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Original Research

Implementation and Efficacy of Plyometric Training: Bridging the Gap Between Practice and Research

Watkins, Casey M.1,2; Storey, Adam G.1; McGuigan, Michael R.1,3; Gill, Nicholas D.4

Author Information
Journal of Strength and Conditioning Research: May 2021 - Volume 35 - Issue 5 - p 1244-1255
doi: 10.1519/JSC.0000000000003985
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Abstract

Introduction

Most athletes benefit from being stronger, faster, and more powerful, the degree to which depends on their sport. Although a powerlifter will primarily benefit from improving absolute maximum strength (typically ∼3–5 seconds), many athletes are regulated by the time available for force production during more ballistic jumping and sprinting actions with short ground contact times (GCTs, ∼0.1–0.6 seconds) (6,30). Thus, practitioners are always looking for ways to bridge the gap between strength gained in the gym and functional competition performance. Plyometrics is one such method used globally to improve linear speed, power, change-of-direction ability, and running economy, which uses the athlete's own mass as a stimulus rather than external weight as traditionally used in resistance training (12). Originally termed “the Shock method” by Yuri Verkhoshansky in the 1950s, a critical component of plyometric exercises is to induce mechanical shock that forces a maximal buildup of tension invoking the stretch reflex. An important distinction is that originally true plyometrics only involved very high-intensity (i.e., 50–100 cm drop jump [DJ]) exercises using “the Shock method,” but at present encompasses a wide spectrum of low-intensity extensive and intensive plyometric exercises.

After years of practice- and research-driven investigation, there is sufficient empirical evidence confirming that plyometric training organizes the structural, neural, and elastic components of the human body to achieve greater power output than isolated muscle actions alone (43). Specifically, the accumulation of kinetic energy during the eccentric portion of stretch-shortening cycle (SSC) movement is conserved and recycled during the subsequent isometric and concentric portions, creating a stretch-recoil action similar to that of a rubber band (20,22,23,32). Concurrently, central nervous system (CNS) motor programs initiate high levels of muscular activation before GC. The preactivity of the associated musculature alongside the stretch reflex initiates the facilitation of energy transfer and force transmission resulting in greater mechanical efficiency (23). However, for an action to be truly considered elastic (i.e., optimal use of the SSC), active eccentric lengthening must occur and the eccentric-concentric coupling action must be performed quickly, resulting in a small amortization (i.e., transition) time (23). If the aforementioned criteria are not met, energy will likely be dissipated as heat, as in static stretching (39).

The benefit from using plyometric training is primarily dependent on the rate and magnitude of muscle-tendon unit (MTU) loading, due to the reliance on collision forces. Newtonian laws dictate that every collision (i.e., between an athlete and the ground surface) conserves momentum, whereas kinetic energy conservation regulates ballistic performance (23,35,38). The difference being CNS energy-dissipating protective or energy-recoiling performance-based strategies which result in either slow or fast GCT (4,17). Historically, this has presented some difficulty in correctly identifying the intensity of plyometric training exercises, leaving coaches to rely on subjective visual ratings. Recommendations by the National Strength and Conditioning Association (NSCA) have attempted to add clarity on this topic, suggesting that jump height is a primary determinant of intensity and that unilateral jump variations are more intense than their bilateral counterparts. However, an important distinction lies in the velocity at which one falls and the direction of landing relative to that of the takeoff, with rapid landings below the takeoff point being more eccentrically stressful. A surplus of scientific publications investigating GCT classifications, reactive strength index, kinetic forces, and joint power absorption now bring into question the traditional classifications of plyometric training and provide more advanced analysis on the specific stress from different exercises (24,42). For instance, analysis of lower-body jump exercises revealed that jumping movements in the forward direction have ∼19–24% greater summed, ankle, knee, and hip joint peak power than the box drop and jump up exercises, although classified as low compared to moderate intensity via subjective ratings (42). Moreover, specific joint analysis reveals that intensity rankings differ by joint contribution, with forward jumps being classified as high intensity for the ankle, but low for the hip (42).

At present, there seems to be some discontinuity between literary recommendations for plyometric training and practitioner-led plyometric programming. Both the NSCA in 2007 and International Journal of Sports Physical Therapy in 2015 have published guidelines directing high-volume session loads of 40–80 and 80–100 GCs for beginners and 100–140 GC for advanced athletes (16). Both organizations went on to recommend high-intensity session volumes of 200–400 GC for elite athletes (10,27). However, new evidence continues to emerge, questioning whether more volume is more beneficial (7,8,15,21,44). Anecdotally, some elite strength and conditioning coaches are regularly using as few as 15–40 GCs in conjunction with other training modalities for international athletes.

Other recommendations have included significant strength requirements (1.5–2.5x bodyweight) for athletes before including even low-level plyometrics (10). In addition, bodyweight restrictions (∼100 kg), the avoidance of depth jumps, and only the use of resilient surfaces are additional criteria that have been proposed (10,13,27). Newer evidence suggests that MTU mechanical tolerance restricts performance (37). For instance, athletes with requisite MTU strength, effective SSC mechanics, and tissue integrity at high velocities will better tolerate large impact forces during high-intensity plyometrics and benefit accordingly (37). By contrast, athletes with poor MTU capabilities relative to their body mass risk injury and are likely to adopt a more compliant strategy to absorb forces over longer durations as an injury-prevention strategy (36). In addition, adaptations may be surface- and exercise-specific (1,2,34).

