Autoregulation in Resistance Training: A Comparison of Subjective Versus Objective Methods.

ABSTRACT: Shattock, K and Tee, JC. Autoregulation in resistance training: A comparison of subjective versus objective methods. J Strength Cond Res 36(3): 641-648, 2022-Autoregulation (AR) is a resistance training periodization approach that adjusts training prescription in response to individual rates of athlete adaptation. AR training prescription can make use of either subjective (rating of perceived exertion [RPE]) or objective (barbell velocity) intensity descriptors. The aim of this research was to compare the efficacy of these 2 approaches in improving sport-specific physical performance measures. Using a randomized crossover design, 20 amateur rugby union players completed two 6-week blocks of training with training intensity prescribed using either objective velocity-based (VB) (measured using a wearable accelerometer device) or objective RPE-based intensity prescriptions. Training volume was matched for both groups while training intensity was equivalent but prescribed using either VB or RPE measures. Performance measurements were countermovement jump (CMJ), 1 repetition maximum back squat and bench press, and 10-, 20-, and 40-m sprint. Testing was conducted before and immediately after each training block. The likelihood that observed changes in performance measures were meaningful was assessed using magnitude-based decisions. Both training programs induced practically meaningful improvements in CMJ (VB most likely +8.2, ±1.1%; RPE likely +3.8, ±0.9%), back squat (VB most likely +7.5, ±1.5%; RPE possibly +3.5, ±1.8%), and bench press (VB most likely +7.7, ±2.1%; RPE possibly +3.8, ±0.9%). Changes in sprint test performance were very likely trivial for both programs. Objective AR programming resulted in larger improvements in CMJ (likely 4.2, ±1.2%), squat (likely 3.7, ±1.5%) performance, and bench press (possibly 3.7, ±1.5%) performance. Autoregulation periodization improved strength and CMJ, but not sprint performance. Autoregulation effects are augmented through the use of objective intensity prescription.

Incidence and characteristics of injury in under-19 academy level rugby league match play: A single season prospective cohort study.

Academy rugby league competition is an important step along the pathway to professional status, but little is known about injury at this level of the game. The aim of this research was to establish the nature, incidence and burden of injury in English academy rugby league. Using an observational prospective cohort study design, and a time-loss injury definition, the injury outcomes of three professional rugby league academies were recorded during the 2017 season. A total of 87 injuries occurred in 59 matches for an overall injury incidence of 85 (95%CI 67-103) injuries per 1000 hours played. The mean severity of injury was 22 ± 19 days resulting in an overall injury burden of 1898 (95%CI 1813-1983) days lost per 1000 hours. The tackle event was the most common cause of injury (77% of all injuries). Forwards sustained a greater proportion of injuries than backs (forwards 67% vs. backs 33% of injuries). Concussion (13 (6-20) per 1000 hours) and ankle sprains (11 (4-17) per 1000 hours) were the most commonly diagnosed injuries. The shoulder joint was the most commonly injured site (17 (9-25) per 1000 hours). The incidence of injury for academy rugby league is similar to senior professional rugby league.

Preseason Functional Movement Screen Component Tests Predict Severe Contact Injuries in Professional Rugby Union Players.

Tee, JC, Klingbiel, JFG, Collins, R, Lambert, MI, and Coopoo, Y. Preseason Functional Movement Screen component tests predict severe contact injuries in professional rugby union players. J Strength Cond Res 30(11): 3194-3203, 2016-Rugby union is a collision sport with a relatively high risk of injury. The ability of the Functional Movement Screen (FMS) or its component tests to predict the occurrence of severe (≥28 days) injuries in professional players was assessed. Ninety FMS test observations from 62 players across 4 different time periods were compared with severe injuries sustained during 6 months after FMS testing. Mean composite FMS scores were significantly lower in players who sustained severe injury (injured 13.2 ± 1.5 vs. noninjured 14.5 ± 1.4, Effect Size = 0.83, large) because of differences in in-line lunge (ILL) and active straight leg raise scores (ASLR). Receiver-operated characteristic curves and 2 × 2 contingency tables were used to determine that ASLR (cut-off 2/3) was the injury predictor with the greatest sensitivity (0.96, 95% confidence interval [CI] = 0.79-1.0). Adding the ILL in combination with ASLR (ILL + ASLR) improved the specificity of the injury prediction model (ASLR specificity = 0.29, 95% CI = 0.18-0.43 vs. ASLR + ILL specificity = 0.53, 95% CI = 0.39-0.66, p ≤ 0.05). Further analysis was performed to determine whether FMS tests could predict contact and noncontact injuries. The FMS composite score and various combinations of component tests (deep squat [DS] + ILL, ILL + ASLR, and DS + ILL + ASLR) were all significant predictors of contact injury. The FMS composite score also predicted noncontact injury, but no component test or combination thereof produced a similar result. These findings indicate that low scores on various FMS component tests are risk factors for injury in professional rugby players.

