|
–
|
–
|
4
|
50-70 RM
|
No
|
5.34
|
0.45
|
|
Pareja-Blanco et al.
|
2017
|
Mor
|
In
|
E
|
10
|
23.8
|
76
|
174
|
6
|
3
|
18
|
V
|
1
|
2-3
|
–
|
–
|
4
|
50-70 RM
|
No
|
-2.62
|
-0.24
|
|
Loturco et al.
|
2015
|
Bra
|
Pre
|
E
|
12
|
23.4
|
76
|
178
|
4
|
2.5
|
10
|
V
|
1
|
6
|
4
|
372
|
2
|
–
|
Yes
|
0.37
|
0.06
|
|
Loturco et al.
|
2015
|
Bra
|
Pre
|
E
|
11
|
24.1
|
76
|
179
|
4
|
2.5
|
10
|
V
|
1
|
6
|
4
|
372
|
2
|
–
|
Yes
|
-1.24
|
-0.15
|
|
Loturco et al.
|
2016
|
Bra
|
Pre
|
E
|
12
|
23.1
|
75
|
176
|
6
|
3
|
18
|
V
|
1
|
6
|
4
|
470
|
1-1.5
|
30-90 RM
|
No
|
11.40
|
1.41
|
|
Loturco et al.
|
2016
|
Bra
|
Pre
|
E
|
11
|
23.9
|
75
|
177
|
6
|
3
|
18
|
V
|
1
|
6
|
6
|
648
|
1-1.5
|
–
|
Yes
|
11.50
|
1.53
|
L: League or competition in which he participates (Gre: Greek Super
league; Cha: Champions League; Nor: Norwegian Premier League; Bra:
Brasil First Division Championship; Mor: Morocco First Division
Championship; Swe: Swedish First Division 1); PoS: Period of the season
(Pre: Pre-season; In: In-season; P-I: Pre-season+In-season) Gr:
Group (E: Experimental group; C: Control Group); Bm: Body mass; H:
Height; Wk: Weeks program duration; FWS: frequency of weekly sessions;
TS: Total sessions;DF: Direction of force applied during the exercise
(V:Vertical; V-H: Vertical+Horizontal; OKC: Open Kinetic Chain
exercise); Nexe: number of exercise per day; Nset: number of sets per
exercise; Nrs: number of repetition per set; TNr: Total number of
repetition during the training period; RI:rest intervals; Iex: Intensity
of the exercise (RM: One repetition maximum, BM: Body mass) ; VC:
Variability of the charge during the training period (Yes/No);
CMJ (%); ES: Effects size
Table 2 Summary of characteristics of all studies meeting the inclusion criteria. T 10m.
|
Authors
|
Year
|
L
|
PoS
|
Gr
|
n
|
Age
|
Bm
|
H
|
Wk
|
FWS
|
TS
|
DF
|
Nexe
|
Nset
|
Nrs
|
TNr
|
IR
|
Iex
|
VC
|
% T 10m
|
ES
|
|
Koundourakis et al.
|
2014
|
Gre
|
P-I
|
E
|
23
|
25.5
|
79
|
182
|
24
|
1.5
|
36
|
V
|
3
|
4
|
10
|
4320
|
4
|
70-80 RM
|
No
|
-2.2
|
-0.66
|
|
Koundourakis et al.
|
2014
|
Gre
|
P-I
|
E
|
22
|
24.7
|
80
|
181
|
24
|
1
|
24
|
OKC
|
4
|
4
|
5-6
|
1920
|
4
|
90 RM
|
No
|
-2.8
|
-0.07
|
|
Koundourakis et al.
|
2014
|
Gre
|
In
|
E
|
23
|
25.5
|
79
|
182
|
18
|
1.5
|
27
|
V
|
3
|
4
|
10
|
2160
|
4
|
70-80 RM
|
No
|
-1,1
|
-0.33
|
|
Koundourakis et al.
|
2014
|
Gre
|
In
|
E
|
22
|
24.7
|
80
|
181
|
18
|
1
|
18
|
OKC
|
4
|
4
|
5-6
|
1440
|
4
|
90 RM
|
No
|
0
|
0
|
|
Helgerud et al.
|
2011
|
Cha
|
Pre
|
E
|
21
|
25
|
78
|
184
|
8
|
2
|
16
|
V
|
1
|
4
|
4
|
256
|
3
|
90 RM
|
Yes
|
-3.2
|
-1
|
|
Rønnestad et al.
|
2008
|
Nor
|
Pre
|
E
|
6
|
23
|
74
|
180
|
7
|
2
|
14
|
V
|
2
|
3-5
|
4-6
|
272
|
1
|
85-90 RM
|
Yes
|
-1.1
|
-1
|
|
Rønnestad et al.
