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The present study aimed to determine whether neuromuscular fatigue monitored through countermovement jump height was a reliable and helpful marker for monitoring acute (session) and chronic (between sessions/periods of the season) fatigue throughout an entire basketball season. A longitudinal observational study analyzed the neuromuscular performance (i.e., through countermovement jump) during a basketball season. Fourteen semiprofessional male basketball players participated in the study between September 2021 and May 2022 (34 weeks, 102 practices, and 1574 jumps analyzed). Upon waking up, they completed an online wellness questionnaire. Before practices began, players performed three countermovement jumps on a contact platform after a structured warm-up, repeating the protocol at the end of each practice. Ten minutes after finishing such practice, they also reported perceived exertion's muscular and cardiovascular ratings. The preseason was the period of the season with the lowest absolute countermovement jump height levels (2.06 to 2.50 cm; d = 1.92 to 2.74, very large, p < 0.02). Average pre-session jumps were very largely higher on Wednesdays (0.62 cm, 95% CI = 0.29 - 0.95, p = 0.0095, d = 2.09) and Fridays (0.62 cm, 95% CI = 0.06 - 0.88, p = 0.06, d = 1.43) compared to Mondays. The countermovement jump is a valuable marker for assessing fatigue in semiprofessional basketball players. Games played on weekends mainly and consistently affected Monday's jumping performance, showing the lowest average values. Finally, preseason values were lower than those observed for the rest of the season.
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This study aimed to quantify the influence of the playing surface on workload-related variables (i.e., external load, Rate of perceived exertion (RPE), and mental load) in training sessions with a Spanish professional soccer team. Twenty professional male players from the same soccer team were involved. A total of thirty training sessions related to the preseason period were included. All the players completed training sessions on three playing surfaces: natural turf of poor quality, natural turf of high quality, and third-generation artificial turf. Monitoring during sessions involved assessing internal load (i.e., RPE and mental load) via self-reported questionnaires, and external load using Global Positioning System devices. Linear mixed models showed that RPE was significantly higher on natural turf of high quality than on natural turf of poor quality (p < 0.001). Total distance, relative total distance, the number of accelerations, decelerations, and high metabolic load distance were significantly lower on third-generation artificial turf compared to natural turf of poor quality (p < 0.001) and high quality (p < 0.001). In addition, high-speed running, sprint running distances, and the number of sprints reached higher values on third-generation artificial turf compared to the other two playing surfaces. These findings highlight the need for coaches to consider the type of training surface in soccer to optimize training load planning and prevent injuries.
Subject(s)
Physical Exertion , Soccer , Soccer/physiology , Humans , Male , Physical Exertion/physiology , Adult , Workload , Athletic Performance/physiology , Young Adult , Spain , Running/physiology , Athletes , Surveys and Questionnaires , Geographic Information SystemsABSTRACT
Background: Exercise offers substantial health benefits but can induce oxidative stress and inflammation, especially in high-intensity formats such as high-intensity interval exercise (HIIE). Exergaming has become an effective, enjoyable fitness tool for all ages, particularly older adults. Enzyme supplements may enhance exercise performance by improving lactate metabolism and reducing oxidative stress. Objective: This study investigates the efficacy of fruit and vegetable enzyme supplementation in modulating fatigue and enhancing aerobic capacity in older adults following HIIE through exergaming. Methods: The study recruited 16 older adult female participants and allocated them into 2 distinct groups (enzyme and placebo) based on their pretest lactate levels. This division used pairwise grouping to guarantee comparability between the groups, ensuring the integrity of the results. They engaged in HIIE using Nintendo Switch Ring Fit Adventure, performing 8 sets of 20 seconds of maximum effort exercise interspersed with 30 seconds of rest, totaling 370 seconds of exercise. Key metrics assessed included blood lactate levels, heart rate, rating of perceived exertion, and training impulse. Participants in the enzyme group were administered a fruit and vegetable enzyme supplement at a dosage of 30 mL twice daily over a period of 14 days. Results: The enzyme group showed significantly lower blood lactate levels compared to the placebo group, notably after the fourth (mean 4.29, SD 0.67 vs mean 6.34, SD 1.17 mmol/L; P=.001) and eighth (mean 5.84, SD 0.63 vs mean 8.20, SD 1.15 mmol/L; P<.001) exercise sessions. This trend continued at 5 minutes (mean 6.85, SD 0.82 vs mean 8.60, SD 1.13 mmol/L; P=.003) and 10 minutes (mean 5.91, SD 1.16 vs mean 8.21, SD 1.27 mmol/L; P=.002) after exercise. Although both groups exceeded 85% of their estimated maximum heart rate during the exercise, enzyme supplementation did not markedly affect the perceived intensity or effort. Conclusions: The study indicates that fruit and vegetable enzyme supplementation can significantly reduce blood lactate levels in older adults following HIIE through exergaming. This suggests a potential role for these enzymes in modulating lactate production or clearance during and after high-intensity exercise. These findings have implications for developing targeted interventions to enhance exercise tolerance and recovery in older adults.
