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We examined performance across one menstrual cycle (MC) and 3 weeks of hormonal contraceptives (HC) use to identify whether known fluctuations in estrogen and progesterone/progestin are associated with functional performance changes. National Rugby League Indigenous Women's Academy athletes [n = 11 naturally menstruating (NM), n = 13 using HC] completed performance tests [countermovement jump (CMJ), squat jump (SJ), isometric mid‐thigh pull, 20 m sprint, power pass and Stroop test] during three phases of a MC or three weeks of HC usage, confirmed through ovulation tests alongside serum estrogen and progesterone concentrations. MC phase or HC use did not influence jump height, peak force, sprint time, distance thrown or Stroop effect. However, there were small variations in kinetic and kinematic CMJ/SJ outputs. NM athletes produced greater mean concentric power in MC phase four than one [+0.41 W·kg−1 (+16.8%), p = 0.021] during the CMJ, alongside greater impulse at 50 ms at phase one than four [+1.7 N·s (+4.7%), p = 0.031] during the SJ, without differences between tests for HC users. Among NM athletes, estradiol negatively correlated with mean velocity and power (r = −0.44 to −0.50, p < 0.047), progesterone positively correlated with contraction time (r = 0.45, p = 0.045), and both negatively correlated with the rate of force development and impulse (r = −0.45 to −0.64, p < 0.043) during the SJ. During the CMJ, estradiol positively correlated to 200 ms impulse (r = 0.45, p = 0.049) and progesterone to mean power (r = 0.51, p = 0.021). Evidence of changes in testing performance across a MC, or during active HC use, is insufficient to justify “phase‐based testing”; however, kinetic or kinematic outputs may be altered in NM athletes. [ABSTRACT FROM AUTHOR]

Background: Athletes can face scenarios in which they are confined to bed rest (e.g., due to injury or illness). Existing research in otherwise healthy individuals indicates that those entering bed rest with the greatest physical performance level might experience the greatest performance decrements, which indirectly suggests that athletes might be more susceptible to the detrimental consequences of bed rest than general populations. Therefore, a comprehensive understanding of the effects of bed rest might help guide the medical care of athletes during and following bed rest. Objective: This systematic and narrative review aimed to (1) establish the evidence for the effects of bed rest on physical performance in athletes; (2) discuss potential countermeasures to offset these negative consequences; and (3) identify the time-course of recovery following bed rest to guide return-to-sport rehabilitation. Methods: This review was performed using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. Four databases were searched (SPORTDiscus, Web of Science, Scopus, and MEDLINE/PubMed) in October of 2022, and studies were included if they were peer-reviewed investigations, written in English, and investigated the effects of horizontal bed rest on changes in physical capacities and qualities in athletes (defined as Tier 3–5 participants). The reporting quality of the research was assessed using a modified version of the Downs & Black checklist. Furthermore, findings from studies that involved participants in Tiers 1–2 were presented and synthesized using a narrative approach. Results: Our systematic review of the literature using a rigorous criterion of 'athletes' revealed zero scientific publications. Nevertheless, as a by-product of our search, seven studies were identified that involved apparently healthy individuals who performed specific exercise training prior to bed rest. Conclusions: Based on the limited evidence from studies involving non-athletes who were otherwise healthy prior to bed rest, we generally conclude that (1) bed rest rapidly (within 3 days) decreases upright endurance exercise performance, likely due to a rapid loss in plasma volume; whereas strength is reduced within 5 days, likely due to neural factors as well as muscle atrophy; (2) fluid/salt supplementation may be an effective countermeasure to protect against decrements in endurance performance during bed rest; while a broader array of potentially effective countermeasures exists, the efficacy of these countermeasures for previously exercise-trained individuals requires further study; and (3) athletes likely require at least 2–4 weeks of progressive rehabilitation following bed rest of ≤ 28 days, although the timeline of recovery might need to be extended depending on the underlying reason for bed rest (e.g., injury or illness). Despite these general conclusions from studies involving non-athletes, our primary conclusion is that substantial effort and research is still required to quantify the effects of bed rest on physical performance, identify effective countermeasures, and provide return-to-sport timelines in bona fide athletes. Trial Registration Number and Date of Registration: Registration ID: osf.io/d3aew; Date: October 24, 2022. [ABSTRACT FROM AUTHOR]

Edwards, T, Weakley, J, Banyard, HG, Cripps, A, Piggott, B, Haff, GG, and Joyce, C. Longitudinal development of sprint performance and force-velocity-power characteristics: influence of biological maturation. J Strength Cond Res 37(11): 2178-2184, 2023--This study was designed to investigate the influence of biological maturation on the longitudinal development of sprint performance. Thirty-two subjects performed 2 assessments of maximal sprint performance that were separated by 18 months. Each sprint assessment was measured through a radar gun that collected instantaneous velocity with the velocity-time data used to derive sprint times and force-velocity-power characteristics. The biological maturity of each subject was assessed using a predictive equation, and subjects were grouped according to predicted years from peak height velocity (circa-PHV: 21.0 to 1.0; post-PHV: .1.0). A 2 3 2 mixed model analysis of variance was used to assess group 3 time interactions, and paired t-tests were used to assess the longitudinal changes for each maturity group. No significant group 3 time interactions were observed for any sprint time or force-velocity-power characteristic. The circa-PHV group experienced significant within-group changes in maximal theoretical velocity (6.35 vs. 5.47%; effect size [ES] 5 1.26 vs. 0.52) and 5-m sprint time (23.63% vs. 22.94%; ES520.64 vs. 20.52) compared with the post-PHV group. There was no significant change in the magnitude of relative theoretical maximum force in either group; however, both the circa-PHV and post-PHV groups significantly improved the orientation of force production at the start of the sprint (RFmax [4.91 vs. 4.46%; ES 5 0.79 vs. 0.74, respectively]). Considering these findings, it is recommended that practitioners adopt training methods aimed to improve relative lower-limb force production, such as traditional strength training and sled pulling and pushing, to improve sprint performance and relative theoretical maximum force. [ABSTRACT FROM AUTHOR]

Background: Augmented feedback is often used during resistance training to enhance acute physical performance and has shown promise as a method of improving chronic physical adaptation. However, there are inconsistencies in the scientific literature regarding the magnitude of the acute and chronic responses to feedback and the optimal method with which it is provided. Objective: This systematic review and meta-analysis aimed to (1) establish the evidence for the effects of feedback on acute resistance training performance and chronic training adaptations; (2) quantify the effects of feedback on acute kinematic outcomes and changes in physical adaptations; and (3) assess the effects of moderating factors on the influence of feedback during resistance training. Methods: Twenty studies were included in this systematic review and meta-analysis. This review was performed using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. Four databases were searched, and studies were included if they were peer-reviewed investigations, written in English, and involved the provision of feedback during or following dynamic resistance exercise. Furthermore, studies must have evaluated either acute training performance or chronic physical adaptations. Risk of bias was assessed using a modified Downs and Black assessment tool. Multilevel meta-analyses were performed to quantify the effects of feedback on acute and chronic training outcomes. Results: Feedback enhanced acute kinetic and kinematic outputs, muscular endurance, motivation, competitiveness, and perceived effort, while greater improvements in speed, strength, jump performance, and technical competency were reported when feedback was provided chronically. Furthermore, greater frequencies of feedback (e.g., following every repetition) were found to be most beneficial for enhancing acute performance. Results demonstrated that feedback improves acute barbell velocities by approximately 8.4% (g = 0.63, 95% confidence interval [CI] 0.36–0.90). Moderator analysis revealed that both verbal (g = 0.47, 95% CI 0.22–0.71) and visual feedback (g = 1.11, 95% CI 0.61–1.61) were superior to no feedback, but visual feedback was superior to verbal feedback. For chronic outcomes, jump performance might have been positively influenced (g = 0.39, 95% CI − 0.20 to 0.99) and short sprint performance was likely enhanced (g = 0.47, 95% CI 0.10–0.84) to a greater extent when feedback is provided throughout a training cycle. Conclusions: Feedback during resistance training can lead to enhanced acute performance within a training session and greater chronic adaptations. Studies included in our analysis demonstrated a positive influence of feedback, with all outcomes showing superior results than when no feedback is provided. For practitioners, it is recommended that high-frequency, visual feedback is consistently provided to individuals when they complete resistance training, and this may be particularly useful during periods of low motivation or when greater competitiveness is beneficial. Alternatively, researchers must be aware of the ergogenic effects of feedback on acute and chronic responses and ensure that feedback is standardised when investigating resistance training. [ABSTRACT FROM AUTHOR]

Background: Repeated-sprint training (RST) involves maximal-effort, short-duration sprints (≤ 10 s) interspersed with brief recovery periods (≤ 60 s). Knowledge about the acute demands of RST and the influence of programming variables has implications for training prescription. Objectives: To investigate the physiological, neuromuscular, perceptual and performance demands of RST, while also examining the moderating effects of programming variables (sprint modality, number of repetitions per set, sprint repetition distance, inter-repetition rest modality and inter-repetition rest duration) on these outcomes. Methods: The databases Pubmed, SPORTDiscus, MEDLINE and Scopus were searched for original research articles investigating overground running RST in team sport athletes ≥ 16 years. Eligible data were analysed using multi-level mixed effects meta-analysis, with meta-regression performed on outcomes with ~ 50 samples (10 per moderator) to examine the influence of programming factors. Effects were evaluated based on coverage of their confidence (compatibility) limits (CL) against elected thresholds of practical importance. Results: From 908 data samples nested within 176 studies eligible for meta-analysis, the pooled effects (± 90% CL) of RST were as follows: average heart rate (HRavg) of 163 ± 9 bpm, peak heart rate (HRpeak) of 182 ± 3 bpm, average oxygen consumption of 42.4 ± 10.1 mL·kg−1·min−1, end-set blood lactate concentration (B[La]) of 10.7 ± 0.6 mmol·L−1, deciMax session ratings of perceived exertion (sRPE) of 6.5 ± 0.5 au, average sprint time (Savg) of 5.57 ± 0.26 s, best sprint time (Sbest) of 5.52 ± 0.27 s and percentage sprint decrement (Sdec) of 5.0 ± 0.3%. When compared with a reference protocol of 6 × 30 m straight-line sprints with 20 s passive inter-repetition rest, shuttle-based sprints were associated with a substantial increase in repetition time (Savg: 1.42 ± 0.11 s, Sbest: 1.55 ± 0.13 s), whereas the effect on sRPE was trivial (0.6 ± 0.9 au). Performing two more repetitions per set had a trivial effect on HRpeak (0.8 ± 1.0 bpm), B[La] (0.3 ± 0.2 mmol·L−1), sRPE (0.2 ± 0.2 au), Savg (0.01 ± 0.03) and Sdec (0.4; ± 0.2%). Sprinting 10 m further per repetition was associated with a substantial increase in B[La] (2.7; ± 0.7 mmol·L−1) and Sdec (1.7 ± 0.4%), whereas the effect on sRPE was trivial (0.7 ± 0.6). Resting for 10 s longer between repetitions was associated with a substantial reduction in B[La] (−1.1 ± 0.5 mmol·L−1), Savg (−0.09 ± 0.06 s) and Sdec (−1.4 ± 0.4%), while the effects on HRpeak (−0.7 ± 1.8 bpm) and sRPE (−0.5 ± 0.5 au) were trivial. All other moderating effects were compatible with both trivial and substantial effects [i.e. equal coverage of the confidence interval (CI) across a trivial and a substantial region in only one direction], or inconclusive (i.e. the CI spanned across substantial and trivial regions in both positive and negative directions). Conclusions: The physiological, neuromuscular, perceptual and performance demands of RST are substantial, with some of these outcomes moderated by the manipulation of programming variables. To amplify physiological demands and performance decrement, longer sprint distances (> 30 m) and shorter, inter-repetition rest (≤ 20 s) are recommended. Alternatively, to mitigate fatigue and enhance acute sprint performance, shorter sprint distances (e.g. 15–25 m) with longer, passive inter-repetition rest (≥ 30 s) are recommended. [ABSTRACT FROM AUTHOR]

