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Background: The regular assessment of hormonal and mood state parameters in professional soccer are proposed as good indicators during periods of intense training and/or competition to avoid overtraining.
Objective: The aim of this study was to analyze hormonal, psychological, workload and physical fitness parameters in elite soccer players in relation to changes in training and match exposure during a congested period of match play.
Methods: Sixteen elite soccer players from a team playing in the first Tunisian soccer league were evaluated three times (T1, T2, and T3) over 12 weeks. The non-congested period of match play was from T1 to T2, when the players played 6 games over 6 weeks. The congested period was from T2 to T3, when the players played 10 games over 6 weeks. From T1 to T3, players performed the Yo-Yo intermittent recovery test level 1 (YYIR1), the repeated shuttle sprint ability test (RSSA), the countermovement jump test (CMJ), and the squat jump test (SJ). Plasma Cortisol (C), Testosterone (T), and the T/C ratio were analyzed at T1, T2, and T3. Players had their mood dimensions (tension, depression, anger, vigor, fatigue, confusion, and a Total Mood Disturbance) assessed through the Profile of Mood State questionnaire (POMS). Training session rating of perceived exertion (sRPE) was also recorded on a daily basis in order to quantify internal training load and elements of monotony and strain.
Results: Significant performance declines (T1 < T2 < T3) were found for SJ performance (p = 0.04, effect size [ES] ES₁₋₂ = 0.15−0.06, ES₂₋₃ = 0.24) from T1 to T3. YYIR1 performance improved significantly from T1 to T2 and declined significantly from T2 to T3 (p = 0.001, ES₁₋₂ = 0.24, ES₂₋₃ = −2.54). Mean RSSA performance was significantly higher (p = 0.019, ES₁₋₂ = −0.47, ES₂₋₃ = 1.15) in T3 compared with T2 and T1. Best RSSA performance was significantly higher in T3 when compared with T2 and T1 (p = 0.006, ES₂₋₃ = 0.47, ES₁₋₂ = −0.56), but significantly lower in T2 when compared with to T1. T and T/C were significantly lower in T3 when compared with T2 and T1 (T: p = 0.03, ES₃₋₂ = −0.51, ES₃₋₁ = −0.51, T/C: p = 0.017, ES₃₋₂ = −1.1, ES₃₋₁ = −1.07). Significant decreases were found for the vigor scores in T3 when compared to T2 and T1 (p = 0.002, ES₁₋₂ = 0.31, ES₃₋₂ = −1.25). A significant increase was found in fatigue scores in T3 as compared to T1 and T2 (p = 0.002, ES₁₋₂ = 0.43, ES₂₋₃ = 0.81). A significant increase was found from T1 < T2 < T3 intension score (p = 0.002, ES₁₋₂ = 1.1, ES₂₋₃ = 0.2) and anger score (p = 0.03, ES₁₋₂ = 0.47, ES₂₋₃ = 0.33) over the study period. Total mood disturbance increased significantly (p = 0.02, ES₁₋₂ = 0.91, ES₂₋₃ = 1.1) from T1 to T3. Between T1-T2, significant relationships were observed between workload and changes in T (r = 0.66, p = 0.003), and T/C ratio (r = 0.62, p = 0.01). There were significant relationships between performance in RSSAbest and training load parameters (workload: r = 0.52, p = 0.03; monotony: r = 0.62, p = 0.01; strain: r = 0.62, p = 0.009). Between T2-T3, there was a significant relationship between Δ% of total mood disturbance and Δ% of YYIR1 (r = −0.54; p = 0.04), RSSAbest (r = 0.58, p = 0.01), SJ (r = −0,55, p = 0.01), T (r = 0.53; p = 0.03), and T/C (r = 0.5; p = 0.04).
Conclusion: An intensive period of congested match play significantly compromised elite soccer players’ physical and mental fitness. These changes were related to psychological but not hormonal parameters; even though significant alterations were detected for selected measures. Mood monitoring could be a simple and useful tool to determine the degree of preparedness for match play during a congested period in professional soccer.
Background/objective
Dry land-training (e.g., plyometric jump training) can be a useful mean to improve swimming performance. This study examined the effects of an 8-week plyometric jump training (PJT) program on jump and sport-specific performances in prepubertal female swimmers.
Methods
Twenty-two girls were randomly assigned to either a plyometric jump training group (PJTG; n = 12, age: 10.01 ± 0.57 years, maturity-offset = -1.50 ± 0.50, body mass = 36.39 ± 6.32 kg, body height = 146.90 ± 7.62 cm, body mass index = 16.50 ± 1.73 kg/m2) or an active control (CG; n = 10, age: 10.50 ± 0.28 years, maturity-offset = -1.34 ± 0.51, body mass = 38.41 ± 9.42 kg, body height = 143.60 ± 5.05 cm, body mass index = 18.48 ± 3.77 kg/m2). Pre- and post-training, tests were conducted for the assessment of muscle power (e.g., countermovement-jump [CMJ], standing-long-jump [SLJ]). Sport-specific-performances were tested using the timed 25 and 50-m front crawl with a diving-start, timed 25-m front crawl without push-off from the wall (25-m WP), and a timed 25-m kick without push-off from the wall (25-m KWP).
