International journal of sports physiology and performance最新文献

Purpose: This study aimed to investigate the impact of a 6-week upper-body plyometric-training (PT) program with varying volumes on the immunoendocrine, physiological parameters, and physical performance adaptations in male volleyball players.

Methods: Twenty-four trained college players were randomly allocated into 3 groups with 8 participants. Each group performed 5 exercises at maximal effort with differences in volume: low (3 sets of 7 repetitions), moderate (3 sets of 10 repetitions), and high (3 sets of 13 repetitions). The training program lasted 6 weeks with participants undertaking 3 sessions of PT per week.

Results: Following the intervention, all groups exhibited significant (P = .001) improvements in physical and physiological parameters, as well as skill-based performances, with effect sizes ranging from small to very large. Comparative analysis of individual changes indicated that the high-volume group resulted in greater adaptive responses in the medicine-ball throw (P = .004), peak (P = .001) and average (P = .022) power output, push-ups (P = .001), and strength (P = .032) compared with the low-volume group. No significant between-groups difference (P > .05) was observed regarding immunoendocrine measures, reaction time, attacking, and serving skills.

Conclusions: The findings indicate that short-term upper-body PT positively influenced performance adaptations, emphasizing that the adaptive response to PT depends on the varying volumes. The study proposes that integrating higher volumes of PT results in more significant adaptive responses among volleyball players with the same immunoendocrine responses as the other training volumes.

Purpose: Competitive cheerleading (cheersport) is a physically demanding sport; however, there is a lack of information regarding its acute physiological responses during training or competition in these athletes. Thus, this study aimed to investigate these responses during both training sessions and simulated cheerleading competition routines (full-outs) among elite cheersport athletes.

Methods: Six Coed and 10 All Girl elite cheerleaders were included in this study. Countermovement-jump (CMJ) height and blood lactate concentration were measured prepractice, after warm-up, after a full-out, and at the end of the training session. Heart rate (HR) was monitored throughout all the sessions. One-way analysis of variance was used to analyze changes over time.

Results: Most of the training time (51%-68%) was spent between 50% and 69% maximum HR. Only 3% to 4% was spent above 90% HRmax. During full-outs, most of the time (67%-80%), HR was ≥80% maximum HR. The blood lactate concentration was significantly elevated post-full-out (6.4 [1.6] mmol/L) compared with pretraining and post-warm-up (P < .001). In addition, blood lactate concentration was higher after training (3.4 [2.2] mmol/L) compared with prepractice and post-warm-up (P ≤ .025). CMJ height did not change over time (P ≤ .268).

Conclusion: Cheersport training leads to a low overall metabolic demand but is interspersed with short, high-intensity "intervals." The highest intensities were achieved during full-outs, indicating the anaerobic nature of competition routines. Therefore, cheerleaders should train both the aerobic and the anaerobic systems to increase recovery capacity between drills and to maximize anaerobic power during competition.

To define training zones, ventilatory thresholds (VTs) are commonly established by cardiopulmonary gas-exchange analysis during incremental exercise tests. Portable near-infrared spectroscopy (NIRS) devices have emerged as a potential tool for detecting these thresholds by monitoring muscle oxygenation. This study evaluated the accuracy of NIRS measurements to determine VTs or critical power (CP) based on muscle oxygen saturation and assesses the device's consistency across 2 constant-load tests. Data from 2 cross-sectional studies involving trained recreational endurance athletes (26 from study 1) and CrossFit athletes (59 from study 2) were examined. Incremental ramp tests on a cycle ergometer were performed and followed by either a constant-load test (study 1) or a CP test (study 2). When comparing power output or heart rate between NIRS-derived breakpoints and VTs, weak to moderate agreement was found. Mean differences in power output and heart rate ranged from 16.8 to 22.4 W and 3.8 to 6.0 beats·min-1 at the first threshold and 27.4 to 31.2 W and 7.1 to 7.8 beats·min-1 at the second threshold. Comparing with CP, mean differences ranged from -0.4 to 0.4 W and -0.6 to 0.9 beats·min-1. Test-retest reliability showed moderate agreement, with a mean bias of 1.2 percentage points between constant-load tests. Thus, NIRS may not be accurate for determining VTs or CP during exercise due to limited agreement in power output or hear rate, notable variability on individual level, and moderate reproducibility.

Purpose: The abundance of data in football presents both opportunities and challenges for decision making. Consequently, this review has 2 primary objectives: first, to provide practitioners with a concise overview of the characteristics of machine-learning (ML) analysis, and, second, to conduct a strengths, weaknesses, opportunities, and threats (SWOT) analysis regarding the implementation of ML techniques in professional football clubs. This review explains the difference between artificial intelligence and ML and the difference between ML and statistical analysis. Moreover, we summarize and explain the characteristics of ML learning approaches, such as supervised learning, unsupervised learning, and reinforcement learning. Finally, we present an example of a SWOT analysis that suggests some actions to be considered in applying ML techniques by medical and sport science staff working in football. Specifically, 4 dimensions are presented: the use of strengths to create opportunities and make the most of them, the use of strengths to avoid threats, working on weaknesses to take advantage of opportunities, and upgrading weaknesses to avoid threats.

Conclusion: ML analysis can be an invaluable tool for football clubs and sport-science and medical departments due to its ability to analyze vast amounts of data and extract meaningful insights. Moreover, ML can enhance performance by assessing the risk of injury, physiological parameters, and physical fitness, as well as optimizing training, recommending strategies based on opponent analysis, and identifying talent and assessing player suitability.

Purpose: Bone mineral measurements and their association with peak impact and sport-specific, persistent muscle loads were examined in 10 elite artistic swimmers age 15-19 years.