The aim of this study was to investigate the effects of traditional, rest redistribution, and velocity-based repeated sprint training methods on repeated sprint performance, perceived effort, heart rate, and changes in force-velocity-power (FVP) profiles in male semiprofessional athletes. In a randomized crossover design, a traditional (2 sets of 6 repetitions [TRAD]), 2 different rest redistribution (4 sets of 3 repetitions [RR4] and 12 sets of 1 repetition [RR12]), and a 5% velocity loss (VL5%) (12 repetitions, with sets terminated when a 5% reduction in mean velocity had occurred) condition were completed. Mean and peak velocity, mean heart rate, and differential ratings of perceived exertion (dRPE) were measured throughout each session, while horizontal FVP profiles were assessed presession and postsession. The RR4 and RR12 conditions allowed the greatest maintenance of velocity, while the RR4, RR12, and VL5% had a moderate, significantly greater mean heart rate than the traditional condition. Trivial, nonsignificant differences between all conditions were observed in dRPE of the legs and breathlessness and FVP profiles. These findings indicate that rest redistribution can allow for greater maintenance of sprint velocity and heart rate, without altering perceived effort during repeated sprint training. In addition, velocity-loss thresholds may be a feasible method of prescription if athletes have diverse physical qualities and reductions in sprint performance during repeated sprint training are undesirable. Practitioners should consider these outcomes when designing repeated sprint training sessions because the strategic use of these methods can alter sprint performance and internal load without changing perceptions of intensity. [ABSTRACT FROM AUTHOR]

Weakley, J, Munteanu, G, Cowley, N, Johnston, R, Morrison, M, Gardiner, C, Pérez-Castilla, A, and García-Ramos, A. The criterion validity and between-day reliability of the Perch for measuring barbell velocity during commonly used resistance training exercises. J Strength Cond Res 37(4): 787–792, 2023—This study aimed to assess the criterion validity and between-day reliability (accounting for technological and biological variability) of mean and peak concentric velocity from the Perch measurement system. On 2 testing occasions, 16 subjects completed repetitions at 20, 40, 60, 80, 90, and 100% of 1-repetition maximum in the free-weight barbell back squat and bench press. To assess criterion validity, values from the Perch and a 3-dimensional motion capture system (criterion) were compared. Technological variability was assessed by determining whether the differences between the Perch and criterion for each load were comparable for both testing sessions, whereas between-day reliability with both technological and biological variability was calculated from Perch values across days. Generalized estimating equations were used to calculate R 2 and root mean square error, whereas Bland-Altman plots assessed magnitude of difference between measures. To support monitoring of athletes over time, standard error of measurement and minimum detectable changes (MDC) were calculated. There was excellent agreement between the Perch and criterion device, with mean velocity in both exercises demonstrating a mean bias ranging from −0.01 to 0.01 m·s−1. For peak velocity, Perch underestimated velocity compared with the criterion ranging from −0.08 to −0.12 m·s−1 for the back squat and −0.01 to −0.02 m·s−1 for the bench press. Technological variability between-days were all less than the MDC. These findings demonstrate that the Perch provides valid and reliable mean and peak concentric velocity outputs across a range of velocities. Therefore, practitioners can confidently implement this device for the monitoring and prescription of resistance training. [ABSTRACT FROM AUTHOR]

This cross-sectional study investigated differences in lower-body power of state and nonstate representative junior Australian football (AF) players through countermovement jump (CMJ) and squat jump (SJ) performance. A total of 627 players performed the CMJ and SJ at the end of the preseason phase over a 2-week period, with each player grouped according to their age (under 18 [U18] or under 16 [U16]), and highest competition level played (state representation and nonstate representation). One-way multivariate analysis of variance (MANOVA), follow up ANOVA's, and Cohen's d effect sizes were used to identify significant main effects and between-group differences. Statistical significance was set at α < 0.05. Significant small-to-moderate effect size differences were observed between competition level, with state U18 and U16 players recording greater CMJ and SJ height, and peak power (PP), compared with their nonstate representative peers, respectively. Similarly, significant small-to-moderate effect size differences existed between age groups, with nonstate U18 players recording greater CMJ and SJ height and PP than nonstate U16 counterparts. However, state U18 and state U16 only differed in CMJ PP. No differences were found between competition level or age groups for the difference between CMJ and SJ jump height (CMJSJdiff). Together, these findings suggest that state and nonstate representative junior AFs may have a similar ability to use the stretch-shortening cycle, despite state representative players jumping higher in the CMJ and SJ. [ABSTRACT FROM AUTHOR]

Sprint testing is commonly used to assess speed and acceleration in athletes. However, vastly different outcomes have been reported throughout the literature. These differences are likely due to the sprint timing method rather than differences in athlete ability. Consequently, this study compared different sprint starting methods on sprint time and quantified the velocity and displacement of the athlete at the moment timing is initiated. Starting in a staggered 2-point stance, 12 team sport athletes were required to accelerate 10 meters for 10 repetitions. During each repetition, 5 independent timing methods were triggered. The methods were (a) triggering a Move sensor; (b) starting 50 cm behind the line; (c) triggering a front-foot switch; (d) triggering a rear-foot switch; and (e) starting with the front foot on the line. Timing for each method was initiated at different points during the acceleration phase, and the displacement and velocity of the centroid of the pelvis at the point of timing initiation was assessed under high-speed motion capture. The Move sensor had the smallest displacement and lowest velocity at the point of timing initiation, whereas the front-foot trigger demonstrated the largest displacement and highest velocities. Trivial to very large effect size differences were observed between all methods in displacement and velocity at the point of timing initiation. Furthermore, small to very large differences in time to 5 m were found. These findings emphasize that sprint outcomes should not be compared, unless starting methods are identical. In addition, to detect real change in performance, consistent standardized protocols should be implemented. [ABSTRACT FROM AUTHOR]

Background: Compression garments are regularly worn during exercise to improve physical performance, mitigate fatigue responses, and enhance recovery. However, evidence for their efficacy is varied and the methodological approaches and outcome measures used within the scientific literature are diverse. Objectives: The aim of this scoping review is to provide a comprehensive overview of the effects of compression garments on commonly assessed outcome measures in response to exercise, including: performance, biomechanical, neuromuscular, cardiovascular, cardiorespiratory, muscle damage, thermoregulatory, and perceptual responses. Methods: A systematic search of electronic databases (PubMed, SPORTDiscus, Web of Science and CINAHL Complete) was performed from the earliest record to 27 December, 2020. Results: In total, 183 studies were identified for qualitative analysis with the following breakdown: performance and muscle function outcomes: 115 studies (63%), biomechanical and neuromuscular: 59 (32%), blood and saliva markers: 85 (46%), cardiovascular: 76 (42%), cardiorespiratory: 39 (21%), thermoregulatory: 19 (10%) and perceptual: 98 (54%). Approximately 85% (n = 156) of studies were published between 2010 and 2020. Conclusions: Evidence is equivocal as to whether garments improve physical performance, with little evidence supporting improvements in kinetic or kinematic outcomes. Compression likely reduces muscle oscillatory properties and has a positive effect on sensorimotor systems. Findings suggest potential increases in arterial blood flow; however, it is unlikely that compression garments meaningfully change metabolic responses, blood pressure, heart rate, and cardiorespiratory measures. Compression garments increase localised skin temperature and may reduce perceptions of muscle soreness and pain following exercise; however, rating of perceived exertion during exercise is likely unchanged. It is unlikely that compression garments negatively influence exercise-related outcomes. Future research should assess wearer belief in compression garments, report pressure ranges at multiple sites as well as garment material, and finally examine individual responses and varying compression coverage areas. [ABSTRACT FROM AUTHOR]

This study aimed to investigate the effect of countermovement depth on the magnitude of the countermovement jump (CMJ) derived reactive strength index modified (RSImod), and to compare the RSImod between the CMJ performed with a self-preferred knee flexion angle (CMJpref) and the CMJ performed from a pre-determined knee flexion angle (CMJrefer) with the countermovement depth more similar to the CMJpref. Sixteen subjects (11 males and 5 females; age 25.1 ± 6.3 years, body mass 69.7 ± 10.2 kg, body height 172.9 ± 8.1 m) randomly performed in a single session the CMJpref and CMJs from five pre-determined knee flexion angles (60°, 75°, 90°, 105°, and 120°). Our results showed that lower knee flexion angles were generally associated with greater RSImod values with the CMJ performed at 60° showing the greatest RSImod (P ≤ 0.049; effect size [ES] range = 0.19–0.63). The greatest RSImod for the CMJ performed at 60° was caused by the proportionally lower values of the time to take-off (ES range = 0.65–1.91) compared to the decrease observed in jump height (ES range = 0.11–0.25). The RSImod was higher for the CMJpref compared to the CMJrefer (P < 0.001; ES = 0.34) due to a higher jump height (P = 0.021; ES = 0.14) and reduced time to take-off (P < 0.001; ES = 0.85). These results indicate that practitioners should be careful when interpreting an individual's changes in RSImod when the countermovement depth is not similar across the testing sessions. However, since the use of pre-determined knee flexion angles negatively impacts the RSImod, we encourage practitioners to use the CMJpref but only compare the RSImod when CMJs are performed using consistent countermovement depths. [ABSTRACT FROM AUTHOR]