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Purpose: Monitoring players' training load allows practitioners to enhance physical performance while reducing injury risk. The aim of this study was to identify the key external load indicators in professional U19 soccer. Methods: Twenty-four-professional Italian young (U19) soccer players were monitored by using the rating of perceived exertion (CR-10 RPE scale) and a wearable inertial sensor during the competitive season. Three main components were detected by a Principal Component Analysis (PCA): i) volume metabolic related component, ii) intensity mechanical stimuli component, and iii) intensity metabolic/mechanical component. We hence computed two scores (i.e. Performance [PERF] and total workload [WORK]) permitting to investigate the weekly microcycle. Results: Correlation analysis showed that scores (i.e. PERF and WORK) are low correlated (r = -0.20) suggesting that they were independent. Autocorrelation analysis showed that a weekly microcycle is detectable in all the scores. Two-way ANOVA RM showed a statistical difference between match day (MD) and playing position for the three PCA components and PERF score. Conclusion: We proposed an innovative approach to assess both the players' physical performance and training load by using a machine learning approach allowing reducing a large dataset in an objective way. This approach may help practitioners to prescribe the training in the microcycle based on the two scores.
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BACKGROUND: Blood flow restriction (BFR) resistance training has demonstrated efficacy in promoting strength gains beneficial for rehabilitation. Yet, the distinct functional advantages of BFR strength training using high-load and low-load protocols remain unclear. This study explored the behavioral and neurophysiological mechanisms that explain the differing effects after volume-matched high-load and low-load BFR training. METHODS: Twenty-eight healthy participants were randomly assigned to the high-load blood flow restriction (BFR-HL, n = 14) and low-load blood flow restriction (BFR-LL, n = 14) groups. They underwent 3 weeks of BFR training for isometric wrist extension at intensities of 25% or 75% of maximal voluntary contraction (MVC) with matched training volume. Pre- and post-tests included MVC and trapezoidal force-tracking tests (0-75%-0% MVC) with multi-channel surface electromyography (EMG) from the extensor digitorum. RESULTS: The BFR-HL group exhibited a greater strength gain than that of the BFR-LL group after training (BFR_HL: 26.96 ± 16.33% vs. BFR_LL: 11.16 ± 15.34%)(p = 0.020). However, only the BFR-LL group showed improvement in force steadiness for tracking performance in the post-test (p = 0.004), indicated by a smaller normalized change in force fluctuations compared to the BFR-HL group (p = 0.048). After training, the BFR-HL group activated motor units (MUs) with higher recruitment thresholds (p < 0.001) and longer inter-spike intervals (p = 0.002), contrary to the BFR-LL group, who activated MUs with lower recruitment thresholds (p < 0.001) and shorter inter-spike intervals (p < 0.001) during force-tracking. The discharge variability (p < 0.003) and common drive index (p < 0.002) of MUs were consistently reduced with training for the two groups. CONCLUSIONS: BFR-HL training led to greater strength gains, while BFR-LL training better improved force precision control due to activation of MUs with lower recruitment thresholds and higher discharge rates.