Currently, there is no agreement on optimal periodization strategies with traditional and undulating strategies resulting in similar adaptations (10). However, there is consensus that any periodization strategy does in fact trump a constant volume approach (41). Some authors recommend using plyometrics throughout all phases of training (10), whereas others claim plyometrics should only be used in preparatory phases (13). Therefore, the primary aim of this investigation is to have a clearer understanding of the practitioner's implementation of plyometric training, including training direction dose, periodization strategies, and efficacy in a real-world setting. Specifically, this survey aimed to determine how closely the current literary recommendations match current practice. Second, this survey investigated trends in program variables by competition level, sport, or training axis.

Methods

Experimental Approach to the Problem

The current study used an integrative mixed-methods online survey (Google Forms, Mountain View, CA) to understand the practitioner's perspective on plyometric training in a real-world setting. The online survey was sent via an email link and included an information sheet intended to introduce the survey and provide details about the aims and benefits of the research project. All coaches were assured of the survey's voluntary nature and their ability to withdraw from the survey at any time. All responses were anonymous, and no identifying information was ever collected.

Subjects

Globally, 61 adult strength and conditioning practitioners volunteered for this study. Strength and conditioning coaches were recruited from semiprofessional, professional, national, and international-level teams and performance centers around the world. Subjects varied in coaching experience, the number of years using plyometric training, and the current level of competition level they work with. Of the subjects, 32.8% of respondents (n = 20) have coached for more than 9 years, 37.7% of respondents (n = 23) have used plyometric training for more than 9 years, and 34.4% of respondents (n = 24) were coaching at the Olympic or international level. The breakdown of responses by practitioner role, coaching experience, country, and sport is shown in Table 1. The Auckland University of Technology ethics committee (14/22) approved this research project, and all subjects provided written or signed and informed consent document.

Table 1 - Background information of survey respondents.*
Background coach information
Competition level International Professional Semipro and amateur Total
34.4% (21) 24.6% (15) 41.0% (25) 100% (61)
What is your primary job?
 Primary job Head S&C Assistant S&C Sport coach Academic Total Chi-square
62.3% (38) 23.0% (14) 8.2% (5) 6.6% (4) 100% (61) NS, p > 0.05
 Region Asia-Pacific Canada Europe United States Total Chi-square
44.3% (27) 24.6% (15) 6.6% (4) 21.3% (13) 97.7% (59) NS, p > 0.05
 Sport category Field team sports Non-field team sports§ Individual sports Mixed§ Total Chi-square
  All 50.8% (31) 13.1% (8) 11.5% (7) 24.6% (15) 100% (61) p < 0.001, C2 = 26.506
  International 38.1% (8) 14.3% (3) 33.3% (7) 14.3% (3) 100% (61) p = 0.026
  Professional 53.3% (8) 33.3% (5) 0.0%(0) 13.3% (2) 100% (61)
  Semipro and amateur 60.0% (15) 0.0% (0) 0.0%(0) 40.0% (10) 100% (61)
Primary source of knowledge
Educational Empirically based research Anecdotal (i.e., blogs and websites) Personal experience Combination Total Chi-square
41.0% (25) 21.3% (13) 16.4% (10) 13.1% (8) 6.6% (4) 100% (61) NS, p > 0.05
Experience 0–3 y 4–9 y 9+ y Total Chi-square
 Coaching, all 26.2% (16) 41.0% (25) 32.8% (20) 100% (61) p = 0.024, C2 = 7.47
 International 23.8% (8) 33.2% (7) 42.9% (9) 100% (61)
 Professional§ 13.3% (2) 33.3% (5) 53.8% (8) 100% (61) p = 0.031, C2 = 13.95
 Semipro and amateur§ 36.0% (9) 52.0% (13) 12.0% (3) 100% (61)
Experience 0–3 y 4–9 y 9+ y Total Chi-square
 PT 19.7% (12) 42.6% (26) 37.7% (23) 100% (61) p = 0.001, C2 = 13.86
 International 19.0% (4) 33.3% (7) 47.6% (10) 100% (61) p = 0.043, C2 = 11.12
 Professional§ 0.0% (0) 33.3% (5) 66.7% (10) 100% (61) p < 0.001, C2 = 19.47
 Semipro and amateur§ 32.0% (8) 56% (14) 12.0% (3) 100% (61)
Background athlete information
Sport experience 0–3 y 4–9 y 9+ y Total Chi-square
 All 6.6% (4) 62.3% (38) 31.1% (19) 100% (61) p = 0.016, C2 = 8.21
 International 4.8% (1) 52.4% (11) 42.9% (9) 100% (61)
 Professional§ 0.0% (0) 53.3% (8) 46.7% (7) 100% (61) p = 0.037, C2 = 12.40
 Semipro and amateur§ 12.0% (3) 76.0% (19) 12.0% (3) 100% (61)
Resistance experience
 RT age, all 44.3% (27) 52.5% (32) 3.3% (2) 100% (61) p = 0.006, C2 = 10.28
 International 28.6% (6) 71.4% (15) 0.0% (0) 100% (61) p = 0.035, C2 = 11.63
 Professional§ 26.7% (4) 60.0% (9) 13.3% (2) 100% (61) p = 0.013, C2 = 14.46
 Semipro and amateur§ 68.0% (17) 32.0% (8) 0.0% (0) 100% (61)
Training requirement before performing plyometric training
Experience None 1–3 y 4–9 y 9+ y Total Chi-square
 Sport requirement 73.8% (45) 18.0% (11) 6.6% (4) 1.6% (1) 100% (61) NS, p > 0.05
 RT requirement 78.7% (48) 18.0% (11) 3.3% (2) 0.0% (0) 100% (61) NS, p > 0.05
Strength requirement before performing plyometric training
None 0.5x BW 1.0x BW 1.5x BW ≥2.0x BW Total Chi-square
 BS 49.2% (30) 6.6% (4) 23.0% (14) 19.7% (12) 1.6% (1) 100% (61) NS between levels, p > 0.05
 DL 57.4% (35) 3.3% (2) 14.8% (9) 18.0% (11) 6.6% (4) 100% (61) NS between levels, p > 0.05
 Clean 73.8% (45) 8.2% (5) 14.8% (9) 1.6% (1) 1.6% (1) 100% (61) NS between levels, p > 0.05
*S&C = strength and conditioning coach; Asia-Pacific includes New Zealand, Australia, and Japan; PT = plyometric training; BS = back squat; DL = deadlift.
Presented as frequency percentage (total responses).
Signals represent significantly different pairs across rows field and individual,
§Signals represent significantly different pairs across rows non field team and mixed
Signals represent significantly different pairs across rows individual and mixed