|
2008
|
Nor
|
Pre
|
E
|
8
|
22
|
80
|
186
|
7
|
2
|
14
|
V-H
|
5
|
2-5
|
4-10
|
928
|
1
|
0-90 RM
|
Yes
|
-1.7
|
-1
|
|
Rønnestad et al.
|
2008
|
Nor
|
Pre
|
C
|
7
|
24
|
81
|
186
|
7
|
–
|
–
|
–
|
–
|
–
|
–
|
–
|
–
|
–
|
–
|
0
|
0
|
|
Loturco et al.
|
2013
|
Bra
|
Pre
|
E
|
16
|
19.2
|
73
|
173
|
6
|
2
|
6
|
V
|
1
|
4
|
4-8
|
296
|
2
|
30-80 RM
|
–
|
-1.6
|
-0.25
|
|
Loturco et al.
|
2013
|
Bra
|
Pre
|
E
|
16
|
19.1
|
72
|
172
|
6
|
2
|
6
|
V
|
1
|
4
|
4-8
|
296
|
2
|
30-80 RM
|
Yes
|
-4.3
|
-0.5
|
|
McGawley et al.
|
2013
|
Swe
|
Pre
|
E
|
9
|
23
|
76
|
180
|
5
|
3
|
15
|
V-H
|
6
|
2-3
|
5-10
|
60
|
1-1.5
|
75-90 RM
|
–
|
-1.4
|
-0.4
|
|
McGawley et al.
|
2013
|
Swe
|
Pre
|
E
|
9
|
23
|
76
|
180
|
5
|
3
|
15
|
V-H
|
6
|
2-3
|
5-10
|
60
|
1-1.5
|
75-90 RM
|
Yes
|
-2.2
|
-0.5
|
|
Gil et al.
|
2018
|
Bra
|
Pre
|
E
|
9
|
22.8
|
78
|
179
|
6
|
1
|
6
|
V-H
|
3
|
2-6
|
4-6
|
348
|
1-3
|
60 BM
|
No
|
-5.3
|
-1.3
|
|
Gil et al.
|
2018
|
Bra
|
Pre
|
E
|
9
|
22
|
76
|
180
|
6
|
1
|
6
|
V-H
|
3
|
2-6
|
4
|
348
|
1-3
|
60 BM
|
No
|
-5.4
|
-1.3
|
|
Loturco et al.
|
2015
|
Bra
|
Pre
|
E
|
12
|
23.4
|
76
|
178
|
4
|
2.5
|
10
|
V
|
1
|
6
|
4
|
372
|
2
|
–
|
Yes
|
-0.5
|
-0.17
|
|
Loturco et al.
|
2015
|
Bra
|
Pre
|
E
|
11
|
24.1
|
76
|
179
|
4
|
2.5
|
10
|
V
|
1
|
6
|
4
|
372
|
2
|
–
|
Yes
|
-1.1
|
-0.31
|
|
Loturco et al.
|
2016
|
Bra
|
Pre
|
E
|
12
|
23.1
|
75
|
176
|
6
|
3
|
18
|
V
|
1
|
6
|
4
|
470
|
1-1.5
|
30-90 RM
|
No
|
-3.3
|
-0.8
|
|
Loturco et al.
|
2016
|
Bra
|
Pre
|
E
|
11
|
23.9
|
75
|
177
|
6
|
3
|
18
|
V
|
1
|
6
|
6
|
648
|
1-1.5
|
–
|
Yes
|
-7.1
|
-2.1
|
|
Loturco et al.
|
2017
|
Bra
|
Pre
|
E
|
7
|
21.7
|
74
|
177
|
5
|
2.5
|
12
|
V-H
|
2
|
4-8
|
1
|
1152
|
–
|
20-60 BM
|
No
|
-5.7
|
-2.5
|
|
Loturco et al.
|
2017
|
Bra
|
Pre
|
E
|
11
|
22.2
|
76
|
179
|
5
|
2.5
|
12
|
V-H
|
2
|
4-6
|
4
|
1704
|
–
|
0-60 BM
|
No
|
-5.17
|
-1.8
|
|
Wong et al.
|
2010
|
Chi
|
P
|
E
|
20
|
24.6
|
71.4
|
176
|
8
|
2
|
18
|
V
|
4
|
6
|
3
|
72
|
3
|
85 RM
|
Yes
|
-5.8
|
-5.5
|
|
Wong et al.
|
2010
|
Chi
|
P
|
C
|
19
|
21
|
63.7
|
173
|
8
|
0
|
0
|
0
|
0
|
0
|
0
|
0
|
0
|
0
|
No
|
0
|
0
|
|
Mc Morrow et al.