Background: Netball is the one of the most popular women's sports in the world. Since gaining professional status in 2008 there has been a rapid growth in research in the applied sports science and medicine of the sport. A scoping review of the area would provide practitioners and researchers with an overview of the current scientific literature to support on-court performance, player welfare and reduce injury. Objective: The primary objective was to identify the current research on the applied sports science and medicine of netball. Additionally, the article provides a brief summary of the research in each topic of sports science and medicine in netball and identifies gaps in the current research. Methods: Systematic searches of PubMed, SPORTDiscus, MEDLINE and CINAHL were undertaken from earliest record to Dec 2020 and reference lists were manually searched. The PRISMA-ScR protocol was followed. Studies were eligible for inclusion if they investigated netball as a sport or the applied sport science and medicine of netball athletes. Results: 962 studies were identified in the initial search, 150 of which met the inclusion criteria. Injury was the most highly investigated sport science and medicine topic (n = 45), followed by physical qualities (n = 37), match characteristics (n = 24), biomechanics (n = 15), psychology (n = 13), fatigue and recovery (n = 9), training load (n = 4) and nutrition (n = 3). A range of cohorts were used from school to elite and international standards. All cohorts were female netballers, except for one study. A rapid growth in studies over recent years was demonstrated with 65% of studies published in the last decade. There still remains gaps in the literature, with a low evidence base for nutrition, training load and fatigue and recovery. Conclusion: This scoping review summarises the current evidence base and key findings that can be used in practice to enhance the applied sport science and medical support to netball athletes across a range of playing standards, and support the growth of the sport. It is evident that netball as a sport is still under-researched. [ABSTRACT FROM AUTHOR]

This study aimed to investigate the influence of chronological age and maturation status on sprint acceleration characteristics in junior Australian football (AF) players. Biological maturity of 109 subjects was assessed and subjects were grouped according to predicted years from peak height velocity (PHV) (pre-, mid-, and post-PHV) and chronological age (13 years, 14 years, and 15 years). A one-way multivariate analysis of variance and magnitude-based decisions were used to determine between-group differences. Instantaneous velocity was measured during two maximal 30m sprints via radar gun with the velocity-time data used to derive the force, velocity, and power characteristics. Chronologically, the greatest differences were observed between the 13 and 14 year old groups with the latter group producing likely greater relative maximum power (Pmax) (ES[effect size]=0.44) and theoretical maximal velocity (V0) (ES=0.49). The post-PHV group likely demonstrated a greater ability to apply force at faster velocity (V0; ES=0.59) and orient the force in a horizontal direction (Drf%; ES=-0.49) than the mid-PHV group. No differences in relative theoretical maximal force (F0) were observed between groups. Considering the findings, practitioners should aim to improve relative lower limb strength through heavy sled push or sled pulls and traditional strength training exercises to improve relative F0. [ABSTRACT FROM AUTHOR]

Background: Monitoring resistance training has a range of unique difficulties due to differences in physical characteristics and capacity between athletes, and the indoor environment in which it often occurs. Traditionally, methods such as volume load have been used, but these have inherent flaws. In recent times, numerous portable and affordable devices have been made available that purport to accurately and reliably measure kinetic and kinematic outputs, potentially offering practitioners a means of measuring resistance training loads with confidence. However, a thorough and systematic review of the literature describing the reliability and validity of these devices has yet to be undertaken, which may lead to uncertainty from practitioners on the utility of these devices. Objective: A systematic review of studies that investigate the validity and/or reliability of commercially available devices that quantify kinetic and kinematic outputs during resistance training. Methods: Following PRISMA guidelines, a systematic search of SPORTDiscus, Web of Science, and Medline was performed; studies included were (1) original research investigations; (2) full-text articles written in English; (3) published in a peer-reviewed academic journal; and (4) assessed the validity and/or reliability of commercially available portable devices that quantify resistance training exercises. Results: A total of 129 studies were retrieved, of which 47 were duplicates. The titles and abstracts of 82 studies were screened and the full text of 40 manuscripts were assessed. A total of 31 studies met the inclusion criteria. Additional 13 studies, identified via reference list assessment, were included. Therefore, a total of 44 studies were included in this review. Conclusion: Most of the studies within this review did not utilise a gold-standard criterion measure when assessing validity. This has likely led to under or overreporting of error for certain devices. Furthermore, studies that have quantified intra-device reliability have often failed to distinguish between technological and biological variability which has likely altered the true precision of each device. However, it appears linear transducers which have greater accuracy and reliability compared to other forms of device. Future research should endeavour to utilise gold-standard criterion measures across a broader range of exercises (including weightlifting movements) and relative loads. [ABSTRACT FROM AUTHOR]

When performing resistance training, verbal kinematic feedback and visual kinematic feedback are known to enhance performance. In addition, providing verbal encouragement can assist in the attenuation of fatigue. However, the effects of these forms of feedback have never been compared. Consequently, this study aimed to quantify the effects of verbal kinematic feedback and visual kinematic feedback, and verbal encouragement on barbell velocity during the back squat. Furthermore, changes in performance were related to individualreported conscientiousness. Twelve semiprofessional rugby union players volunteered to participate in the study that consisted of the subjects completing a set of the barbell back squat across 4 conditions (i.e., no-feedback [control], verbal feedback of kinematic information [verbal], visual feedback of kinematic information [visual], and verbal encouragement [encouragement]). In addition, participants completed a questionnaire before the study to assess conscientiousness. Magnitude-based inferences were used to assess differences between conditions, whereas Spearman's rank correlation coefficient was used to assess relationships between conscientiousness and changes in barbell velocity. All 3 forms of feedback showed almost certain improvements in barbell velocity, while differences between interventions were likely to very likely trivial. Changes in barbell velocity showed small to large inverse relationships with conscientiousness. These findings suggest that practitioners should supply kinematic feedback (verbally or visually) or, when technology is not available, provide athletes with encouraging statements while resistance training. Verbal encouragement may be of greatest benefit for individuals who demonstrate low levels of conscientiousness. Given these findings, practitioners are advised to use either technology or verbal encouragement to manipulate acute training outcomes. [ABSTRACT FROM AUTHOR]

The aim of this study was to assess the criterion validity, interunit reliability (accounting for technological and biological variance), and between-day reliability of a novel optic laser device (FLEX) for quantifying mean concentric velocity. To assess the validity against a three-dimensional motion capture system and interunit reliability with both technological and biological variation, 18 men and women completed repetitions at 20, 40, 60, 80, 90, and 100% of one repetition maximum in the free-weight barbell back squat and bench press. To assess interunit (technological only) reliability, a purpose-built, calibrated rig completed a set protocol with 2 devices. To assess between-day reliability of the technology, the same protocol was repeated 21 days later. Standardized bias, typical error of the estimate (TEE; %), and Pearson's correlation coefficient (r) were used to assess validity, whereas typical error and coefficient of variation (CV%) were calculated for reliability. Overall, TEE (±90 CL) between the FLEX and criterion measure was 0.03 (±0.004) and 0.04 (±0.005) m·s−1 in the back squat and bench press, respectively. For measures of reliability, overall interunit technological variance (CV% [± 90% confidence interval]) was 3.96% (3.83–4.12) but increased to 9.82% (9.31–10.41) and 9.83% (9.17–10.61) in the back squat and bench press, respectively, when biological variance was introduced. Finally, the overall between-day reliability was 3.77% (3.63–3.91). These findings demonstrate that the FLEX provides valid and reliable mean concentric velocity outputs across a range of velocities. Thus, practitioners can confidently implement this device for the monitoring and prescription of resistance training loads. [ABSTRACT FROM AUTHOR]

The aim of this study was to investigate the differences and long-term reliability in perceptual, metabolic, and neuromuscular responses to velocity loss resistance training protocols. Using a repeated, counterbalanced, crossover design, twelve team-sport athletes completed 5-sets of barbell back-squats at a load corresponding to a mean concentric velocity of ~0.70 m·s−1. On different days, repetitions were performed until a 10%, 20% or 30% velocity loss was attained, with outcome measures collected after each set. Sessions were repeated after four-weeks. There were substantial between-protocol differences in post-set differential ratings of perceived exertion (dRPE, i.e., breathlessness and leg muscles, AU) and blood lactate concentration (B[La], mmol·L−1), such that 30%>20%>10% by small to large magnitudes. Differences in post-set countermovement jump (CMJ) variables were small for most variables, such that 30%<20%<10%. Standard deviations representing four-week variability of post-set responses to each protocol were: dRPE, 8–11; B[La], 0.8–1.0; CMJ height, 1.6–2.0; CMJ PPO, 1.0–1.8; CMJ PCV, 0.04–0.06; CMJ 100ms-Impulse, 5.7–11.9. Velocity loss thresholds control the magnitude of perceptual, metabolic, and neuromuscular responses to resistance training. For practitioners wanting to reliably prescribe training that can induce a given perceptual, metabolic, or neuromuscular response, it is strongly advised that velocity-based thresholds are implemented. [ABSTRACT FROM AUTHOR]

Training that is efficient and effective is of great importance to an athlete. One method of improving efficiency is by incorporating supersets into resistance training routines. However, the structuring of supersets is still unexplored. Therefore, the purpose of this study was to assess the effects of agonist-antagonist (A-A), alternate peripheral (A-P), and similar biomechanical (SB) superset configurations on rate of perceived exertion (RPE), kinetic and kinematic changes during the bench press. Ten subjects performed resistance training protocols in a randomized-crossover design, with magnitude-based inferences assessing changes/differences within and between protocols. Changes in rate of perceived exertion were very likely and almost certainly greater in the A-P and SB protocols when compared with the A-A, whereas all superset protocols had very likely to almost certain reductions in mean velocity and power from baseline. Reductions in mean velocity and power were almost certainly greater in the SB protocol, with differences between the A-A and A-P protocols being unclear. Decreases in peak force were likely and almost certain in the A-A and SB protocols respectively, with changes in A-P being unclear. Differences between these protocols showed likely greater decreases in SB peak forces when compared to A-A, with all other superset comparisons being unclear. This study demonstrates the importance of exercise selection when incorporating supersets into a training routine. It is suggested that the practitioner uses A-A supersets when aiming to improve training efficiency and minimize reductions in kinetic and kinematic output of the agonist musculature while completing the barbell bench press. [ABSTRACT FROM AUTHOR]

It is unknown whether instantaneous visual feedback of resistance training outcomes can enhance barbell velocity in younger athletes. Therefore, the purpose of this study was to quantify the effects of visual feedback on mean concentric barbell velocity in the back squat and to identify changes in motivation, competitiveness, and perceived workload. In a randomized-crossover design (Feedback vs. Control), feedback of mean concentric barbell velocity was or was not provided throughout a set of 10 repetitions in the barbell back squat. Magnitude-based inferences were used to assess changes between conditions, with almost certainly greater differences in mean concentric velocity between the Feedback (0.70 ± 0.04 m⋅s-1) and Control (0.65 ± 0.05 m⋅s-1) observed. In addition, individual repetition mean concentric velocity ranged from possibly (repetition number 2: 0.79 ± 0.04 vs. 0.78 ± 0.04 m⋅s-1) to almost certainly (repetition number 10: 0.58 ± 0.05 vs. 0.49 ± 0.05 m⋅s-1) greater when provided feedback, whereas almost certain differences were observed in motivation, competitiveness, and perceived workload, respectively. Providing adolescent male athletes with visual kinematic information while completing resistance training is beneficial for the maintenance of barbell velocity during a training set, potentially enhancing physical performance. Moreover, these improvements were observed alongside increases in motivation, competitiveness, and perceived workload providing insight into the underlying mechanisms responsible for the performance gains observed. Given the observed maintenance of barbell velocity during a training set, practitioners can use this technique to manipulate training outcomes during resistance training. [ABSTRACT FROM AUTHOR]