Procedures

The survey was sent out through direct communication lines to a broad network of primary and secondary connections, as well as shared through social media resources (i.e., Twitter, Instagram, and LinkedIn). In addition, national performance centers from multiple countries were contacted using a brief introduction paragraph along with the survey link. This survey aimed to obtain responses from both northern and southern hemisphere countries, including a broad variety of individual and team sport settings of differing competition levels.

Survey

This survey comprised 5 sections: 1. Sport and coaching background information, 2. Plyometric training focus, 3. Periodization strategy, 4. Plyometric program details, and 5. Efficacy of plyometrics for sport performance. Response types included yes/no, multiple choice, Likert scale, percentage-based, and open-ended questions. Multiple choice answers were divided into single answer and multiple answer questions, but always included a fill-in option. Open-ended questions were divided into direct answer and more subjective probing type questions. The survey was originally piloted with a group of expert strength and conditioning coaches (n = 15), and areas that were identified as unclear were edited or removed from the survey.

Statistical Analyses

Both quantitative and qualitative analysis methods were used to analyze survey responses. Following completion, all responses were downloaded to Microsoft Excel, and answers were coded such that different variations (e.g., United States vs. US) were grouped, and all single-answer multiple choice responses converted to numerical expressions. For answers where multiple choices were allowed, a variable was created for each possible response, such that each subject had an entry (0 or 1) for each possible answer, and all variables were analyzed separately. All statistical analysis was subsequently completed in R (Auckland, New Zealand) software. For all statistical analysis, an alpha level of 0.05 was used. For categorical variables, a chi-square test was conducted. In accordance, groups with less than 5 responses, or <4% of the analysis, were combined to make broader categories. In cases where this was not possible, a Fisher's exact test was conducted. For analysis between categorical and ordinal variables, a Kruskal Wallace test was conducted. p-values were adjusted via the Holm method. For paired ordinal data, a T-Test was conducted, whereas a Friedman's test was conducted for paired categorical data or a Cochran's Q test for paired binary variables, with McNemar post-hoc analysis. All categorical variable analyses are presented as a percentage (frequency), otherwise as mean ± SD. For open-ended questions, answers were categorized into themes by 2 separate researchers using an inductive method and collated for analysis. Final themes were then coded similar to multiple choice answers. A copy of the questionnaire is provided as a supplemental file in attempts of full transparency. However, due to the magnitude of data provided, only a subset of relevant questions were reported on in the current article.

Results

Background Coach and Athlete Information

The background information for survey respondents and their athletes is reported in Table 1. There was a difference between sport and competition level of responses (p < 0.05). Notably, all 7 individual sport responses competed at the international level, which has been considered during further analysis. Significant differences also occurred between competition levels and years of plyometric training (p < 0.001), years of coaching (p = 0.024) as practitioners, and sport and resistance training experience of athletes (p < 0.01; Table 1). Overwhelmingly, 96.7% (n = 59) of practitioners reported positive feedback from athletes, 1.6% (n = 1) responded athletes are warming to them slowly, and 1.6% (n = 1) responded that some athletes, referring to large force-dominant front-row forwards, “do not love it as much.” Emergent themes for positive attitudes toward plyometric training included: 1. Increased social engagement using different variations, being competitive, challenging, and fun; 2. Perceived effectiveness in the context of speed, or feeling and moving fast; 3. Direct transferability and resemblance to sporting actions; 4. Positive technological feedback and results (i.e., GymAware, GPS, jump height); 5. Good rationale, credibility, and alternative inspiration including improvements from friends, older athletes who excel, and exercises they see on Instagram. A large consensus emerged on the critical role education and having a valid reason played in the perception of plyometric training with their athletes, citing lack of understanding or intent is sometimes an issue.

Extent of Plyometric Training

The reported extent of plyometric training (1–10) in a program did not significantly differ by competition level, with 47.6, 53.3, and 29.2% of international, professional, and semiprofessional or amateur practitioners, respectively, reporting a 7 out of 10 or greater (p = 0.38). Including the entire cohort, the average plyometric confidence level of and the extent to which survey respondents used plyometric training in programs was 7.5 ± 1.6 and 5.4 ± 2.6 out of 10, respectively. Furthermore, 78.7% (n = 48) and 41% (n = 25) of respondents reported their plyometric training confidence and their extent of plyometric programming as 7 out of 10 or higher. An overwhelming majority, 70.5% (n = 43), of respondents reported yes to using plyometric training with all their athletes (barring injury or other specific cases), 24.6% (n = 15) responded no, and 4.9% (n = 3) reported it depended on circumstance. There were no differences in planned program changes between sport categories or competition levels (p > 0.05). Categories and response types are shown in Figure 1.

