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This study examined the effect of 6 weeks of progressed and nonprogressed volume-based overload plyometric training (PT) on components of physical fitness and body composition measures in young male basketball players, compared with an active control group. Subjects were randomly assigned to a progressed PT (PPT, n = 7; age = 14.6 +/- 1.1 years), a non-PPT (NPPT, n = 8, age = 13.8 +/- 2.0 years), or a control group (CG, n = 7, age = 14.0 +/- 2.0 years). Before and after training, body composition measures (muscle mass and fat mass), countermovement jump with arms (CMJA) and countermovement jump without arms (CMJ), horizontal bilateral (HCMJ) and unilateral jump with right leg (RJ) and left leg (LJ), 20-cm drop jump (DJ20), sprint speed (10 m sprint), and change of direction speed (CODS [i.e., T-test]) were tested. Significant effects of time were observed for muscle and fat mass, all jump measures, and CODS (all p < 0.01; d = 0.37-0.83). Significant training group x time interactions were observed for all jump measures (all p < 0.05; d = 0.24-0.41). Post hoc analyses revealed significant pre-post performance improvements for the PPT (RJ and LJ: increment 18.6%, d = 0.8 and increment 22.7%, d = 0.9, respectively; HCMJ: increment 16.4%, d = 0.8; CMJ: increment 22.4%, d = 0.7; CMJA: increment 23.3%, d = 0.7; and DJ20: increment 39.7%, d = 1.1) and for the NPPT group (LJ: increment 14.1%, d = 0.4; DJ20: increment 32.9%, d = 0.8) with greater changes after PPT compared with NPPT for all jump measures (all p < 0.05; d = 0.21-0.81). The training efficiency was greater (p < 0.05; d = 0.22) after PPT (0.015% per jump) compared with NPPT (0.0053% per-jump). The PPT induced larger performance improvements on measures of physical fitness as compared to NPPT. Therefore, in-season progressive volume-based overload PT in young male basketball players is recommended.
Recently, there has been a proliferation of published articles on the effect of plyometric jump training, including several review articles and meta-analyses. However, these types of research articles are generally of narrow scope. Furthermore, methodological limitations among studies (e.g., a lack of active/passive control groups) prevent the generalization of results, and these factors need to be addressed by researchers. On that basis, the aims of this scoping review were to (1) characterize the main elements of plyometric jump training studies (e.g., training protocols) and (2) provide future directions for research. From 648 potentially relevant articles, 242 were eligible for inclusion in this review. The main issues identified related to an insufficient number of studies conducted in females, youths, and individual sports (~ 24.0, ~ 37.0, and ~ 12.0% of overall studies, respectively); insufficient reporting of effect size values and training prescription (~ 34.0 and ~ 55.0% of overall studies, respectively); and studies missing an active/passive control group and randomization (~ 40.0 and ~ 20.0% of overall studies, respectively). Furthermore, plyometric jump training was often combined with other training methods and added to participants’ daily training routines (~ 47.0 and ~ 39.0% of overall studies, respectively), thus distorting conclusions on its independent effects. Additionally, most studies lasted no longer than 7 weeks. In future, researchers are advised to conduct plyometric training studies of high methodological quality (e.g., randomized controlled trials). More research is needed in females, youth, and individual sports. Finally, the identification of specific dose-response relationships following plyometric training is needed to specifically tailor intervention programs, particularly in the long term.
This study aimed to investigate the relationship between the acute to chronic workload ratio (ACWR), based upon participant session rating of perceived exertion (sRPE), using two models [(1) rolling averages (ACWRRA); and (2) exponentially weighted moving averages (ACWREWMA)] and the injury rate in young male team soccer players aged 17.1 ± 0.7 years during a competitive mesocycle. Twenty-two players were enrolled in this study and performed four training sessions per week with 2 days of recovery and 1 match day per week. During each training session and each weekly match, training time and sRPE were recorded. In addition, training impulse (TRIMP), monotony, and strain were subsequently calculated. The rate of injury was recorded for each soccer player over a period of 4 weeks (i.e., 28 days) using a daily questionnaire. The results showed that over the course of the study, the number of non-contact injuries was significantly higher than that for contact injuries (2.5 vs. 0.5, p = 0.01). There were also significant positive correlations between sRPE and training time (r = 0.411, p = 0.039), ACWRRA (r = 0.47, p = 0.049), and ACWREWMA (r = 0.51, p = 0.038). In addition, small-to-medium correlations were detected between ACWR and non-contact injury occurrence (ACWRRA, r = 0.31, p = 0.05; ACWREWMA, r = 0.53, p = 0.03). Explained variance (r²) for non-contact injury was significantly greater using the ACWREWMA model (ranging between 21 and 52%) compared with ACWRRA (ranging between 17 and 39%). In conclusion, the results of this study showed that the ACWREWMA model is more sensitive than ACWRRA to identify non-contact injury occurrence in male team soccer players during a short period in the competitive season.
