Effects of Plyometric Training on Physical Performance: An Umbrella Review

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Effects of Plyometric Training on Physical Performance: An Umbrella Review
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Short Title: Plyometric Training and Performance
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Rafael L. Kons1, Lucas B. R. Orssatto2, Jonathan Ache-Dias3, Kevin De Pauw4, Romain Meeusen4,
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Gabriel S. Trajano2, Juliano Dal Pupo5 & Daniele Detanico5
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1Department of Education, Faculty of Education, Federal University of Bahia, Bahia, Brazil;
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2School of Exercise and Nutrition Sciences, Faculty of Health, Queensland University of Technology,
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Brisbane, QLD, Australia
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3Research Group on Technology, Sport and Rehabilitation, Catarinense Federal Institute - IFC,
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Araquari, Brazi
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4 Brussels Human Robotic Research Center (BruBotics), Vrije Universiteit Brussel, Pleinlaan 2, 1050
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Brussels, Belgium
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5Biomechanics Laboratory, Centre of Sports - CDS, Federal University of Santa Catarina,
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Florianópolis, Santa Catarina, Brazil
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Corresponding author:
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Rafael Lima Kons, PhD
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Federal University of Bahia, Department of Education, Faculty of Education
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ZIP-CODE: 40110-100
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Salvador, Bahia, Brazil
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Phone: +55 48 3721-8530
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E-mail address: rafael.kons@ufba.br
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This is a pre-print and has not been peer-reviewed and should be cited as follows:
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Kons RLK; Orssatto LBR; Ache-Dias J; De Paw K; Meeusen R; Trajano GS; Dal Pupo J; Detanico D.
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Effects of Plyometric Training on Physical Performance: An Umbrella Review. Pre-print, SporRxiv,
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2022
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Abstract
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Background: Plyometric training can be performed through many types of exercises involving the
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stretch-shortening cycle in lower limbs. In the last decades, a high number of studies have investigated
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the effects of plyometric training on several outcomes in different populations.
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Objectives: To systematically review, summarize the findings, and access the quality of published
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meta-analyses investigating the effects of plyometric training on physical performance.
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Design: Systematic umbrella review of meta-analyses.
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Data Sources: Meta-analyses were identified using a systematic literature search in the databases
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PubMed/MEDLINE, Scopus, SPORTDiscus, Web of Science, Cochrane Library and Scielo.
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Eligibility Criteria for Selecting Meta-analyses: Meta-analyses that examined the effects of
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plyometric training on physical fitness in different populations, age groups, and sex.
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Results: Twenty-nine meta-analyses with moderate-to-high methodological quality were included in
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this umbrella review. We identified a relevant weakness in the current literature, in which only one
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meta-analysis included control group comparisons, while 24 included pre-to-post effect sizes. Trivial
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to large effects were found considering the effects of plyometric training on physical performance for
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healthy individuals, medium-trivial effects for the sports athletes’ groups and medium effects for
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different sports athletes’ groups, age groups, and physical performance.
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Conclusion: It is evidenced that plyometric training improves vertical jump height, but there is also a
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transfer to other physical fitness parameters and sports performance. However, it is important to outline
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that most meta-analyses included papers lacking a control condition. As such the results should be
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interpreted with caution.
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Key-Words: vertical jump, motor actions, sports-performance, muscle power
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Key Points
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1. This umbrella review identified 29 systematic meta-analyses investigating the effects of
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plyometric training on physical performance characteristics in the healthy and athletes’
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population with different age ranges, male and female groups.
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2. This umbrella review identified some important gaps in the literature. Most meta-analysis used
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a within-subjects design (pre vs post intervention effect sizes) with no control group
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comparison. This was consequence of a lack of original controlled trials in the literature.
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Control groups are fundamental to ensure that the observed adaptations can be attributed to the
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proposed intervention rather than other confounding factors. Also, most of the included studies
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were considered with low-to-moderate quality. Therefore, the outcomes provided by the
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available meta-analyses must not be considered level 1 evidence and should be taken with
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caution.
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3. The available meta-analyses suggest that plyometric training induces trivial to large effects on
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physical performance for healthy people, and enhanced performance for the athletes from
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different sports (e.g., vertical jump height, sprint performance and muscle strength). However,
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this should be interpreted cautiously as, for example, the lack of control group for studies with
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athletes from different sports does not allow to discriminate if other training characteristics
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influenced their enhanced performance.
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4. Future original studies should include control groups in their experimental design to support
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the effects of plyometric training on physical and sports performance.
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1. Introduction
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Plyometric training is broadly used to improve physical performance in many sports activities
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involving sprinting, jumping, change of direction ability and so forth [1-6]. The definition for
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plyometric training has been debated in the literature over the years and it is normally associated with
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stretch-shortening cycle (SSC) process. A general concept proposes that plyometric training can
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include many types of exercises involving the SSC [7,8]. It can be divided into different classifications,
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such as impact and non-impact plyometrics, or even according to the velocity of the SSC (e.g. short or
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long use of SSC) [9-11]. The effective use of the SSC is related to the different contributions of
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mechanisms associated with SSC, such as the accumulation of elastic energy [7], pre-load [12],
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increase the time to muscle activation [13], muscle history dependence (force enhancement) [14],
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stretch-reflexes [15] and muscle-tendon interactions [16] that facilitates greater mechanical work
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production in subsequent concentric muscle actions [17,18], which justifies the great use of plyometric
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exercises in physical training programs.
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Over the last decades numerous experimental studies suggest positive effects of plyometric
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training on neuromuscular performance (e.g., power output of lower limbs) [19-22], muscle
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mechanical properties (e.g., change in the musculotendinous stiffness and architecture) [23,24], and
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physiological parameters (e.g., running economy and endurance performance) [21, 25]. The significant
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number of publications investigating the effects of plyometric training on physical capacities has
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grown widely, as are systematic reviews with meta-analyses studies. Especially in the last 14 years
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papers included a wide range of sports activities, ages, and physical performance outcomes. To
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summarize the current knowledge on the topic and to identify possible methodological limitations in
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published meta-analyses, an umbrella review might be conducted [26], as this kind of review is
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considered on the highest level of the evidence pyramid [27]. Umbrella reviews highlight findings
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from already published meta-analyses, providing the state of the art about a given overarching topic
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with a high number of publications. Thus, it can help the reader to understand the current strengths and
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limitations of the entire body of literature on a specific topic from different perspectives and
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applications.
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This study aimed (i) to systematically review the available meta-analytical evidence that has
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examined the effects of plyometric training on physical fitness performance (e.g., muscle strength,
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muscle power, change of direction, sprint ability) considering different populations (ii) to address the
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quality, strengths and limitations of the meta-analytical evidence considering plyometric training; and
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(iii) to identify current limitations in the literature and provide suggestions for future research. Our
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findings may be useful for coaches, scientists, athletes and physical training practitioners in
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understanding the meaningful and clinical effects of the plyometric training for different populations
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(athletes and non-athletes, male and female) and different age ranges (young and older adults).
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2. Methods
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Our umbrella review was conducted in accordance with recommendations of Aromataris and
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colleagues [26] and addressed all items recommended in the PRISMA statement [27]. It was registered
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in the PROSPERO data base with the number: CRD42020217918.
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2.1 Literature Search
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We conducted a systematic literature search in the databases PubMed/MEDLINE, Scopus,
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SPORTDiscus, Web of Science, Cochrane Library and Scielo during February and May 2022. A
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Boolean search syntax was used (appendix 1). The reference list of each included meta-analysis was
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screened for titles to identify additional meta-analyses to be included in the umbrella review.
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2.2 Selection Criteria
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Based on a priori defined inclusion/exclusion criteria (PICOS = population, intervention, comparison,
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outcome, study design; Table 1), four independent reviewers (Author name, Author name, Author
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name, Author name) screened potentially relevant articles by analyzing titles, abstracts, and full texts
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of the respective articles to elucidate their eligibility. When the four reviewers did not reach an
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agreement concerning inclusion of an article, LBRO adjudicated.
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Table 1. Selection criteria used in this Umbrella review.
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2.3 Data Extraction
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The following data were extracted from the included meta-analyses: (1) first author and year of
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publication; (2) the number and type of primary studies included in the meta-analysis; (3) the study
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characteristics and the number of included participants; (4) the respective physical fitness outcome;
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(5) effect sizes and the equations used to compute effect sizes with their respective confidence intervals
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Category
Inclusion criteria
Exclusion criteria
Population
Healthy people, with no restrictions
on sex, age or sports modalities.
People with health problems
(e.g., injuries and recent surgery).
Intervention
A plyometric jump training program,
defined as lower and upper body
unilateral or bilateral bounds, jumps,
and hops that commonly utilize a
pre-stretch or countermovement
stressing the stretch-shortening
cycle.
Exercise interventions not involving
plyometric jump training or exercise
interventions involving plyometric jump
delivered in conjunction with other
training interventions (e.g., resistance
training).
Comparator
Control group or control situation.
No active control group or control
situation.
Outcome
Direct measure of physical fitness
(e.g., jump height), maximal
velocity speed, change of direction,
or muscle strength) before and after
the training intervention.
Lack of baseline or follow-up data.
Study design
A Systematic Reviews and meta-
analysis or only meta-analysis.
No meta-analysis.