|
2019
|
Ire
|
I
|
E
|
7
|
24.7
|
80.6
|
180
|
6
|
2
|
10
|
V-H
|
1-6
|
2-9
|
6
|
4
|
1-5
|
85-95 RM
|
Yes
|
-4
|
-1.06
|
|
Mc Morrow et al.
|
2019
|
Ire
|
I
|
E
|
6
|
24.7
|
80.6
|
180
|
6
|
2
|
10
|
V-H
|
1-6
|
2-9
|
6
|
4
|
1-5
|
85-95 RM
|
Yes
|
-5
|
-1.31
|
Fig 1 Flow of study selection.
Each article was read and coded by two investigators for the following variables:
1) descriptive information (i.e., age, body-mass, and height), league or
competition in which the players participate (i.e., Greek Super league,
Champions League, Norwegian Premier League, Brazilian First Division, Morocco
First Division, Swedish First Division, China First Division, Ireland First
Division); period of the season (i.e., pre-season, in-season,
pre-season+in-season); 2) training exercises: direction of force applied
(vertical, vertical+horizontal, or open kinetic chain movements),
variability of loads throughout the training period (yes or no); 3) training
variables and content: program duration in weeks, frequency of weekly sessions,
total training sessions, number of exercises per day, number of sets per
exercise, number of repetitions per set, total number of repetitions during the
training period, rest intervals, and exercise intensity. Mean agreement was
calculated using the intraclass correlation coefficient (ICC). The coding
agreement between investigators was determined by dividing the variables coded
by the total number of variables. The mean agreement between coding for this
study was 0.90. A mean agreement of 0.90 is accepted as an appropriate level of
reliability for such procedures [36]. Any coding
differences between investigators were scrutinized and resolved before the
analysis.
Gain effect size (ES) was calculated using the Hedges’ g and
Olkin’s formula (1):
where Mpost is the mean for the post-test, Mpre is
the mean for the pre-test, and SDpooled is the pooled SD of the measurements
(2):
The ES is a standardized value that permits the determination of the magnitude of
the differences between the groups or experimental conditions. It has been
suggested that the ES should be corrected for the magnitude of the sample size
of each study[35]. Therefore, corrections were
performed using the formula (3):
where m=n -1, as proposed by Hedges and
Olkin [36].
Statistical analyses
To determine the effects of the categorical independent variables (league or
competition in which players participated, period of the season, and programmed
exercises [direction of force applied during the exercise, variability of the
load during the training period (yes or no)], on CMJ and T10m effect sizes (ES),
an analysis of variance (ANOVA) was employed. In the case of quantitative
independent variables (e.g., age, body-mass, height, program duration in weeks,
frequency of weekly sessions, total sessions, number of exercises per day,
number of sets per exercise, number of repetitions per set, total number of
repetitions during the training period, rest intervals, and exercise intensity)
a Pearson’s (r) correlation test was used to examine the relationships
between CMJ ES and T10m ES, and the descriptive information of players and
training variables. The level of significance was set at p≤0.05. In
addition, data were also assessed for clinical significance using an approach
based on the magnitude of the changes. Threshold values for assessing magnitudes
of ES were<0.35, 0.35–0.80, 0.80–1.50, and>2.0
for trivial, small, moderate, and large, respectively [37].
Results
The analysis demonstrated that there were no statistical differences between average
ES of the experimental (0.10±1.24; n=44) and control groups
(0.11±0.19; n=3), for the two assessed variables (i.e., CMJ and
T10m) (p=0.986).
CMJ
There were no significant differences (p=0.2) between average ES in the
experimental (ES=0.62; n=24) and control groups
(ES=−0.33; n=1) when examining the CMJ performance.
Similarly, regarding subjects’ characteristics, the results indicated
that there were no significant correlations for age, body-mass, or height and
the CMJ ES magnitude ([Table 3]). ANOVA results
revealed a possible effect for some of the assessed variables (i.e., period of
the season, p=0.063; [Table 4]). No
significant relationships were detected between the training program variables
with CMJ ES ([Table 5]).