Adolescent rugby players benefit from the implementation of resistance training. However resistance training practices and how they influence short-term physical change is unknown. Therefore, the purpose of this study was to quantify resistance training practices, evaluate physical development, and relate these changes to resistance training variables across 12 weeks in adolescent rugby union players. Thirty-five male adolescent rugby union players participated in the study with subjects completing an anthropometric and physical testing battery before and after a 12-week in-season mesocycle. Subjects recorded resistance training frequency, exercises, repetitions, load, minutes, and rating of perceived exertion for each session using weekly training diaries during the 12-week period. Paired sample t tests and Cohen's d effect sizes were used to assess change, whereas Pearson correlation coefficients assessed relationships between variables. Resistance training practices were variable, although significant (p ≤ 0.05) improvements in body mass, countermovement jump (CMJ) height, front squat, bench press, and chin-up strength were observed. Resistance training volume load had moderate to strong relationships with changes in CMJ (r = 0.71), chin up (r = 0.73), and bench press (r = 0.45). Frequency of upper and lower-body compound exercises had significant moderate to large relationships with changes in CMJ (r = 0.68), chin up (r = 0.65), and bench press (r = 0.41). Across a 12-week in-season period, adolescent rugby union players have varying resistance training practices, although anthropometric and physical characteristics seem to improve. Given the observed relationships, increased volume loads through the implementation of free-weight compound exercises could be an effective method for improving physical qualities in young rugby players. [ABSTRACT FROM AUTHOR]

Purpose: Investigate the acute and short-term (i.e., 24 h) effects of traditional (TRAD), superset (SS), and tri-set (TRI) resistance training protocols on perceptions of intensity and physiological responses.Methods: Fourteen male participants completed a familiarisation session and three resistance training protocols (i.e., TRAD, SS, and TRI) in a randomised-crossover design. Rating of perceived exertion, lactate concentration ([Lac]), creatine kinase concentration ([CK]), countermovement jump (CMJ), testosterone, and cortisol concentrations was measured pre, immediately, and 24-h post the resistance training sessions with magnitude-based inferences assessing changes/differences within/between protocols.Results: TRI reported possible to almost certainly greater efficiency and rate of perceived exertion, although session perceived load was very likely lower. SS and TRI had very likely to almost certainly greater lactate responses during the protocols, with changes in [CK] being very likely and likely increased at 24 h, respectively. At 24-h post-training, CMJ variables in the TRAD protocol had returned to baseline; however, SS and TRI were still possibly to likely reduced. Possible increases in testosterone immediately post SS and TRI protocols were reported, with SS showing possible increases at 24-h post-training. TRAD and SS showed almost certain and likely decreases in cortisol immediately post, respectively, with TRAD reporting likely decreases at 24-h post-training.Conclusions: SS and TRI can enhance training efficiency and reduce training time. However, acute and short-term physiological responses differ between protocols. Athletes can utilise SS and TRI resistance training, but may require additional recovery post-training to minimise effects of fatigue. [ABSTRACT FROM AUTHOR]

Criterion validity of force and power outputs for a commonly used flywheel resistance training device and bluetooth app. J Strength Cond Res 33(5): 1180-1184,2019—Flywheels are a resistance training device that can increase lean body mass, strength, and power. However, because of their unique design and the inertia from the concentric portion directly relating to the force that is applied during the eccentric portion, monitoring the training stimulus can be difficult. Consequently, the aim of this study was to assess the validity of the kMeter app for quantifying force and power at a range of different isoinertial loads from a flywheel training device when compared against a criterion measure. Eleven subjects volunteered to take part in this study, with subjects completing between 5 and 35 repetitions of the harness squat with 0.05, 0.10, 0.15 k g v r r2 isoinertial load. A synchronized dual force plate and tricamera optoelectronic setup was used as the criterion measure to calculate force and power output, while the kMeter app was used as the practical measure. Very large to nearly perfect relationships were observed between the 2 measures, with trivial to moderate bias reported. In addition, typical error of the estimate (TEE) was found to be <10% at all isoinertial loads. These findings suggest that the kMeter app, when used in conjunction with the kBox flywheel device, demonstrates acceptable levels of validity. However, because of the TEE, the kMeter app may not be able to accurately detect small differences and therefore be suitable for research purposes. These findings suggest that the kMeter app is an acceptable method of monitoring flywheel resistance training. Furthermore, it is advised that practitioners use mean power rather than mean force. [ABSTRACT FROM AUTHOR]

This study aimed to explore the goodness-of-fit and accuracy of both general and individual relationships between the number of repetitions in reserve (RIR) and the repetition velocity during the Smith machine prone bench pull exercise. Fifteen male sports science students completed 3 sessions separated by 48-72 hours. The first session was used to determine the bench pull 1 repetition maximum (1RM). The second and third sessions were identical and consisted of 3 single sets (60, 70, and 80% 1 RM) of repetitions to momentary muscular failure separated by 10 minutes during the Smith machine prone bench pull exercise. General (i.e., pooling together the data from the 15 subjects) and individual RIR- velocity relationships were constructed from the data collected in the second session by pooling the data from the 3 loads (multiple-loads) or specifically for each load (load-specific). The 4 RIR-velocity relationship models were ranked by their goodness-of-fit as follows: individuals-specific (r = 0.93) > individualmultiple-loads (r = 0.83) > generalmultiple-loads (r = 0.65) > generalload-specific (r = 0.61). The accuracy when predicting the RIR in the third session based on the RIR-velocity equations obtained in the second session was acceptable and comparable for the 4 RIR-velocity relationship models (absolute errors ≤ 2 RIR). However, the 4 RIR-velocity relationship models significantly underestimated the RIR for ≥1 RIR and overestimated the RIR for 0 RIR. These results suggest that the 4 RIR-velocity relationship models are equally effective to quantify proximity-to-failure during the Smith machine prone bench pull exercise. [ABSTRACT FROM AUTHOR]

The purpose of this study was to determine the between-day reliability of commonly used strength measures in male youth athletes while considering resistance training experience. Data were collected on 25 male athletes over 2 testing sessions, with 72 hours rest between, for the 3 repetition maximum (3RM) front squat, chin-up, and bench press. Subjects were initially categorized by resistance training experience (inexperienced; 6-12 months, experienced; .2 years). The assessment of the between-day reliability (coefficient of variation [CV%]) showed that the front squat (experienced: 2.90%; inexperienced: 1.90%), chin-up (experienced: 1.70%; inexperienced: 1.90%), and bench press (experienced: 4.50%; inexperienced: 2.40%) were all reliable measures of strength in both groups. Comparison between groups for the error of measurement for each exercise showed trivial differences. When both groups were combined, the CV% for the front squat, bench press, and chin-up were 2.50, 1.80, and 3.70%, respectively. This study provides scientists and practitioners with the between-day reliability reference data to determine real and practical changes for strength in male youth athletes with different resistance training experience. Furthermore, this study demonstrates that 3RM front squat, chin-up, and bench press are reliable exercises to quantify strength in male youth athletes. [ABSTRACT FROM AUTHOR]

Male academy rugby league players are required to undertake field and resistance training to develop the technical, tactical and physical qualities important for success in the sport. However, limited research is available exploring the training load of academy rugby league players. Therefore, the purpose of this study was to quantify the field and resistance training loads of academy rugby league players during a pre-season period and compare training loads between playing positions (i.e., forwards vs. backs). Field and resistance training load data from 28 adolescent male (age 17 ± 1 years) rugby league players were retrospectively analysed following a 13-week pre-season training period (85 total training observations; 45 field sessions and 40 resistance training sessions). Global positioning system microtechnology, and estimated repetition volume was used to quantify external training load, and session rating of perceived exertion (sRPE) was used to quantify internal training load. Positional differences (forwards n = 13 and backs n = 15) in training load were established using a linear mixed effect model. Mean weekly training frequency was 7 ± 2 with duration totaling 324 ± 137 minutes, and a mean sRPE of 1562 ± 678 arbitrary units (AU). Backs covered more high-speed distance than forwards in weeks two (p = 0.024), and 11 (p = 0.028). Compared to the forwards, backs completed more lower body resistance training volume in week one (p = 0.02), more upper body volume in week three (p< 0.001) and week 12 (p = 0.005). The findings provide novel data on the field and resistance-based training load undertaken by academy rugby league players across a pre-season period, highlighting relative uniformity between playing positions. Quantifying training load can support objective decision making for the prescription and manipulation of future training, ultimately aiming to maximise training within development pathways. [ABSTRACT FROM AUTHOR]

Background: Repeated-sprint training (RST) is a common training method for enhancing physical fitness in athletes. To advance RST prescription, it is important to understand the effects of programming variables on physical fitness and physiological adaptation. Objectives: This study (1) quantifies the pooled effects of running RST on changes in 10 and 20 m sprint time, maximal oxygen consumption (VO2max), Yo-Yo Intermittent Recovery Test Level 1 (YYIR1) distance, repeated-sprint ability (RSA), countermovement jump (CMJ) height and change of direction (COD) ability in athletes, and (2) examines the moderating effects of program duration, training frequency, weekly volume, sprint modality, repetition distance, number of repetitions per set and number of sets per session on changes in these outcome measures. Methods: Pubmed, SPORTDiscus and Scopus databases were searched for original research articles up to 04 July 2023, investigating RST in healthy, able-bodied athletes, between 14 and 35 years of age, and a performance calibre of trained or above. RST interventions were limited to repeated, maximal running (land-based) sprints of ≤ 10 s duration, with ≤ 60 s recovery, performed for 2–12 weeks. A Downs and Black checklist was used to assess the methodological quality of the included studies. Eligible data were analysed using multi-level mixed-effects meta-analysis, with standardised mean changes determined for all outcomes. Standardised effects [Hedges G (G)] were evaluated based on coverage of their confidence (compatibility) intervals (CI) using a strength and conditioning specific reference value of G = 0.25 to declare an improvement (i.e. G > 0.25) or impairment (i.e. G < − 0.25) in outcome measures. Applying the same analysis, the effects of programming variables were then evaluated against a reference RST program, consisting of three sets of 6 × 30 m straight-line sprints performed twice per week for 6 weeks (1200 m weekly volume). Results: 40 publications were included in our investigation, with data from 48 RST groups (541 athletes) and 19 active control groups (213 athletes). Across all studies, the effects of RST were compatible with improvements in VO2max (G 0.56, 90% CI 0.32–0.80), YYIR1 distance (G 0.61, 90% CI 0.43–0.79), RSA decrement (G − 0.61, 90% CI − 0.85 to − 0.37), linear sprint times (10 m: G − 0.35, 90% CI − 0.48 to − 0.22; 20 m: G − 0.48, 90% CI − 0.69 to − 0.27), RSA average time (G − 0.34, 90% CI − 0.49 to − 0.18), CMJ height (G 0.26, 90% CI 0.13–0.39) and COD ability (G − 0.32, 90% CI − 0.52 to − 0.12). Compared with the reference RST program, the effects of manipulating training frequency (+ 1 session per week), program duration (+ 1 extra training week), RST volume (+ 200 m per week), number of reps (+ 2 per set), number of sets per session (+ 1 set) or rep distance (+ 10 m per rep) were either non-substantial or comparable with an impairment in at least one outcome measure per programming variable. Conclusions: Running-based RST improves speed, intermittent running performance, VO2max, RSA, COD ability and CMJ height in trained athletes. Performing three sets of 6 × 30 m sprints, twice per week for 6 weeks is effective for enhancing physical fitness and physiological adaptation. Additionally, since our findings do not provide conclusive support for the manipulation of RST variables, further work is needed to better understand how programming factors can be manipulated to augment training-induced adaptations. Study Registration: Open Science Framework registration https://doi.org/10.17605/OSF.IO/RVNDW. [ABSTRACT FROM AUTHOR]