(CI). Data were extracted and crosschecked for accuracy by Author name, Author name, Author name,
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Author name and Author name.
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2.4 Evaluation of the Methodological Quality
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Meta-analyses of randomized controlled trials and controlled studies are subject to different sources of
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bias. Therefore, it is important that readers have the option to distinguish between low- and high-
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quality meta-analyses. The methodological quality of the included meta-analyses was independently
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assessed by three reviewers (Author name, Author name, and Author name) using the validated
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AMSTAR2 (A Measurement Tool to Assess Systematic Reviews) checklist [28]. This checklist
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contains 16 items that include the literature search procedure, data extraction, quality assessment, and
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statistical analyses of the meta-analyses (for more details see Shea et al. [28]. Each item on this
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checklist was answered with a ‘yes’ (1 point), ‘partial yes’ (0.5 points) or ‘no’ (0 points). Based on the
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summary point scores (i.e., maximum 16 points), the meta-analyses were categorized as high quality
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if ≥ 80% of the possible score was achieved, moderate quality if 40–79% of the possible score was
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reached, or low quality if < 40% of the possible score was achieved [29].
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2.5 Data Interpretation
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The main objective of this umbrella review is summarize the findings, and access the quality of
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published meta-analyses investigating the effects of plyometric training on physical performance. The
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use of one effect size measure makes this comparison straightforward. However, it is important to
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acknowledge that even if most of the included meta-analyses used the standardized mean difference
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(SMDs) as an effect size measure, differences were found in the respective equations that were used
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to compute SMDs. For instance, some meta-analyses weighted single studies and/or conducted sample
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size adjustment (e.g., Hedges’ g). Therefore, we extracted the equations used to compute effect sizes
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for each included meta-analysis (Table 2). According to Cohen [30,31], the SMD values were
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classified as: < 0.20 as trivial, 0.20 ≤ SMD < 0.50 as small, 0.50 ≤ SMD < 0.80 as moderate, and SMD
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≥ 0.80 as large effects.
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Table 2. Included meta-analyses that examined the effects of plyometric training on physical fitness in
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different populations groups
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Study
Population/Sport
N
participan
ts
N
study
desig
n
Statistical
model
Physical fitness
outcome
Effect size (95%
CI, p value); I2 (p
value)
Alfaro-
Jimenez
et al. [39]
Team sports – young
and adults (e.g.,
basketball, handball,
volleyball, football
and netball)
N = 50
N =
31
Within
subject
SMD
Explosive Strength
0.98 (0.77–1.19, p
< 0.05); 72% (p =
n.a)
Asadi et
al. [37]
Youth athletes –
practitioners and non-
practitioners of sports
N = 46
N =
24
Within
subject
SMD
Change of direction
0.59 (-0.08 - 1.24,
n.a); n.a
Asadi et
al. [36]
Youth athletes –
practitioners and non-
practitioners of sports
N = 667
N=
16
Within
subject
SMD
Change of direction
0.96 (n.a, n.a); n.a
Behm et
al. [38]
Healthy trained or
untrained boys and
girls
N = 1351
N =
107
Within
subject
SMD
Vertical jump
height, sprint
performance and
Lower body
strength
Jump Measures
Total
0.69 (0.53–0.84, p
< 0.001); 51% (p <
0.001)
Trained Boys
0.67 (0.52–0.82, p
< 0.001); 39% (p <
0.05)
Untrained
0.80 (0.24–1.35, p
< 0.001); 80% (p =
0.005)
Children
0.74 (0.53–0.94, p
< 0.001); 62% (p <
0.001)
Adolescents
0.57 (0.37–0.77, p
< 0.01); 14% (p >
0.05)
Sprint
Performance
Total
0.38 (0.23–0.53, p
(p < 0.001); 12% (p
> 0.05)
Trained Boys
0.32 (0.18 – 0.46, p
< 0.001); 0% (p >
0.05)
Untrained

