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Previous studies contrasted the effects of plyometric training (PT) conducted on stable vs. unstable surfaces on components of physical fitness in child and adolescent soccer players. Depending on the training modality (stable vs. unstable), specific performance improvements were found for jump (stable PT) and balance performances (unstable PT). In an attempt to combine the effects of both training modalities, this study examined the effects of PT on stable surfaces compared with combined PT on stable and unstable surfaces on components of physical fitness in prepuberal male soccer athletes. Thirty-three boys were randomly assigned to either a PT on stable surfaces (PTS; n = 17; age = 12.1 +/- 0.5 years; height = 151.6 +/- 5.7 cm; body mass = 39.2 +/- 6.5 kg; and maturity offset = 22.3 +/- 0.5 years) or a combined PT on stable and unstable surfaces (PTC; n = 16; age = 12.2 +/- 0.6 years; height = 154.6 +/- 8.1 cm; body mass = 38.7 +/- 5.0 kg; and maturity offset = 22.2 +/- 0.6 years). Both intervention groups conducted 4 soccer-specific training sessions per week combined with either 2 PTS or PTC sessions. Before and after 8 weeks of training, proxies of muscle power (e.g., countermovement jump [CMJ], standing long jump [SLJ]), muscle strength (e.g., reactive strength index [RSI]), speed (e.g., 20-m sprint test), agility (e.g., modified Illinois change of direction test [MICODT]), static balance (e.g., stable stork bal-ance test [SSBT]), and dynamic balance (unstable stork balance test [USBT]) were tested. An analysis of covariance model was used to test between-group differences (PTS vs. PTC) at posttest using baseline outcomes as covariates. No significant between-group differences at posttest were observed for CMJ (p > 0.05, d = 0.41), SLJ (p > 0.05, d = 0.36), RSI (p > 0.05, d = 0.57), 20-m sprint test (p > 0.05, d = 0.06), MICODT (p > 0.05, d = 0.23), and SSBT (p > 0.05, d = 0.20). However, statistically significant between-group differences at posttest were noted for the USBT (p < 0.01, d = 1.49) in favor of the PTC group. For most physical fitness tests (except RSI), significant pre-to-post improvements were observed for both groups (p < 0.01, d = 0.55-3.96). Eight weeks of PTS or PTC resulted in similar performance improvements in components of physical fitness except for dynamic balance. From a performance-enhancing perspective, PTC is recommended for pediatric strength and conditioning coaches because it produced comparable training effects as PTS on proxies of muscle power, muscle strength, speed, agility, static balance, and additional effects on dynamic balance.
This study aimed to determine the specific physical and basic gymnastics skills considered critical in gymnastics talent identification and selection as well as in promoting men’s artistic gymnastics performances. Fifty-one boys from a provincial gymnastics team (age 11.03 ± 0.95 years; height 1.33 ± 0.05 m; body mass 30.01 ± 5.53 kg; body mass index [BMI] 16.89 ± 3.93 kg/m²) regularly competing at national level voluntarily participated in this study. Anthropometric measures as well as the men’s artistic gymnastics physical test battery (i.e., International Gymnastics Federation [FIG] age group development programme) were used to assess the somatic and physical fitness profile of participants, respectively. The physical characteristics assessed were: muscle strength, flexibility, speed, endurance, and muscle power. Test outcomes were subjected to a principal components analysis to identify the most representative factors. The main findings revealed that power speed, isometric and explosive strength, strength endurance, and dynamic and static flexibility are the most determinant physical fitness aspects of the talent selection process in young male artistic gymnasts. These findings are of utmost importance for talent identification, selection, and development.
This study aimed to determine the specific physical and basic gymnastics skills considered critical in gymnastics talent identification and selection as well as in promoting men's artistic gymnastics performances. Fifty-one boys from a provincial gymnastics team (age 11.03 ± 0.95 years; height 1.33 ± 0.05 m; body mass 30.01 ± 5.53 kg; body mass index [BMI] 16.89 ± 3.93 kg/m²) regularly competing at national level voluntarily participated in this study. Anthropometric measures as well as the men's artistic gymnastics physical test battery (i.e., International Gymnastics Federation [FIG] age group development programme) were used to assess the somatic and physical fitness profile of participants, respectively. The physical characteristics assessed were: muscle strength, flexibility, speed, endurance, and muscle power. Test outcomes were subjected to a principal components analysis to identify the most representative factors. The main findings revealed that power speed, isometric and explosive strength, strength endurance, and dynamic and static flexibility are the most determinant physical fitness aspects of the talent selection process in young male artistic gymnasts. These findings are of utmost importance for talent identification, selection, and development.
