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Background Although performance of the Nordic hamstring exercise (NHE) has been shown to elicit adaptations that may reduce hamstring strain injury (HSI) risk and occurrence, compliance in NHE interventions in professional soccer teams is low despite a high occurrence of HSI in soccer. A possible reason for low compliance is the high dosages prescribed within the recommended interventions. The aim of this review was to investigate the effect of NHE-training volume on eccentric hamstring strength and biceps femoris fascicle length adaptations. Methods A literature search was conducted using the SPORTDiscus, Ovid, and PubMed databases. A total of 293 studies were identified prior to application of the following inclusion criteria: (1) a minimum of 4 weeks of NHE training was completed; (2) mean ± standard deviation (SD) pre- and post-intervention were provided for the measured variables to allow for secondary analysis; and (3) biceps femoris muscle architecture was measured, which resulted in 13 studies identified for further analysis. The TESTEX criteria were used to assess the quality of studies with risk of bias assessment assessed using a fail-safe N (Rosenthal method). Consistency of studies was analysed using I2 as a test of heterogeneity and secondary analysis of studies included Hedges’ g effect sizes for strength and muscle architecture variables to provide comparison within studies, between-study differences were estimated using a random-effects model. Results A range of scores (3–11 out of 15) from the TESTEX criteria were reported, showing variation in study quality. A ‘low risk of bias’ was observed in the randomized controlled trials included, with no study bias shown for both strength or architecture (N = 250 and 663, respectively; p I2 = 62.49%) and muscle architecture (I2 = 88.03%). Within-study differences showed that following interventions of ≥ 6 weeks, very large positive effect sizes were seen in eccentric strength following both high volume (g = 2.12) and low volume (g = 2.28) NHE interventions. Similar results were reported for changes in fascicle length (g ≥ 2.58) and a large-to-very large positive reduction in pennation angle (g ≥ 1.31). Between-study differences were estimated to be at a magnitude of 0.374 (p = 0.009) for strength and 0.793 (p Conclusions Reducing NHE volume prescription does not negatively affect adaptations in eccentric strength and muscle architecture when compared with high dose interventions. These findings suggest that lower volumes of NHE may be more appropriate for athletes, with an aim to increase intervention compliance, potentially reducing the risk of HSI.

Buckner et al. [1] have submitted a letter in response to our recent review [2] on the general adaptation syndrome (GAS) and its application to training periodization. As Buckner et al. state, this topic deserves fair and thorough discussion from multiple perspectives, and we thank them for the opportunity to continue such dialogue. Their letter restates many of the points in their original reviews [3, 4], which we addressed in our manuscript. Nevertheless, we will address the main points of their letter to provide further clarity on how the GAS does in fact serve as an appropriate mechanistic model to conceptualize training periodization.

Correction to: Sports Medicine https://doi.org/10.1007/s40279-019-01178-7

The sport of American football (AmF) exposes athletes to high-velocity movements and frequent collisions during competition and training, placing them at risk of contact and non-contact injury. Due to the combative nature of the game, the majority of injuries are caused by player contact; however, a significant number are also non-contact soft-tissue injuries. The literature suggests that this mechanism of injury can be prevented through workload monitoring and management. The recent introduction of microtechnology into AmF allows practitioners and coaches to quantify the external workload of training and competition to further understand the demands of the sport. Significant workload differences exist between positions during training and competition; coupling this with large differences in anthropometric and physical characteristics between and within positions suggests that the training response and physiological adaptations will be highly individual. Effective athlete monitoring and management allows practitioners and coaches to identify how athletes are coping with the prescribed training load and, subsequently, if they are prepared for competition. Several evidence-based principles exist that can be adapted and applied to AmF and could decrease the risk of injury and optimise athletic performance.