Table 3 CMJ (cm). Analysis for independent variables of
subject characteristics.
|
Independent Variables
|
% of change±SD
|
F
|
Level
|
ES
|
SD
|
n
|
r
|
p
|
|
Subject Characteristics
|
|
|
|
|
|
|
|
|
|
Age (y)
|
|
|
|
|
|
24
|
−0.059
|
0.758
|
|
Body mass (kg)
|
|
|
|
|
|
24
|
−0.087
|
0.685
|
|
Height (cm)
|
|
|
|
|
|
24
|
−0.038
|
0.861
|
|
League
|
F(5,18)=0.245
|
p=0.937
|
|
|
|
|
|
Greece
|
4.63±3.59
|
|
|
0.58
|
0.49
|
4
|
|
|
|
Champions League
|
5.24
|
|
|
0.64
|
–
|
1
|
|
|
|
Norway
|
1.71±3.11
|
|
|
0.63
|
0.92
|
5
|
|
|
|
Brazil
|
6.56±0.77
|
|
|
0.75
|
0.82
|
10
|
|
|
|
Sweden
|
4.45±3.60
|
|
|
0.51
|
0.45
|
2
|
|
|
|
Morocco
|
1.36±5.62
|
|
|
0.10
|
0.48
|
2
|
|
|
|
Period of the season
|
F(2,21)=3.157
|
p=0.063
|
|
|
|
|
|
Pre-Season
|
5.7±5.4
|
|
|
0.79
|
0.74
|
16
|
|
|
|
In-Season
|
0.6±3.2
|
|
|
0.05
|
0.30
|
6
|
|
|
|
Pre-Season+In-Season
|
7.3±0.17
|
|
|
0.97
|
0.14
|
2
|
|
|
ES=Effect size; n=sample; Level=alpha level;
r=Pearson Correlation coefficient; p=alpha level
* p<0.05,**p<0.01
Table 4CMJ (cm). Analysis of variance results on the
differences of ES between various elements of eccentric training
independent variables of program elements.
|
Independent Variables
|
% of change±SD
|
F
|
Level
|
ES
|
SD
|
n
|
r
|
p
|
|
Program Exercises
|
|
|
|
|
|
|
|
|
|
Direction of force applied during the exercise
|
F(2,21)=0.044
|
p=0.957
|
|
|
|
|
|
Vertical
|
4.09±4.51
|
|
|
0.60
|
0.68
|
15
|
|
|
|
Vertical+Horizontal
|
5.83±7.1
|
|
|
0.68
|
0.84
|
7
|
|
|
|
Open Kinetic Chain Exercise
|
3.63±5.4
|
|
|
0.53
|
0.77
|
2
|
|
|
|
Variability of the charge during the training period
|
F(1,22)=0.843
|
p=0.368
|
|
|
|
|
|
Yes
|
3.06±4.10
|
|
|
0.50
|
0.67
|
14
|
|
|
|
No
|
6.66±6.16
|
|
|
0.77
|
0.75
|
10
|
|
|
ES=Effect size; n=sample; Level=alpha level;
r=Pearson Correlation coefficient; p=alpha
level.*p<0.05,**p<0.01.
Table 5CMJ (cm). Pearson correlation coefficients (r) between
various program elements and training gains.
|
Training Program Variables
|
n
|
r
|
p
|
|
Frequency session/week
|
24
|
−0.094
|
0.663
|
|
Program duration (wk)
|
24
|
−0.009
|
0.968
|
|
Total of session
|
24
|
0.061
|
0.775
|
|
Number of exercises per day
|
24
|
0.075
|
0.729
|
|
Min number of sets per day
|
24
|
−0.058
|
0.789
|
|
Max number of sets per day
|
24
|
0.172
|
0.422
|
|
Min number of rep. per set
|
22
|
0.137
|
0.543
|
|
Max number of rep. per set
|
22
|
−0.248
|
0.265
|
|
Total of repetitions
|
22
|
−0.048
|
0.833
|
|
Min intensity of the exercise
|
21
|
−0.022
|
0.925
|
|
Max intensity of the exercise
|
21
|
−0.224
|
0.329
|
|
Rest
|
19
|
−0.228
|
0.347
|
n=sample; r=Pearson Correlation coefficient;
p=alpha level
* p<0.05,**p<0.01
T10m
There were no significant differences (p=0.2) between average ES in the
experimental (ES=−0.97; n=20) and control groups
(ES=0.0; n=2) when examining the T10m. Regarding the
subjects’ characteristics, the results indicated that there were no
significant correlations for age, body-mass, or height and the T10m ES magnitude
([Table 6]). However, ANOVA results revealed
significant effects for certain variables analyzed (i.e., League,
p<0.000; [Table 7]). The league analysis
demonstrated that the average ES in the China First Division
(ES=−5.5; n=1) was significantly higher (p<0.05)
than the ES observed in other leagues (ES ranging from −0.26 to
−1.18). No significant relationships were noted between training program
variables and T10m ES ([Table 8]).