1.19 (− 0.32 - 2.69,
p < 0.001); 87% (p
<0.001)
Children
0.47 (0.28–0.67, p
< 0.001); 31% (p >
0.05)
Adolescents
0.13 (− 0.17 - 0.44,
p > 0.05); 0% (p >
0.05)
Lower body
strength
Adolescents
0.16 (-0.26–0.58,
p= 0.59); 0% (p >
0.05)
Berton et
al. [45]
Healthy individuals
trained or
untrained men
N = 158
N = 7
Within
subject
SMD
Vertical Jump
Height
0.15 (-0.30–0.60, p
= 0.51); 21% (p =
0.97)
de
Villarreal
et al. [41]
Healthy individuals -
with elite, good,
normal and bad levels
N= 122
N =
56
Within
subject
SMD
Vertical Jump
Height
Squat jump
0.79 (n.a, n.a); n.a
CMJ
0.74 (n.a, n.a); n.a
Drop jump
0.71 (n.a, n.a); n.a
Sargent jump
0.57 (n.a, n.a); n.a
de
Villarreal
et al. [42]
Healthy individuals -
with elite, good,
normal and bad levels
N = 24
N =
15
Within
subject
SMD
Strength
performance
0.97 (n.a, n.a); n.a
de
Villarreal
et al. [43]
Healthy individuals -
with elite, good,
normal and bad levels
N = 41
N =
26
Within
subject
SMD
Sprint
0.37 (n.a, n.a); n.a
Kayantas
et al. [48]
Athletes in general
sports (e.g.,
basketball and
football)
N = 1201
N = 6
Within
subject
SMD
Speed parameters
0.67 (0.38–0.96, p
< 0.001); 68% (p <
0.007)
Kayantas
et al. [40]
Athletes in general
sports (e.g., judo,
basketball, volleyball,
handball, football and
wrestling)
N = 362
N =
11
Within
subject
SMD
Muscle Strength
0.40 (0.19–0.61, p
< 0.001); 7% (p =
0.36)
Makaruk
et al. [46]
Healthy individuals -
age > 18 years
N = 602
N =
11
Within
subject
SMD
Vertical Jump
Height
Traditional
Plyometric
0.68 (0.37–0.99, p
< 0.001); 31% (p =
0.16)
Assisted Plyometric
0.70 (0.20–1.20, p
= 0.006); 0% (p =
0.94)
Resisted Plyometric
0.48 (0.17–1.19, p
= 0.002); 33% (p =
0.14)

Markovic
et al. [31]
Healthy individuals –
athletes and non-
athletes
N = 1024
N =
43
Experiment
al vs.
Control
SMD
Vertical jump
height
Squat jump
0.44 (0.15–0.72,
n.a); 33% (n.a)
CMJ
0.88 (0.64–1.11,
n.a); 11% (n.a)
CMJ with the arm
swing
0.71 (0.49–0.93,
n.a); 26% (n.a)
Drop jump
0.62 (0.18–1.05,
n.a); 20% (n.a)
Moran et
al. [32]
Older healthy
individuals’ adults
(>50)
N = 444
N = 9
Experiment
al vs.
Control
SMD
Lower limbs power
0.66 (0.33–0.98, p
= 0.02); 51% (p <
0.001)
Moran et
al. [33]
Healthy trained or
untrained girls
(8-18
years);
N = 452
N =
14
Experiment
al vs.
Control
SMD
Vertical jump
height
0.57 (0.21–0.93; p
< 0.01); 68%
(p < 0.001)
Moran et
al. [47]
Healthy individuals –
Untrained and trained
N = n.r
N = 9
Within
subject
SMD
Vertical and
Horizontal jump
performance
Horizontal
plyometric training
Horizontal Jump
1.05 (0.38 - 1.72,
n.a); 73% (p =
0.002)
Vertical Jump
0.74 (0.08 – 1.40,
n.a); 75% (p =
0.03)
Vertical plyometric
training
Horizontal Jump
0.84 (0.37 – 1.31,
n.a); 52% (p =
0.0005)
Vertical Jump
0.72 (0.02 – 1.43,
n.a); 78% (p =
0.04)
Ozdemir
et al. [50]
Athletes in general
sports (e.g.,
badminton,
basketball, football,
wrestling, handball
and volleyball
N = 40
N =
43
Within
subject
SMD
Vertical jump
performance
0.68 (0.57–0.80, p
< 0.001); 49% (p <
0.001)
Ramirez-
Campillo
[56]
Handball players
N = 129
N = 5
Within
subject
SMD
Vertical jump
height
2.15 (0.95–3.36, p
< 0.001); 51% (p <
0.001))
Ramirez-
Campillo
[53]
Volleyball players
N = 346
N =
14
Within
subject
SMD
Vertical jump
height
2.07 (1.22–2.93, p
< 0.001); 34.4% (p
= 0.087))
Ramirez-
Campillo
[52]
Team Sports (e.g.
soccer, volleyball,
basketball and futsal)
N = 278
N =
14
Within
subject
SMD
Vertical jump
height
0.73 (0.45–1.02, p
< 0.001); 18% (p =
0.22))

