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Abstract: Thompson, SW, Lake, JP, Rogerson, D, Ruddock, A, and Barnes, A. Kinetics and kinematics of the free-weight back squat and loaded jump squat. J Strength Cond Res 37(1): 1-8, 2023-The aim of this study was to compare kinetics and kinematics of 2 lower-body free-weight exercises, calculated from concentric and propulsion subphases, across multiple loads. Sixteen strength-trained men performed back squat 1 repetition maximum (1RM) tests (visit 1), followed by 2 incremental back squat and jump squat protocols (visit 2) (loads = 0% and 30-60%, back squat 1RM). Concentric phase and propulsion phase force-time-displacement characteristics were derived from force plate data and compared using analysis of variance and Hedges' g effect sizes. Intrasession reliability was calculated using intraclass correlation coefficient (ICC) and coefficient of variation (CV). All dependent variables met acceptable reliability (ICC >0.7; CV < 10%). Statistically significant 3-way interactions (load × phase × exercise) and 2-way main effects (phase × exercise) were observed for mean force, velocity (30-60% 1RM), power, work, displacement, and duration (0%, 30-50% 1RM) ( p < 0.05). A significant 2-way interaction (load × exercise) was observed for impulse ( p < 0.001). Jump squat velocity ( g = 0.94-3.80), impulse ( g = 1.98-3.21), power ( g = 0.84-2.93), and work ( g = 1.09-3.56) were significantly larger across concentric and propulsion phases, as well as mean propulsion force ( g = 0.30-1.06) performed over all loads ( p < 0.001). No statistically significant differences were observed for mean concentric force. Statistically longer durations ( g = 0.38-1.54) and larger displacements ( g = 2.03-4.40) were evident for all loads and both subphases ( p < 0.05). Ballistic, lower-body exercise produces greater kinetic and kinematic outputs than nonballistic equivalents, irrespective of phase determination. Practitioners should therefore use ballistic methods when prescribing or testing lower-body exercises to maximize athlete's force-time-displacement characteristics., (Copyright © 2021 National Strength and Conditioning Association.)

Purpose: This study compared pooled against individualized load-velocity profiles (LVPs) in the free-weight back squat and power clean., Methods: A total of 10 competitive weightlifters completed baseline 1-repetition maximum assessments in the back squat and power clean. Three incremental LVPs were completed, separated by 48 to 72 hours. Mean and peak velocity were measured via a linear-position transducer (GymAware). Linear and nonlinear (second-order polynomial) regression models were applied to all pooled and individualized LVP data. A combination of coefficient of variation (CV), intraclass correlation coefficient, typical error of measurement, and limits of agreement assessed between-subject variability and within-subject reliability. Acceptable reliability was defined a priori as intraclass correlation coefficient > .7 and CV < 10%., Results: Very high to practically perfect inverse relationships were evident in the back squat (r = .83-.96) and power clean (r = .83-.89) for both regression models; however, stronger correlations were observed in the individualized LVPs for both exercises (r = .85-.99). Between-subject variability was moderate to large across all relative loads in the back squat (CV = 8.2%-27.8%) but smaller in the power clean (CV = 4.6%-8.5%). The power clean met our criteria for acceptable reliability across all relative loads; however, the back squat revealed large CVs in loads ≥90% of 1-repetition maximum (13.1%-20.5%)., Conclusions: Evidently, load-velocity characteristics are highly individualized, with acceptable levels of reliability observed in the power clean but not in the back squat (≥90% of 1-repetition maximum). If practitioners want to adopt load-velocity profiling as part of their testing and monitoring procedures, an individualized LVP should be utilized over pooled LVPs.