Table 6 T10m (s). Analysis for independent variables of
subject characteristics.
|
Independent Variables
|
% of change±SD
|
F
|
Level
|
ES
|
SD
|
n
|
r
|
p
|
|
Subject Characteristics
|
|
|
|
|
|
|
|
|
|
Age (y)
|
|
|
|
|
|
22
|
−0.075
|
0.741
|
|
Body mass (kg)
|
|
|
|
|
|
22
|
0.410
|
0.058
|
|
Height (cm)
|
|
|
|
|
|
22
|
−0.229
|
0.305
|
|
League
|
F(6,21)=8.847
|
p=0.000**
|
|
|
|
|
|
Greece
|
−1.54±1.24
|
|
|
−0.26
|
0.30
|
4
|
|
|
|
Champions League
|
−3.21
|
|
|
−1
|
–
|
1
|
|
|
|
Norway
|
−1.41±0.38
|
|
|
−1
|
0
|
2
|
|
|
|
Brazil
|
−3.95±2.22
|
|
|
−1.1
|
0.82
|
10
|
|
|
|
Sweden
|
−1.8±0.56
|
|
|
−0.45
|
0.07
|
2
|
|
|
|
China
|
−5.8
|
|
|
−5.5
|
–
|
1
|
|
|
|
Ireland
|
−4.52±0.67
|
|
|
−1.18
|
0.17
|
2
|
|
|
|
Period of the season
|
F(1,19)=0.398
|
p=0.677
|
|
|
|
|
|
Pre-Season
|
−3.18±1.9
|
|
|
−1.25
|
1.38
|
14
|
|
|
|
In-Season
|
−2.54±2.36
|
|
|
−0.67
|
0.61
|
4
|
|
|
|
Pre-Season+In-Season
|
−3.86±2.2
|
|
|
−0.91
|
0.85
|
4
|
|
|
ES=Effect size; n=sample; Level=alpha level;
r=Pearson Correlation coefficient; p=alpha level
* p<0.05,**p<0.01
Table 7T10m (s). Analysis of variance results on the
differences of ES between various elements of eccentric training
independent variables of program elements.
|
Independent Variables
|
% of change±SD
|
F
|
Level
|
ES
|
SD
|
n
|
r
|
p
|
|
Program Exercises
|
|
|
|
|
|
|
|
|
|
Direction of force applied during the exercise
|
F(2,19)=0.867
|
p=0.436
|
|
|
|
|
|
Vertical
|
−2.85±2.13
|
|
|
1.14
|
1.54
|
11
|
|
|
|
Vertical+Horizontal
|
−3.99±1.74
|
|
|
−1.24
|
0.63
|
9
|
|
|
|
Open Kinetic Chain Exercise
|
−1.4±1.98
|
|
|
−0.03
|
0.04
|
2
|
|
|
|
Variability of the charge during the training period
|
|
F(1,20)=1.463
|
p=0.242
|
|
|
|
|
|
Yes
|
−3.12±2.12
|
|
|
−1.23
|
1.44
|
12
|
|
|
|
No
|
−3.26±2.01
|
|
|
−0.90
|
0.81
|
10
|
|
|
ES=Effect size; n=sample; Level=alpha level;
r=Pearson Correlation coefficient; p=alpha level
* p<0.05,**p<0.01
Table 8T10m (s). Pearson correlation coefficients (r) between
various program elements and training gains.
|
Training Program Variables
|
n
|
r
|
p
|
|
Frequency session/week
|
22
|
−0.116
|
0.608
|
|
Program duration (wk)
|
22
|
0.239
|
0.285
|
|
Total of session
|
22
|
0.25
|
0.911
|
|
Number of exercises per day
|
22
|
0.056
|
0.805
|
|
Min number of sets per day
|
22
|
0.015
|
0.947
|
|
Max number of sets per day
|
22
|
−0.238
|
0.287
|
|
Min number of rep. per set
|
22
|
−0.080
|
0.725
|
|
Max number of rep. per set
|
22
|
0.354
|
0.106
|
|
Total of repetitions
|
22
|
0.172
|
0.445
|
|
Min intensity of the exercise
|
22
|
0.057
|
0.817
|
|
Max intensity of the exercise
|
22
|
0.217
|
0.372
|
|
Rest
|
22
|
−0.026
|
0.913
|
n=sample; r=Pearson Correlation coefficient;
p=alpha
level * p<0.05,**p<0.01.
Discussion
The objective of this review was to determine the chronic effects of different
strength training protocols on short-sprint and vertical jump performance in
professional soccer players playing in the first division of their countries. The
main findings from this review were: a) the distinct strength training programs
analysed here produced similar performance improvements, regardless of their
specific characteristics (i.e., training exercises, volume, and intensity), and they
were not significantly different from the improvements exhibited by the control
groups; b) the different strength training protocols appear to have a lower effect
when applied during in-season phases than when applied during pre-season
and/or inter-season periods.
