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Purpose: Prescribing resistance training using velocity loss thresholds can enhance exercise quality by mitigating neuromuscular fatigue. As little is known regarding performance during these protocols, we aimed to assess the effects of 10%, 20%, and 30% velocity loss thresholds on kinetic, kinematic, and repetition characteristics in the free-weight back squat. Methods: Using a randomized crossover design, 16 resistance-trained men were recruited to complete 5 sets of the barbell back squat. Lifting load corresponded to a mean concentric velocity (MV) of ∼0.70 m·s−1 (115 [22] kg). Repetitions were performed until a 10%, 20%, or 30% MV loss was attained. Results: Set MV and power output were substantially higher in the 10% protocol (0.66 m·s−1 and 1341 W, respectively), followed by the 20% (0.62 m·s−1 and 1246 W) and 30% protocols (0.59 m·s−1 and 1179 W). There were no substantial changes in MV (−0.01 to −0.02 m·s−1) or power output (−14 to −55 W) across the 5 sets for all protocols, and individual differences in these changes were typically trivial to small. Mean set repetitions were substantially higher in the 30% protocol (7.8), followed by the 20% (6.4) and 10% protocols (4.2). There were small to moderate reductions in repetitions across the 5 sets during all protocols (−39%, −31%, −19%, respectively), and individual differences in these changes were small to very large. Conclusions: Velocity training prescription maintains kinetic and kinematic output across multiple sets of the back squat, with repetition ranges being highly variable. Our findings, therefore, challenge traditional resistance training paradigms (repetition based) and add support to a velocity-based approach. [ABSTRACT FROM AUTHOR]

To (i) quantify the differences in locomotor and technical characteristics between different drill categories in female soccer and (ii) explore the training drill distributions between different standards of competition. Technical (ball touches, ball releases, high-speed ball releases) and locomotor data (total distance, high-speed running distance [>5.29 m∙s−1]) were collected using foot-mounted inertial measurement units from 458 female soccer players from three Women's Super League (WSL; n = 76 players), eight Women's Championship (WC; n = 217) and eight WSL Academy (WSLA; n = 165) teams over a 28-week period. Data were analysed using general linear mixed effects. Across all standards, the largest proportion of time was spent in technical (TEC) (WSL = 38%, WC = 28%, WSLA = 29%) and small-sided extensive games (SSGe) (WSL = 20%, WC = 31%, WSLA = 30%) drills. WSL completed more TEC and tactical (TAC) training whilst WC and WSLA players completed more SSGe and possession (POS) drills. Technical drills elicited the highest number of touches, releases and the highest total distance and high-speed activity. Position-specific drills elicited the lowest number of touches and releases and the lowest total distance. When the technical and locomotor demand of each drill were made relative to time, there were limited differences between drills, suggesting drill duration was the main moderating factor. Findings provide novel understanding of the technical and locomotor demands of different drill categories in female soccer. These results can be used by coaches and practitioners to inform training session design. [ABSTRACT FROM AUTHOR]

This study aimed to quantify the duration-specific peak average running speeds of Academy-level rugby league match play, and compare between playing positions. Global positioning system data were collected from 149 players competing across 9 teams during 21 professional Academy (under-19) matches. Players were split into 6 positions: hookers (n = 40), fullbacks (n = 24), halves (n = 47), outside backs (n = 104), middles (n = 118), and backrow forwards (n = 104). Data were extracted and the 10-Hz raw velocity files exported to determine the peak average running speeds, via moving averages of speed (m·min-1), for 10- and 30-second, and 1- to 5- and 10-minute durations. The data were log transformed and analyzed using linear mixed-effect models followed by magnitude-based inferences, to determine differences between positions. Differences in the peak average running speeds are present between positions, indicating the need for position-specific prescription of velocity-based training. Fullbacks perform possibly to most likely greater average running speeds than all other positions, at each duration, except at 10 seconds vs. outside backs. Other differences are duration dependent. For 10 seconds, the average running speed is most likely greater for outside backs vs. the hookers, middles, and backrow forwards, but likely to most likely lower for 10 minutes. Hookers have possibly trivial or lower average speed for 10 seconds vs. middles and backrow forwards, but very likely greater average running speed for 10 minutes. The identified peak average running speeds of Academy-level match play seem similar to previously reported values of senior professional level. [ABSTRACT FROM AUTHOR]

Accurate quantification of energy intake is imperative in athletes; however traditional dietary assessment tools are frequently inaccurate. Therefore, this study investigated the validity of a contemporary dietary assessment tool or wearable technology to determine the total energy intake (TEI) of professional young athletes. The TEI of eight professional young male rugby league players was determined by three methods; Snap-N-Send, SenseWear Armbands (SWA) combined with metabolic power and doubly labelled water (DLW; intake-balance method; criterion) across a combined ten-day pre-season and seven-day in-season period. Changes in fasted body mass were recorded, alongside changes in body composition via isotopic dilution and a validated energy density equation. Energy intake was calculated via the intake-balance method. Snap-N-Send non-significantly over-reported pre-season and in-season energy intake by 0.21 (2.37) MJ.day−1 (p = 0.833) and 0.51 (1.73) MJ.day−1 (p = 0.464), respectively. This represented a trivial and small standardised mean bias, and very large and large typical error. SenseWear Armbands and metabolic power significantly under-reported pre-season and in-season TEI by 3.51 (2.42) MJ.day−1 (p = 0.017) and 2.18 (1.85) MJ.day−1 (p = 0.021), respectively. This represents a large and moderate standardised mean bias, and very large and very large typical error. There was a most likely larger daily error reported by SWA and metabolic power than Snap-N-Send across pre-season (3.30 (2.45) MJ.day−1; ES = 1.26 ± 0.68; p = 0.014) and in-season periods (1.67 (2.00) MJ.day−1; ES = 1.27 ± 0.70; p = 0.012). This study demonstrates the enhanced validity of Snap-N-Send for assessing athlete TEI over combined wearable technology, although caution is required when determining the individual TEIs of athletes via Snap-N-Send. [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]