Figure 1.
Figure 1.:
Planned changes qualitative answer coding map.

Limitations

Limitations significantly differed by competition level. For international-level practitioners, 42.9% (n = 9) reported no limitations. Conversely, 40.0% (n = 6) of professional practitioners reported program and periodization limitations and 44.0% (n = 11) of semiprofessional practitioners reported resources as limitations (p < 0.05). There were no differences in injury or athlete characteristics limitations between groups or sport categories (Figure 2).

Figure 2.
Figure 2.:
Limitations by competition level. Answers presented as percentage of total respondents in each competition level group (international = 21, professional = 15, semiprofessional = 25). Open answer where answers were coded, and could contain multiple categories. Each category analyzed separately so each subject had only one response (0 or 1) for each category. Significantly different to other groups (p < 0.05).

Program Variables

Significant differences in program details are reported in Table 2. Typical training surface differed across sport categories (p < 0.05; Table 2). Training on track demonstrated significant differences across competition, with 52.4% (n = 11) and 40.0% (n = 10) of international and semiprofessional or amateur practitioners, respectively, reporting regular use of a synthetic track, compared to 6.7% (n = 1) of professional practitioners (p = 0.016, C2 = 8.215, df = 2).

Table 2 - Program variables.*
Footwear Uncontrolled Bare feet Sport-specific shoes Cross-training shoes Total Chi-square
All 13.1% (8) 11.5% (7) 19.7% (12) 54.1% (33) 98.4% (60) p = 0.022, C2 = 13.24
What surface do you typically train on? (Respondents were allowed to answer with multiple, as such, each variable is analyzed separately)
Turf Grass§ Track‖ Wood floor Mixture Other Chi-square
All 49.2% (20) 21.1% (19) 36.1% (22) 23% (14) 60.7% (37) 9.9% (6)
Field sports 54.8% (17) 38.7% (12) 35.5% (11) 16.1% (5) 58.1% (18)
Court sports 37.5% (3) 0.0% (0)§ 0.0% (0)‖ 37.5% (3) 75.0% (6) §p = 0.019, C2 = 9.234
Individual 14.3% (1) 0.0% (0)§ 85.7% (6)‖ 0.0% (0) 28.6% (2) p = 0.006, C2 = 11.688
Mixed 60.0% (9) 46.7% (7) 33.3% (5) 40.0% (6) 73.3% (11)
Plyometric frequency as a specific focus
0x week 1x week 2x week 3x week 4x week Total Chi-square
Frequency 1.6% (1) 13.1% (8) 52.5% (32) 24.6% (15) 8.2% (5) 100% (61) NS p > 0.05
Rest
Intersession 0 d 1 d 2 d 3 d ≥4 d Total Chi-square
1.6% (1) 24.6% (15) 39.3% (24) 21.3% (13) 13.1% (8) 100% (61) NS, p > 0.05
Precompetition rest 0–2 d 3–5 d ≥6 d Total Chi-square
59% (36) 36.1% (22) 4.9% (3) 100% (61) NS, p > 0.05
Interset rest 30–60 s 1–2 min >2 min Other Total Kruskal-Wallace
 All 19.7% (12) 39.3% (24) 31.1% (19) 4.9% (3) 90.1% (55) p = 0.032, C2 = 6.90
 International§ 10.0% (2) 40.0% (8) 50.0% (10) 0.0% (0) 95.2% (20) p = 0.026, C2 = 13.95
 Professional§ 46.2% (6) 38.5% (5) 15.4% (2) 0.0% (0) 86.67% (13)
 Semipro and amateur 18.2% (4) 50.0% (11) 31.8% (7) 0.0% (0) 88.0% (22)
Other modalities used in conjunction with plyometric training
RT Eccentric Gymnastics WL Sprinting Chi-square
All 78.7% (48) 31.1% (19) 9.8% (6) 68.9% (42) 62.3% (38) NS p > 0.05
*NS = not significant; C2 = chi-square; RT = resistance training; WL = the sport of weightlifting.
Reported as frequency percentage (absolute number).
Categories equalling <5% were eliminated from analysis due to insufficient data.

Periodization

There were no significant differences between periodization styles. However, 96.7% (n = 59) of practitioners reported using a form of periodization strategy over constant volume. Of periodization styles, 42.6% (n = 26) reported using undulating, 24.6% (n = 15) reported changes in exercise selection, 18% (n = 11) reported linear periodization, and 11.5% (n = 7) reported using a combination, depending on the circumstance. For incremental increases in volume, there was no difference across competition levels. Including all respondents, 54.1% (n = 33) responded 10 contacts per week, 23% (n = 14) reported no increases, instead citing constant volume, 21.3% (n = 13) responded with 20 contacts per week, and 1.6% (n = 1) of practitioners reported 40+ GC increases. Across sport categories, significant differences existed with 62.5% (n = 5) and 37.5% (n = 3) of non-field team sports and 73.3% (n = 11) and 26.7% (n = 4) of mixed sports reporting only increases of 10 and 20 GC per week. However, field and individual sports were more varied, with 38.7% (n = 12) and 28.6% (n = 2) of respondents reporting constant volume. Otherwise, 41.9% (n = 13) of field sports and 57.1% (n = 4) of individual sports reported increases of 10 GC, with 16.1% (n = 5) and 14.1% (n = 1) reporting 20 GC, and 3.2% (n = 1) of field team sports reporting increases of 40 or more GC per week (p < 0.05, C2 = 15.07, df = 3). Overwhelmingly, 68.9% (n = 42) of survey respondents reported using a taper before competition, 29.5% (n = 18) reported not using one, and 1.6% (n = 1) of practitioners reported that it depended on the circumstance. There was no difference between competition level for incremental increases, or for inclusion of taper for either competition level or sport (p > 0.05).