Subject(s)
Electromyography , Resistance Training , Wrist , Humans , Male , Resistance Training/methods , Female , Wrist/physiology , Young Adult , Adult , Isometric Contraction/physiology , Muscle, Skeletal/physiology , Muscle, Skeletal/blood supply , Muscle Strength/physiology , Blood Flow Restriction Therapy/methodsABSTRACT
PURPOSE: Without appropriate standardization of exercise doses, comparing high- (HI) and low-intensity (LI) training outcomes might become a matter of speculation. In athletic preparation, proper quantification ensures an optimized stress-to-recovery ratio. This review aims to compare HI and LI doses by estimating theoretically the conversion ratio, 1:x, between HI and LI: How many minutes, x, of LI are equivalent to 1 minute of HI using various quantification methods? A scrutinized analysis on how the dose increases in relation to duration and intensity was also made. ANALYSIS: An estimation was conducted across 4 categories encompassing 10 different approaches: (1) "arbitrary" methods, (2) physiological and perceptual measurements during exercise, (3) postexercise measurements, and comparison to (4a) acute and (4b) chronic intensity-related maximum dose. The first 2 categories provide the most conservative estimation for the HI:LI ratio (1:1.5-1:10), and the third, slightly higher (1:4-1:11). The category (4a) provides the highest estimation (1:52+) and (4b) suggests 1:10 to 1:20. The exercise dose in the majority of the approaches increase linearly in relation to duration and exponentially in relation to intensity. CONCLUSIONS: As dose estimations provide divergent evaluations of the HI:LI ratio, the choice of metric will have a large impact on the research designs, results, and interpretations. Therefore, researchers should familiarize themselves with the foundations and weaknesses of their metrics and justify their choice. Last, the linear relationship between duration and exercise dose is in many cases assumed rather than thoroughly tested, and its use should be subjected to closer scrutiny.
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Physical Endurance , Humans , Physical Endurance/physiology , Time FactorsABSTRACT
PURPOSE: The aim of this study was to determine if machine learning models could predict the perceived morning recovery status (AM PRS) and daily change in heart rate variability (HRV change) of endurance athletes based on training, dietary intake, sleep, HRV, and subjective well-being measures. METHODS: Self-selected nutrition intake, exercise training, sleep habits, HRV, and subjective well-being of 43 endurance athletes ranging from professional to recreationally trained were monitored daily for 12 weeks (3572 days of tracking). Global and individualized models were constructed using machine learning techniques, with the single best algorithm chosen for each model. The model performance was compared with a baseline intercept-only model. RESULTS: Prediction error (root mean square error [RMSE]) was lower than baseline for the group models (11.8 vs. 14.1 and 0.22 vs. 0.29 for AM PRS and HRV change, respectively). At the individual level, prediction accuracy outperformed the baseline model but varied greatly across participants (RMSE range 5.5-23.6 and 0.05-0.44 for AM PRS and HRV change, respectively). CONCLUSION: At the group level, daily recovery measures can be predicted based on commonly measured variables, with a small subset of variables providing most of the predictive power. However, at the individual level, the key variables may vary, and additional data may be needed to improve the prediction accuracy.
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Purpose: This study aims to explore the variations in external and internal loads on a quarter-by-quarter basis among professional Chinese basketball players. It emphasizes the crucial impact of these variations on optimizing athletic performance and match strategies. Method: An observational longitudinal study design was employed, involving sixteen male players from the National Basketball League during the 2024 season in China. Data collection was facilitated through the use of Catapult S7 devices for measuring external loads and session ratings of perceived exertion (sRPE) for assessing internal loads. Linear mixed-effects models were utilized for the statistical analysis to identify differences in workload intensities across game quarters based on player positions. The Pearson correlation coefficient was used to examine the relationship between external and internal load throughout the game. Results: The analysis uncovered significant positional differences in workload intensities across game quarters. Guards were found to have a higher PlayerLoad™ (PL) per minute in the first quarter, while centers demonstrated an increase in high-intensity accelerations and jumps in the fourth quarter. Furthermore, a significant moderate correlation between sRPE and PL was observed across all game quarters, indicating a link between physical exertion and athletes' perceptions of effort. Conclusion: The study offers new insights into the dynamic physical demands faced by basketball players and the importance of using both objective and subjective measures for a comprehensive assessment of athlete performance and wellbeing. The findings underscore the interconnectedness of physical exertion and athlete perception, providing a foundation for future research and practical applications in the field of basketball science.