The aim of this study was to assess whether lifting velocity (MV) can provide accurate estimations of the maximum number of repetitions that can be performed to failure (RTF) during the parallel back‐squat exercise performed in a Smith machine. Thirty male wrestlers from the Turkey Olympic preparation center (age = 22.6 ± 2.2 years) completed four testing sessions: a session to determine the back‐squat one‐repetition maximum [1RM], two sessions consisting of single sets to failure against three loads (90%‐80%‐70%1RM), and one session consisting of four sets to failure against the 75%1RM. The goodness‐of‐fit of the generalized RTF‐MV relationship was strong (r2 = 0.838), but the individualized RTF‐MV relationships were stronger (r2 = 0.957 ± 0.058). Only 3 out of 60 individualized RTF‐MV relationships revealed a r2 lower than the r2 of the generalized RTF‐MV relationship (r2 = 0.685, 0.779 and 0.810). The reliability of the fastest MV associated with each RTF ranged from acceptable (4 out of 15 RTFs) to high (11 out of 15 RTFs). The raw and absolute errors in the prediction of RTF did not increase under fatigue and were comparable for both generalized (raw errors: −1.0–0.3 repetitions; absolute errors: 1.1–1.7 repetitions) and individualized (raw errors: −0.8 to 0.1 repetitions; absolute errors: 1.2–1.8 repetitions) RTF‐MV relationships. These results indicate that RTF can be predicted with acceptable precision from MV recordings in resistance‐trained skilled wrestlers during the parallel back‐squat exercise performed in a Smith machine. Highlights: The maximum number of repetitions completed to failure (RTF) can be predicted with acceptable precision from mean velocity (MV) recordings in resistance‐trained skilled wrestlers during the parallel back‐squat exercise performed in a Smith machine.The raw and absolute errors in the prediction of RTF is not influenced by the fatigue levels experienced at the beginning of the set.For more accurate RTF‐MV relationships, familiarity with lifting at maximal intended velocity and performing sets to failure seems beneficial. [ABSTRACT FROM AUTHOR]

Purpose: This study aimed to investigate the effect of an isometric (ISO) or Nordic hamstring exercise (NHE) intervention, alongside a sprint training program on hamstring strength, architecture, and sprinting performance in Australian footballers. Methods: Twenty-five male athletes undertook NHE (n = 13) or ISO (n = 12) training across a 38-wk period (including preseason and in season). Biceps femoris long head (BFlh) architecture, ISO, and eccentric knee flexor strength were assessed at baseline, at the end of preseason (14 wk), and at the conclusion of the intervention. Sprint times and force–velocity profiles were determined at baseline and at the end of preseason. Results: After the intervention, both groups had significant improvements in BFlh fascicle length (NHE: 1.16 cm, 95% CI = 0.68 to 1.63 cm, d = 1.88, P < 0.001; ISO: 0.82 cm, 95% CI = 0.57 to 1.06 cm, d = 1.70, P < 0.001), muscle thickness (NHE: 0.11 cm, 95% CI = 0.01 to 0.21 cm, d = 0.51, P = 0.032; ISO: 0.21 cm, 95% CI = 0.10 to 0.32 cm, d = 0.86, P = 0.002), and eccentric strength (NHE: 83 N, 95% CI = 53 to 114 N, d = 1.79, P < 0.001; ISO: 83 N, 95% CI = 17 to 151 N, d = 1.17, P = 0.018). Both groups also finished the intervention weaker isometrically than they started (NHE: −45 N, 95% CI = −81 to −8 N, d = −1.03, P = 0.022; ISO: −80 N, 95% CI = −104 to −56 N, d = −3.35, P < 0.001). At the end of preseason, the NHE group had improved their 5-m sprint time by 3.3% ± 2.0%), and their maximum horizontal velocity was 3% ± 2.1% greater than the ISO group who saw no changes. Conclusions: Both ISO and NHE training with a periodized sprinting program can increase BFlh fascicle length, thickness, and eccentric strength in Australian footballers. NHE training also improves 5-m sprint time and maximum velocity. However, both interventions reduced ISO strength. These findings provide unique, contextually relevant insights into the adaptations possible in semiprofessional athletes. [ABSTRACT FROM AUTHOR]

This study aimed to investigate how squat protocols performed at maximal and submaximal intended velocities during interset periods of paired upper‐body exercises that impact the mechanical performance of these multijoint upper‐body exercises. Twenty‐one young and healthy adults (seven women) completed three experimental sessions, each comprising four sets of five repetitions at 75% of their 1‐repetition maximum, with a 4‐min break between sets using the bench press and bench pull exercises. The experimental sessions differed in the protocol utilized during the interset periods: (i) Passive—no physical exercise was performed; (ii) SQfast—5 repetitions of the squat exercise at maximal intended velocity against the load associated with a mean velocity (MV) of 0.75 m s−1; and (iii) SQslow—5 repetitions of the squat exercise at submaximal velocity (intended MV of 0.50 m s−1) against the load associated with an MV of 0.75 m s−1. Level of significance was p ≤ 0.05. The main findings revealed negligible differences (effect size [ES] < 0.20) among the exercise protocols (passive vs. SQfast vs. SQslow) for all mechanical variables during the bench pull, whereas during the bench press, small differences (ES from 0.23 to 0.31) emerged favoring the passive protocol over SQfast and SQslow in terms of mean set velocity and fastest MV of the set. The absence of significant differences between the SQfast and SQslow protocols, irrespective of the particular upper‐body exercise, implies that the intended lifting velocity does not influence the potential interference effect during paired set training procedures. Highlights: Supersets with the squat exercise appear to exert minimal influence on bench pull mechanical performance but modest interference arises concerning the bench press exercise.The intended lifting velocity utilized in lower‐body exercises does not exert an influence on mechanical performance within paired upper‐body exercise sets.Exercise selection holds greater significance than intended lifting velocity when striving to mitigate interference in superset training. [ABSTRACT FROM AUTHOR]

This study examined the influence of inter-set rest periods of 1 (R1), 3 (R3) and 5 (R5) minutes on the number of repetitions completed before exceeding the minimum velocity thresholds of 0.45 m⋅s−1 (MVT0.45) and 0.35 m⋅s−1 (MVT0.35) during the bench press exercise. Twenty-three physically active individuals, 15 men and eight women, randomly completed six testing sessions consisting of four sets of the bench press exercise performed with maximal intent against 75% of the one-repetition maximum. Testing sessions differed in the length of inter-set rest periods (R1, R3, and R5) and MVT applied (MVT0.45 and MVT0.35). The number of repetitions was lower using shorter inter-set rest periods (R1 < R3 < R5), but R3 was more similar to R1 and R5 using MVT0.45 and MVT0.35, respectively. The fastest velocity of the set was reduced with the increment in the number of sets for the three protocols using MVT0.35 (greater reduction for shorter rest periods), but it was only reduced for R1 when using MVT0.45. The results suggest that, to maintain bench press mechanical performance, 5-min inter-set rest periods are necessary when sets are terminated close to failure (MVT0.35), while 3 min may suffice when sets are terminated farther from failure (MVT0.45). [ABSTRACT FROM AUTHOR]

Background: Rugby union match demands are complex, requiring the development of multiple physical qualities concurrently. Quantifying the physical qualities of age grade rugby union players is vital for practitioners to support athlete preparation and long-term development. Aim: This systematic review aimed to identify the methods used to quantify the physical qualities of male age grade (≤ Under-20) rugby union players, present the normative values for physical qualities, and compare physical qualities between age grades and positions. Methods: Electronic databases were systematically reviewed from the earliest record to November 2019 using key words relating to sex, age, sport and physical testing. Results: Forty-two studies evaluated the physical qualities of age grade rugby union players. Seventy-five tests were used to quantify body composition, muscular strength, muscular power, linear speed, change of direction ability, aerobic capacity and anaerobic endurance. Thirty-one studies met the eligibility criteria to present the physical qualities. Physical qualities differentiate between age groups below Under-16, while differences in older age groups (Under-16 to Under-20) are not clear. Positional differences are present with forwards possessing greater height, body mass, body fat percentage and strength while backs are faster and have greater aerobic capacities. Conclusions: A wide variety of tests are used to assess physical qualities limiting between study comparisons. Although differences in older age grades are unclear, older age groups (Under-19-20) generally performed better in physical tests. Positional differences are associated with match demands where forwards are exposed to less running but a greater number of collisions. Practitioners can use the results from this review to evaluate the physical qualities of age grade rugby union players to enhance training prescription, goal setting and player development. Future research should consider the use of national standardised testing batteries due to the inconsistency in testing methods and small samples limiting the reporting of positional differences. [ABSTRACT FROM AUTHOR]

Background: With the increasing professionalisation of youth sports, training load monitoring is increasingly common in adolescent athletes. However, the research examining the relationship between training load and changes in physical qualities, injury, or illness in adolescent athletes is yet to be synthesised in a systematic review. Objective: The aim of this review was to systematically examine the research assessing internal and external methods of monitoring training load and physical qualities, injury, or illness in adolescent athletes. Methods: Systematic searches of SPORTDiscus, Web of Science, CINAHL and SCOPUS were undertaken from the earliest possible records to March 2022. Search terms included synonyms relevant to adolescents, athletes, physical qualities, injury, or illness. To be eligible for inclusion, articles were required to (1) be original research articles; (2) be published in a peer-reviewed journal; (3) include participants aged between 10 and 19 years and participating in competitive sport; (4) report a statistical relationship between a measure of internal and/or external load and physical qualities, injury or illness. Articles were screened and assessed for methodological quality. A best-evidence synthesis was conducted to identify trends in the relationships reported. Results: The electronic search yielded 4125 articles. Following screening and a review of references, 59 articles were included. The most commonly reported load monitoring tools were session ratings of perceived exertion (n = 29) and training duration (n = 22). Results of the best-evidence synthesis identified moderate evidence of positive relationships between resistance training volume load and improvement in strength, and between throw count and injury. However, evidence for other relationships between training load and change in physical qualities, injury, or illness were limited or inconsistent. Conclusions: Practitioners should consider monitoring resistance training volume load for strength training. Additionally, where appropriate, monitoring throw counts may be useful in identifying injury risk. However, given the lack of clear relationships between singular measures of training load with physical qualities, injury, or illness, researchers should consider multivariate methods of analysing training load, as well as factors that may mediate the load–response relationship, such as maturation. [ABSTRACT FROM AUTHOR]