Figure 3.
Figure 3.:
Weeks of plyometric training programmed across competition phases. (p < 0.001; chi-square = 50.65; df = 10); Significantly different to off-season (p ≤ 0.01); = significant difference between phases (p < 0.001); = significant difference between phases (p ≤ 0.01); † = significant difference between phases (p = 0.03).

Weeks of Plyometric Training

There were no differences in total weeks of plyometric training per year (international = 25 ± 15 weeks; professional = 23 ± 14; semiprofessional = 24 ± 13; p > 0.05). However, there were significant differences across competition phases (p < 0.001; Figure 3) and between competition levels for different phases of training. For international-level practitioners, 81.0% (n = 17) reported 1–4 weeks of plyometric training compared to 46.7% (n = 7) of professional and 52.0% (n = 13) of semiprofessional practitioners during late competition (p < 0.05, C2 = 8.06, df = 4) and 71.5% (n = 15) compared to 46.7% (n = 7) and 48.0% (n = 12) during playoffs (p < 0.05). Across sports, there were significant differences for weeks programmed during playoff periods. Mixed sports were significantly less likely to report using 1–4 weeks of plyometric training during playoff periods, with 26.7% (n = 4) compared to 67.7% (n = 21) of field sports, 71.4% (n = 5) individual sports, and 50.0% (n = 4) of non-field team sports. Mixed sports were significantly more likely to report using zero weeks of plyometrics during playoff periods, with 66.7% (n = 10) compared to 32.3% (n = 10) field sports, 50.0% non-field team sports, and 14.3% (n = 1) individual sports. Neither team-sport category reported planning >5 weeks of plyometrics during playoffs, whereas 14.3% (n = 1) of individual sport and 6.7% (n = 1) of mixed sport reported so (p = 0.03).

Figure 4.
Figure 4.:
A–D) Sessional GCs programmed across competition phases for international-level practitioners (A), semiprofessional-level practitioners (B), professional practitioners (C), and all survey respondents collated (D). Responses presented as a percentage of group responses, missing (n = 11), international (n = 19), professional (n = 13), semiprofessional (n = 18), and all practitioners (n = 50). *GC volume significantly differed between seasons (up to 20 GC: Q = 15.74, p = 0.04; 40–60 GC: Q = 18.58, p < 0.001); GC volume significantly differed between seasons (up to 20 GC: Q = 15.74, p = 0.01; 40–60 GC: Q = 18.58, p = 0.037); GC volume significantly differed between seasons (40–60 GC: Q = 18.58, p < 0.01); Significant differences compared to other GC volumes for same phase, in all cases. df = 5 international: off-season (up to 20; Q = 46.67, p < 0.0001), pre-season (20–40 GC; Q = 23.48, p < 0.0001), early competition (20–40 GC; Q = 15.10, p = 0.01), late competition (up to 20 and 20–40; Q = 36.66, p < 0.0001); professional: pre-season (20–40; Q:11.82, p = 0.037), early competition (20–40 and 40–60; Q = 16.97, p < 0.01), late competition (up to 20 and 20–40; Q = 14.33, p = 0.014); semiprofessional: pre-season (40–60; Q = 18.41, p < 0.01), mid-competition (up to 20; Q = 15.00, p = 0.01), late competition (up to 20; Q = 22.54, p < 0.0001); Significantly greater than other competition levels during off-season (Up to 20 GC: C2 = 10.94, df = 2, p = 0.004; 40–60 GC: C2 = 5.96, df = 2, p = 0.027; 60–100 GC: C2 = 9.11, df = 2, p = 0.008).

Sessional Ground Contacts

Sessional GC volumes differed significantly across competition phases, within competition phases for each competition level, and between competition levels for the same competition phase (p < 0.05; Figure 4 and Table 3).