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The current study investigated the associations between female football players' training loads and their sleep variations. The sample included 21 female elite football players from a Norwegian top-league club with a mean age of 24 years (±2.8). Sleep duration, sleep quality, and training load were monitored every day over 273 consecutive days with a Somnofy sleep monitor based on ultra-wideband (IR-UWB) pulse radar and Doppler technology, and a FIFA-approved STATSports APEX 10 Hz GPS tracking system monitoring players' training loads. A multivariate analysis of variance (MANOVA) was conducted to investigate the relationships between the players' training loads and sleep. It was revealed that very high training loads were associated with reduced time in bed (p = 0.005), total sleep time (p = 0.044)), and rapid eye movement (p < 0.001). The present findings show that the female football players' sleep was disrupted when the training load, based on total distance (TDI), was very high. It appears to be a point where their sleep is somewhat consistent through low, medium, and high training loads, but with disrupted sleep when the training load reaches a very high level. Considering the reduced TIB after a very high training load, there should be suggested strategies to improve their sleep, such as extended TIB, to aid in longer TST and improved recovery.
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PURPOSE: The relationship between external load and creatine-kinase (CK) response at the team/position or individual level using Global Positioning Systems (GPS) has been studied. This study aimed to compare GPS-derived and Football Movement Profile (FMP) -derived CK-prediction models for national-team soccer players. The second aim was to compare the performance of general and individualized CK prediction models. METHODS: Four hundred forty-four national-team soccer players (under 15 [U15] to senior) were monitored during training sessions and matches using GPS. CK was measured every morning from whole blood. The players had 19.3 (18.1) individual GPS-CK pairs, resulting in a total of 8570 data points. Machine learning models were built using (1) GPS-derived or (2) FMP-based parameters or (3) the combination of the 2 to predict the following days' CK value. The performance of general and individual-specific prediction models was compared. The performance of the models was described by R2 and the root-mean-square error (RMSE, in units per liter for CK values). RESULTS: The FMP model (R2 = .60, RMSE = 144.6 U/L) performed similarly to the GPS-based model (R2 = .62, RMSE = 141.2 U/L) and the combination of the 2 (R2 = .62, RMSE = 140.3 U/L). The prediction power of the general model was better on average (R2 = .57 vs R2 = .37) and for 73% of the players than the individualized model. CONCLUSIONS: The results suggest that FMP-based CK-prediction models perform similarly to those based on GPS-derived metrics. General machine learning models' prediction power was higher than those of the individual-specific models. These findings can be used to monitor postmatch recovery strategies and to optimize weekly training periodization.
