Improving sprint performance is beneficial to many sports for a multitude of reasons from winning a race to providing an advantage during sprint duels that allow players to reach the ball before the opponent (53). Because of the advantage of having greater speed, a great deal of research has focused on the development of sprint performance using a myriad of training methods, including speed training, sprint drills, sprinting against resistances, weight training, combined resistance and speed training, and plyometric training (PT) (17,18,31,42,46). The focus of this article is on the effects of PT on sprint performance. Plyometrics refers to exercises that are designed to enhance muscle, mainly through the use of jump training. Plyometric exercises constitute a natural part of most sport movements because they involve jumping, hopping, and skipping (i.e., such as high jumping, throwing, or kicking) (3-5). The identifying feature of plyometric exercise is a lengthening (eccentric contraction) of the muscle-tendon unit followed directly by a shortening or concentric contraction, otherwise termed a stretch-shortening cycle (SSC). The SSC is integral to plyometric exercise because it enhances the ability of the muscle-tendon unit to produce maximal force in the shortest amount of time.
The plyometric exercises used in a training program should match the individual needs of the athlete in relation to the characteristics of the sporting activity that they are involved with. That is, to optimize transference to sport plyometric exercises should reflect the type of activity implicit in that sport, that is, the principle of specificity. For example, jumping exercises that were nonspecific to running performance (i.e., vertical-type jump exercise) did not cause any effect on running speed (16,21). When exercises were specific (e.g., speed bounding) to running performance, the training program had a positive effect on running velocity (42).
Plyometric exercises can either be combined within a training program (combination training) or can be used as standalone exercises. Furthermore, plyometrics can be performed at various intensity levels, ranging from low-intensity hops to high unilateral-intensity drills such as bounding (alternating single-leg jumps for maximum horizontal distance). As far as the lower body is concerned, plyometrics include the performance of various types of body-weight jumping exercises, such as the drop jump (DJ) or countermovement jump (CMJ), alternate-leg bounding, hopping, and other SSC jumping exercises (7,8,10,12).
Although athletes and coaches involved in sprint training continue to use plyometric exercises (16,32), there are few studies describing the transfer of the training effects from PT in the horizontal plane to sprint performance in the acceleration phases of a sprint. The findings from the small number of studies in the literature regarding the effects of plyometrics on sprinting are inconsistent. Researchers have reported some improvements (18,42,46) and no improvements (22,32,61) in sprint times resulting from plyometric interventions. The plyometric exercises employed in these studies were not specific to sprinting, however, and the lack of specificity of the exercises to sprinting may have been responsible for the absence or small improvements in sprint times. On the other hand, improvements in 10- and 100-m sprint times have been found after a training intervention that incorporated some sprint-specific plyometric exercises (17).
The effects of PT may differ depending on the various subjects' characteristics, such as strength training level (14,20,32), gender (22,29), age (19,30,33,36,55), sport activity, or familiarity with PT (17,37). Research studies that combine these variables in different ways sometimes lead to conflicting results (14,30,32). Other factors that seem to determine the effectiveness of PT are program duration, type of plyometrics (i.e., vertical- or horizontal-type jump exercise), training intensity, or volume. Researchers have used numerous combinations of these variables (20,26,46,61); therefore, the optimal combination of these factors for maximum achievement remains unclear.
The principal issue of determining the optimal loading parameters of a plyometric program remains inconclusive. Using a meta-analytical approach may lend some clarity to this area. Meta-analysis is a quantitative approach in which individual study findings addressing a common problem are statistically integrated and analyzed (25,41) overcoming the problems associated with small sample size and low statistical power. Because meta-analyses can effectively increase the overall sample size, it can also provide a more precise estimate of the effect of plyometrics on sprint performance. In addition, meta-analyses can account for the factors partly responsible for the variability in treatment effects observed among different training studies (22,29,30,46,61). Thus, the purpose of this review was to examine the influence of various factors on the effectiveness of PT using a meta-analytical approach.
