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Purpose: Rugby union is a contact team sport demanding high levels of physical capacity, and understanding the match workloads can be useful to inform training. In this study, the factors influencing locomotion and contact workloads for offensive and defensive ball-in-play periods are quantified. Methods: Locomotion and contact metrics were collected from global positioning system units and videos for 31 professional players of a Super Rugby team across 14 games in the 2021 season. Data were analyzed with a generalized mixed-model procedure that included effects for type of play, playing position, match outcome, and ball-in-play time. Magnitudes were assessed with standardization, and evidence for substantial magnitudes was derived from sampling uncertainty. Results: When offense was compared to defense, most metrics showed decisively substantial increases (small to moderate) for forwards and backs. There was decisive evidence that locomotion metrics were substantially lower (large differences) and contact metrics were higher (very large differences) when comparing forwards to backs on offense and defense. When winning was compared to losing, there was good evidence that forwards experienced small increases in overall workload on defense, and backs experienced a small increase in high-speed running and a moderate decrease in contacts on offense. Match-to-match changes associated with ball-in-play time, attributed to fatigue, were decisive (moderate to very large) across most metrics for forwards and backs in offense and defense. Conclusions: The increased locomotion and contact workloads in offensive periods and the differing physical requirements between positions and match outcomes for both types of play are novel findings that should aid practitioners in designing effective training.

Purpose: To examine the effects of 4 programming models (linear [LP], undulating [UP], reverse [RP], and constant [CP]) on physical performance. Methods: Forty-eight moderately strength-trained men were randomly assigned to LP, UP, RP, and CP groups according to their 1-repetition maximum (1RM) in the full-squat exercise (SQ) and followed an 8-week training intervention using the SQ and monitoring movement velocity for every repetition. All groups trained with similar mean relative intensity (65% 1RM), number of repetitions (240), sets (3), and interset recovery (4 min) throughout the training program. Pretraining and posttraining measurements included, in the SQ, 1RM load, the average velocity attained for all absolute loads common to pretests and posttests (AV), and the average velocity for loads that were moved faster (AV > 1) and slower (AV < 1) than 1 m·s⁻¹ at pretraining tests. Moreover, countermovement jump height and 20-m running sprint time were measured. Results: A significant time effect was found for all variables analyzed (P < .05), except for 20-m running sprint time. Significant group × time interactions were observed for 1RM, AV > 1, and AV (P < .05). After training, all groups attained significant strength gains on 1RM, AV, AV > 1, and AV < 1 (P < .001–.01). LP and RP groups improved their countermovement jump height (P < .01), but no significant changes were observed for UP and CP. No significant improvements were achieved in 20-m running sprint time for any groups. Conclusions: These different programming models are all suitable for improving physical performance. LP and RP induce similar or greater gains in physical performance than UP and CP.

Purpose : This study compared the effects of individualizing supramaximal interval rowing interventions using anaerobic power reserve (APR [high-intensity interval training (HIIT) prescribed according to individual APR (HIIT_APR)]) and power associated with maximal oxygen uptake ( ${\mathrm{W}\dot{\mathrm{V}}\mathrm{O}}_2\text{max}$ [HIIT prescribed based on the individual ${\mathrm{W}\dot{\mathrm{V}}\mathrm{O}}_2\text{max}$ (HIIT_W)]) on the homogeneity of physiological and performance adaptations. Methods : Twenty-four well-trained rowers (age 24.8 [4.3] y, stature 182.5 [3] cm, body mass 86.1 [4.3]) were randomized into interventions consisting of 4 × 30-second intervals at 130%APR ( ${\mathrm{W}\dot{\mathrm{V}}\mathrm{O}}_2\text{max}$ + 0.3 × maximal sprint power) with weekly progression by increasing the number of repetitions per set (5, 6, 7, 8, 9, and 10, from first to sixth session) and the same sets and repetitions with the intensity described as 130% ${\mathrm{W}\dot{\mathrm{V}}\mathrm{O}}_2\text{max}$ . The work-to-recovery ratio was 1:1 for repetitions and 3 minutes between sets. Responses of aerobic fitness indices, power output, cardiac hemodynamics, locomotor abilities, and time-trial performance were examined. Results : Both HIIT_APR and HIIT_W interventions significantly improved ${\dot{\mathrm{V}}\mathrm{O}}_2\text{max}$ , lactate threshold, cardiac hemodynamics, and 2000-m performance, with no between-groups difference in changes over time. However, HIIT_APR resulted in a lower interindividual variability in adaptations in ${\dot{\mathrm{V}}\mathrm{O}}_2\text{max}$ and related physiological parameters, but this is not the case for athletic performance, which can depend on a multitude of factors beyond physiological parameters. Conclusions : Results demonstrated that expressing supramaximal interval intensity as a proportion of APR facilitates imposing the same degrees of homeostatic stress and leads to more homogeneous physiological adaptations in maximal variables when compared to prescribing a supramaximal HIIT intervention using ${\mathrm{W}\dot{\mathrm{V}}\mathrm{O}}_2\text{max}$ . However, lower interindividual variability would be seen in submaximal variables if HIIT interventions were prescribed using ${\mathrm{W}\dot{\mathrm{V}}\mathrm{O}}_2\text{max}$ .