The Effect of Rugby Union Match Play on Sleep Patterns and Subsequent Impact on Postmatch Fatigue Responses.

PURPOSE: Sleep is recognized as an important recovery strategy, yet little is known regarding its impact on postmatch fatigue. The aims of this study were to (1) describe sleep and postmatch fatigue, (2) understand how sleep is affected by contextual and match factors, and (3) assess how changes in sleep can affect postmatch fatigue. METHODS: Twenty-three male rugby union players were monitored across 1 season (N = 71 player-match observations). Actigraphy was used during preseason to establish baseline sleep quality and quantity. Sleep was then measured 1 and 2 days after each match day (MD + 1 and MD + 2). Global positioning systems, notational analysis, and rating of perceived exertion represented external and internal load from matches. Subjective wellness and a standardized run were used to characterize postmatch fatigue 2 days prior (baseline) and at MD + 1 and MD + 2. Linear mixed models established the magnitude of change (effect size [ES]) between baseline, MD + 1, and MD + 2 for sleep and postmatch fatigue. Stepwise forward selection analysis ascertained the effect of match load on sleep and the effect of sleep on postmatch fatigue. Each analysis was combined with magnitude-based decisions. RESULTS: Sleep characteristics and neuromuscular and perceptual postmatch fatigue were negatively affected at MD + 1 and MD + 2 (ES = small to very large). Kickoff and travel time had the greatest effect on sleep (ES = small). Wellness and soreness were influenced by sleep (fall-asleep time and fragmentation index) and collisions, respectively (ES = small). CONCLUSION: Sleep quality and quantity were affected independently of the match load (ie, running activity) sustained, and changes in sleep marginally affected postmatch fatigue.

The Travel Demands of an Elite Rugby Sevens Team: Effects on Objective and Subjective Sleep Parameters.

PURPOSE: To explore the effects of travel related to international rugby sevens competition on sleep patterns. METHODS: A total of 17 international male rugby sevens players participated in this study. Actigraphic and subjective sleep assessments were performed daily during 2 separate Sevens World Series competition legs (Oceania and America). The duration of each competition leg was subdivided into key periods (pretour, precompetition, tournament 1, relocation, tournament 2, and posttour) lasting 2 to 7 nights. Linear mixed models in combination with magnitude-based decisions were used to assess (1) the difference between preseason and key periods and (2) the effect of travel direction (eastward or westward). RESULTS: Shorter total sleep time (hours:minutes) was observed during tournament 2 (mean [SD], 06:16 [01:08]), relocation (06:09 [01:09]), and the pretour week (06:34 [01:24]) compared with the preseason (06:52 [01:00]). Worse sleep quality (arbitrary units) was observed during tournament 1 (6.1 [2.0]) and 2 (5.7 [1.2]), as well as during the relocation week (6.3 [1.5]) than during the preseason (6.5 [1.8]). When traveling eastward compared with westward, earlier fall-asleep time was observed during tournament 1 (ES - 0.57; 90% CI, -1.12 to -0.01), the relocation week (-0.70 [-1.11 to -0.28]), and the posttour (-0.57 [-0.95 to -0.18]). However, possibly trivial and unclear differences were observed during the precompetition week (0.15 [-0.15 to 0.45]) and tournament 2 (0.81 [-0.29 to 1.91]). CONCLUSION: The sleep patterns of elite rugby sevens players are robust to the effects of long-haul travel and jet lag. However, the staff should consider promoting sleep during the tournament and relocation week.