Subject(s)
Creatine Kinase , Geographic Information Systems , Machine Learning , Soccer , Soccer/physiology , Humans , Creatine Kinase/blood , Adolescent , Movement , Male , Team SportsABSTRACT
Purpose: TRIMP and sRPE are both representative indicators of training load(TL), and the correlation between two has been widely demonstrated across various sports. The aim of this study was to investigate the reliability of sRPE-TRIMP correlation across different intensities/duration of training in cross-country skiing, and whether sRPE can serve as an validity supplement to TRIMP data in cases of lost heart rate data. Method: 10 athletes were used as the experimental objects. The intensity, duration and RPE of 273 different types of training sessions were collected, and statistical methods were used for data analysis. Results: 1. There was a significant correlation between sRPE and TRIMP (r = 0.68, p < 0.05), but the correlation differs among the LIT, MIT and HIT groups (r = 0.70, 0.46, r = 0.31, p < 0.05) 2. sRPE-TRIMP correlation among three different time duration in the LIT group (0-60 min, 60-120 min and 120-180 min), are all highly significant (r = 0.70, 0.67, 0.69, p < 0.05) and the LRsRPE-TRIMP of 3 duration have no significant differences (chow test, p > 0.05). 3. The difference in actual training duration between samples was the main reason for the difference in the application effect of sRPE, because the actual training duration ratio of LIT was 89.7 ± 16.4%; MIT, 98.5 ± 6.2%; and HIT, 94.4 ± 13.5%. Conclusion: 1. The linear relationship between sRPE and TRIMP (LRsRPE-TRIMP) is more significant in LIT compared to that in MIT and HIT. 2. Variations in the duration of LIT sessions do not affect the consistency of the relationship between sRPE and TRIMP. 3. Discrepancies between actual and planned training durations directly impact the significance of the LRsRPE-TRIMP.
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Cardiac rehabilitation (CR) is recommended for all patients with stable angina (SA) as an effective treatment. Hemoglobin (Hgb) levels predict exercise performance and may affect symptom threshold in SA patients. A multidisciplinary CR intervention was individually tailored for a 72-year-old patient with a diagnosis of SA, low Hgb (<10 g/dL), and typical chest pain at light-to-moderate exercise (<5 metabolic equivalent task), who was stratified as at high risk for cardiac events during exercise. Two symptom-limited exercise tests were performed before and after 36 sessions of supervised exercise training producing near-optimal accumulated total volume load and chronic training load. In this case report, we show that an individually tailored CR intervention in a patient with SA and low Hgb is feasible, effective, and safe at reducing the burden of symptoms while increasing peak exercise capacity, health-related quality of life, and physical activity engagement.
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This study aimed to achieve two objectives: firstly, to analyze the relationships between aerobic fitness, as represented by the VIFT, and the heart rate and locomotor responses of youth male soccer players across various teams; and secondly, to compare players with lower and higher VIFT in terms of performance outcomes extracted during small-sided games (SSGs). A total of twenty-six youth male soccer players, aged 16.5 ± 0.32 years, with 3.4 ± 1.1 years of experience, voluntarily participated in the study. These players belonged to two regional-level tier 2 teams (trained/developmental). In the initial week of observation, the 30-15 Intermittent Fitness Test was implemented to measure the final velocity (VIFT) achieved by the players. Subsequently, the 5v5 format of play was conducted twice a week over two consecutive weeks, during which heart rate responses and locomotor demands were measured. The Pearson product-moment correlation test revealed a significant correlation between VIFT and the total distance covered during the 5v5 format (r = 0.471 [95% CI: 0.093; 0.721], p = 0.015). Conversely, small and non-significant correlations were identified between VIFT and mean heart rate (r = 0.280 [95% CI: - 0.126; 0.598]; p = 0.166), VIFT and peak heart rate (r = 0.237 [95% CI: - 0.170; 0.569]; p = 0.243), as well as VIFT and high-speed running (r = 0.254 [95% CI: - 0.153; 0.580]; p = 0.211). Players with higher VIFT demonstrated a significantly greater total distance, with a large effect size (+ 6.64%; p = 0.015; d = 1.033), compared to those with lower VIFT. Our findings suggest that improved performance in VIFT may lead to covering more distance in 5v5 matches. However, the lack of significant associations between VIFT and heart rate levels during SSGs suggests that they are not strongly correlated, possibly because VIFT is more closely linked to locomotor profile. As a practical implication, coaches may consider organizing players during SSGs based on their VIFT if the goal is to standardize locomotor demands.