Previous research in academy rugby league players has evaluated the development of physical qualities according to chronological age. However, no study has considered the training age, defined as the number of formalized years of strength and conditioning training, of these players. Therefore, the purpose of this study was to present and compare the annual changes in physical qualities of academy rugby league players according to training age. Sixty-one academy players undertook a fitness testing assessment, including anthropometric (height, body mass, sum of 4 skinfolds) and physical (10 and 20 m sprint, 10m momentum, vertical jump, Yo-Yo intermittent recovery test level 1 [Yo-Yo IRTL1], one-repetition maximum [1RM] squat, bench press and prone row) measures at the start of preseason on 2 consecutive annual occasions. Players were categorized into one of 3 training age groups (i.e., 0, 1, or 2 years) and were analyzed using magnitude-based inferences. Almost certain, very likely or likely annual improvements were identified for body mass, 10m momentum, Yo-Yo IRTL1, vertical jump, and all strength measures for the 3 training age groups. When training age groups were compared, 1 year showed possibly or likely lower strength increases than 0 years training age. However, the 2 years training age group demonstrated possibly or likely increased strength changes compared with 1 year. These findings suggest that training age is an important consideration for strength and conditioning practitioners but it is likely to be a combination of chronological age, biological maturity, and training experience alongside dynamic interplayer variability that influences the physical development of academy rugby league players. [ABSTRACT FROM AUTHOR]

Interpreting the physical qualities of youth athletes is complex due to the effects of growth, maturation and development. This study aimed to evaluate the effect of position, chronological age, relative age and maturation on the physical qualities of elite male academy rugby union players. 1,424 participants (n = 2,381 observations) from nine Rugby Football Union regional academies prospectively completed a physical testing battery at three time points, across three playing seasons. Anthropometrics, body composition, muscular power, muscular strength, speed, aerobic capacity and running momentum were assessed. Positional differences were identified for all physical qualities. The largest effect sizes were observed for the associations between chronological age (d = 0.65–0.73) and maturation (d = −0.77 to −0.69) and body mass related variables (i.e. body mass and running momentum). Relative strength, maximum velocity and aerobic capacity were the only models to include two fixed effects with all other models including at least three fixed effects (i.e. position and a combination of chronological age, relative age and maturation). These findings suggest a multidimensional approach considering position, chronological age, relative age and maturation is required to effectively assess the physical qualities of male age grade rugby union players. Therefore practitioners should use regression equations rather than traditional descriptive statistic tables to provide individualised normative comparisons thus enhancing the application of testing results for talent identification and player development. Highlights Practitioners should record and incorporate position, chronological age, relative age and maturation into the physical evaluation of elite academy rugby union players. The regression equations provided within this study offer highly generalisable comparative values that are specific to a players chronological and biological development. Through the use of enhanced player evaluation practitioners will be able to make more informed decisions surrounding talent identification and athlete development. [ABSTRACT FROM AUTHOR]

Background: Nutrition guidance for athletes must consider a range of variables to effectively support individuals in meeting energy and nutrient needs. Resistance exercise is a widely adopted training method in athlete preparation and rehabilitation and therefore is one such variable that will influence nutrition guidance. Given its prominence, the capacity to meaningfully quantify resistance exercise energy expenditure will assist practitioners and researchers in providing nutrition guidance. However, the significant contribution of anaerobic metabolism makes quantifying energy expenditure of resistance exercise challenging.The aim of this scoping review was to investigate the methods used to assess resistance exercise energy expenditure.A literature search of Medline, SPORTDiscus, CINAHL and Web of Science identified studies that included an assessment of resistance exercise energy expenditure. Quality appraisal of included studies was performed using the Rosendal Scale.A total of 19,867 studies were identified, with 166 included after screening. Methods to assess energy expenditure included indirect calorimetry (n = 136), blood lactate analysis (n = 25), wearable monitors (n = 31) and metabolic equivalents (n = 4). Post-exercise energy expenditure was measured in 76 studies. The reported energy expenditure values varied widely between studies.Indirect calorimetry is widely used to estimate energy expenditure. However, given its limitations in quantifying glycolytic contribution, indirect calorimetry during and immediately following exercise combined with measures of blood lactate are likely required to better quantify total energy expenditure. Due to the cumbersome equipment and technical expertise required, though, along with the physical restrictions the equipment places on participants performing particular resistance exercises, indirect calorimetry is likely impractical for use outside of the laboratory setting, where metabolic equivalents may be a more appropriate method.Objective: Nutrition guidance for athletes must consider a range of variables to effectively support individuals in meeting energy and nutrient needs. Resistance exercise is a widely adopted training method in athlete preparation and rehabilitation and therefore is one such variable that will influence nutrition guidance. Given its prominence, the capacity to meaningfully quantify resistance exercise energy expenditure will assist practitioners and researchers in providing nutrition guidance. However, the significant contribution of anaerobic metabolism makes quantifying energy expenditure of resistance exercise challenging.The aim of this scoping review was to investigate the methods used to assess resistance exercise energy expenditure.A literature search of Medline, SPORTDiscus, CINAHL and Web of Science identified studies that included an assessment of resistance exercise energy expenditure. Quality appraisal of included studies was performed using the Rosendal Scale.A total of 19,867 studies were identified, with 166 included after screening. Methods to assess energy expenditure included indirect calorimetry (n = 136), blood lactate analysis (n = 25), wearable monitors (n = 31) and metabolic equivalents (n = 4). Post-exercise energy expenditure was measured in 76 studies. The reported energy expenditure values varied widely between studies.Indirect calorimetry is widely used to estimate energy expenditure. However, given its limitations in quantifying glycolytic contribution, indirect calorimetry during and immediately following exercise combined with measures of blood lactate are likely required to better quantify total energy expenditure. Due to the cumbersome equipment and technical expertise required, though, along with the physical restrictions the equipment places on participants performing particular resistance exercises, indirect calorimetry is likely impractical for use outside of the laboratory setting, where metabolic equivalents may be a more appropriate method.Methods: Nutrition guidance for athletes must consider a range of variables to effectively support individuals in meeting energy and nutrient needs. Resistance exercise is a widely adopted training method in athlete preparation and rehabilitation and therefore is one such variable that will influence nutrition guidance. Given its prominence, the capacity to meaningfully quantify resistance exercise energy expenditure will assist practitioners and researchers in providing nutrition guidance. However, the significant contribution of anaerobic metabolism makes quantifying energy expenditure of resistance exercise challenging.The aim of this scoping review was to investigate the methods used to assess resistance exercise energy expenditure.A literature search of Medline, SPORTDiscus, CINAHL and Web of Science identified studies that included an assessment of resistance exercise energy expenditure. Quality appraisal of included studies was performed using the Rosendal Scale.A total of 19,867 studies were identified, with 166 included after screening. Methods to assess energy expenditure included indirect calorimetry (n = 136), blood lactate analysis (n = 25), wearable monitors (n = 31) and metabolic equivalents (n = 4). Post-exercise energy expenditure was measured in 76 studies. The reported energy expenditure values varied widely between studies.Indirect calorimetry is widely used to estimate energy expenditure. However, given its limitations in quantifying glycolytic contribution, indirect calorimetry during and immediately following exercise combined with measures of blood lactate are likely required to better quantify total energy expenditure. Due to the cumbersome equipment and technical expertise required, though, along with the physical restrictions the equipment places on participants performing particular resistance exercises, indirect calorimetry is likely impractical for use outside of the laboratory setting, where metabolic equivalents may be a more appropriate method.Results: Nutrition guidance for athletes must consider a range of variables to effectively support individuals in meeting energy and nutrient needs. Resistance exercise is a widely adopted training method in athlete preparation and rehabilitation and therefore is one such variable that will influence nutrition guidance. Given its prominence, the capacity to meaningfully quantify resistance exercise energy expenditure will assist practitioners and researchers in providing nutrition guidance. However, the significant contribution of anaerobic metabolism makes quantifying energy expenditure of resistance exercise challenging.The aim of this scoping review was to investigate the methods used to assess resistance exercise energy expenditure.A literature search of Medline, SPORTDiscus, CINAHL and Web of Science identified studies that included an assessment of resistance exercise energy expenditure. Quality appraisal of included studies was performed using the Rosendal Scale.A total of 19,867 studies were identified, with 166 included after screening. Methods to assess energy expenditure included indirect calorimetry (n = 136), blood lactate analysis (n = 25), wearable monitors (n = 31) and metabolic equivalents (n = 4). Post-exercise energy expenditure was measured in 76 studies. The reported energy expenditure values varied widely between studies.Indirect calorimetry is widely used to estimate energy expenditure. However, given its limitations in quantifying glycolytic contribution, indirect calorimetry during and immediately following exercise combined with measures of blood lactate are likely required to better quantify total energy expenditure. Due to the cumbersome equipment and technical expertise required, though, along with the physical restrictions the equipment places on participants performing particular resistance exercises, indirect calorimetry is likely impractical for use outside of the laboratory setting, where metabolic equivalents may be a more appropriate method.Conclusions: Nutrition guidance for athletes must consider a range of variables to effectively support individuals in meeting energy and nutrient needs. Resistance exercise is a widely adopted training method in athlete preparation and rehabilitation and therefore is one such variable that will influence nutrition guidance. Given its prominence, the capacity to meaningfully quantify resistance exercise energy expenditure will assist practitioners and researchers in providing nutrition guidance. However, the significant contribution of anaerobic metabolism makes quantifying energy expenditure of resistance exercise challenging.The aim of this scoping review was to investigate the methods used to assess resistance exercise energy expenditure.A literature search of Medline, SPORTDiscus, CINAHL and Web of Science identified studies that included an assessment of resistance exercise energy expenditure. Quality appraisal of included studies was performed using the Rosendal Scale.A total of 19,867 studies were identified, with 166 included after screening. Methods to assess energy expenditure included indirect calorimetry (n = 136), blood lactate analysis (n = 25), wearable monitors (n = 31) and metabolic equivalents (n = 4). Post-exercise energy expenditure was measured in 76 studies. The reported energy expenditure values varied widely between studies.Indirect calorimetry is widely used to estimate energy expenditure. However, given its limitations in quantifying glycolytic contribution, indirect calorimetry during and immediately following exercise combined with measures of blood lactate are likely required to better quantify total energy expenditure. Due to the cumbersome equipment and technical expertise required, though, along with the physical restrictions the equipment places on participants performing particular resistance exercises, indirect calorimetry is likely impractical for use outside of the laboratory setting, where metabolic equivalents may be a more appropriate method. [ABSTRACT FROM AUTHOR]