Experimental Approach to the Problem
In the present study, the meta-analysis was performed in different steps, grounded in previous recommendations (48).
A search was performed using key words in the English, French, and Spanish languages (e.g., jump training, sprint training, sprint performance, sprint times, SSC, plyometric, plyometrics, training of power, PT, pliometrique, entrainement pliometrique, salto pliométrico, velocidad). These key words were applied in the databases ADONIS, ERIC, SPORTSDiscus, EBSCOhost, MedLine, and PubMed. Moreover, manual searches of relevant journals and reference lists obtained from articles were conducted. The present meta-analysis includes studies published in journals that have presented original research data on healthy human subjects. No age, gender, or language restrictions were imposed during the search stage.
Research studies implementing PT programs for lower-limb muscles were the primary focus so research investigating the training of the upper-limb musculature was rejected. A total of 33 studies were initially identified.
The next step was to select studies with respect to their internal validity. Selection was based on the recommendations by Campbell and Stanley (11) and included (a) randomized control studies; (b) studies using instruments with high reliability and validity; (c) studies with minimal experimental mortality; (d) studies where the plyometric program was described; and (e) studies where the sprint test was conducted preintervention and postintervention. Twenty-six studies were selected after having completed all quality conditions (2,13,14,17,20-22,26,27,29,30,32,33,36-38,42-44,46,47,50,52,55,58,61) (Table 1).
Each study was read and coded independently by 2 investigators using different moderator variables. Because of the high number of variables that may affect training efficacy, independent variables were grouped into the following areas: (a) subject characteristics: variables included age (years), body mass (kilograms), height (centimeters), previous experience, group size, level of fitness, sports level, and type of sport activity; (b) program exercises: variables included combination with other types of exercise, intensity of session, type of plyometric exercises and resistance; (c) program elements: variables included frequency of weekly sessions, program duration, drop height, number of jumps per session, number of exercises per session, and rest intervals between series of exercises; and (d) outcome measurements the type of sprint test used to identify performance gains (e.g., 50, 40, 30 m). The mean agreement was calculated by intraclass correlation coefficient. The coding agreement between investigators was determined by dividing the variables coded the same by the total number of variables. A mean agreement of 0.90 is accepted as an appropriate level of reliability for such coding procedures (37). The mean agreement between coding for this study was 0.90. Any coding differences between investigators were scrutinized and resolved apriori to the analysis.
The effect size (ES) is a standardized value that permits the determination of the magnitude of the differences between the groups or experimental conditions (54). Gain ESs were calculated using Hedges and Olkin's g (25), using the formula
where Mpost is the mean for the posttest, Mpre is the mean for the pretest, and SDpooled is the pooled SD of the measurements:
It has been suggested (45,48,54) that ES should be corrected for the magnitude of sample size of each study. Therefore, correction was performed using the formula
where m = n − 1, as proposed by Hedges and Olkin (25).
To examine the effect of the categorical independent variables on the ES, an analysis of variance (ANOVA) was used (23,45,56). In the case of quantitative independent variables (e.g., age, height, duration of the treatment in weeks, number of jump per session), a Pearson's (r) correlation test was used to examine the relationships between ESs and variable values (45). Statistical significance was set at p ≤ 0.05 for all analyses. The scale used for interpretation was the one proposed by Rhea (39,40), which is specific to training research and the training status of the subjects to evaluate the relative magnitude of an ES. The magnitudes of the ESs were considered either trivial (<0.35), small (0.35–0.80), moderate (0.80–1.50), or large (>1.5).
The analysis showed that the average ES of the PT group (0.37; n = 41; 20.081 seconds) was significantly higher (p < 0.05) compared with the ES of controls (0.03; n = 15; −0.013 seconds).
With regards to the subjects' characteristics, the results indicate no significant correlation coefficient for age (r = 0.221), body mass (r = −0.104), height (r = −0.107), and group size (r = 0.170), with the magnitude of the ES (Table 2). The ANOVA showed no significant effects in any of the variables measured (i.e., previous experience, fitness level, gender and sport level). However, there is a significant effect (p < 0.05) in the variable sport activity.