This study aimed to investigate the relationship between the acute to chronic workload ratio (ACWR), based upon participant session rating of perceived exertion (sRPE), using two models [(1) rolling averages (ACWRRA); and (2) exponentially weighted moving averages (ACWREWMA)] and the injury rate in young male team soccer players aged 17.1 ± 0.7 years during a competitive mesocycle. Twenty-two players were enrolled in this study and performed four training sessions per week with 2 days of recovery and 1 match day per week. During each training session and each weekly match, training time and sRPE were recorded. In addition, training impulse (TRIMP), monotony, and strain were subsequently calculated. The rate of injury was recorded for each soccer player over a period of 4 weeks (i.e., 28 days) using a daily questionnaire. The results showed that over the course of the study, the number of non-contact injuries was significantly higher than that for contact injuries (2.5 vs. 0.5, p = 0.01). There were also significant positive correlations between sRPE and training time (r = 0.411, p = 0.039), ACWRRA (r = 0.47, p = 0.049), and ACWREWMA (r = 0.51, p = 0.038). In addition, small-to-medium correlations were detected between ACWR and non-contact injury occurrence (ACWRRA, r = 0.31, p = 0.05; ACWREWMA, r = 0.53, p = 0.03). Explained variance (r 2) for non-contact injury was significantly greater using the ACWREWMA model (ranging between 21 and 52%) compared with ACWRRA (ranging between 17 and 39%). In conclusion, the results of this study showed that the ACWREWMA model is more sensitive than ACWRRA to identify non-contact injury occurrence in male team soccer players during a short period in the competitive season.
This study aimed to investigate the relationship between the acute to chronic workload ratio (ACWR), based upon participant session rating of perceived exertion (sRPE), using two models [(1) rolling averages (ACWRRA); and (2) exponentially weighted moving averages (ACWREWMA)] and the injury rate in young male team soccer players aged 17.1 ± 0.7 years during a competitive mesocycle. Twenty-two players were enrolled in this study and performed four training sessions per week with 2 days of recovery and 1 match day per week. During each training session and each weekly match, training time and sRPE were recorded. In addition, training impulse (TRIMP), monotony, and strain were subsequently calculated. The rate of injury was recorded for each soccer player over a period of 4 weeks (i.e., 28 days) using a daily questionnaire. The results showed that over the course of the study, the number of non-contact injuries was significantly higher than that for contact injuries (2.5 vs. 0.5, p = 0.01). There were also significant positive correlations between sRPE and training time (r = 0.411, p = 0.039), ACWRRA (r = 0.47, p = 0.049), and ACWREWMA (r = 0.51, p = 0.038). In addition, small-to-medium correlations were detected between ACWR and non-contact injury occurrence (ACWRRA, r = 0.31, p = 0.05; ACWREWMA, r = 0.53, p = 0.03). Explained variance (r²) for non-contact injury was significantly greater using the ACWREWMA model (ranging between 21 and 52%) compared with ACWRRA (ranging between 17 and 39%). In conclusion, the results of this study showed that the ACWREWMA model is more sensitive than ACWRRA to identify non-contact injury occurrence in male team soccer players during a short period in the competitive season.
This study aimed to investigate the relationship between the acute to chronic workload ratio (ACWR), based upon participant session rating of perceived exertion (sRPE), using two models [(1) rolling averages (ACWRRA); and (2) exponentially weighted moving averages (ACWREWMA)] and the injury rate in young male team soccer players aged 17.1 ± 0.7 years during a competitive mesocycle. Twenty-two players were enrolled in this study and performed four training sessions per week with 2 days of recovery and 1 match day per week. During each training session and each weekly match, training time and sRPE were recorded. In addition, training impulse (TRIMP), monotony, and strain were subsequently calculated. The rate of injury was recorded for each soccer player over a period of 4 weeks (i.e., 28 days) using a daily questionnaire. The results showed that over the course of the study, the number of non-contact injuries was significantly higher than that for contact injuries (2.5 vs. 0.5, p = 0.01). There were also significant positive correlations between sRPE and training time (r = 0.411, p = 0.039), ACWRRA (r = 0.47, p = 0.049), and ACWREWMA (r = 0.51, p = 0.038). In addition, small-to-medium correlations were detected between ACWR and non-contact injury occurrence (ACWRRA, r = 0.31, p = 0.05; ACWREWMA, r = 0.53, p = 0.03). Explained variance (r 2) for non-contact injury was significantly greater using the ACWREWMA model (ranging between 21 and 52%) compared with ACWRRA (ranging between 17 and 39%). In conclusion, the results of this study showed that the ACWREWMA model is more sensitive than ACWRRA to identify non-contact injury occurrence in male team soccer players during a short period in the competitive season.