Subject(s)
Athletic Performance , Heart Rate , Physical Fitness , Running , Soccer , Humans , Soccer/physiology , Heart Rate/physiology , Male , Adolescent , Athletic Performance/physiology , Running/physiology , Physical Fitness/physiology , Exercise Test/methods , Locomotion/physiologyABSTRACT
BACKGROUND: The influence of external workload variables on the development of calf muscle strainsin football players has not been previously explored. HYPOTHESIS: Overloaded players would have an increased risk of calf muscle strain injury. STUDY DESIGN: Prospective observational study. LEVEL OF EVIDENCE: Level 4. METHODS: A total of 41 professional football players from 1 team were monitored for 2 consecutive seasons. Total distance covered (TD), and distances covered at high-intensity running, high sprint running, low (LACC) and high (HACC) acceleration, low (LDEC) and high (HDEC) deceleration, and at high metabolic load distance (HMLD) were monitored with GPS units. Accumulated players' external workload in the week before injury was compared with the weekly mean value of the 6 weeks before injury occurred for each player. RESULTS: Ten players (24.3%) suffered 16 calf muscle strain injuries (3.1 injuries per 1000 hours of match play; 0.5 injuries per 1000 hours of training exposure). Players with a calf muscle injury were older (p = 0.03), with higher body weight (p = 0.01) and height (p = 0.03). Injured players displayed substantially higher total training volume (p < 0.01), TD (p < 0.01), LACC (p < 0.01), LDEC (p < 0.01), HACC (p < 0.01), HDEC (p < 0.01), and HMLD (p = 0.03) in the week before injury, in comparison with the mean values of these variables in the 6 weeks before injury. CONCLUSION: A week with a higher-than-habitual external workload might increase the risk of calf muscle strain injury in professional football players. Calf muscle injuries were preceded by a week with unusually high workloads associated with accelerating and decelerating distances and higher training volumes. CLINICAL RELEVANCE: Monitoring external workload indicators may be helpful in determine players with a higher risk of calf muscle strain injury due to excessive workload during training/competition.
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The aim of this study was to compare the running demands of transition games (TGs) and official matches, analysing their requirements according to the performance of each position. An observational design was used to examine the activity of 20 soccer players during official matches and TGs. GPS technology was used to monitor the total distance covered (DC), distance at speeds between 14-17.9 kmâ¢h-1, 18-21 kmâ¢h-1, and above 21 kmâ¢h-1, peak speed, accelerations and decelerations above 2.5 mâ¢s-2, and Player Load for both activities. All players were assigned to groups: centre-backs (CBs), fullbacks (FBs), defensive midfielders (DMFs), offensive midfielders (OMFs), wide midfielders (WMFs) and strikers (Ss). TGs showed greater total DC, DC 14-17.9 kmâ¢h-1, DC 18-21 kmâ¢h-1, DC >21 kmâ¢h-1, accelerations and decelerations >2.5 mâ¢s-2, and Player Load (p < 0.01). CBs, FBs and Ss showed more DC, DC 14-17.9 kmâ¢h-1, DC 18-21 kmâ¢h-1, DC >21 kmâ¢h-1, accelerations and decelerations >2.5 mâ¢s-2 and Player Load in TGs (p < 0.01). In the midfielder positions, transition game players showed greater DC 18-21 kmâ¢h-1, DC >21 kmâ¢h-1, accelerations and decelerations >2.5 mâ¢s-2 than in matches (p < 0.05). DMFs showed higher total DC (p < 0.05) and WMFs greater DC and DC 14-17.9 kmâ¢h-1 (p < 0.01) in these drills. During transition games CBs showed greater DC 14-17.9 kmâ¢h-1 than FBs, and greater DC than Ss (p < 0.05). FBs performed more decelerations >2.5 mâ¢s-2 than DMFs and OMFs (p < 0.05). TGs produced a homogenized load in soccer players, independent of their position, which exceeded the external load of official matches.