Ramirez-
Campillo
[57]
Female soccer
players
N = 99
N = 8
Within
subject
SMD
Vertical jump
height
1.01 (0.36–1.66, p
= 0.002); 13% (p =
0.33)
Ramirez-
Campillo
[55]
Basketball players
N = 818
N =
32
Within
subject
SMD
Vertical jump
power,
Countermovement
jump with arm
swing height,
Countermovement
jump height, Squat
jump height, drop
jump height,
Horizontal jump
distance, <10-m
linear sprint time,
>10-m linear sprint
time, <40-m
change-of-direction
performance time,
>40-m change-of-
direction
performance time,
Dynamic balance,
Static balance,
Maximal strength,
Hamstring/quadrice
ps strength ratio at
60°/s,
Hamstring/quadrice
ps strength ratio at
≥120°/s
Jumping
Vertical jump
power,
0.45 (0.07 - 0.84, p
= 0.021); 0% (p =
0.32)
Countermovement
jump with arm
swing height
1.24 (0.72 - 1.75,
<0.001); 71%
(p<0.001)
Countermovement
jump height
0.88 (0.55 - 1.22,
p<0.001) 67% (p =
0.071)
Squat jump height
0.80 (0.47 - 1.14,
p<0.001); 52%
(p=0.008)
Drop jump height
0.53 (0.25 - 0.80,
p<0.001); 0.0%
(p=0.567)
Horizontal jump
distance
0.65 (-0.02 - 1.31,
p< 0.001); 80% (p=
0.008)
Sprint
<10-m linear sprint
time
1.67 (0.32 - 3.03,
p=0.016); 85%
(p=0.307)
>10-m linear sprint
time
0.92 (0.40 - 1.44,
p<0.001); 74%
(p=0.061)
<40-m change-of-
direction
performance time
1.15 (0.75 - 1.55,
p<0.001); 59%
(p=0.189)
>40-m change-of-
direction
performance time
1.02 (0.29 - 1.76,
p=0.006); 64%
(p=0.272)
Balance
Dynamic balance

1.16 (0.43 - 1.89,
p=0.002); 76%
(p=0.586)
Static balance
1.48 (-0.19 - 3.15,
p=0.002); 93%
(p=0.252)
Strength variables
Maximal strength
0.57 (0.07 - 1.07,
p=0.025); 38%
(p=0.117)
Hamstring/quadrice
ps strength ratio at
60°/s
-0.10 (-0.56 -0.36,
p=0.661); 23%
(p=0.060)
Hamstring/quadrice
ps strength ratio at
≥120°/s
-0.04 (-0.56 to 0.48,
p=0.885); 39%
(p=0.785)
Ramirez-
Campillo
[54]
Volleyball players
N = 746
N =
18
Within
subject
SMD
Linear sprint speed,
squat jump height,
countermovement
jump height, CMJ
with arm swing,
drop jump and
spike jump height
Linear sprint speed
0.70 (0.31 - 1.09, p
< 0.001); 46%
p=0.609
Squat jump
0.56 (0.24–0.88, p
= 0.001); 0%
p=0.409
Countermovement
jump
0.80 (0.37–1.22, p
< 0.001); 66% p =
0.270
Countermovement
jump
with arm swing,
0.63 (0.21–1.04, p
= 0.003); 0% p =
0.002
Drop jump
0.81 (0.15 – 1.47, p
= 0.016); 37%
p=0.496
Spike jump height
0.84 (0.36–1.32, p
= 0.001); 0% (p <
0.05)
Sánchez
et al.
[58]
Female soccer
players
N = 250
N =
10
Within
subject
SMD
countermovement
jump, drop jump,
kicking
performance, linear
sprint, change of
direction speed, and
endurance
Countermovement
jump
0.71 (0.20–1.23, p
= 0.007); 62% (p=
0.224)
Countermovement
jump with Arm
Swing

0.41 (-0.34–1.15, p
= 0.28); 65% (p=
0.452)
Drop jump
0.79 (0.12–1.47, p
= 0.021); 73% (p =
0.063)
Kicking
performance
2.24 (0.13–4.36, p
< 0.037); 89%
(p=0.040)
Linear sprint
0.79 (0.39–1.18, p
< 0.001); 38% (p =
0.257)
Change of direction
speed
0.73 (0.39–1.06, p
< 0.001); 0% (p =
0.813)
Endurance
0.60 (0.09–1.10, p
= 0.020); 53% (p
=0.328)
Singla et
al. [48]
Healthy individuals -
practitioners and non-
practitioners of sports
N = 287
N =
11
Within
subject
SMD
Ball throwing
velocity and
distance. Upper
body power and
strength.
Velocity
0.68 (0.01–1.36, p
< n.a); 7% (p =
0.07)
Distance
0.42 (-0.07–0.92, p
< n.a); 3% (p =
0.17)
Power
-0.08 (-0.45–0.29, p
< n.a); 1% (p
=0.45)
Strength
0.15 (-0.52–0.82, p
< n.a); 4% (p =
0.14)
Slimani
et al. [34]
Soccer players
N = 355
N =
10
Experiment
al vs.
Control
SMD
Vertical jump
height
0.85 (0.47–1.23, p
< 0.001); 68% (p <
0.001)
Sole et
al. [51]
Individual sport athlet
es (e.g., runners,
gymnastics, golfers,
tennis, swimmers,
throwers, fencers,
cyclists and
recreational
resistance training)
N = 667
N =
26
Within
subject
SMD
Vertical jump,
linear sprint,
maximal strength,
endurance
performance
Vertical jump
0.49 (0.32–0.65, p
< 0.001); 0% (p <
0.117)
Linear sprint
0.23 (0.02–0.44, p
= 0.032); 10% (p =
0.518)
Maximal strength
0.50 (0.23–0.77, p
< 0.001); 0% (p =
0.004)
Sprint with change
of direction