Table 3 - Ground contacts across seasons and competition level.*
Off-season Pre-season Early-competition Mid-competition Late-competition Cochran's Q (df = 4)
Up to 20 GC all (n = 50) 40.0% (20) 16.0% (8) 24.0% (12) 32.0% (16) 46% (23) Q = 15.74, p < 0.001
International (n = 19) 68.4% (13)† 26.3% (5) 31.6% (6) 36.8% (7) 52.6% (10) Q = 11.88, p = 0.01
Professional (n = 13) 30.8% (4) 15.4% (2) 23.1% (3) 15.4% (2) 38.5% (5) NS
Semiprofessional (n = 18) 16.7% (3) 5.6% (1) 16.7% (3) 38.9% (7) 44.4% (8) Q = 11.00, p = 0.02
Between competition levels C2 = 10.94, df = 2, p = 0.004 NS NS NS NS
20–40 GC all (n = 50) 16.0% (8) 40.0% (20) 32.0% (16) 30.0% (15) 28.0% (14) NS (p = 0.09)
International (n = 19) 26.3% (5) 52.6% (10) 21.1% (4) 21.1% (4) 42.1% (8) NS
Professional (n = 13) 15.4% (2) 46.2% (6) 46.2% (6) 53.9% (7) 23.1% (3) NS
Semiprofessional (n = 18) 5.6% (1) 22.2% (4) 33.3% (6) 22.2% (4) 16.7% (3) NS
Between competition levels NS NS NS NS NS
40–60 GC all (n = 50) 16.0% (8) 32.0% (16) 32.0% (16) 22.0% (11) 6.0% (3) Q = 18.58, p < 0.0001
International (n = 19) 0% (0)† 26.3% (5) 47.4% (9) 26.3% (5) 0% (0) Q = 18.96, p < 0.0001
Professional (n = 13) 23.1% (3) 15.4% (2) 38.5% (5) 23.1% (3) 7.7% (1) NS
Semiprofessional (n = 18) 27.8% (5) 50.0% (9) 22.2% (4) 16.7% (3) 11.1% (2) Q = 9.73, p = 0.04
Between competition levels C2 = 5.96, df = 2, p = 0.027 NS NS NS NS
60–100 GC (n = 50) 14.0% (7) 14.0% (7) 8.0% (4) 8.0% (4) 0% (0) NS (p = 0.09)
International (n = 19) 0% (0) 5.26% (1) 10.5% (2) 15.8% (3) 0% (0) NS
Professional (n = 13) 7.7% (1) 23.1% (3) 0% (0) 0% (0) 0% (0) NS
Semiprofessional (n = 18) 33.3% (6)† 16.7% (3) 11.1% (2) 5.6% (1) 0% (0) NS (p = 0.055)
Between competition levels C2 = 9.11, df = 2, p = 0.008 NS NS NS NS
100–200 GC (n = 50) 8.0% (4) 2.0% (1) 4.0% (2) 2.0% (1) 0% (0) NS (p > 0.1)
International (n = 19) 0% (0) 0% (0) 5.26% (1) 5.26% (1) 0% (0) NS
Professional (n = 13) 7.7% (1) 0% (0) 0% (0) 0% (0) 0% (0) NS
Semiprofessional (n = 18) 16.7% (3) 5.6% (1) 5.6% (1) 0% (0) 0% (0) NS
Between competition levels NS NS NS NS NS
200 + GC (n = 50) 2.0% (1) 0% (0) 2.0% (1) 2.0% (1) 0% (0) NS (p > 0.6)
International (n = 19) 0% (0) 0% (0) 5.26% (1) 5.26% (1) 0% (0) NS
Professional (n = 13) 0% (0) 0% (0) 0% (0) 0% (0) 0% (0) NS
Semiprofessional (n = 18) 5.6% (1) 0% (0) 0% (0) 0% (0) 0% (0) NS
Between competition levels NS NS NS NS NS
Cochran's Q level across all GC for each individual competition phase (df = 5)
International Up to 20, Q = 46.67, p < 0.001 20–40 40–60 NS Up to 20 and 20-40
Q = 23.48 Q = 15.10 Q = 36.66
p < 0.001 p = 0.01 p < 0.001
Professional NS 20–40 20-40 and 40-60 20–40 Up to 20 and 20-40
Q = 11.82 Q = 16.97 Q = 19.66 Q = 14.33
p = 0.03 p < 0.01 p < 0.001 p = 0.01
Semiprofessional NS 40–60 NS Up to 20 Up to 20
Q = 18.41 Q = 15.00 Q = 22.54
p < 0.01 p = 0.01 p < 0.001
*Presented as frequency percentage (absolute number) Q= Cochran's Q; NS = not significant; C2 = chi-square; GC = ground contact.
†Significantly different to other competition groups for that phase.

Frequency and Rest

There were no differences in weekly session count, intersession rest, or precompetition rest between competition levels, or sports (p > 0.05). However, there was a significant difference between competition levels for interset rest time (Table 2; p < 0.05), but not sport.

Load Determination and Intensity

There was no difference between competition levels or sport categories for sessional load determination (p > 0.05), with the majority, 45.9% (n = 28), electing to use GC, 27.9% (n = 17) using subjective scores and athlete wellness, 14.8% (n = 9) using performance output, and 11.5% (n = 7) using a combination of quantitative, subjective, and GC considerations. There was, however, a significant difference between competition levels for average program intensity (p = 0.026; C2 = 10.98, df = 4), but not direction (p > 0.05). Professional practitioners were significantly less likely to report using low-intensity programs, compared to semiprofessional practitioners (3.3% [n = 1] vs. 24% [n = 12], p = 0.03). Of international practitioners, 9.5% (n = 4) reported prescribing low-intensity programs. In comparison, 54.8% (n = 23) and 35.7% (n = 15) of international practitioners, 43.3% (n = 13) and 53.3% (n = 16) of professional practitioners, and 50.0% (n = 25) and 26.0% (n = 13) of semiprofessional practitioners reported moderate-intensity and high-intensity programs, respectively. There were also significant differences for quantifying plyometric intensity, regulating intensity, and loaded intensities ranges for horizontal exercises between competitions (p < 0.05, Figure 5).

Figure 5.
Figure 5.:
Percentage of responses by competition levels for methods of quantifying, regulating, and adding intensity for vertical and horizontal exercises.

Exercise Choice

In terms of combined plyometric use with other exercise modalities, 78.7% (n = 48) reported resistance training, 31.1% (n = 19) eccentric training, 9.8% (n = 6) gymnastics, 68.9% (n = 42) using weightlifting, and 62.3% (n = 38) sprint training. There were no significant differences between competition level or sport category (p > 0.05).

By contrast, exercise choice highlighted significant differences across competition level and sport categories (p < 0.05). For the single-leg DJ (SLDJ), 47.6% (n = 10) of international-level practitioners reported using this exercise compared to only 20.0% (n = 3) of professional and 16.0% (n = 4) of semiprofessional practitioners (p = 0.043). Similar nonsignificant trends could be seen for bilateral vertical (p = 0.055) and horizontal DJ (p = 0.059), and SL box jump downs (p = 0.060). Across sports, mixed sport categories were significantly less likely to use countermovement jump (CMJ), whereas field team sports and mixed sports were less likely to use SL box jump downs, and individual sports were less likely to use SL hurdle jumps (p < 0.05). Differences in commonly used exercises across sports are shown in Figure 6.