Although post-activation potentiation (PAP) has been extensively examined following the completion of a conditioning activity (CA), the precise effects on subsequent jump, sprint, throw, and upper-body ballistic performances and the factors modulating these effects have yet to be determined. Moreover, weaker and stronger individuals seem to exhibit different PAP responses; however, how they respond to the different components of a strength–power–potentiation complex remains to be elucidated. This meta-analysis determined (1) the effect of performing a CA on subsequent jump, sprint, throw, and upper-body ballistic performances; (2) the influence of different types of CA, squat depths during the CA, rest intervals, volumes of CA, and loads during the CA on PAP; and (3) how individuals of different strength levels respond to these various strength–power–potentiation complex components. A computerized search was conducted in ADONIS, ERIC, SPORTDiscus, EBSCOhost, Google Scholar, MEDLINE, and PubMed databases up to March 2015. The analysis comprised 47 studies and 135 groups of participants for a total of 1954 participants. The PAP effect is small for jump (effect size [ES] = 0.29), throw (ES = 0.26), and upper-body ballistic (ES = 0.23) performance activities, and moderate for sprint (ES = 0.51) performance activity. A larger PAP effect is observed among stronger individuals and those with more experience in resistance training. Plyometric (ES = 0.47) CAs induce a slightly larger PAP effect than traditional high-intensity (ES = 0.41), traditional moderate-intensity (ES = 0.19), and maximal isometric (ES = –0.09) CAs, and a greater effect after shallower (ES = 0.58) versus deeper (ES = 0.25) squat CAs, longer (ES = 0.44 and 0.49) versus shorter (ES = 0.17) recovery intervals, multiple- (ES = 0.69) versus single- (ES = 0.24) set CAs, and repetition maximum (RM) (ES = 0.51) versus sub-maximal (ES = 0.34) loads during the CA. It is noteworthy that a greater PAP effect can be realized earlier after a plyometric CA than with traditional high- and moderate-intensity CAs. Additionally, shorter recovery intervals, single-set CAs, and RM CAs are more effective at inducing PAP in stronger individuals, while weaker individuals respond better to longer recovery intervals, multiple-set CAs, and sub-maximal CAs. Finally, both weaker and stronger individuals express greater PAP after shallower squat CAs. Performing a CA elicits small PAP effects for jump, throw, and upper-body ballistic performance activities, and a moderate effect for sprint performance activity. The level of potentiation is dependent on the individual’s level of strength and resistance training experience, the type of CA, the depth of the squat when this exercise is employed to elicit PAP, the rest period between the CA and subsequent performance, the number of set(s) of the CA, and the type of load used during the CA. Finally, some components of the strength–power–potentiation complex modulate the PAP response of weaker and stronger individuals in a different way.

Although lower-body strength is correlated with sprint performance, whether increases in lower-body strength transfer positively to sprint performance remain unclear. This meta-analysis determined whether increases in lower-body strength (measured with the free-weight back squat exercise) transfer positively to sprint performance, and identified the effects of various subject characteristics and resistance-training variables on the magnitude of sprint improvement. A computerized search was conducted in ADONIS, ERIC, SPORTDiscus, EBSCOhost, Google Scholar, MEDLINE and PubMed databases, and references of original studies and reviews were searched for further relevant studies. The analysis comprised 510 subjects and 85 effect sizes (ESs), nested with 26 experimental and 11 control groups and 15 studies. There is a transfer between increases in lower-body strength and sprint performance as indicated by a very large significant correlation (r = −0.77; p = 0.0001) between squat strength ES and sprint ES. Additionally, the magnitude of sprint improvement is affected by the level of practice (p = 0.03) and body mass (r = 0.35; p = 0.011) of the subject, the frequency of resistance-training sessions per week (r = 0.50; p = 0.001) and the rest interval between sets of resistance-training exercises (r = −0.47; p ≤ 0.001). Conversely, the magnitude of sprint improvement is not affected by the athlete’s age (p = 0.86) and height (p = 0.08), the resistance-training methods used through the training intervention, (p = 0.06), average load intensity [% of 1 repetition maximum (RM)] used during the resistance-training sessions (p = 0.34), training program duration (p = 0.16), number of exercises per session (p = 0.16), number of sets per exercise (p = 0.06) and number of repetitions per set (p = 0.48). Increases in lower-body strength transfer positively to sprint performance. The magnitude of sprint improvement is affected by numerous subject characteristics and resistance-training variables, but the large difference in number of ESs available should be taken into consideration. Overall, the reported improvement in sprint performance (sprint ES = −0.87, mean sprint improvement = 3.11 %) resulting from resistance training is of practical relevance for coaches and athletes in sport activities requiring high levels of speed.