0.34 (-0.19–0.87, p
= 0.205); 70% (p =
0.657)
Endurance
performance
0.30 (0.03–0.57, p
= 0.028); 11% (p =
0.119)
Stojanovi
c et al.
[59]
Female general
athletes (e.g.,
basketball, amateur
soccer, elite runners,
collegiate soccer
players, hockey and
volleyball players
N = 437
N =
16
Within
subject
SMD
Countermovement
Jump Without Arm
Swing,
Countermovement
Jump with Arm
Swing, Squat Jump,
Drop Jump
Countermovement
Jump Without Arm
Swing
1.87 (0.73–3.01,
n.a); 75% (n.a)
Countermovement
Jump with Arm
Swing
1.31 (-0.04–2.65,
n.a); 92% (n.a)
Squat Jump
0.44 (-0.09–0.97,
n.a); 0% (n.a)
Drop Jump
3.62 (3.03–4.21,
n.a); 96% (n.a)
Taylor et
al. [44]
Healthy individuals
trained sports
practitioners
N = 188
N =
31
Within
subject
SMD
Vertical jump,
Sprint (10, 20,
30m) ability and
high-intensity
intermittent running
performance
Vertical jump
0.33 (0.03 - 0.63),
n.a); 33% (n.a)
Sprint 10m
0.42 (0.18 - 0.66,
n.a); 0% (n.a)
Sprint 20m
0.49 (0.03 – 0.95
0.46, n.a); 61%
(n.a)
Sprint 30m
1.01 (0.08 – 1.94±
0.93, n.a); 47%
(n.a)
Repeated sprint
ability
0.62 (0.37 - 0.87,
n.a); 0% (n.a)
High intermittent
running
performance
0.61 (0.07 – 1.15;
0.54, n.a); 56%
(n.a)
van de
Hoef et
al. [35]
Male Soccer Players
N = 564
N =
17
Experiment
al vs.
Control
SMD.
Vertical jump,
Sprint (5, 10, 15,
20, 30m) CMJ
vertical jump height
performance,
strength, agility and
Yo-Yo Intermittent
Recovery Test 1 &
2
Vertical jump (cm)
1.07 (0.13–2.00,
n.a); 0% (p = 0.46)
Sprint 5m (s)
0.00 (-0.02– 0.02,
n.a); 0% (p = 0.98)
Sprint 10m (s)
0.01 (-0.01–0.04,
n.a); 27% (p =
0.23)
Sprint 15m (s)

0.04 (-0.03–0.12,
n.a); 46% (p =
0.17) Sprint 20m
(s)
0.05 (-0.01–0.10,
n.a); 0% (p = 0.48)
Sprint 30m (s)
0.05 (-0.02–0.11,
n.a); 0% (p = 0.53)
Strength (kg)
8.49 (-10.64–27.61,
n.a); 97% (p <
0.001)
Agility (s)
0.01 (-0.07–0.10,
n.a); 34% (p =
0.18)
Yo-Yo Intermittent
Recovery Test 1
and 2 (cm)
120.74 (3.00–
238.49, n.a); 42%
(p = 0.16)
n.a = not assessed; n.r = not reported; SMD= Standardized Mean Difference
167
***Table 2 here***
168
169
3. Results
170
3.1 Search Results
171
A total of 612 potentially relevant studies were identified in the electronic databases (Figure 1). Finally,
172
29 meta-analyses were eligible for inclusion in this umbrella review based on a priori defined selection
173
criteria. We further separated the included meta-analyses into those that reported between subject
174
effect sizes (i.e., post-test comparison of the intervention versus control group, n = 5) and those that
175
reported within-subject effect sizes (i.e., pre- versus post-test comparison of the intervention group, n
176
= 24) (Table 2).
177
178
179
180
181
182
183
184
185
186
187
Records identified from*:
Databases (n = 612)
Registers (n = 4)
Records removed before
screening:
Duplicate records removed (n
= 190)
Records marked as ineligible
by automation tools (n = 0)
Records removed for other
reasons (n = 6)
Identification of studies via databases and registers
Identification

188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
Figure 1. PRISMA 2020 flow diagram for new systematic reviews which included searches of
214
databases and registers only
215
216
217
3.2 Characteristics of the Meta
‑
Analyses
218
The 29 included meta-analyses were published from 2007 to 2022 (Table 2). Five meta-analyses
219
compared the effects of intervention to control group [31-35], while the other compared within-
220
intervention-group effects (i.e., pre vs post effect sizes). The number of included original studies
221
ranged from six to 107 with an average of 22 original studies. Sample sizes included 24 to 2471 athletes
222
of specific sports (e.g., volleyball, soccer, handball and basketball), groups of sports (e.g., team sports
223
and individual sports), healthy people, and individuals from different age groups (i.e., young, young
224
adults and older adults) (on average 459 participants). The chronological age of the included
225
participants ranged from 15 to 71 years. Five meta-analyses included adolescents [36-40], ten meta-
226
analyses involved healthy people [31, 32, 41-48,], three meta-analyses focused on athletes participating
227
Records screened
(n = 416)
Records excluded**
(n = 330)
Reports sought for retrieval
(n = 10)
Reports not retrieved
(n = 0)
Reports assessed for eligibility
(n = 76)
Full-text articles excluded (n= 47)
Reports excluded:
Only systematic reviews related to the plyometric training (n = 17)
Reviews related to combined training (n = 10)
Reviews related to post-activation potentiation (n = 2)
Reviews related to lower limb injury prevention (n = 6)
Reviews related to the influence of stretching on the lower limbs
(n = 2)
Reviews involving complex training (n = 10)
Studies included in review
(n = 29)
Reports of included studies
(n = 0)
Screening
Included