Figure 6.
Figure 6.:
Percentage of responses for exercise choice for vertical and horizontal exercises across competition levels and sport categories.

Training Direction

Overwhelmingly, 68.9% (n = 42) of all respondents reported regularly combining both horizontal and vertical components, whereas 27.9% (n = 17) predominately used directionally specific training sessions, and 3.3% (n = 2) of practitioners did not provide an answer. Interestingly, there was a significant difference between the average amount of time spent using vertical (54.8 ± 15.9%) and horizontal exercises (43.0 ± 15.2%) (p < 0.01). Similarly, the proportion of a program spent in bilateral as opposed to unilateral exercises significantly differed between vertical and horizontal axes, with practitioners reportedly spending more time bilaterally during vertical exercises than horizontal exercises (58.4 ± 17.1% vs. 48.0 ± 20.4%; t(60) = 19.3, p < 0.001). Across one set, there were no differences in GC rep ranges between vertical and horizontal exercises (p > 0.05). The majority of practitioners reported using low rep ranges: 16.4% (n = 10) and 21.3% (n = 13) reported 1–3 GC for vertical and horizontal exercises; 67.2% (n = 41) and 52.5% (n = 32) reported 3–6; and 9.8% (n = 6) and 18% (n = 11) reported 10–20 GC per set. There were no differences between sport category or competition level (p > 0.05). Similarly, there were no differences between average program intensity and direction, with 11.5% (n = 7) and 16.4% (n = 10) reporting low average intensity for vertical and horizontal programming, 52.5% (n = 32) and 45.9% (n = 28) reporting moderate average intensity, and 36.1% (n = 22) and 37.7% (n = 23) reporting high average intensity for vertical and horizontal plyometrics.

Discussion

The primary aim of this investigation was to better understand strength and conditioning practitioner's perspectives and implementation of plyometrics while obtaining more clarity on how well their reported programs match current literary recommendations. The primary finding showed several differences in reported programs compared to previous literature, most notably with lower sessional volume loads. The secondary aim was to investigate trends in programming across different competition levels, sport categories, and training axes, in which reported findings highlighted discernible trends for all 3 considerations, but more so for competition level than for sport category.

Several reported findings from this survey differ from literary recommendations. Most notably, sessional GC were considerably lower than previous recommendations (10,16,27). Very few practitioners in the current investigation reported using frequently researched moderate-high volumes (>100) regularly with their athletes (31,33). Practically speaking, >60 GC per session may offer diminishing returns for athletes working to maintain a multifaceted athletic profile. Indeed, previous session volumes of >100 have left athletes feeling sore for 5–7 days, hindering the athlete's ability to compete on a weekly basis (19). More recently, investigations have reported equivocal benefit from high-volume and low-volume protocols, questioning the need for increased volumes (7,15). In fact, sessional volumes of just 40 SLDJ have demonstrated an effective stimulus for improving sprint performance in elite athletes (12). Such findings highlight the need for further research surrounding the optimal dose response, particularly in well-trained athletes.

In contrast with published evidence, most practitioners (49.2–78.7%) did not require athletes to possess a minimum strength or sport experience requirement before starting plyometric training, and only 11% of practitioners cited injury as a limitation. Instead, many practitioners reported progression, movement screens, and modifications as key characteristics to successful plyometric training. Consensus surrounds the frequency of training with the majority of literature and practitioners reporting twice weekly for the greatest training efficiency (11). However, some authors suggest 72 over 48 hours of rest between sessions for maximal velocity, if training on sand (3). Interestingly, although quite prevalent in research, only 26% of practitioners reported using tuck jump as a common exercise. From this survey, it is difficult to say whether this cohort believed it to be suboptimal, difficult to execute, or just opted for different exercises. Kinetic analysis of plyometric exercises suggests the tuck jump may be of lower priority to practitioners, having greater takeoff ground reaction forces, but slower time to take off than DJ, and lesser power, jump height, and eccentric velocity than both CMJ and DJ varieties (14). Some debate exists around its viability as an injury screen (29). The results provide a rationale for researchers to consider dissimilarities for future investigations.

Reported findings demonstrate unique competition-specific programming considerations. Both international and professional practitioners tended to have greater coaching, plyometric training, and athlete experience than semiprofessional and amateur practitioners. One can assume practitioners working in elevated competitions with greater stakes will typically have athletes and coaching staff with more coaching experience; however, this relationship was even stronger for plyometric training that emphasizes the importance of identifying optimal practice.

Interestingly, reported limitations offer some insight into competition-level programming considerations, with each increasing level offering more resources, specific scheduling constructs, and unique constraints. International practitioners were more likely to report no limitations, citing the ability to vary the nature of the drill to accommodate the athlete as an important characteristic. By contrast, professional-level practitioners were more likely to cite sport-specific limitations such as other coach's requirements and practice times that can negate training stimulus, total workloads, and postgame fatigue. Furthermore, semiprofessional practitioners were most likely to report lack of resources as a limitation. Interestingly, expert practitioners have been identified by their ability to effectively coach large groups while still tending to individual needs, and prescribing athlete-based modifications that are easily understood (28). This suggests that limitations may be a facet of coaching capability, subsiding as a practitioner gains more experience. Alternatively, competition-level differences in workload, athlete ability, schedules, and resources may be important drivers for programming decisions. Professional- and semiprofessional-level practitioners were less likely to use relative loading to modify vertical and horizontal intensity compared to international practitioners, presumably due to added resources and setup time required. Furthermore, semiprofessional practitioners were more likely to use primarily bodyweight horizontal exercises, and only 4.0% (n = 1), compared to 40% (n = 6) of professional and 40% (n = 8) international practitioners, reported using added intensities of 9–12%, despite the fact that some authors deem this load to be optimal for improving lower-body power (9).

