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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.

Purpose: This study aimed to comprehensively investigate the global implementation of flywheel training (FT) by basketball strength and conditioning (S&C) coaches in various contexts, encompassing daily practice, games, and sessions. Methods: Survey data were collected from 117 basketball S&C coaches who participated in a 24-question online survey. The survey was structured into 6 key areas, including country and competition, S&C coach context, training methodology, flywheel and competition, postactivation performance enhancement, and recovery. Results: Notably, all respondents emphasized the necessity of a familiarization period with flywheel technology, with a substantial 96% indicating that FT yielded improved player performance on the court. The predominant mention was the conical pulley system. During the season, the prevalent approach involved integrating FT into training twice a week, allocating <15 minutes per session, often in conjunction with traditional strength training. A diverse array of lower-body closed kinetic chain exercises were reported, encompassing squats, decelerations, and backward lunges. Intriguingly, FT implementation on match days was unlikely (77%), with the primary aims cited as injury prevention (34%) and enhancing players’ strength levels during various phases of the regular season (27%). Conclusions: Recognizing its inherent limitations, this descriptive study provides valuable contextual insights and practical applications for professional basketball practitioners grappling with the utilization of FT.

Introduction: This case study aimed to describe potential changes in neuromuscular activation and synergies after an 8-day cross-country mountain-bike stage race. Methods: A peak power output test was performed 5 days before the race. Two days before the start and after 7 days of racing, the athlete performed a power-based Lamberts Submaximal Cycling Test, including surface electromyography, and completed a Daily Analysis of Life Demands of Athletes questionnaire. Neuromuscular activation, in terms of root mean square, timing (onset-offset) of muscle activation, and synergies, was obtained from electromyography recordings. Results: The athlete reported an increase in symptoms of experienced stress after the stage race on the Daily Analysis of Life Demands of Athletes questionnaire. Both biceps femoris and tibialis anterior muscles showed a reduction in normalized amplitude after the stage race. In addition, the number of synergies that was necessary to describe neuromuscular activation increased from 2 to 3. Conclusions: In this case study, the increase in synergies suggests that, after the stage race, the athlete showed a more complex muscle-recruitment pattern. This may indicate that muscle coordination can change when muscle fatigue occurs; however, further research is needed to confirm these results in a larger sample.

Purpose: As a multidisciplined combat sport, relationships between external and internal training loads and intensities of mixed martial arts (MMA) have not been described. The aim of this study was to determine the external loads and intensities of MMA training categories and their relationship to internal loads and intensities. Methods: Twenty MMA athletes (age = 23.3 [5.3] y, mass = 72.1 [7.2] kg, stature = 171.5 [8.4] cm) were observed for 2 consecutive weeks. Internal load and intensity (session rating of perceived exertion [sRPE]) were calculated using the Foster RPE for the session overall (sRPE-training load [TL]) and segmented RPE (segRPE-TL) for each training category: warm-up, striking drills, wrestling drills, Brazilian jiujitsu (BJJ) drills, striking sparring, wrestling sparring, BJJ sparring, and MMA sparring. External load and intensity were measured via Catapult OptimEye S5 for the full duration of each session using accumulated Playerload (PLd_ACC) and PLd_ACC per minute (PLd_ACC·min⁻¹). Differences in loads between categories and days were assessed via Bayesian analysis of variance (BF₁₀ ≥ 3). Predictive relationships between internal and external variables were calculated using Bayesian regression. Results: Session overall sRPE-TL = 448.6 (191.1) arbitrary units (AU); PLd_ACC = 310.6 (112) AU. Category segRPE-TL range = 33.8 (22.6) AU (warm-up) to 122.8 (54.6) AU (BJJ drills). Category PLd_ACC range = 44 (36.3) AU (warm-up) to 125 (58.8) AU (MMA sparring). Neither sRPE-TL nor PLd_ACC changed between days. PLd_ACC was different between categories. Evidence for regressions was strong-decisive except for BJJ drills (BF₁₀ = 7, moderate). R ² range = .50 to .77, except for warm-up (R ² = .17), BJJ drills (R ² = .27), BJJ sparring (R ² = .49), and session overall (R ² = .13). Conclusions: While MMA training categories may be differentiated in terms of external load, overall session external load does not change within or between weeks. Resultant regression equations may be used to appropriately plan MMA technical/tactical training loads.