The most commonly used exercises in the different strength programs for the
“vertical direction” were the back squat [8][9][10][11][17][18][19][20][21][22] and the jump squat (JS) [8][17][18][20][23][24]; and for the “horizontal
direction” the resisted sprints (i.e., sled towing) [23][24][25] and unloaded horizontal jumps [10][24]. Curiously, there were no significant differences
in performance improvements between protocols that used exercises with different
directions (i.e., vertical or horizontal) of force application during the training
sessions ([Tables 4] and [7]). The first study that addressed this topic in professional soccer
players (Norwegian Premier League) was conducted by Ronnestad et al. [10], who examined the chronic effects of training under
vertical or vertical-horizontal training schemes. These authors compared, throughout
a pre-season period, a 6-week training protocol composed of two sessions per week,
based on 3–5 sets of 4–6 repetitions of vertically-oriented
exercises (e.g., half squats) at 85–90% 1RM with a similar protocol
combined with 2–4 sets of 5–10 repetitions of
vertically-horizontally-oriented exercises (i.e., alternate leg bound, double leg
hurdle jump, and single leg forward hop), and with a control group. There were no
significant effects of time for CMJ (from 1.94 to 4.95%) and T10m (from -1.1
to -0.7%) and no significant differences between groups for any other
performance variables. Subsequently, the authors pooled the two groups into the same
experimental group, who showed a significantly higher increase than the control
group in the T10m. Similarly, Koundourakis et al. [9]
(Greek Super league soccer players), compared vertically-oriented vs. open kinetic
chain exercises during the pre-season, the first half of the season (24 weeks), and
the second half of the season (throughout 18 weeks): the first protocol was based
on
1-2 sessions per week of 4 sets of 10 repetitions of circuit strength training using
vertical exercises (e.g., lunge, squats, steps up on bench with external weight) at
70-80% 1RM; and the second protocol was based on 1 session per week of 4
sets of 10 repetitions of open kinetic chain movements (e.g., leg extension,
hamstring curl) at 90% 1RM. Both groups showed increases in CMJ (from 7.2 to
7.5%) and decreases in T10m (from -2.2 to 2.8%) from the beginning
of the pre-season to the end of the first half of the season. During the second half
of the season, only the vertically-oriented protocol produced increases in CMJ
(4.3%) and T10m (from -2.2 to 2.8%), but there were no significant
differences for the open kinetic chain group. Nevertheless, the strength training
schemes which used vertically-horizontally-oriented exercises obtained a
non-significantly higher CMJ mean of 5.83% [10][11][23][24] and a lower T10m mean of -3.57% [10][11][23][24][25], compared to the training scheme using solely
vertically-oriented exercises (CMJ mean=4.09%) [8][9][10][17][18][19][21][22] and T10m mean=-2.85% [8][9][10][17][18][20][21]), and to the program using only open kinetic
chain exercises (CMJ mean=3.63% and T10m mean=-1.4%
)[9] (see [Tables
4] and [7]). In fact, the different
combinations of exercises used to design these protocols (i.e., vertically- or
horizontally-oriented exercises) and the variations in loading strategies (e.g.,
resisted sprints and horizontal-vertical jumps) could provide more comprehensive and
effective mechanical stimuli to improve neuromuscular performance in professional
soccer players. This argument certainly requires deeper analysis.