Overall, weeks of plyometric training per year across competition levels were almost identical (∼24 weeks); however, differences existed in the periodization across different competition phases, highlighting unique athlete characteristics. International-level practitioners were more likely to program 1–4 and >5 weeks of plyometrics during late competition and playoff periods, and nonsignificant trends followed a similar pattern during other in-season competition phases. Conversely, international practitioners tended to program less plyometrics during off-season periods. Sporadic schedules, heightened competition, high workloads, and sufficient strength may prime athlete to withstand and benefit from more plyometric training especially during later-season periods. Alternatively, professional athletes often endure lengthy seasons with frequent (1–3x weekly) contests, where fatigue-induced performance decrements in later competition phases is well reported (5). By contrast, reported findings suggest that semiprofessional practitioners may focus more on developmental athlete progression, using exercise difficulty to quantify exercise intensity, and tending to use more low-intensity programs (24 vs. 5% professional and 0% international practitioners). In addition, semiprofessional practitioners were more likely to program higher session volumes during the off-season period, suggesting that increasing work capacity and SSC tissue resiliency may be a priority for lesser-trained athletes (25). However, not one international-level practitioner reported programming >40 GC during off-season. The findings may reflect the high level of intensity during the competitive season, requiring considerably reduced training volumes in off-season periods. Alternatively, considering the caliber of competition, athletes may instead retain high MTU capacity, potentially allowing for more advanced plyometric exercises such as SLDJ and requiring less volume.

The reported findings demonstrated differences between sport categories mainly in exercise choice and training surface. Although there were differences in training surface between competition levels as well, these results are more likely a factor of uneven professional individual sport group frequencies, rather than a true representation of competition-level characteristics. Not surprisingly, training surface typically fell in line with training availability, field-sport athletes reporting turf and grass more so than individual sport athletes.

Differences in exercise choice may reflect kinematic characteristics relating to that sport. For example, non-field team sports (i.e., court and rink) were most likely to use horizontal DJs, single-leg box jump down, single-leg hurdle hop, and single-leg hurdle bounding, and trended similar for the SLDJ. Considering the fact that these sports involve frequent short sprints and substantial change-of-direction demands, these athletes will rely heavily on eccentric force absorption and single-leg power during deceleration and reacceleration. Thus, practitioners may preferentially choose eccentric and single-leg variations to accommodate sport-specific needs (26).

The reported findings demonstrate subtle differences in vertical vs. horizontal program details. Results showed practitioners typically used ∼10% more vertical exercises in their program and were more likely to use bilateral vertical exercises as opposed to horizontal exercises. This may be a result of vertical exercises historically being researched to a greater extent or reference to subjective perception of traditional bilaterally based CMJ compared to unilaterally based horizontal sprinting athlete assessments. Proponents of the force-vector theory suggest training with respect to specific characteristics of jumping and sprinting, for instance, using unilateral exercises performed horizontally to will preferentially improve sprint performance (18). By contrast, unilateral hops performed vertically have also been shown to preferentially increase speed and explosive power compared to their bilateral counterparts (26). However, some horizontally oriented exercises may cause more stress than commonly prescribed vertical exercises due to added anterior-posterior forces and pelvic stability, and thus may require less volume (24).

As with any study, this project is not without limitations. Although efforts were taken to seek advice from qualitative research experts, and multiple pilot trials were conducted with elite strength and conditioning practitioners to ensure answers provided matched the question intent, no formal reliability analysis was conducted. In addition, low sample sizes from certain countries primarily prevented any cultural analysis. However, that does not eliminate the potential for societal differences in perceived efficacy or programming styles. The impact of culture and ethnicity on sport management, participation, and training practices is well understood (40). Moreover, although anonymity was prioritized, no further probing or interviewing to clarify vague or nonresponses was able to occur. Finally, due to the nature of individual reports, this study can only comment on the perceived efficacy and reported programming practices of the respondents. Future studies should investigate reported information through experimentally designed protocols to determine optimal training practices and to further bridge the disconnect between theory and practice.

Practical Applications

Practitioners seem to use significantly lower plyometric training volumes than what is currently recommended in the literature. Researchers should consider this observation when formulating plyometric program interventions that are both beneficial and ecologically valid. In addition, practitioners would benefit from researchers providing more comprehensive reporting on monitoring tools including GCT for specific exercises, and relevant force-time or velocity-based metrics for improved programming and periodization. Our reported findings additionally allude to competition-level characteristics and specific programming considerations that seem to be more prevalent than across sports. Particularly, periodization across competition phases, horizontal intensities, and the inclusion of SLDJ indicate unique considerations between practitioners working in international, professional, and semiprofessional or amateur competitions. Finally, training differences also exist in vertical and horizontal programming strategies, which may reflect sport-specific kinematic characteristics, an exercise progression spectrum, or coaching familiarity. Investigating these reported programming practices is necessary to provide ecologically valid recommendations to help bridge the gap between theory and real-world applications.

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Keywords:

plyometrics; programming; practitioner; knowledge transfer

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