Purpose: This study investigated the postactivation performance-enhancement effect of maximal voluntary isometric contraction (MVIC) at the starting position on power-clean performance over a series of contrast sets. Methods: Eighteen male (age: 31 [3.7] y, body mass: 76.8 [9.1] kg, height: 175.0 [5.2] cm) and 2 female (age: 27.5 [3.5] y, body mass: 53.3.8 [2.0] kg, height: 158.5 [4.9] cm) resistance-trained individuals performed a contrast postactivation performance-enhancement protocol (isometric contrast training condition [ISO]) consisting of 3 sets of 3 MVICs alternated with 3 power cleans, with an intracontrast rest period of 1 minute. A control protocol consisted of 3 sets of 3 power cleans were performed in a separate session. Barbell velocity during the power clean was measured as an indicator of performance. Results: A significant time effect was observed for both mean velocity (MV; P < .001) and peak velocity (PV; P = .008). Time × group (P = .415–.444) and group (P = .158–.210) effects showed no significant difference for either MV or PV. However, differences in MV and PV between the corresponding sets of ISO and control condition exceeded the minimum worthwhile change, showing a small to moderate effect (MV: d = 0.38–0.50, PV: d = 0.35–0.50) in favor of ISO. There was no significant difference in rating of perceived exertion between conditions (P = .385, d = 0.22). Conclusion: Power-clean performance was potentiated after 1 minute of rest following 3 repetitions of MVIC across 3 sets. Furthermore, the ISO protocol did not result in greater perception of exertion. These results indicate that coaches may incorporate MVICs as the postactivation performance-enhancement stimulus during contrast training involving the power-clean exercise.

Purpose: To compare the effects of unilateral flywheel training (FT), using a rotational conical pulley, including multidirectional movements with either preplanned or random unanticipated/unexpected executions on functional performance in football players. Methods: A total of 32 young male football players were randomly assigned to an FT program including preplanned unilateral multidirectional movements (PTG, n = 11), an FT executing the same unilateral movements through random (ie, right or left leg) unanticipated (ie, verbal or visual cue) or unexpected (ie, moment where the cue was provided) situations (UTG, n = 11), or a control group (n = 10) that followed their football training routine. FT consisted of 1 set × 5–12 repetitions of 4 exercises performed once a week for 10 weeks. Intermittent endurance performance, repeated unilateral and bilateral jumping ability, change-of-direction (COD) ability, linear sprint velocity, preplanned repeated-sprint ability (RSA), and uncertainty RSA (RSA-RANDOM) were assessed preintervention and postintervention. Results: Significant improvements were found in RSA-RANDOM performance (P < .05, effect size [ES] range: UTG [1.83–2.16], PTG [0.69–0.73]) and COD (P < .05, ES: UTG = 1.34, PTG = 0.98]) in both training groups. Furthermore, significant improvements were also found in intermittent endurance performance (P = .016, ES = 0.37) and sprinting (P = .006, ES = 0.45) in UTG. No changes in any variable were found in the control group. No significant between-groups differences (P > .05) were reported between UTG and PTG, while differences were observed to the control group in unilateral jumping ability, COD, and RSA-RANDOM for UTG, and in RSA-RANDOM for PTG. Conclusions: A 10-week unilateral FT improved RSA-RANDOM and COD ability in youth football players, so both preplanned and unexpected situations should be included on strength training.