To date, little is known about overreaching (OR) and the overtraining syndrome (OTS) in strength sports and resistance training (RT) populations. However, the available literature may elucidate the occurrence of both conditions in these populations. A scoping review was conducted. SPORTDiscus, Scopus and Web of Science were searched in a robust and systematic manner, with relevant articles analysed. 1170 records were retrieved during an initial search, with a total of 47 included in the review. Two broad themes were identified during data extraction: 1) overreaching in strength sports; 2) overreaching and overtraining syndrome in RT. Short-term periods of OR achieved with either high-volume or high-intensity RT can elicit functional OR (FOR) but there is also evidence that chronic high-volume and/or intensity RT can lead to non-functional overreaching (NFOR). There is minimal evidence to suggest that true OTS has occurred in strength sports or RT based on the studies entered during this review. More research is needed to develop robust guiding principles for practitioners. Additionally, due to the heterogeneous nature of the existing literature, future research would benefit from the development of practical tools to identify and diagnose the transition from FOR to NFOR, and subsequently OTS in strength athletes and RT populations., Abbreviations: RT: Resistance training; OR: Overreaching; FOR: Functional overreaching; NFOR: Non-functional overreaching; OTS: Overtraining syndrome; WP: Weightlifting performance.

Background: Optimal prescription of resistance exercise load (kg) is essential for the development of maximal strength. Two methods are commonly used in practice with no clear consensus on the most effective approach for the improvement of maximal strength., Objective: The primary aim of this review was to compare the effectiveness of percentage 1RM (% 1RM) and repetition maximum targets (RM) as load prescription methods for the development of maximal strength., Methods: Electronic database searches of MEDLINE, SPORTDiscus, Scopus, and CINAHL Complete were conducted in accordance with PRISMA guidelines. Studies were eligible for inclusion if a direct measure of maximal strength was used, a non-training control group was a comparator, the training intervention was > 4 weeks in duration and was replicable, and participants were defined as healthy and between the ages of 18-40. Methodological quality of the studies was evaluated using a modified Downs and Black checklist. Percentage change (%) and 95% confidence intervals (CI) for all strength-based training groups were calculated. Statistical significance (p < 0.05) was reported from each study., Results: Twenty-two studies comprising a total of 761 participants (585 males and 176 females) were found to meet the inclusion criteria. 12 studies were returned for % 1RM, with 10 for RM. All studies showed statistically significant improvements in maximal strength in the training groups (31.3 ± 21.9%; 95% CI 33.1-29.5%). The mean quality rating for all studies was 17.7 ± 2.3. Four studies achieved a good methodological rating, with the remainder classified as moderate., Conclusions: Both % 1RM and RM are effective tools for improving maximal strength. % 1RM appears to be a better prescriptive method than RM potentially due to a more sophisticated management of residual fatigue. However, large heterogeneity was present within this data. Lower body and multi-joint exercises appear to be more appropriate for developing maximal strength. Greater consensus is required in defining optimal training prescriptions, physiological adaptations, and training status.

Hills, SP, Rogerson, DJ. Associatons between self-reported well-being and neuromuscular performance during a professional rugby union season. J Strength Cond Res 32(9): 2498-2509, 2018-Self-reported wellness is often used to monitor fatigue responses to training and competition. Constraints within team sports mean short-form wellness questionnaires are typically preferred to literature-validated documents. This research aimed to assess the relationship between self-reported wellness and neuromuscular (NM) performance during a professional rugby union season, and to identify changes in these parameters over a 12-week period. On the first training day each week, before activity, 37 players rated 5 wellness subscales ("fatigue/vigor," "upper-body soreness," "lower-body soreness," "mood," and "sleep quality/duration") on a 1-5 Likert scale (1 representing the lowest wellness), and 5-repetition countermovement jumps (CMJs) were completed after a warm-up. Each week, total wellness, wellness subscales, and 4 CMJ measures for each participant were calculated as change from baseline. Within-participant correlations were determined between changes in wellness and CMJ measures, whereas week-to week differences and differences from baseline were assessed using Wilcoxon signed-rank tests. Within-participant correlations were compared for players grouped by age and position. Wellness and CMJ scores fluctuated according to physical stress, persisted beneath baseline throughout, and showed declining trends over 12 weeks. Very large (r = 0.7-0.89)/large (r = 0.5-0.69) correlations were identified between wellness and CMJ variables (positive: velocity, dip, time; negative: duration), and each wellness subscale displayed large/very large positive correlations with CMJ velocity. This was true for all subgroups, although subtle differences existed between ages and positions. It was concluded that players' subjective wellness is a useful tool, ideally used within a broader monitoring scheme, for monitoring ongoing NM fatigue, which increased from week to week.