The ANOVA showed no differences in ESs regarding the intensity of session, the different combinations of PT or among programs with and without added resistance. However, significant differences (p < 0.05) were found among the type of plyometric exercises (Table 3).
There was a relationship (p < 0.05) between the frequency session per week (r = 0.362), program duration (weeks) (r = −0.505) and rest between sets (r = −0.663) with PT ES, but no significant effects were found between drop height (centimeters) (r = 0.041), number of jumps per session (r = 0.347), and number of exercises per session (r = −0.151) with the PT ES (Table 4). No differences in ES (p > 0.05) were found among the different sprint tests (Table 5).
The current metanalysis support those of previous studies (2,14,17,21,30) that have concluded that PT seems to be an effective training method for the improvement of the sprint performance (ES = 0.37, i.e., plyometric group). Thus, the reported sprint time gains of >−0.081 seconds resulting from PT could be of practical relevance for trained athletes in sports (i.e., short-distance sprints, high-intensity sprints, initial accelerations, specific explosive actions). The present meta-analysis offers robust quantitative evidence to this conclusion and provides some valuable information concerning the importance of controlling some determinant variables for the improvement of the performance.
The results of the meta-analysis indicate that when subjects can adequately follow plyometric exercises (e.g., technical ability and adequate musculoskeletal strength), the training gains are independent of the fitness level (i.e., maximal aerobic power). Some authors explain that the gains that can be made via PT are dependent on training status (6). For example, Delecluse (17) studied beginner and experienced sprinters and found greater sprint increases for the beginner and smaller gains for the experienced sprinters. Furthermore, a major part of the improvements in untrained subjects during the initial weeks in power-type strength training is probably because of adaptations of the neural system (1,14,24,28,60).
Sprint performance improvement was found to be nonsignificantly greater when plyometrics was performed combined with other types of exercises (i.e., plyometric + weight training or plyometric + electrostimulation) than when performed alone (Table 3). There is a possibility that the subjects in the combination training group were exposed to a higher volume of training than those in the others groups, that is, the total workload was not equated between groups. It would be very interesting if future studies made an attempt to equate workloads between groups when comparing different training methods. Another difference is the model used to provide the training stimulus to the subjects. Training intensity, volume, and exercise selection followed the principle of progressive overload, starting with lower intensities, single-joint exercises, and less complex exercise techniques, and progressing to higher intensities, multijoint exercises, and more complex techniques. In any case, the optimal training strategy to enhance sprint performance appears to be a specific PT. That is, sprint performance gains will be optimized by the use of training programs that incorporate greater horizontal acceleration (i.e., skipping, jumps with horizontal displacement). It is generally accepted that the more specific a training exercise is to a competitive movement, the greater is the transfer of the training effect to performance (17,49). Athletes, such as sprinters, who require power for moving in the horizontal plane engage in bounding plyometric exercises, whereas athletes, such as high jumpers and volleyball players, who require power to be exerted in the vertical direction train using vertical jumping exercises (15,59).
It can also be concluded that when plyometric exercise intensity is high during the session, there is a greater improvement in sprint performance (Table 3). Some authors (9,51,57,63) determined that plyometric or SSC loading is higher during DJs, followed by CMJs, and then during squat jumps (SJs), there is little SSC loading. This is mainly attributed to the different characteristics of movement and, thus, to the different use of SSC characteristics. For these reasons, the combination of various exercises may result in higher gains compared with the performance of each exercise alone. Furthermore, it was found that a combination of plyometric exercises (i.e., SJ + DJ, bounding + CMJ) resulted in better training effects (ESs = 0.76) compared with the use of a single type of exercise (DJ) (ESs = 0.27) (Table 3). The higher improvements in sprint performance may be because of a training specificity. It is possible that a training program incorporating more horizontal acceleration (e.g., bounding and form running) may improve sprint times. In fact, it has been reported that no significant increase in sprint acceleration and velocity has resulted from training programs involving essentially vertical plyometric exercises (2,22,61). In contrast, significant improvements in running velocity, as measured by a 40-yd sprint, have resulted from the use of form running in conjunction with weighted depth jumps (21,38). Besides, improvements in 10- and 100-m sprint times have been found after a training intervention that incorporated some sprint-specific plyometric exercises (17).