Loturco et al. [24] (Brazilian First Division
Championship) compared a training protocol of twelve training sessions in 5 weeks,
based on 6 sets of 6 repetitions of JS performed at the optimum power load (i.e.,
the load that maximizes power output), combined with 6-8 sets of 6 repetitions of
horizontal jumps and CMJ, with the same JS protocol mixed with 6–8 sets of
resisted sprints (i.e., 20-30m) with 5–20% body mass overload. The
training that combined JS and horizontal-vertical jumps increased the CMJ
(2%), with substantial differences from the training that combined JS and
resisted sprints (-2.9%). The training that combined JS and resisted sprints
showed no significant differences from the training that combined JS and
horizontal-vertical jumps in T10m. These results are in accordance with the
force-vector theory, where one group used more vertically-oriented exercises than
the other, which could play a crucial role in increasing CMJ performance [31]. Equally, previous investigations have shown that
horizontal plyometrics and resisted sprints improve short-distance acceleration
performance (i.e.,T10m) [38]. In fact, recently,
McMorrow et al. [25] (Ireland First Division) showed
similar results combining the front squat exercise with 20m resisted sprint (T10m
-4–5%); therefore, it is not a surprise that the T10m performance
could be similar in both groups. Nevertheless, Gil et al. [23] (Brazil First Division Championship) implementing a training scheme
similar to that proposed by Loturco et al.[24] found
higher CMJ (15%) and T10m (-5%) performance. Briefly, the training
protocol was based on 6 weeks, one session per week, including: (1) 4–6 sets
of 6 repetitions of JS with 60% of body mass, (2) 2–4 sets of 7-m
linear sprint, and (3) 2-4 sets of change of direction drills. During the 7-m linear
sprint, one of the groups executed resisted sprints (VertiMax, Model V8, Genetic
Potential, Tampa, Florida) with an overload capable of reducing sprint velocity by
10% (compared to the unresisted condition). There were no significant
differences between groups in any assessed variable. In agreement with Loturco et
al. [17], both groups performed the ballistic JS,
which appeared to be more indicated for developing the kinematic aspects of both
jump- and speed-related capacities (at least for professional soccer players). The
main difference was that Loturco et al. [24] used as
overload the “optimum power load”, while Gil et al. [23] used 60% of the body-mass of each player as
a fixed overload. Accordingly, Loturco et al. [18]
(Brazil First Division Championship) revealed that training continuously at the
“optimum power zone” and training under different%1RM (i.e.,
“traditional” strength-power periodization) produced significant
increases in CMJ (11.5; 11.4%) and T10m (-7.1%; -3.3%);
respectively, without differences between groups. However, delta change scores
demonstrated a superior effect of optimum power loads to improve T10m. The strength
training protocol proposed by Loturco et al. [18]
comprised 4 weeks, 3 sessions per week, 6 sets of 10-4 repetitions of half squat
from 60% to 90% 1RM or optimum power load; and two weeks, 6 times
per week, 6 sets of 6 repetitions of JS at 30% 1RM or optimum power load.
The results obtained in that study [18] are nearer to
those obtained by Gil et al. [23] and those obtained
by Loturco et al. [24]. Both studies used the JS with
overload at approximately 30% 1RM, and their results were higher than other
studies that used half squat or JS with loads higher than 30%1RM [8][9][10][17][19][21][22]. For example, Loturco et al. [17] (Brazilian First Division Championship) did not
find differences between half squat and JS training protocols under optimum loading
conditions, and the authors reported changes in CMJ from -1.24 to 0.37% and
in T10m from -0.5 to-1.1%, in 10 training sessions during a 4-week
pre-season period, based on 6 sets of 4-8 repetitions of each exercise. Equally,
Loturco et al. [8] (Brazil First Division
Championship) obtained better results when combining JS and half squat in the same
strength training protocol, in a study that compared the effects of
“increasing” or “decreasing” exercise velocity
within a 6-week training period. Both groups demonstrated increases in CMJ (6.70;
6.90%) and decreases in T10m (-1.6; -4.3%), without differences
between groups. Specifically, the protocol used was composed of 3 weeks, 2 days per
week, and based on 4 sets of 6-8 repetitions of back squat with
50–80% 1RM overload, followed by 3 weeks comprising 4 sets of
4–6 repetitions of JS increasing or reducing the exercise velocity with
loads ranging from 30% to 60%1RM. Pareja-Blanco et al. [22] (Morocco First Division Championship) using a half
squat with overloads between 50 and 70% 1RM, during 6 weeks, three sessions
per week, based on 2–3 sets of 4 repetitions, obtained similar results in
CMJ performance (5.34%). Helgerud et al. [21]
(Champions League soccer players), when increasing the training intensity to
90% 1RM overload, showed increments in CMJ (5.2%) and decrements in
T10m (-3.2%) after 8 weeks, two sessions per week, using 4 sets of 4
repetitions of half squats. Therefore, it seems that lighter intensities may provide
improvements towards the high-velocity end of the force-velocity spectrum, and it
is
possible to speculate that in strength training protocols, during
vertically-oriented exercises, overloads ~30% 1RM could optimize
jumping and sprinting performance in professional soccer players. However, we need
to consider that the majority of the protocols that used an overload of around
30% 1RM were preceded by a strength training foundation based on overload
above 30% 1RM [8]. Although there is evidence
that this strength training foundation is not able to “increase” the
transference of maximum strength capacity to the ability to produce force at higher
velocities in elite soccer players [18], more studies
are clearly required to corroborate this notion.
Our analysis revealed a possible effect for the period of the season in which the
strength training was performed (see [Table 4]).
Ronnestad et al. [19] (Norwegian Premier League), were
the first authors to investigate the effects of strength training in different
season periods. These authors proposed a training protocol during a pre-season of
10
weeks, two sessions per week, with 3 sets of 4–10 repetitions of
vertically-oriented exercises (i.e., half squats), with 80-90% RM overload.