in general sports [40,49,50], one meta-analysis involved older adults (> 50 years) [32], one meta-
228
analyses included female athletes participating in general sports [40] and one meta-analyses focused
229
on individual sports athletes (e.g., runners, gymnasts, golfers, swimmers, tennis players, javelin,
230
fencers and cyclists) [51]. When considering the sports modality, two meta-analyses included general
231
team sports [39,52] and one meta-analysis individual sports [51]. Within the team sports, two meta-
232
analyses analyzed female soccer players [34,59], two meta-analyses volleyball players [53,54], two
233
meta-analyses male soccer players, [34,35] one meta-analysis basketball players [55], and one meta-
234
analysis handball players [56] considering both sexes.
235
236
3.3 Assessment of the Methodological Quality
237
The assessment of the methodological quality (AMSTAR2) of the included meta-analyses is
238
summarized in Electronic Supplementary Material (supplementary material 1). The included articles
239
received scores ranging from 12 to 84% of the maximum score (16 points). Twenty-two meta-analyses
240
(75.9% of total articles included) [31-34,37,38,41-44,46-48,51-59] were considered of moderate
241
quality, six were low quality (20.7% of total articles included) [36,39,40,45,49,50] and one scored high
242
(3.4% of total articles included) [35]. The following criteria were not sufficiently addressed in the
243
included meta-analyses: (n=2) establish methods prior to the conduct the meta-analysis (written
244
protocol); (n=3) explain the choice of study design for inclusion; (n=7) provide a list of excluded
245
studies to justify the exclusion; and (n=10) report sources of funding for included studies.
246
247
3.4 Effect of Plyometric training on sprint or speed performance
248
Nine meta-analyses identified positive effects and one meta-analysis reported no effect of plyometric
249
training on sprint or speed performance. Figure 2 summarizes the effects in terms of standardized mean
250
difference between baseline and post training values. In a general population of healthy individuals,
251
there was small effect for 10-m and 20-m sprint performance, and large effect for 30-m sprint
252

performance [44], and a small effect for general sprint performance [43] (Figure 2). For young (<18
253
years old) participants, there was a small effect when analyzing the total effect from trained and
254
untrained participants [38]. When analyzing meta-analyses that including only athletes, there was a
255
small effect observed for individual sport [51], but a moderate effect for athletes in general sports [49].
256
A moderate effect was observed for female soccer players [58], handball players [56], and volleyball
257
players [53], while a large effect size was observed for basketball players (for sprints > or < than 10
258
m) [55]. There was an unclear effect in 5, 10, 15, 20, and 30-m sprint performance in male soccer
259
players [35].
260
261
262
Figure 2. Summary of standardized mean difference and 95% confidence intervals reported in
263
meta-analyses comparing the baseline to post plyometric training changes on sprint or speed
264
performance. Author name and year are followed by the quality of the studies score ranked with the
265
AMSTAR 2. Positive values represent improved performance effects. Each colored area represents a
266
different magnitude of effect: gray = trivial, blue = small, yellow = moderate, and green = large effects.
267
De Villareal et al. [43] 95% confidence interval is not clearly described in their manuscript, therefore
268
we reported standardized mean difference only. Taylor et al. [44] reported results from 30-, 20-, and
269

10-m sprints, presented in the respective order. Ramirez-Campillo et al. [55] reported results from >10-
270
and <10-m sprints, presented in the respective order.
271
272
3.5 Effect of Plyometric training on change of direction
273
Figure 3 summarizes the effects observed in change of direction in the four studies reporting
274
standardized mean difference comparing baseline and post training values. Two meta-analyses
275
reported improvements and two found unclear differences on change of direction performance after
276
plyometric training. A large effect was observed in basketball players (for running distances shorter or
277
longer than 40 m) [55] and moderate effect for female soccer players [58]. Unclear effect was observed
278
for individual sport athletes [51] and young athletes [37]. For instance, a study reported no effect of
279
plyometric training on agility in male soccer players after comparing groups’ mean differences [35].
280
281
282
Figure 3. Summary of standardized mean difference and 95% confidence intervals reported in
283
meta-analyses comparing the baseline to post plyometric training changes on change of direction
284
performance. Author name and year are followed by the quality of the studies score ranked with the
285
AMSTAR 2. Positive values represent improved performance effects and negative values detrimental
286
effects. Each colored area represents a different magnitude of effect: gray, trivial; blue, small; yellow,
287
moderate; and green, large effects. Ramirez-Campillo et al. [55] reported results from >40- and <40-
288
m testing distances, presented in the respective order.
289
290
3.6 Effect of Plyometric training on maximal strength
291

Figure 4 summarizes the effects of plyometric training on maximal strength performance. Seven
292
studies reported standardized mean difference comparing baseline and post training values. Four meta-
293
analyses reported positive effects and three reported unclear differences on strength performance after
294
plyometric training. A large effect was observed for healthy individuals [42], a moderate effect for
295
basketball players [55] and individual sport athletes [51], and a small effect for athletes from general
296
sports [40]. An unclear effect was observed for healthy individuals [48] and adolescents [38]. Also,
297
one study reported unclear effect in soccer players [35]. Only one study showed that an unclear effect
298
was also observed for hamstring/quadriceps strength ratios at 60 and ≥120°/s in basketball players
299
[55].
300
301
302
Figure 4. Summary of standardized mean difference and 95% confidence intervals reported in
303
meta-analyses comparing the baseline to post plyometric training changes on maximal strength
304
performance. Author name and year are followed by the quality of the studies score ranked with the
305
AMSTAR 2. Positive values represent improved performance effects and negative values detrimental
306
effects. Each colored area represents a different magnitude of effect: gray = trivial, blue = small, yellow
307
= moderate, and green = large effects; while red area represents detrimental effects. De Villareal et al.
308
[43] did not clearly describe the 95% confidence interval, thus we only reported standardized mean
309
difference.
310
311