Background: As basketball match-play requires players to possess a wide range of physical characteristics, many tests have been introduced in the literature to identify talent and quantify fitness in various samples of players. However, a synthesis of the literature to identify the most frequently used tests, outcome variables, and normative values for basketball-related physical characteristics in adult male basketball players is yet to be conducted. Objective: The primary objectives of this systematic review are to (1) identify tests and outcome variables used to assess physical characteristics in adult male basketball players across all competition levels, (2) report a summary of anthropometric, muscular power, linear speed, change-of-direction speed, agility, strength, anaerobic capacity, and aerobic capacity in adult male basketball players based on playing position and competition level, and (3) introduce a framework outlining recommended testing approaches to quantify physical characteristics in adult male basketball players. Methods: A systematic review of MEDLINE, PubMed, SPORTDiscus, Scopus, and Web of Science was performed following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines to identify relevant studies. To be eligible for inclusion, studies were required to: (1) be original research articles; (2) be published in a peer-reviewed journal; (3) have full-text versions available in the English language; and (4) include the primary aim of reporting tests used and/or the physical characteristics of adult (i.e., ≥ 18 years of age) male basketball players. Additionally, data from the top 10 draft picks who participated in the National Basketball Association combined from 2011–12 to 2020–21 were extracted from the official league website to highlight the physical characteristics of elite 19- to 24-year-old basketball players. Results: A total of 1684 studies were identified, with 375 being duplicates. Consequently, the titles and abstracts of 1309 studies were screened and 231 studies were eligible for full-text review. The reference list of each study was searched, with a further 59 studies identified as eligible for review. After full-text screening, 137 studies identified tests, while 114 studies reported physical characteristics in adult male basketball players. Conclusions: Physical characteristics reported indicate a wide range of abilities are present across playing competitions. The tests and outcome variables reported in the literature highlight the multitude of tests currently being used. Because there are no accepted international standards for physical assessment of basketball players, establishing normative data is challenging. Therefore, future testing should involve repeatable protocols that are standardised and provide outcomes that can be monitored across time. Recommendations for testing batteries in adult male basketball players are provided so improved interpretation of data can occur. Clinical Trial Registration: This review was registered with the International Prospective Register of Systematic Reviews and allocated registration number CRD42020187151 on 28 April, 2020. [ABSTRACT FROM AUTHOR]

Background: Technology has long been used to track player movements in team sports, with initial tracking via manual coding of video footage. Since then, wearable microtechnology in the form of global and local positioning systems has provided a less labour-intensive way of monitoring movements. As such, there has been a proliferation in research pertaining to these devices. Objective: A systematic review of studies that investigate the validity and/or reliability of wearable microtechnology to quantify movement and specific actions common to intermittent team sports. Methods: A systematic search of CINAHL, MEDLINE, and SPORTDiscus was performed; studies included must have been (1) original research investigations; (2) full-text articles written in English; (3) published in a peer-reviewed academic journal; and (4) assessed the validity and/or reliability of wearable microtechnology to quantify movements or specific actions common to intermittent team sports. Results: A total of 384 studies were retrieved and 187 were duplicates. The titles and abstracts of 197 studies were screened and the full texts of 88 manuscripts were assessed. A total of 62 studies met the inclusion criteria. Additional 10 studies, identified via reference list assessment, were included. Therefore, a total of 72 studies were included in this review. Conclusion: There are many studies investigating the validity and reliability of wearable microtechnology to track movement and detect sport-specific actions. It is evident that for the majority of metrics, validity and reliability are multi-factorial, in that it is dependent upon a wide variety of factors including wearable technology brand and model, sampling rate, type of movement performed (e.g., straight line, change of direction) and intensity of movement (e.g., walk, sprint). Practitioners should be mindful of the accuracy and repeatability of the devices they are using when making decisions on player training loads. [ABSTRACT FROM AUTHOR]

Pearson, J, Spathis, JG, van den Hoek, DJ, Owen, PJ, Weakley, J, and Latella, C. Effect of competition frequency on strength performance of powerlifting athletes. J Strength Cond Res 34(5): 1213-1219, 2020-Powerlifting (PL) requires athletes to achieve the highest possible total weight lifted across squat, bench press, and deadlift. Athletes compete multiple times per year; however, it is not well understood how often PL athletes should compete to facilitate maximal strength performance. This study investigated the effect of competition frequency on strength (relative and absolute) in PL athletes over a 12-month period. Results across all male (n = 563, mean ± SD; age; 28 ± 10 years, body mass; 89.3 ± 19.3 kg) and female (n = 437, age; 31 ± 11 years, body mass; 70.1 ± 15.8 kg) PL athletes were collated. Total competition scores were used to calculate absolute and relative strength for each competition. Linear mixed models with random effects, and effect sizes ± 95%% confidence intervals compared competition frequency and total score for (a) all, (b) male, and (c) female competition entries, respectively. The association between total score at each competition was assessed with Pearsons correlation coefficient for the same independent variables. Results demonstrate greater absolute strength at competition 2 for all athletes (5.1%: p=0.043: d=0.16) and males (2.9%: p=0.049: d= 0.15). For females, absolute strength was greater at competition 5 compared to 1 (12.0%: p = 0.001: d = 0.65) and 2 (9.6%: p = 0.007: d = 0.50). Weak positive correlations for relative strength and number of times competed for males were evident between competitions 1 to 4 (r2 = 0.070-0.085, p =0.003-0.043). For females, 3 competitions weakly correlated with absolute strength (r2 = 0.106, p = 0.016). PL athletes who compete multiple times per year are more likely to achieve higher totals; however, there is an upper limit to the number of competitions (4 per year) that seem to allow a performance increase [ABSTRACT FROM AUTHOR]

This study examined the reliability and validity of three methods of estimating the one-repetition maximum (1RM) during the free-weight prone bench pull exercise. Twenty-six men (22 rowers and four weightlifters) performed an incremental loading test until reaching their 1RM, followed by a set of repetitions-to-failure. Eighteen participants were re-tested to conduct the reliability analysis. The 1RM was estimated through the lifts-to-failure equations proposed by Lombardi and O'Connor, general load-velocity (L-V) relationships proposed by Sánchez-Medina and Loturco and the individual L-V relationships modelled using four (multiple-point method) or only two loads (two-point method). The direct method provided the highest reliability (coefficient of variation [CV] = 2.45% and intraclass correlation coefficient [ICC] = 0.97), followed by the Lombardi's equation (CV = 3.44% and ICC = 0.94), and no meaningful differences were observed between the remaining methods (CV range = 4.95–6.89% and ICC range = 0.81–0.91). The lifts-to-failure equations overestimated the 1RM (3.43–4.08%), the general L-V relationship proposed by Sánchez-Medina underestimated the 1RM (−3.77%), and no significant differences were observed for the remaining prediction methods (−0.40–0.86%). The individual L-V relationship could be recommended as the most accurate method for predicting the 1RM during the free-weight prone bench pull exercise. [ABSTRACT FROM AUTHOR]

The use of unstable surfaces during resistance training has demonstrated a maintenance or reduction on force production. However, the use of unstable surface on force variability has not been assessed using non-linear methods that may be better suited to detect changes in movement variability throughout a given movement. Consequently, this study compared the use of stable vs unstable surfaces on force variability during bilateral squats performed with an inertial flywheel device (Eccoteck, Byomedic System SCP, Spain). Twenty healthy men (mean ± SD: age 22.9 ± 2.9 years, height 1.81 ± 0.7 m, body mass 76.4 ± 7.6 kg and 1RM back squat 110.9 ± 19.7 kg) with a minimum of four years in resistance training performed six sets of six repetitions of squats at maximal concentric effort with one minute rest between sets. Force output on the vertical axes was measured using a strain gauge and the results were processed using non-linear sample entropy (SampEn). Results showed no differences for any of the dependent variables between stable and unstable conditions. SampEn showed no differences between conditions (chi-squared = 0.048 P = 0.827), while Force mean and SampEn presented a small correlation (r = 0.184; p < 0.01). No changes in entropy were found over the course of the series. Together, these results suggest that the structure of force variability between stable and unstable surfaces are similar. This lack of difference between surfaces may be due to postural and anticipatory adjustments. Consequently, by introducing unstable surfaces to the flywheel bilateral squat exercise, practitioners may not observe changes in Force mean and force variability when compared to stable surface training suggesting that increased training volumes or intensity may be required during unstable environments to cause a desired training stimulus. [ABSTRACT FROM AUTHOR]

This aims of this study were (I) to determine the velocity variable and regression model which best fit the load-velocity relationship during the free-weight prone bench pull exercise, (II) to compare the reliability of the velocity attained at each percentage of the one-repetition maximum (1RM) between different velocity variables and regression models, and (III) to compare the within- and between-subject variability of the velocity attained at each %1RM. Eighteen men (14 rowers and four weightlifters) performed an incremental test during the free-weight prone bench pull exercise in two different sessions. General and individual load-velocity relationships were modelled through three velocity variables (mean velocity [MV], mean propulsive velocity [MPV] and peak velocity [PV]) and two regression models (linear and second-order polynomial). The main findings revealed that (I) the general (Pearson's correlation coefficient [r] range = 0.964–0.973) and individual (median r = 0.986 for MV, 0.989 for MPV, and 0.984 for PV) load-velocity relationships were highly linear, (II) the reliability of the velocity attained at each %1RM did not meaningfully differ between the velocity variables (coefficient of variation [CV] range = 2.55–7.61% for MV, 2.84–7.72% for MPV and 3.50–6.03% for PV) neither between the regression models (CV range = 2.55–7.72% and 2.73–5.25% for the linear and polynomial regressions, respectively), and (III) the within-subject variability of the velocity attained at each %1RM was lower than the between-subject variability for the light-moderate loads. No meaningful differences between the within- and between-subject CVs were observed for the MV of the 1RM trial (6.02% vs. 6.60%; CVratio = 1.10), while the within-subject CV was lower for PV (6.36% vs. 7.56%; CVratio = 1.19). These results suggest that the individual load-MV relationship should be determined with a linear regression model to obtain the most accurate prescription of the relative load during the free-weight prone bench pull exercise. [ABSTRACT FROM AUTHOR]

Limited research has compared the physical qualities of adolescent rugby union (RU) players across differing playing standards. This study therefore compared the physical qualities of academy and school Under-18 RU players. One-hundred and eighty-four (professional regional academy, n = 55 school, n = 129) male RU players underwent a physical testing battery to quantify height, body mass, strength (bench press and pull-up), speed (10, 20 and 40 m), 10 m momentum (calculated; 10 m velocity * body mass) and a proxy measure of aerobic fitness (Yo-Yo Intermittent Recovery Test Level 1; IRTL1). The practical significance of differences between playing levels were assessed using magnitude-based inferences. Academy players were taller (very likely small), heavier (likely moderate) and stronger (bench press possibly large; pull-up plus body mass likely small) than school players. Academy players were faster than school players over 20 and 40 m (possibly and likely small), although differences in 10 m speed were not apparent (possibly trivial). Academy players displayed greater 10 m momentum (likely moderate) and greater IRTL1 performance (likely small) than school players. These findings suggest that body size, strength, running momentum, 40 m speed and aerobic fitness contribute to a higher playing standard in adolescent rugby union. [ABSTRACT FROM AUTHOR]

