Effects of plyometric training on technical skill performance among athletes: A systematic review and meta-analysis

Abstract

Background: The literature has proven that plyometric training (PT) improves various physical performance outcomes in sports. Even though PT is one of the most often employed strength training methods, a thorough analysis of PT and how it affects technical skill performance in sports needs to be improved.

Methods: This study aimed to compile and synthesize the existing studies on the effects of PT on healthy athletes' technical skill performance. A comprehensive search of SCOPUS, PubMed, Web of Science Core Collection, and SPORTDiscus databases was performed on 3rd May 2023. PICOS was employed to establish the inclusion criteria: 1) healthy athletes; 2) a PT program; 3) compared a plyometric intervention to an active control group; 4) tested at least one measure of athletes' technical skill performance; and 5) randomized control designs. The methodological quality of each individual study was evaluated using the PEDro scale. The random-effects model was used to compute the meta-analyses. Subgroup analyses were performed (participant age, gender, PT length, session duration, frequency, and number of sessions). Certainty or confidence in the body of evidence was assessed using the Grading of Recommendations Assessment, Development, and Evaluation (GRADE).

Results: Thirty-two moderate-high-quality studies involving 1078 athletes aged 10-40 years met the inclusion criteria. The PT intervention lasted for 4 to 16 weeks, with one to three exercise sessions per week. Small-to-moderate effect sizes were found for performance of throwing velocity (i.e., handball, baseball, water polo) (ES = 0.78; p < 0.001), kicking velocity and distance (i.e., soccer) (ES = 0.37-0.44; all p < 0.005), and speed dribbling (i.e., handball, basketball, soccer) (ES = 0.85; p = 0.014), while no significant effects on stride rate (i.e., running) were noted (ES = 0.32; p = 0.137). Sub-analyses of moderator factors included 16 data sets. Only training length significantly modulated PT effects on throwing velocity (> 7 weeks, ES = 1.05; ≤ 7 weeks, ES = 0.29; p = 0.011). The level of certainty of the evidence for the meta-analyzed outcomes ranged from low to moderate.

Conclusion: Our findings have shown that PT can be effective in enhancing technical skills measures in youth and adult athletes. Sub-group analyses suggest that PT longer (> 7 weeks) lengths appear to be more effective for improving throwing velocity. However, to fully determine the effectiveness of PT in improving sport-specific technical skill outcomes and ultimately enhancing competition performance, further high-quality research covering a wider range of sports is required.

Fig 1. PRISMA flow diagram.

Fig 2. Forest plot of changes in throwing velocity performance in athletes participating in plyometric training compared to controls.

Values shown are effect sizes (Hedges’s g) with 95% confidence intervals (CI). The size of the plotted squares reflects the statistical weight of the study.

Fig 3. Forest plot of changes in kicking velocity performance in athletes participating in plyometric training compared to controls.

Values shown are effect sizes (Hedges’s g) with 95% confidence intervals (CI). The size of the plotted squares reflects the statistical weight of the study.

Fig 4. Forest plot of changes in kicking distance performance in athletes participating in plyometric training compared to controls.

Values shown are effect sizes (Hedges’s g) with 95% confidence intervals (CI). The size of the plotted squares reflects the statistical weight of the study.

Fig 5. Forest plot of changes in speed dribbling performance in athletes participating in plyometric training compared to controls.

Values shown are effect sizes (Hedges’s g) with 95% confidence intervals (CI). The size of the plotted squares reflects the statistical weight of the study.

Fig 6. Forest plot of changes in stride rate performance in athletes participating in plyometric training compared to controls.

Values shown are effect sizes (Hedges’s g) with 95% confidence intervals (CI). The size of the plotted squares reflects the statistical weight of the study.