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BACKGROUND: For athletes, overcoming obstacles in challenging situations like pandemic home training is crucial. Strategies and approaches in this context are not well-documented. Our study aims to investigate such a scenario from a performance standpoint, based on a major global crisis: the COVID-19 pandemic and lockdown. METHODS: This cross-sectional study surveyed athletes without disabilities using online questionnaires (35 languages) from May to July 2020. Questions included aspects of alternative routines, training monitoring, recovery, sleep patterns, injury occurrence/prevention based on structured answers, and an open-ended question on lockdown training experiences. RESULTS: Of the 11,762 athletes from 142 countries, 63% were male, including at World-Class, International, National, State and Recreational levels. During lockdown, 25% athletes used innovative or modern ways to maintain or improve fitness e.g., virtual reality and tracking devices (favoring World-Class level, 30%). Many athletes, regardless of gender (43%) watched video competitions to improve/maintain their mental skills and performance [World-Class (47%) and International (51%)]. Contact frequency between athletes and their coaches was mainly at least once a week (36%), more among higher-level (World-Class/International) than lower-level athletes (27 vs. 16%). Higher-level athletes (≥ 54%) monitored training load and were assisted by their coaches (21%). During lockdown, stretching (67%) was considered one of the primary means of recovery, especially for higher-level athletes (> 70%). Compared to pre-lockdown, about two-thirds of athletes reported "normal" or "improved" sleep quality and quantity, suggesting a low sleep quality pre-lockdown. On average, 40% utilized injury prevention exercises (at least) once a week [World-Class (51%) and International (39%)]. Most injury occurrences during lockdown involved the knee (18%), ankle (16%), and back (9%). Four key themes emerged regarding lockdown experiences: remote training adaptation (e.g., shifting training focus), training creativity (e.g., using household items), performance enhancement opportunities (e.g., refocusing neglected aspects), and mental and motivation challenges. CONCLUSIONS: Both male and female athletes, particularly those of higher levels, displayed some adaptalibity during the COVID-19 lockdown, employing innovative approaches and technology for training. Many athletes implemented load monitoring, recovery, and attentive of injury prevention, while optimizing their sleep quality and quantity. Athletes demonstrated their abilities to navigate challenges, and utilized different coping strategies in response to the lockdown's constraints.
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The study aimed to calculate training intensity and load using muscle oxygen saturation (SmO2) during two differentiated physical tasks. 29 university athletes participated in a 40-m Maximal Shuttle Run Test (MST, 10 × 40-m with 30 s recovery between sprints) and a 3000-m time trial run. Distance and time were used to calculate external load (EL). Internal load indicators were calculated based on percentage of maximum heart rate (%HRMAX) and SmO2 variables: muscle oxygen extraction (∇%SmO2) and the cardio-muscle oxygen index (CMOI) was also provided by relating ∇%SmO2 ÷ %HRMAX, and the training load were calculated as the product of speed (m/min × IL) and the efficiency index [Effindex (m/min ÷ IL)]. A student t test was applied based on Bayesian factor analysis. As expected, EL differed in the 40-m MST (331 ± 22.8) vs. 3000-m trials (222 ± 56.8) [BF10 = 6.25e+6; p = <0.001]. Likewise, IL showed higher values in 40-m MST (39.20 ± 15.44) vs. 3000-m (30.51 ± 8.67) in CMOI: [BF10 = 1.70; p = 0.039]. Training load was greater in 40-m MST (85.77 ± 27.40) vs. 3000-m (15.55 ± 6.77) [(m/min × ∇%SmO2): BF10 = 12.5; p = 0.003] and 40-m MST (129.27 ± 49.44) vs. 3000-m (70.63 ± 32.98) [(m/min × CMOI): BF10 = 169.6; p = <0.001]. Also, the Effindex was higher in 40-m MST (10.19 ± 4.17) vs. 3000-m (6.06 ± 2.21) [(m/min × ∇%SmO2): BF10 = 137.03; p = <0.001] and 40-m MST (9.69 ± 4.11) vs. 3000-m (7.55 ± 1.87) [(m/min × CMOI): BF10 = 1.86; p = 0.035]. This study demonstrates calculations of training intensity and load based on SmO2 as an internal load indicator along with speed as an external load indicator during two differentiated exercises.