Methods: Bone mineral density (BMD) and bone mineral content (BMC) of total body, total body less head, spine, and dominant and nondominant limbs were assessed by dual-energy X-ray absorptiometry. Peak ground-reaction forces of 2 dry jumps (countermovement jump and frog jump) were measured on a force plate. Peak forces applied during in-water exercises (vertical scull, barracuda push, and kick pull) were measured.

Results: On average, artistic swimmers' total-body BMD (1.12 [0.08] g/cm2) was similar to values reported for young swimmers and nonathletic females, and total-body BMC (2359 [399] g) was higher than previously reported in race swimmers. Based on previously published reference curves, 9 out of 10 artistic swimmers had total-body less head BMD and BMC at or above the 90th percentile, with average to above average z scores and height-adjusted z scores for their age. Countermovement jump and frog jump exhibited moderate peak ground-reaction forces (2.61 [0.46] and 1.93 [0.42] N/kg, respectively). In water, greater force was exerted in kick pull (60.4 [4.8] N) compared with vertical skull (45.5 [6.4] N) and barracuda push (40.6 [4.8] N). Bone measurements were correlated with the peak ground-reaction forces exerted in both dry jumps (r = .61-.83, P ≤ .05) and the peak force output of the in-water exercises (r = .63-.80, P ≤ .05).

Conclusion: These results imply robust bone health among artistic swimmers, partially associated with the high muscle forces regularly applied during their sport-specific training that seem to counteract the low-impact nature of the sport.

Purpose: In world-class middle- and long-distance running races, a Wavelight signal has recently been used as a pacing guide for setting records. The aim of the present study was to compare performance and psychophysiological effects between light-guided, drafting, and nonassisted pacing conditions in distance runners.

Methods: Fifteen male middle- and long-distance runners of national and regional standard ran three 5000-m time trials in a counterbalanced order with the following pacing distribution: the first 4000 m and last 1000 m were covered at submaximal and maximal intensities, respectively. The 3 trials (conditions) were (1) self-paced, (2) guided by a light signal, and (3) guided by a cyclist in front (drafting condition). Pace, heart rate, rating of perceived exertion, and affective valence were recorded every 500 m.

Results: No statistically significant differences were found between pacing-light and self-paced conditions. Running time was shorter in the drafting versus self-paced condition in the final 500-m section (P = .031; d = 0.76). No differences were found between drafting and light conditions. Similarly, whereas 9 out of 10 significant differences in terms of lower heart rate, or rating of perceived exertion, or higher affective valence responses were found in the drafting versus self-paced condition (P = .004-.041; d = 0.63-1.39), only 4 were found across the tests in the drafting versus light condition (P = .005-.016; d = 0.66-0.84).

Conclusion: Light-guided pacing did not influence performance or psychophysiological responses in distance runners during a 5000-m test, but drafting produced a large effect.

Purpose: To correlate speed and heat scores with anthropometric variables and lower-limb strength and power in professional surfers.

Methods: A total of 19 men participated in simulated competitions on different days. All surfed waves were scored, and each athlete's best 2 were used for their total heat score. Speed values were extracted by global positioning system and adjusted by Z score. Squat jump, countermovement jump, and drop jump were executed. Anthropometric variables and 1-repetition maximum (1RM) in the half squat were measured. Pearson product-moment correlation was used to analyze the relationships.

Results: Height had a significant (P < .05) inverse association with speed indicators (r = -.36 to - .68), and body mass index had a moderate association with maximum wave speed of the highest score. Significant correlations with moderate to large magnitudes were found between maximum speed and vertical jumps (r = .46 to .56), average speed and vertical jumps (r = .48 to .59), and both maximum and average speed with 1RM (r = .52-.53). Athletes' best score and total heat score showed moderate to large associations with vertical jumps and 1RM (r = .48-.64), whereas second scores were correlated with the reactive strength index of the drop jump (r = .48) and 1RM (r = .51).

Conclusions: Shorter surfers with lower center of gravity and those with superior lower-limb strength and power achieved greater speed and higher scores. Accordingly, surf coaches may consider prescribing dynamic strength and balance training based on an athlete's profile to improve performance.

Purpose: To compare the acute effects on mechanical, metabolic, neuromuscular, and muscle contractile responses to different velocity-loss (VL) thresholds (20% and 40%) under distinct blood-flow conditions (free [FF] vs restricted [BFR]) in full squat (SQ).

Methods: Twenty strength-trained men performed 4 SQ protocols with 60% 1-repetition maximum that differed in the VL within the set and in the blood-flow condition (FF20: FF with 20% VL; FF40: FF with 40% VL; BFR20: BFR with 20% VL; and BFR40: BFR with 40% VL). The level of BFR was 50% of the arterial occlusion pressure. Before and after the SQ protocols, the following tests were performed: (1) tensiomyography, (2) blood lactate, (3) countermovement jump, (4) maximal voluntary isometric SQ contraction, and (5) performance with the load that elicited a 1 m·s-1 at baseline measurements in SQ.

Results: No "BFR × VL" interactions were observed. BFR protocols resulted in fewer repetitions and lower increases in lactate concentration than FF protocols. The 40% VL protocols completed more repetitions but resulted in lower mechanical performance and electromyography median frequency during the exercise than the 20% VL protocols. At postexercise, the 40% VL protocols also experienced greater blood lactate concentrations, higher alterations in tensiomyography-derived variables, and accentuated impairments in SQ and countermovement-jump performances. The 20% VL protocols showed an increased electromyography median frequency at postexercise maximal voluntary isometric contraction.

Conclusions: Despite BFR-accelerated fatigue development during exercise, a given VL magnitude induced similar impairments in the distinct performance indicators assessed, regardless of the blood-flow condition.