Purpose: This study examined performance and physiological adaptations following 3 weeks of repeated-sprint training (RST) with blood-flow restriction (BFR) or without (non-BFR). Methods: Twenty-six semiprofessional and amateur adult male team-sport players were assessed for repeated-sprint ability, anaerobic capacity, leg lean mass, neuromuscular function, and maximal aerobic capacity before and after RST. Participants completed 9 cycling RST sessions (3 sets of 5–7 × 5-s sprints, 25-s passive recovery, 3-min rest) over a 3-week period with BFR or non-BFR. Results: During RST sessions, the BFR group demonstrated lower mean power output compared with non-BFR (−14.5%; g = 1.48; P = .001). Significant improvements (P < .05) in mean and peak power output during repeated-sprint ability (+4.1%; g = 0.42, and + 2.2%; g = 0.25, respectively) and anaerobic capacity (+4.8%; g = 0.47, and + 4.7%; g = 0.32, respectively) tests, leg lean mass (+2.0%; g = 0.16), and peak aerobic power (+3.3%; g = 0.25) were observed from pretesting to posttesting without any between-groups differences. No significant changes (P > .05) were observed for maximal isometric voluntary contraction and maximal aerobic capacity. Peak rate of force development decreased (P = .003) in both groups following RST (−14.6%; g = 0.65), without any between-groups differences. Conclusions: Repeated-sprint ability, anaerobic capacity, leg lean mass, and peak aerobic power improved following 3 weeks of RST; however, the addition of BFR did not further enhance adaptations. Interestingly, comparable improvements were achieved between groups despite lower external loads experienced during RST sessions with BFR.

Despite previous support for plyometric training, optimal dosing strategies remain unclear. Purpose: To investigate vertical and horizontal jump kinetic performance following a low-volume plyometric stimulus with progressively increased session jump volume. Methods: Sixteen academy rugby players (20.0 [2.0] y; 103.0 [17.6] kg; 184.3 [5.5] cm) volunteered for this study. Vertical and horizontal jump sessions were conducted 1 week apart and consisted of a 40-jump low-volume plyometric stimulus using 4 exercises, after which volume was progressively increased to 200 jumps, using countermovement jump (CMJ) for vertical sessions and horizontal broad jump (HBJ) for horizontal sessions. Jump performance was assessed via force-plate analysis at baseline (PRE-0), following the low-volume plyometric stimulus (P-40), and every subsequent 10 jumps until the end of the session (P-50, P-60, P-70, ... P-200). Results: The low-volume stimulus was effective in potentiating HBJ (2% to 5%) but not CMJ (0% to −7%) performance (P < .001). The HBJ performance enhancements were maintained throughout the entire high-volume session, while CMJ realized small but significant decrements (−5% to −7%) in jump height P-50 to P-80 before recovering to presession values. Moreover, increases in eccentric impulse (5% to 24%; P < .001) in both sessions were associated with decreased or maintained concentric impulse, indicating a breakdown in performance-augmenting mechanisms and less effective power transfer concentrically after moderate volumes. Conclusion: Practitioners should consider kinetic differences between HBJ and CMJ with increasing volume to better inform and understand session dosing strategies.

Objectives: To analyze the positional distances covered above generic and individualized speed thresholds within the most demanding phases of match play. Categorized by position, 17 English Premier League players’ match data were analyzed over 2 consecutive seasons (2019–20 and 2020–21). The most demanding phases of play were determined using a rolling average across 4 periods of 1, 3, 5, and 10 minutes. Distance covered in the time above the standard speed of 5.5 m/s was analyzed, with individualized metrics based on the maximal aerobic speed (MAS) test data. Results: Central defenders displayed lower values for high-intensity periods when compared with fullbacks, midfielders, and wide midfielders for both generic and individualized metrics. MAS during 1-minute periods was significantly higher for forwards when compared with central defenders (82.9 [18.9] vs 67.5 [14.8] for maximum high-speed running [HSR] and 96.0 [15.9] vs 75.7 [13.8] HSR for maximum MAS activity). The maximum effect size differences between the central midfielders, wide midfielders, and fullbacks for HSR and MAS measures under the maximum HSR criterion was 0.28 and 0.18 for the 1-minute period, 0.36 and 0.19 for the 3-minute period, 0.46 and 0.31 for the 5-minute period, and 0.49 and 0.315 for the 10-minute period. Conclusions: Individualized speed metrics may provide a more precise and comparable measure than generic values. Data appear to be consistent across playing positions except for central defenders. This information may allow practitioners to directly compare individualized physical outputs of non–central defenders during the most demanding phases of play regardless of the players’ positional group. This may provide coaches with important information regarding session design, training load, and fatigue monitoring.