Short-term periods of increased resistance exercise training are often used by athletes to enhance performance, and can induce functional overreaching (FOR), resulting in improved physical capabilities. Non-functional overreaching (NFOR) or overtraining syndrome (OTS), occur when training demand is applied for prolonged periods without sufficient recovery. Overtraining (OT) describes the imbalance between training demand and recovery, resulting in diminished performance. While research into the effects of resistance exercise OT has gathered attention from sports scientists in recent years, the current research landscape is heterogeneous, disparate, and underrepresented in the literature. To date, no studies have determined a reliable physiological or psychological marker to assist in the early detection of NFOR or OTS following periods of resistance exercise OT. The purpose of this work is to highlight the conceptual and methodological limitations within some of the current literature, and to propose directions for future research to enhance current understanding. [ABSTRACT FROM AUTHOR]

Optimal physical performance is achieved through the careful manipulation of training and recovery. Short-term increases in training demand can induce functional overreaching (FOR) that can lead to improved physical capabilities, whereas nonfunctional overreaching (NFOR) or the overtraining syndrome (OTS) occur when high training-demand is applied for extensive periods with limited recovery. To date, little is known about the OTS in strength sports, particularly from the perspective of the strength sport coach. Fourteen high-performance strength sport coaches from a range of strength sports (weightlifting; n = 5, powerlifting; n = 4, sprinting; n = 2, throws; n = 2, jumps; n = 1) participated in semistructured interviews (mean duration 57; SD = 10 min) to discuss their experiences of the OTS. Reflexive thematic analysis resulted in the identification of four higher order themes: definitions, symptoms, recovery and experiences and observations. Additional subthemes were created to facilitate organisation and presentation of data, and to aid both cohesiveness of reporting and publicising of results. Participants provided varied and sometimes dichotomous perceptions of the OTS and proposed a multifactorial profile of diagnostic symptoms. Prevalence of OTS within strength sports was considered low, with the majority of participants not observing or experiencing long-term reductions in performance with their athletes. [ABSTRACT FROM AUTHOR]

This study investigated the inter-day and intra-device reliability, and criterion validity of six devices for measuring barbell velocity in the free-weight back squat and power clean. In total, 10 competitive weightlifters completed an initial one repetition maximum (1RM) assessment followed by three load-velocity profiles (40–100% 1RM) in both exercises on four separate occasions. Mean and peak velocity was measured simultaneously on each device and compared to 3D motion capture for all repetitions. Reliability was assessed via coefficient of variation (CV) and typical error (TE). Least products regression (LPR) (R2) and limits of agreement (LOA) assessed the validity of the devices. The Gymaware was the most reliable for both exercises (CV < 10%; TE < 0.11 m·s−1, except 100% 1RM (mean velocity) and 90‒100% 1RM (peak velocity)), with MyLift and PUSH following a similar trend. Poorer reliability was observed for Beast Sensor and Bar Sensei (CV = 5.1–119.9%; TE = 0.08–0.48 m·s−1). The Gymaware was the most valid device, with small systematic bias and no proportional or fixed bias evident across both exercises (R2 > 0.42–0.99 LOA = −0.03–0.03 m·s−1). Comparable validity data was observed for MyLift in the back squat. Both PUSH devices produced some fixed and proportional bias, with Beast Sensor and Bar Sensei being the least valid devices across both exercises (R2 > 0.00–0.96, LOA = −0.36–0.46 m·s−1). Linear position transducers and smartphone applications could be used to obtain velocity-based data, with inertial measurement units demonstrating poorer reliability and validity. [ABSTRACT FROM AUTHOR]