During the next 12 weeks (in-season phase), the authors compared the effects of
applying this training protocol once a week versus every two weeks. The results
showed increments in CMJ (4.58%) during the pre-season period. During the
in-season period, the values of CMJ height were reduced (-1.46%) in both
groups. These results agreed with those obtained by Koundourakis et al. [9] for the group who performed 1 session per week of 4
sets of 10 repetitions of open kinetic chain exercises (e.g., leg extension,
hamstring curl), with 90% RM overload (CMJ: -0.21%). However, the
group who performed a circuit strength training program composed of 1–2
sessions per week of 4 sets of 10 repetitions of vertically-oriented exercises
(e.g., lunge, squats, steps up on bench with external weight), from 70 to
80% 1RM, improved the CMJ performance by 4%. This phenomenon could
be better elucidated when examining the high physical and physiological demands and
the very congested fixture schedules usually imposed by elite soccer leagues.
Indeed, during the in-season period, there are increased demands of aerobic-based
activities (e.g., technical-tactical training and official matches), which may
hamper the proper development of strength-power capacities [39][40]. In this regard, the strength training seems to
work more as an effective strategy to maintain the strength-power levels achieved
during the preparatory phases (being unable to elicit substantial gains in sprint
and jump performance) [19]. For example, it is
possible that heavy strength training, as proposed by Ronnestad et al. [19], once a week, is sufficient to maintain the initial
strength gains obtained by professional soccer players during preparatory phases,
but only when the resistance training sessions are applied at least once a week.
Still in this context, it could be possible that the mixed strength-speed training
protocol proposed by Koundourakis et al. [9], applied
1–2 times a week, was a more effective stimulus for these players,
increasing CMJ and T10m performance, while avoiding excessive training load and
insufficient recovery.
Interventions with professional soccer players present two evident problems: the lack
of control over some aspects of the intervention and the nonexistence of control
groups that receive the same attention from the coaching staff during the
intervention [21]. It is surprising that the majority
of the proposed strength training protocols improved athletic performance but did
not present significant differences from the players who did not perform a specific
strength-training protocol. As mentioned above, this could be partially explained
by
the concurrent effects of endurance and strength-power adaptations, which typically
occur during congested soccer seasons and pre-seasons [17][19][20][21][24]. However, there are studies showing that regular
technical-tactical training sessions and high intensity interval running can be
simultaneously performed with strength training in order to enhance the strength and
endurance capacities of professional soccer players [11][20][21]. Accordingly, McGawley et al. [11] (Swedish First Division) analyzed the effects of
performing a physical training program 3 times per week during a 5-week preseason
on
some soccer-specific variables and compared the impacts of completing high intensity
training (HIT) and strength-power training sessions in different orders within the
same session. The authors observed a positive effect of the concurrent training
approach on key measures of soccer performance (increased CMJ from 1.9 to 7%
and T10m from -1.4 to 2.2%), but the order of completing HIT and
strength-power training seemed not to affect performance adaptations. Equally, Wong
et al. [20] proposed training protocols where high
intensity interval running was concurrently performed with heavy strength training
based on 8 weeks, two sessions per week, comprising 4 sets of 6 repetitions of
vertically-oriented exercises (i.e., half squats and jump squats) at 85%1RM,
with a 3-min recovery. The professional soccer players presented decreases in T10m
time (~6%) and increases in aerobic capacity with significant
differences compared to the control group. Therefore, additional studies are still
needed to better elucidate the influence of concurrent training practices on the
physical performance of professional soccer players.
In general, researchers suggest that the lack of differences between experimental
and
control groups commonly found after strength training interventions in soccer
players may be due to inadequate (low) volumes and frequencies of resistance
training sessions throughout the professional soccer seasons, especially when
compared to the total training content [8][10][17][24]. In fact, it is widely known that the specific
soccer training (i.e., technical-tactical sessions) places competing demands on
complementary training sessions [11], which may
compromise the proper development of speed- and power-related performance.
Therefore, at least for the moment, it appears that the only practical solution is
to search for more time-efficient strength and power training strategies, which are
viable and effective in real soccer scenarios.
Conclusions
After examining the data available in the literature, it is possible to infer that
strength training – in the way it has been applied - may have a limited
impact on the short-sprint and jump performance of elite soccer players. The
congested fixture schedules and the high-volume of soccer-specific training usually
performed by these players during some specific training phases likely contribute
to
these “reduced effects”. Coaches and sport scientists are advised to
prioritize time-efficient training strategies as well as to use any available time
(e.g., warm-up sessions) in an attempt to maximize the strength development of elite
soccer players, since an increased number of matches, journeys, and training
sessions are commonplace in modern soccer.