Pacing characteristics of whole and part-game players in professional rugby union.

Contemporary theories on players' intensity distribution in team sports suggest that they regulate their outputs using pacing strategies. There is currently limited information on how movement patterns and pacing strategies of rugby union players in different position groups (forwards and backs) vary when exposed to different bout types (whole game, starter or finisher). Global positioning system (GPS) and accelerometer data were collected from 100 professional match participations to determine temporal effects on movement patterns. For forwards, finishers (players who entered the game as substitutes) demonstrated significantly greater high-speed running distance (% difference, ± 90%CI; magnitude-based inference and effect size) (↑ 55, ±17%; very likely large) and acceleration frequency (↑ 78, ±59%; very likely large) than whole game players. For backs, starters (players who started the game and were later substituted) displayed greater high-speed running distance than whole game players (↑ 27, ±21%; ES = likely medium) but this difference did not achieve statistical significance (p = .07). Forwards displayed "slow-positive" pacing strategies regardless of bout type, while backs displayed "flat" pacing strategies. Forwards and backs adopt different pacing strategies regardless of bout type, with forwards demonstrating progressively greater performance decrements over the course of the match. These findings reflect differing physical demands, notably contact and running loads, of players in different positions.

Sports Injury Prevention is Complex: We Need to Invest in Better Processes, Not Singular Solutions.

In recent years, an understanding has developed that sports injuries are the emergent outcomes of complex, dynamic systems. Thus, the influence of local contextual factors on injury outcomes is increasingly being acknowledged. These realisations place injury prevention research at a crossroads. Currently, injury prevention researchers develop universally applicable injury prevention solutions, but the adoption of these solutions in practice is low. This occurs because implementation contexts are both unique and dynamic in nature, and as a result singular, static solutions are often incompatible. In contrast, practitioners address injury prevention through iterative cycles of trial and error, aiming to optimise the injury prevention process within their own unique contexts. The purpose of this critical review is to draw attention to the misalignment between research and practice-based approaches to injury prevention. In light of this, we propose alternative research approaches that acknowledge the process-driven nature of injury prevention in practice. We propose that a core focus of sport injury prevention research should be to provide practitioners with useful and relevant information to support their decision making around their localised injury prevention practice. Through this approach, injury prevention research ceases to be about what works, and begins to engage with understanding what works in what contexts and why?

The efficacy of an iterative "sequence of prevention" approach to injury prevention by a multidisciplinary team in professional rugby union.

OBJECTIVES: Due to the complex systems nature of injuries, the responsibility for injury risk management cannot lie solely within a single domain of professional practice. Interdisciplinary collaboration between technical/tactical coaches, strength and conditioning coaches, team doctors, physical therapists and sport scientists is likely to have a meaningful impact on injury risk. This study describes the application and efficacy of a multidisciplinary approach to reducing team injury risk in professional rugby union. DESIGN: Observational longitudinal cohort study. METHODS: Epidemiological injury data was collected from a professional rugby union team for 5 consecutive seasons. Following each season, these data informed multidisciplinary intervention strategies to reduce injury risk. The effectiveness of these strategies was iteratively assessed to inform future interventions. Specific examples of intervention strategies are provided. RESULTS: Overall team injury burden displayed a likely beneficial decrease (-8%; injury rate ratio (IRR) 0.9, 95%CI 0.9-1.0) from 2012 to 2016. This was achieved through a most likely beneficial improvement in non-contact injury burden (-39%; IRR 0.6, 95%CI 0.6-0.7). Contact injury burden was increased, but to a lesser extent (+18%; IRR 1.2, 95%CI 1.1-1.3, most likely harmful) during the same period. CONCLUSIONS: The range of skills required to effectively manage complex injury phenomena in professional collision sport crosses disciplinary boundaries. The evidence presented here points to the effectiveness of a multidisciplinary approach to reducing injury risk. This model will likely be applicable across a range of team and individual sports.

Metabolic consequences of exercise-induced muscle damage.