Objective: To examine the effect of plyometric jump training on skeletal muscle hypertrophy in healthy individuals.
Methods: A systematic literature search was conducted in the databases PubMed, SPORTDiscus, Web of Science, and Cochrane Library up to September 2021.
Results: Fifteen studies met the inclusion criteria. The main overall finding (44 effect sizes across 15 clusters median = 2, range = 1–15 effects per cluster) indicated that plyometric jump training had small to moderate effects [standardised mean difference (SMD) = 0.47 (95% CIs = 0.23–0.71); p < 0.001] on skeletal muscle hypertrophy. Subgroup analyses for training experience revealed trivial to large effects in non-athletes [SMD = 0.55 (95% CIs = 0.18–0.93); p = 0.007] and trivial to moderate effects in athletes [SMD = 0.33 (95% CIs = 0.16–0.51); p = 0.001]. Regarding muscle groups, results showed moderate effects for the knee extensors [SMD = 0.72 (95% CIs = 0.66–0.78), p < 0.001] and equivocal effects for the plantar flexors [SMD = 0.65 (95% CIs = −0.25–1.55); p = 0.143]. As to the assessment methods of skeletal muscle hypertrophy, findings indicated trivial to small effects for prediction equations [SMD = 0.29 (95% CIs = 0.16–0.42); p < 0.001] and moderate-to-large effects for ultrasound imaging [SMD = 0.74 (95% CIs = 0.59–0.89); p < 0.001]. Meta-regression analysis indicated that the weekly session frequency moderates the effect of plyometric jump training on skeletal muscle hypertrophy, with a higher weekly session frequency inducing larger hypertrophic gains [β = 0.3233 (95% CIs = 0.2041–0.4425); p < 0.001]. We found no clear evidence that age, sex, total training period, single session duration, or the number of jumps per week moderate the effect of plyometric jump training on skeletal muscle hypertrophy [β = −0.0133 to 0.0433 (95% CIs = −0.0387 to 0.1215); p = 0.101–0.751].
Conclusion: Plyometric jump training can induce skeletal muscle hypertrophy, regardless of age and sex. There is evidence for relatively larger effects in non-athletes compared with athletes. Further, the weekly session frequency seems to moderate the effect of plyometric jump training on skeletal muscle hypertrophy, whereby more frequent weekly plyometric jump training sessions elicit larger hypertrophic adaptations.
Objective: To examine the effect of plyometric jump training on skeletal muscle hypertrophy in healthy individuals.
Methods: A systematic literature search was conducted in the databases PubMed, SPORTDiscus, Web of Science, and Cochrane Library up to September 2021.
Results: Fifteen studies met the inclusion criteria. The main overall finding (44 effect sizes across 15 clusters median = 2, range = 1–15 effects per cluster) indicated that plyometric jump training had small to moderate effects [standardised mean difference (SMD) = 0.47 (95% CIs = 0.23–0.71); p < 0.001] on skeletal muscle hypertrophy. Subgroup analyses for training experience revealed trivial to large effects in non-athletes [SMD = 0.55 (95% CIs = 0.18–0.93); p = 0.007] and trivial to moderate effects in athletes [SMD = 0.33 (95% CIs = 0.16–0.51); p = 0.001]. Regarding muscle groups, results showed moderate effects for the knee extensors [SMD = 0.72 (95% CIs = 0.66–0.78), p < 0.001] and equivocal effects for the plantar flexors [SMD = 0.65 (95% CIs = −0.25–1.55); p = 0.143]. As to the assessment methods of skeletal muscle hypertrophy, findings indicated trivial to small effects for prediction equations [SMD = 0.29 (95% CIs = 0.16–0.42); p < 0.001] and moderate-to-large effects for ultrasound imaging [SMD = 0.74 (95% CIs = 0.59–0.89); p < 0.001]. Meta-regression analysis indicated that the weekly session frequency moderates the effect of plyometric jump training on skeletal muscle hypertrophy, with a higher weekly session frequency inducing larger hypertrophic gains [β = 0.3233 (95% CIs = 0.2041–0.4425); p < 0.001]. We found no clear evidence that age, sex, total training period, single session duration, or the number of jumps per week moderate the effect of plyometric jump training on skeletal muscle hypertrophy [β = −0.0133 to 0.0433 (95% CIs = −0.0387 to 0.1215); p = 0.101–0.751].
Conclusion: Plyometric jump training can induce skeletal muscle hypertrophy, regardless of age and sex. There is evidence for relatively larger effects in non-athletes compared with athletes. Further, the weekly session frequency seems to moderate the effect of plyometric jump training on skeletal muscle hypertrophy, whereby more frequent weekly plyometric jump training sessions elicit larger hypertrophic adaptations.