3.7 Effect of Plyometric training on muscle power and explosive strength
312
There was a large effect observed for explosive strength in team sport athletes [39]. For muscular
313
power, there was a moderate effect for older adults [32], a small effect for basketball players [55], and
314
an unclear effect for healthy individuals [48]. Figure 5 summarizes the effects observed on power and
315
explosive strength performance in the four studies reporting standardized mean difference comparing
316
baseline and post training values.
317
318
319
Figure 5. Summary of standardized mean difference and 95% confidence intervals reported in
320
meta-analyses comparing the baseline to post plyometric training changes on power or explosive
321
strength performance. Author name and year are followed by the quality of the studies score ranked
322
with the AMSTAR 2. Positive values represent improved performance effects and negative values
323
detrimental effects. Each colored area represents a different magnitude of effect: gray = trivial, blue =
324
small, yellow = moderate, and green = large effects; while red area represents detrimental effects.
325
Alfaro-Jimenez et al. [39] investigated the effects on explosive strength and the other authors on
326
muscular power.
327
328
3.8 Effect of plyometric training on vertical and horizontal jump performance
329
Several studies investigated the effects of plyometric training on squat jump, countermovement jump
330
(with arm swing or hands on the hip), drop jump, Sargent jump, and/or spike jump performance (i.e.,
331
jump height). In summary, for healthy people an unclear to large effect was observed [31,41,44,45].
332
Athletes from team sports, such as soccer [34,35,57,58], volleyball [53,54], basketball [55], handball
333

[56], or when grouped as team sports [52], presented mostly moderate to large effects. Trained and
334
untrained young individuals presented moderate effect sizes [35,38].
335
Two studies investigated the effects on horizontal jump performance. One study reported a
336
large effect on horizontal jump performance after either horizontal (SMD = 1.05) or vertical plyometric
337
training (SMD = 0.84) [47]. Another study reported unclear effects of plyometric training on horizontal
338
jump distance in basketball players [55]. Detailed SMDs for each study are reported in Table 2 and
339
Figure 6 summarizes the 18 studies reporting standardized mean difference comparing baseline and
340
post training values.
341
342
Figure 6. Summary of standardized mean difference and 95% confidence intervals reported in
343
meta-analyses comparing the baseline to post plyometric training changes on jump performance.
344

Author name and year are followed by the quality of the studies score ranked with the AMSTAR 2.
345
Positive values represent improved performance effects and negative values detrimental effects. Each
346
colored area represents a different magnitude of effect: gray = trivial, blue = small, yellow = moderate,
347
and green = large effects; while red area represents detrimental effects.
348
349
3.9 Effect of Plyometric training on additional outcomes
350
Plyometric training resulted in a small effect on endurance performance for individual sport athletes
351
[51]), and moderate effect for endurance in female soccer players [58] and for high intermittent running
352
performance in healthy peoples [44]. A large effect was observed on kicking performance in female
353
soccer players [58]. There was also a large effect on dynamic balance, but an unclear effect on static
354
balance in basketball players [55]. Plyometric training is effective to improve the yo-yo intermittent
355
recovery test when comparing baseline and post training mean differences [35]. Table 2 presents
356
detailed SMD for each of these studies and variables.
357
358
4. Discussion
359
This umbrella review aimed to systematically review the meta-analytical evidence about the effects of
360
plyometric training on physical performance considering different groups, to address the quality,
361
strengths and limitations of the evidence, and to identify current gaps in the literature, which helps in
362
providing suggestions for future research. The most concerning finding from our study is the lack of
363
control group comparisons and the low-to-moderate quality for most of the meta-analyses available in
364
literature. Therefore, we highlight that the outcomes from these meta-analyses should not be
365
interpreted as level 1 evidence. After summarizing the findings from the available meta-analyses, we
366
observed that plyometric training induces trivial to large effects on different physical performance
367
(e.g., jump height, sprint performance and muscle strength) for healthy people; enhances performance
368
of athletes from different sports in several motor tasks (e.g., vertical jump height, change of direction,
369
kicking performance and linear sprint); and induces moderate effects on physical fitness (e.g., power
370

output in lower limbs, change of direction and vertical jump height) of older adults (>60 years) and
371
young individuals (<18 years).
372
373
4.1 Quality of the Included Meta
‑
analyses
374
The methodological quality of the included meta-analyses varied from low to high. However, the
375
majority of the studies (~75%) presented moderate quality. For the assessment of the methodological
376
quality, Shea et al. [28] recommend that individual AMSTAR2 item ratings should not be combined
377
to create an overall score. Users should consider the potential impact of an inadequate rating for each
378
item independently. Unfortunately, although it is important to record the meta-analysis protocols in a
379
specific platform, only the study of van de Hoef et al.[35], registered their protocol on the specific
380
platform (PROSPERO). Overall, evidence shows a low-quality bias of umbrella reviews [60,61]. The
381
reasons are probably related to the type of review, which is recently adopted in movement science
382
literature, as well as word/table/figure restrictions and/or the absence of databases for supplementary
383
materials.
384
A very important limitation observed in most of the meta-analyses included in our umbrella
385
review (24 out of 29) was the absence of control groups, and thus, these meta-analyses only included
386
within-group pre to post effect sizes. A control group allows the interpretation of the research outcomes
387
removing the influence of possible factors (e.g. direct effect in the specific group). This is crucial when
388
investigating sports performance enhancement because (recreational) athletes follow a training plan
389
during a season, which also influences sports performance. Therefore, the majority of findings
390
presented in this umbrella review should be interpreted with caution. Only five systematic reviews
391
with meta-analysis [31-35] considered the analysis between control versus experimental group. We
392
strongly recommend that future studies investigating the effects of plyometric training on physical
393
performance adopt randomized controlled trial designs.
394
395