Roe, G, Shaw, W, Darrall-Jones, J, Phibbs, PJ, Read, D, Weakley, JJ, Till, K, and Jones, B. Reliability and validity of a medicine ball–contained accelerometer for measuring upper-body neuromuscular performance. J Strength Cond Res 32(7): 1915–1918, 2018—The aim of the study was to assess the between-day reliability and validity of a medicine ball–contained accelerometer (MBA) for assessing upper-body neuromuscular performance during a throwing task. Ten professional rugby union players partook in the study. Between-day reliability was assessed from the best score attained during 2 sets of 3 throws, on 2 testing occasions separated by 7 days. Validity was assessed against a criterion measure (Optioelectronic system) during 75 throws from a subgroup of 3 participants. The MBA exhibited a small between-day error of 2.2% (90% confidence intervals; 2.0–4.6%) and an almost perfect relationship with a criterion measure (r = 0.91 [90% CIs; 0.87–0.94]). However, the mean bias and standard error were moderate (7.9% [90% CIs; 6.6–9.2%] and 4.9% [90% CIs; 4.2–5.7%], respectively). Practitioners using an MBA to assess neuromuscular performance of the upper body must take into account the overestimation and error associated with such assessment with respect to a criterion measure. However, as the error associated with between-day testing was small and testing is easy to implement in applied practice, an MBA may provide a useful tool for monitoring upper-body neuromuscular performance over time. [ABSTRACT FROM AUTHOR]

The aim of this study was to quantify the mean weekly training load (TL) of elite adolescent rugby union players participating in multiple teams and examine the differences between playing positions. Twenty elite male adolescent rugby union players (17.4 ± 0.7 years) were recruited from a regional academy and categorized by playing position: forwards (n = 10) and backs (n = 10). Global positioning system and accelerometer microtechnology was used to quantify external TL, and session rating of perceived exertion (sRPE) was used to quantify internal TL during all sessions throughout a 10-week in-season period. A total of 97 complete observations (5 ± 3 weeks per participant) were analyzed, and differences between positions were assessed using Cohen's d effect sizes (ES) and magnitude-based inferences. Mean weekly sRPE was 1,217 6 364 arbitrary units (AU) (between-subject coefficient of variation [CV] = 30%), with a total distance (TD) of 11,629 6 3,445 m (CV = 30%), and PlayerLoad (PL) of 1,124 ± 330 AU (CV = 29%). Within-subject CV ranged between 5 and 78% for sRPE, 24 and 82% for TD, and 19 and 84% for PL. Mean TD (13,063 ± 3,933 vs. 10,195 ± 2,242 m) and PL (1,246 ± 345 vs. 1,002 ± 279 AU) were both likely greater for backs compared with forwards (moderate ES); however, differences in sRPE were unclear (small ES). Although mean internal TLs and volumes were low, external TLs were higher than previously reported during preseason and in-season periods in senior professional players. Additionally, the large between-subject and within-subject variation in weekly TL suggests that players participate in a chaotic training system. [ABSTRACT FROM AUTHOR]

The aims of this study were to determine the variability of weekly match and training loads in adolescent rugby union players across a competitive season, and to investigate the effect of match frequency on load distribution across different activities. Internal match and training load data (i.e. session-rating of perceived exertion (sRPE)) were collected daily from 20 players from a regional academy across a 14-week season. Data were analysed using a mixed-effects linear model, and variability was reported as a coefficient of variation (CV). Differences between 0-, 1-, 2-, and 3-match weeks were assessed using Cohen's d effect sizes and magnitude-based inferences. Mean weekly total match and training sRPE load was 1425 ± 545 arbitrary units (AU), with a between-player CV of 10 ± 6% and within-player CV of 37 ± 3%. Mean week-to-week change in total sRPE load was 497 ± 423 AU (35%), and 40% of weekly observations were outside the suggested acute: chronic workload ratio 'safe zone'. Total weekly sRPE loads increased substantially with match frequency (1210 ± 571, 1511 ± 489, and 1692 ± 517 AU, for 0-, 1-, and 2-match weeks, respectively), except for 3-match weeks (1520 ± 442 AU). Weekly match and training loads were highly variable for adolescent rugby players during the competitive season, and match frequency has a substantial effect on the distribution of loads. Therefore, match and training loads should be coordinated, monitored, and managed on an individual basis to protect players from negative training consequences, and to promote long-term athlete development. [ABSTRACT FROM AUTHOR]

The aim was to compare the physical characteristics of under-18 academy and schoolboy rugby union competition by position (forwards and backs). Using a microsensor unit, match characteristics were recorded in 66 players. Locomotor characteristics were assessed by maximum sprint speed (MSS) and total, walking, jogging, striding and sprinting distances. The slow component (<2 m · s-1) of PlayerLoadTM (PLslow), which is the accumulated accelerations from the three axes of movement, was analysed as a measure of low-speed activity (e.g., rucking). A linear mixed-model was assessed with magnitude-based inferences. Academy forwards and backs almost certainly and very likely covered greater total distance than school forwards and backs. Academy players from both positions were also very likely to cover greater jogging distances. Academy backs were very likely to accumulate greater PLslow and the academy forwards a likely greater sprinting distance than school players in their respective positions. The MSS, total, walking and sprinting distances were greater in backs (likely-almost certainly), while forwards accumulated greater PLslow (almost certainly) and jogging distance (very likely). The results suggest that academy-standard rugby better prepares players to progress to senior competition compared to schoolboy rugby. [ABSTRACT FROM AUTHOR]

The aim of this study was to compare the physical and movement demands between training and matchplay in schoolboy and academy adolescent rugby union (RU) players. Sixty-one adolescent male RU players (mean ± SD; age 17.0 ± 0.7 years) were recruited from four teams representing school and regional academy standards. Players were categorised into four groups based on playing standard and position: schoolboy forwards (n = 15), schoolboy backs (n = 15), academy forwards (n = 16) and academy backs (n = 15). Global positioning system and accelerometry measures were obtained from training and matchplay to assess within-group differences between conditions. Maximum data were analysed from 79 match files across 8 matches (1.3 ± 0.5 matches per participant) and 152 training files across 15 training sessions (2.5 ± 0.5 training sessions per participant). Schoolboy forwards were underprepared for low-intensity activities experienced during match-play, with schoolboy backs underprepared for all movement demands. Academy forwards were exposed to similar physical demands in training to matches, with academy backs similar to or exceeding values for all measured variables. Schoolboy players were underprepared for many key, position-specific aspects of match-play, which could place them at greater risk of injury and hinder performance, unlike academy players who were better prepared. [ABSTRACT FROM AUTHOR]

Repeated physical contact in rugby union is thought to contribute to post-match fatigue; however, no evidence exists on the effect of contact activity during field-based training on fatigue responses. Therefore, the purpose of this study was to examine the effect of contact during training on fatigue markers in rugby union players. Twenty academy rugby union players participated in the cross-over study. The magnitude of change in upper- and lower-body neuromuscular function (NMF), whole blood creatine kinase concentration [CK] and perception of well-being was assessed pre-training (baseline), immediately and 24 h post-training following contact and non-contact, field-based training. Training load was measured using mean heart rate, session rating of perceived exertion (sRPE) and microtechnology (Catapult Optimeye S5). The inclusion of contact during field-based trainingalmost certainlyincreased mean heart rate (9.7; ±3.9%) and sRPE (42; ±29.2%) and resulted inlikelyandvery likelygreater decreases in upper-body NMF (−7.3; ±4.7% versus 2.7; ±5.9%) and perception of well-being (−8.0; ±4.8% versus  −3.4; ±2.2%) 24 h post-training, respectively, andalmost certainlygreater elevations in [CK] (88.2; ±40.7% versus 3.7; ±8%). The exclusion of contact from field-based trainingalmost certainlyincreased running intensity (19.8; ±5%) and distance (27.5; ±5.3%), resulting inpossiblygreater decreases in lower-body NMF (−5.6; ±5.2% versus 2.3; ±2.4%). Practitioners should be aware of the different demands and fatigue responses of contact and non-contact, field-based training and can use this information to appropriately schedule such training in the weekly microcycle. [ABSTRACT FROM PUBLISHER]

The purpose of this study was to quantify the physical demands of representative adolescent rugby union match-play and investigate the difference between playing positions and age groups. Players (n = 112) were classified into 6 groups by playing position (forwards and backs) and age group (U16, U18, and U20). The physical demands were measured using microsensor-based technology and analyzed using magnitude-based inferences to assess practical importance. Backs had a greater relative distance (except U16s) and a greater high-speed running distance per minute than forwards, with the magnitude of difference between the positions becoming larger in older age groups. Forwards had higher values of PlayerLoad (PL) per minute (accumulated accelerations from the 3 axes of movement) and PL slow per minute (accumulated accelerations from the 3 axes of movement where velocity is <2 m⋅s-1) than backs at all age groups. Relative distance, low-, and high-speed running per minute all had a trend to be lower in older age groups for both positions. PlayerLoad per minute was greater in U18 than that in U16 and U20 for both positions. PlayerLoad slow per minute was greater for older age groups besides the U18 and U20 comparisons, which were unclear. The contrasts in physical demands experienced by different positions reinforce the need for greater exposure to sprinting and collision-based activity for backs and forwards, respectively. Given PL metrics peak at U18 and locomotor demands seem to be lower in older ages, the demands of representative adolescent rugby union do not seem to be greater at U20 as expected. [ABSTRACT FROM AUTHOR]

The primary aim of the study was to assess the level of agreement between the criterion session rating of perceived exertion (sRPE30min) and a practical measure of a self-reported Web-based training load questionnaire 24 hours after training (sRPE24h) in adolescent athletes. The secondary aim was to assess the agreement between weekly summated sRPE24h values (ΣsRPE24h) and a weekly Web-based training diary (sRPEweekly) for all field-based training accumulated on a subsequent training week. Thirty-six male adolescent rugby players (age, 16.7 ± 0.5 years) were recruited from a regional academy. Measures of sRPE30min were recorded 30 minutes after a typical field-based training session. Participants then completed the sRPE24h via a Web-based training load questionnaire 24 hours after training, reporting both session duration and intensity. In addition, on a subsequent week, participants completed the sRPE24h daily and then completed the sRPEweekly at the end of the week, using the same Web-based platform, to recall all field-based training session durations and intensities over those 7 days. Biases were trivial between sRPE30min and sRPE24h for sRPE (0.3% [-0.9 to 1.5]), with nearly perfect correlations (0.99 [0.98-0.99]) and small typical error of the estimate (TEE; 4.3% [3.6-5.4]). Biases were trivial between ΣsRPE24h and sRPEweekly for sRPE (5.9% [ - 2.1 to 14.2]), with very large correlations (0.87 [0.78-0.93]) and moderate TEE of 28.5% [23.3-36.9]. The results of this study show that sRPE24h is a valid and robust method to quantify training loads in adolescent athletes. However, sRPEweekly was found to have a substantial TEE (28.5%), limiting practical application [ABSTRACT FROM AUTHOR]