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The aim was to determine how jump load affects knee complaints in elite men's volleyball. We collected data from four men's premier league volleyball teams through three seasons in a prospective cohort study (65 players, 102 player-seasons). Vert inertial measurement devices captured the jump load (jump frequency and jump height) from 21 088 daily player sessions, and knee complaints were reported in 3568 weekly OSTRC-O questionnaires. Mixed complementary log-log regression models described the probability of (i) experiencing symptoms if players were currently asymptomatic, (ii) worsening symptoms if players had symptoms, and (iii) recovery from knee complaints. Based on our causal assumptions, weekly jump load was modeled as the independent variable, adjusted for age (years), weight (kg), position on volleyball team, and past jump load. No certain evidence of an association was found between weekly jump load and probability of (i) knee complaints (p from 0.10 to 0.32 for three restricted cubic splines of load), (ii) worsening symptoms if the player already had symptoms (p from 0.11 to 0.97), (iii) recovery (p from 0.36 to 0.63). The probability of knee complaints was highest for above-average weekly jump load (~1.2% for an outside hitter with mean age and height) compared with low loads (~1%) and very high loads (â ~ 0%). The association between jump load and knee complaints risk remains unclear. Small differences in risk across observed jump load levels were observed. It would likely require substantially increased sample sizes to detect this association with certainty.
Subject(s)
Volleyball , Humans , Male , Volleyball/injuries , Prospective Studies , Young Adult , Adult , Knee Joint/physiology , Surveys and QuestionnairesABSTRACT
PURPOSE: This study aimed at evaluating the effect of level of competition and drill typology on loads during the preseason period in male volleyball players. METHODS: Internal (percentage of peak heart rate [HR] and summated HR zone) and external (PlayerLoad per minute, total and high accelerations per minute [tACCmin and hACCmin], decelerations per minute [tDECmin and hDECmin], and jumps per minute [tJUMPmin and hJUMPmin]) loads were monitored across a 5-week preseason period in 12 Division 1 (age: 22.5 [3.9] y; stature: 188 [6.2] cm; body mass: 85 [11.6] kg; training experience: 9.4 [4.2] y) and 12 Division 2 (age: 20.7 [2.9] y; stature: 186 [6.2] cm; body mass: 77.8 [9.6] kg; training experience: 5.6 [2.3] y) male volleyball players. Furthermore, differences in load were assessed for each drill typology (warm-up, conditioning, technical, tactical, and integral). RESULTS: No effects (P > .05) of level of competition on the internal (except for summated HR zone, P = .05) and external loads (except for tJUMPmin, P = .002) were found. Differently, drill typologies showed an effect (P < .001) on all the investigated internal- and external-load measures. The main post hoc results revealed higher (P < .05) percentage of peak HR, summated HR zone, PlayerLoad per minute, and tACCmin in warm-up and conditioning drills, while higher (P < .05) hDECmin and hJUMPmin were found in tactical and integral drills. CONCLUSIONS: These results suggest that volleyball coaches use warm-up and conditioning drills when aiming at increasing the internal loads, PlayerLoad per minute, and tACCmin, while tactical and integral drills should be preferred to enhance the number of hDECmin and hJUMPmin.
Subject(s)
Acceleration , Athletic Performance , Competitive Behavior , Heart Rate , Volleyball , Humans , Male , Volleyball/physiology , Young Adult , Heart Rate/physiology , Competitive Behavior/physiology , Athletic Performance/physiology , Physical Conditioning, Human/methods , Warm-Up Exercise/physiology , DecelerationABSTRACT
It has now been established that preoperative physical activity plays an essential role in minimizing postoperative complications. Patients who have undergone physical preparation recover their preoperative abilities more quickly. However, only about a third of those with access to such preparation report an improvement in their physical abilities. The modalities of intervention and follow-up, such as the training load and the generic format of the proposed sessions, seem to hinder patient participation in these programs, thus explaining the mixed results. In this context, it seems necessary to individualize prehabilitation in order to improve the functional capacities of people in this phase or in the phase of accelerated recovery after treatment or surgery.