4.2 Effect of Plyometric training on physical performance in healthy people
396
Most studies indicate an improvement of vertical jump height, muscle strength and to a lesser extent
397
speed performance in healthy people after plyometric training. Considering this population,
398
experimental protocols using plyometric exercises may be a good strategy to optimize health related
399
aspects [62,63]. Muscle strength and lower limb muscle power are important capacities for healthy
400
people during daily activities (e.g. walking and climbing stairs), especially when using mechanisms
401
related to the SSC [64].
402
The vertical jump height was the variable most positively affected by plyometric training
403
according to the included meta-analyses. This variable may be considered as an indicator of muscle
404
power of lower limbs [31,65,66] and it is commonly used to verify the effects of plyometric training
405
on physical performance [21,31,41-43,45]. These results are not surprising due to the great specificity,
406
since the same skill (i.e., vertical jump) is used in the testing method and applied in the plyometric
407
training. For the sprint performance, a small effect was found for 10-m and 20-m sprint, a large effect
408
for 30-m sprint and a small effect for sprint performance. For muscle strength, a large effect was
409
observed for healthy individuals, a moderate effect for basketball players and individual sport athletes,
410
a small effect for athletes involved in common sports activities, and an unclear effect for healthy
411
individuals. These results demonstrate a transfer from plyometric training to other physical tasks
412
involving lower limbs [41-43], probably due to neural and muscular adaptations [67].
413
Upper limb muscle power also demonstrated trivial to medium effects of plyometric training.
414
A previous experimental study indicates that plyometric push-ups results in better outcomes compared
415
to non-plyometric push-ups (i.e., dynamic push-ups) [68]. Therefore, neuromuscular adaptations in the
416
upper limbs from plyometric training can be verified especially in movements involving plyometric
417
push-ups (e.g. medicine ball throw).
418
419
4.3 Effect of Plyometric training on physical performance of athletes in different sports
420

When focusing on different sports, plyometric training induces a large effect on vertical jump height,
421
power output and explosive strength (i.e. rate of force development), while a small effect was observed
422
for agility. Most meta-analyses including athletes analyzed the effects of plyometric training on
423
physical performance, since maximizing aspects related to sports performance beneficially impacts the
424
training process and competitions [69].
425
The effects of plyometric training for individual sports demonstrated a medium effect for
426
different variables (e.g., vertical jump height, strength, sprint and change of direction performances)
427
[51]. When considering team sports, the effects of plyometric training were moderate to large, showing
428
the greater relevance in enhancing performance in this target population. Particularly, for female soccer
429
athletes a high effect was found on vertical jump task [57]. Plyometric training is a practice of physical
430
training widely spread in the sports context, performed by athletes of different modalities. In this
431
review larger effect sizes were observed for team sports compared to the other sports groups. Probably
432
athletes from sports such as volleyball, basketball, handball, among others, allow greater adaptation to
433
plyometric training due to the greater specificity of the jumping motor task that is present in training
434
and during the matches.
435
436
4.4 Effect of Plyometric training on physical performance in different age groups
437
This umbrella review indicates that plyometric interventions can enhance physical fitness in children
438
and adolescents beyond a level which is not exclusively achievable from growth and maturation. In
439
addition, improvements also occurred in middle-aged adults who did not practice sports. Positive
440
effects of plyometric training were found in untrained children and adolescents, especially in vertical
441
jump height, sprint performance and muscle strength [38]. Recently, Lesinski et al. [60] observed
442
small-to-medium effects of plyometric training on muscle power of lower limbs in children and
443
adolescent athletes. Other studies also support that plyometric training is an effective training method
444
to improve exercise performance in non-athlete young people [70]. However, moderating factors, such
445

as maturity, sex and age in the youth group appear to modulate the effects following plyometric training
446
[60,61]. Thus, future studies should consider these aspects.
447
In older people, plyometric training improved indicators of muscle power of lower limbs,
448
however, it is supported by only one systematic review with meta-analysis [33]. The aging process is
449
associated with a progressive decline of neuromuscular function, increased risk of falls and injuries
450
related to the impaired functional performance [71,72]. From this perspective, Vetrovsky et al. [74]
451
verified that plyometric training positively affected muscular strength, vertical jump performance, and
452
functional performance (e.g., 30-s sit-to-stand test, figure-of-8 running test, timed up-and-go test, 6-m
453
walk, stair climb) in older adults. Therefore, plyometric training can be considered as a feasible and
454
safe alternative to improve physical fitness in older adults. Future investigations should further explore
455
moderating variables (e.g., age, level of conditioning and body composition).
456
457
4.6 Strengths and Methodological Limitations
458
This umbrella review presented findings on the highest level of the evidence regarding the effects of
459
plyometric training on several physical performance variables in different populations (athletes and
460
non-athletes, male and female) and different age ranges (young and older adult). The majority of the
461
included studies (75%) presented moderate methodological quality when AMASTAR2 was
462
considered. Finally, this study identified some gaps in the literature to provide guidelines for future
463
research. As limitation, despite the inclusion of a reasonable number of studies (n=29), few represented
464
females and older individuals. Ultimately, the most important limitation observed in our study was the
465
high prevalence of meta-analysis with the absence of control group comparisons. This is likely a
466
consequence of low-quality original studies and this should be addressed in future investigations.
467
468
5. Conclusion
469

There is empirical support that plyometric training benefits, however, bear in mind that most meta-
470
analyses do not include a control condition. This systematic umbrella review unveiled an important
471
weakness of the present research topic. Although several meta-analyses investigated the effects of
472
plyometric training on physical performance outcomes, most of them lack comparisons with control
473
groups and are classified as low-to-moderate quality. It is advised that the outcomes from this umbrella
474
review must not be considered as level 1 evidence. Future research should opt for randomized
475
controlled trials, which will eventually lead to higher-quality meta-analyses. The current evidence,
476
presented by this umbrella review, suggesting that plyometric training may improve a large number of
477
physical fitness-related variables for healthy people and performance for athletes from different sports,
478
and its effects are verified in different age groups and sex, should be taken with caution.
479
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480
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481
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