Exercise-induced muscle damage (EIMD) is commonly experienced following either a bout of unaccustomed physical activity or following physical activity of greater than normal duration or intensity. The mechanistic factor responsible for the initiation of EIMD is not known; however, it is hypothesised to be either mechanical or metabolic in nature. The mechanical stress hypothesis states that EIMD is the result of physical stress upon the muscle fibre. In contrast, the metabolic stress model predicts that EIMD is the result of metabolic deficiencies, possibly through the decreased action of Ca(2+)-adenosine triphosphatase. Irrespective of the cause of the damage, EIMD has a number of profound metabolic effects. The most notable metabolic effects of EIMD are decreased insulin sensitivity, prolonged glycogen depletion and an increase in metabolic rate both at rest and during exercise. Based on current knowledge regarding the effects that various types of damaging exercise have on muscle metabolism, a new model for the initiation of EIMD is proposed. This model states that damage initiation may be either metabolic or mechanical, or a combination of both, depending on the mode, intensity and duration of exercise and the training status of the individual.

Impact of Fatigue on Positional Movements During Professional Rugby Union Match Play.

PURPOSE: In team sports, fatigue is manifested by a self-regulated decrease in movement distance and intensity. There is currently limited information on the effect of fatigue on movement patterns in rugby union match play, particularly for players in different position groups (backs vs forwards). This study investigated the effect of different match periods on movement patterns of professional rugby union players. METHODS: Global positioning system (GPS) data were collected from 46 professional match participations to determine temporal effects on movement patterns. RESULTS: Total relative distance (m/min) was decreased in the 2nd half for both forwards (-13%, ±8%, ES = very likely large) and backs (-9%, ±7%, ES = very likely large). A larger reduction in high-intensity-running distance in the 2nd half was observed for forwards (-27%, ±16%, ES = very likely medium) than for backs (-10%, ±15%; ES = unclear). Similar patterns were observed for sprint (>6 m/s) frequency (forwards -29%, ±29%, ES = likely small vs backs -13% ±18%, ES = possibly small) and acceleration (>2.75 m/s2) frequency (forwards -27%, ±24%, ES = likely medium vs backs -5%, ±46%, ES = unclear). Analysis of 1st- and 2nd-half quartiles revealed differing pacing strategies for forwards and backs. Forwards display a "slow-positive" pacing strategy, while the pacing strategy of backs is "flat." CONCLUSIONS: Forwards suffered progressively greater performance decrements over the course of the match, while backs were able to maintain performance intensity. These findings reflect differing physical demands, notably contact and running loads, of players in different positions.

Physical fitness components associated with performance in a multiple-sprint test.

PURPOSE: The 5-m repeat-sprint test (5-m RST) measures resistance to fatigue after repeated bouts of short-duration, high-intensity activity. This study determined the components of fitness associated with performance in 5-m RSTs. METHODS: Speed (10-m and 40-m sprints), strength (bench press), agility, strength endurance (pull-ups and push-ups), and aerobic power (20-m shuttle-run test) were measured in male provincial- or national-level rugby (n = 110), hockey (n = 59), and soccer (n = 55) players. RESULTS: Subjects with either high (HI) or low (LO) resistance to fatigue in the 5-m RST differed in body mass (76.9 +/- 11.6 kg vs 102.1 +/- 18.9 kg, HI vs LO, respectively, P < .001), agility (14.55 +/- 0.41 seconds vs 15.56 +/- 0.30 seconds, P < .001), bench press (86 +/- 20 kg vs 114 +/- 33 kg, P = .03), pull-ups (13 +/- 4 vs 8 +/- 5, P = .02), push-ups (56 +/- 12 vs 39 +/- 13, P = .002), and 20-m shuttle-run test (20-m SRT; 133 +/- 11 vs 87 +/- 12 shuttles, P < .001). Body mass, strength, and aerobic power were the best predictors of 5-m RST performance: 5-m RST = -1.274(mass) + 0.756(1RM bench press) + 2.053(number of 20-m SRT shuttles) + 549.409 (R2 = .66). CONCLUSIONS: Performance in the 5-m RST is predicted best by a combination of factors including body mass, strength, and aerobic ability, rather than by any single component of fitness.