Adaptations to resistance training and subsequent performance can be undermined by inadequate interset recovery. Methods typically used to monitor recovery were developed for longitudinal use, making them time-inefficient within singular exercise bouts. If valid, perceptual recovery status (PRS) may be used as an efficient and inexpensive assessment tool to monitor individual recovery. Purpose: The aim of this study was to assess the validity of PRS on monitoring recovery during a high-intensity back-squat session. Methods: Ten healthy men participated in the 2-session study (separated by at least 48 h). Session 1 included anthropometrics, PRS familiarization, and a 1-repetition-maximum back squat. Session 2 included a high-intensity protocol (5 sets of 5 repetitions; 5-min interset recovery; 85% of 1-repetition maximum). PRS was obtained before the first set and during the last 30 seconds of each 5-minute recovery; rating of perceived exertion (RPE) was also collected. A linear position transducer collected mean barbell velocity (MBV). Repeated-measures correlations assessed the common intraindividual relationships of PRS scores to intraset MBV and RPE, respectively. Results: A very large, positive correlation appeared between PRS and MBV (r [95% CI] = .778 [.613 to .878]; P < .0001). A large, negative correlation emerged between PRS and RPE (r [95% CI] = −.549 [−.737 to −.282]; P < .001). Conclusions: Results indicate that PRS can be a means for practitioners to monitor individualized recovery. PRS tracked well with RPE, strengthening its utility in a practitioner-based setting. Findings provide insight into the practicality of PRS for recovery monitoring. It could be used alongside other measures (eg, MBV and countermovement jump) to individually program and maintain performance.

Ski mountaineering sprint competitions are short individual races involving 3 uphill sections (U), 3 transitions (T), and a final descent. To date, relatively little is known about this novel Olympic discipline, and here we examined (1) the contribution of the time spent on U, T, and final descent to overall finishing time and (2) the potential relationships with final ranking. During the different rounds of 2 International Ski Mountaineering Federation World Cup sprint competitions, male and female ski mountaineers were video recorded. Correlation and multiple linear regression analyses were used to investigate the impact of U, T, and final descent on the best overall finishing time. Linear-mixed model analysis was applied to explore potential interactions between section times, rounds, and final ranking. Overall, U (r = .90–.97) and T (r = .57–.89) were closely correlated with the best overall finishing time (all P < .05). U explained approximately 80% to 90% of the variation in the best finishing time for both sexes, with U + T explaining approximately 95% to 98% of this variation. In each successive round, the ski mountaineers eliminated were all slower on U than the Top 3 (all P < .05). The fastest skiers increased their performance on U in the later rounds of the competitions, while those eliminated showed a tendency toward a decrease. Our findings reveal that world-class sprint ski mountaineers conduct transitions optimally and perform effectively uphill. Training for such competitions should aim to improve short supramaximal uphill performance (∼1.5–2.5 min), ensuring that this does not decline with multiple efforts. These insights into ski mountaineering sprint performance are of considerable value in connection with training for the 2026 Winter Olympics.

Background: Submaximal fitness test (SMFT) outcome measures are frequently collected with a wide array of technologies and methodological approaches. Purpose: To examine the test–retest reliability of various SMFT outcome measures derived from different protocols and analytical techniques. Methods: Twenty-six semiprofessional adult soccer players performed 3 SMFT protocols, including 2 continuous (3 min, 11 and 12.8 km·h⁻¹) and 1 intermittent (4 × 50 m, 18 km·h⁻¹) twice, each separated by 7 days. Heart-rate (HR) indices (exercise HR, HR recovery) and scapula-mounted (PlayerLoad vector magnitude) and foot-mounted (flight time and contact time, stride length) microelectrical mechanical system–derived variables were collected using different time frames and analytical approaches adopted in the literature and practice. Absolute reliability was quantified as the group mean difference, typical error of measurement, also expressed as the coefficient of variation (where appropriate) and standardized units (ie, d). Intraclass correlation coefficient was used to quantify relative reliability. Results: The highest degrees of reliability were evident for exercise HR (typical error: 1.0%–1.6% points), the vertical component of PlayerLoad (expressed in arbitrary units; coefficient of variation: 5.5%–7.0%), and contact time (coefficient of variation: 1.5%–3.0%). These estimates were not influenced by SMFT protocol or analytical approach. All other measures displayed poorer reliability and/or were different between protocols and analytical methods. Conclusions: SMFT protocols impact the test–retest reliability of various outcome measures; however, exercise HR, vertical PlayerLoad, and contact time (derived from foot-mounted micro-electrical mechanical systems) appear to have stable measurement properties to assist the assessment of aerobic capacity and lower-limb neuromuscular status, respectively.