Some research studies have shown that the PT with additional weights (vests, bars on the back, etc.) resulted in greater gains in sprint performance (21,38). The results of the meta-analysis indicated no significant differences among the training conditions (Table 3). Intuitively, this would make sense because adding weights increases ground contact times, and therefore, the duration of the eccentric and concentric phases are longer. Given that the magnitude of reflex potentiation, storage, and use of elastic energy is related to movement velocity and the time between the end of the eccentric phase and beginning of the concentric phase (coupling time), once more, the use of weights would seem problematic in the plyometric exercises and the sprints (i.e., the contact times) (42). The contact times during the initial acceleration phase of a sprint are similar to the contact times of the exercises employed (34,35,62,63). Therefore, the greatest transfer of the plyometrics to sprinting likely occurred during the initial acceleration phase. This theory is supported by Young (62), who suggested that bounding may be considered a specific exercise for the development of acceleration because of the similar contact times of bounding and sprinting during the initial acceleration phase. Further research is required to test the theory that the greatest transfer of sprint-specific plyometrics to sprinting occurs during the phase of the sprint when the contact times of the sprint during that phase are the same as the contact times of the plyometric exercises. Therefore, training effects using additional weights are not guaranteed.
Volume and frequency are very important parameters to be taken into account for an optimum PT program design. The results showed that training for <10 weeks (i.e., between 6 and 8 weeks) with 3–4 sessions per week is more beneficial than similar programs of a longer duration. Similarly, treatment with more than 18 sessions increases sprint performance, whereas performance of >80 jumps per session seemed to result in the most beneficial volume (Table 4).
The finding of this study is that a sprint-specific plyometrics training program can improve sprint performance over distances down to 40 m in length. The effects of a sprint-specific plyometrics program appear to be the greatest over the initial meters (10–40 m). The results suggest that sports participants who are accustomed to performing sprints over distances up to 40 m could potentially improve sprint speed, particularly in the initial acceleration phase, by adding sprint-specific plyometric exercises to their training. Explosive speed is required in many sports and physical activities; coaches and participants should therefore consider a plyometrics training program that incorporates sprint-specific exercises as part of the overall training plan.
In conclusion, the present meta-analysis demonstrates that PT significantly improves sprint performance. The estimated improvements in velocity as a result of PT could be considered as practically relevant—for example, an improvement in sprint time of >−0.081 seconds (i.e., ES = 0.37) could be of high importance for trained athletes in sports relying on sprint performance. A training volume of <10 weeks (with >18 sessions) using high intensities (with >80 jumps per session) is the strategy that will maximize one's probability of obtaining significant improvements in performance. Another important conclusion is that sprint performance gains will be optimized by the use of training programs that incorporates greater horizontal acceleration (i.e., sprint-specific plyometric exercises, jumps with horizontal displacement). However, there are no extra benefits gained from doing plyometrics with added weight.
Plyometrics can be recommended as an effective form of physical conditioning for augmenting the sprint performance; yet, the effects of PT could vary because of a large number of variables, such us program duration, training volume, or intensity. The velocity and conditioning coach may consider taking into account the dose-response trends identified in this analysis to prescribe the appropriate level of training. Therefore, in addition to the well-known training methods such as resistance training, explosive and sprint training, strength and conditioning professionals may well incorporate PT into an overall conditioning program of athletes striving to achieve a high level of explosive leg power and dynamic athletic performance.
The authors have no professional relationships with companies or manufacturers that might benefit from the results of this study. The results of this study do not constitute endorsement of any product by the authors or the National Strength and Conditioning Association.
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