Results
Findings showed a significant main effect of time for the CMJ (d = 0.78), the SLJ (d = 0.91), 25-m front crawl test (d = 2.5), and the 25-m-KWP (d = 1.38) test. Significant group × time interactions were found for CMJ, SLJ, 25-m front crawl, 50-m front crawl, 25-m KWP, and 25-m WP test (d = 0.29–1.63) in favor of PJTG (d = 1.34–3.50). No significant pre-post changes were found for CG (p > 0.05).
Conclusion
In sum, PJT is effective in improving muscle power and sport-specific performances in prepubertal swimmers. Therefore, PJT should be included from an early start into the regular training program of swimmers.
Sprint and jump performances in highly trained young soccer players of different chronological age
(2020)
Objective
The aim of this study was to examine the effects of two different sprint-training regimes on sprint and jump performances according to age in elite young male soccer players over the course of one soccer season.
Methods
Players were randomly assigned to two training groups. Group 1 performed systematic change-of-direction sprints (CODST, U19 [n = 9], U17 [n = 9], U15 [n = 10]) while group 2 conducted systematic linear sprints (LST, U19 [n = 9], U17 [n = 9], U15 [n = 9]). Training volumes were similar between groups (40 sprints per week x 30 weeks = 1200 sprints per season). Pre and post training, all players performed tests for the assessment of linear and slalom sprint speed (5-m and 10-m), countermovement jump, and maximal aerobic speed performance.
Results
For all physical fitness measures, the baseline-adjusted means data (ANCOVA) across the age groups showed no significant differences between LST and CODST at post (0.061 < p < 0.995; 0.0017 < d < 1.01). The analyses of baseline-adjusted means for all physical fitness measures for U15, U17, and U19 (LST vs. CODST) revealed no significant differences between LST and CODST for U15 (0.213 < p < 0.917; 0.001 < d < 0.087), U17 (0.132 < p < 0.976; 0.001 < d < 0.310), and U19 (0.300 < p < 0.999; 0.001 < d < 0.049) at post.
Conclusions
The results from this study showed that both, LST and CODST induced significant changes in the sprint, lower limbs power, and aerobic performances in young elite soccer players. Since no significant differences were observed between LST and CODST, the observed changes are most likely due to training and/or maturation. Therefore, more research is needed to elucidate whether CODST, LST or a combination of both is beneficial for youth soccer athletes’ performance development.
There is ample evidence that youth resistance training (RT) is safe, joyful, and effective for different markers of performance (e.g., muscle strength, power, linear sprint speed) and health (e.g., injury prevention). Accordingly, the first aim of this narrative review is to present and discuss the relevance of muscle strength for youth physical development. The second purpose is to report evidence on the effectiveness of RT on muscular fitness (muscle strength, power, muscle endurance), on movement skill performance and injury prevention in youth. There is evidence that RT is effective in enhancing measures of muscle fitness in children and adolescents, irrespective of sex. Additionally, numerous studies indicate that RT has positive effects on fundamental movement skills (e.g., jumping, running, throwing) in youth regardless of age, maturity, training status, and sex. Further, irrespective of age, sex, and training status, regular exposure to RT (e.g., plyometric training) decreases the risk of sustaining injuries in youth. This implies that RT should be a meaningful element of youths’ exercise programming. This has been acknowledged by global (e.g., World Health Organization) and national (e.g., National Strength and Conditioning Association) health- and performance-related organizations which is why they recommended to perform RT as an integral part of weekly exercise programs to promote muscular strength, fundamental movement skills, and to resist injuries in youth.
The aim of this study was to establish maturation-, age-, and sex-specific anthropometric and physical fitness percentile reference values of young elite athletes from various sports. Anthropometric (i.e., standing and sitting body height, body mass, body mass index) and physical fitness (i.e., countermovement jump, drop jump, change-of-direction speed [i.e., T-test], trunk muscle endurance [i.e., ventral Bourban test], dynamic lower limbs balance [i.e., Y-balance test], hand grip strength) of 703 male and female elite young athletes aged 8–18 years were collected to aggregate reference values according to maturation, age, and sex. Findings indicate that body height and mass were significantly higher (p<0.001; 0.95≤d≤1.74) in more compared to less mature young athletes as well as with increasing chronological age (p<0.05; 0.66≤d≤3.13). Furthermore, male young athletes were significantly taller and heavier compared to their female counterparts (p<0.001; 0.34≤d≤0.50). In terms of physical fitness, post-pubertal athletes showed better countermovement jump, drop jump, change-of-direction, and handgrip strength performances (p<0.001; 1.57≤d≤8.72) compared to pubertal athletes. Further, countermovement jump, drop jump, change-of-direction, and handgrip strength performances increased with increasing chronological age (p<0.05; 0.29≤d≤4.13). In addition, male athletes outperformed their female counterpart in the countermovement jump, drop jump, change-of-direction, and handgrip strength (p<0.05; 0.17≤d≤0.76). Significant age by sex interactions indicate that sex-specific differences were even more pronounced with increasing age. Conclusively, body height, body mass, and physical fitness increased with increasing maturational status and chronological age. Sex-specific differences appear to be larger as youth grow older. Practitioners can use the percentile values as approximate benchmarks for talent identification and development.
Several studies have investigated the effects of music on both submaximal and maximal exercise performance at a constant work-rate. However, there is a lack of research that has examined the effects of music on the pacing strategy during self-paced exercise. The aim of this study was to examine the effects of preferred music on performance and pacing during a 6 min run test (6-MSPRT) in young male adults. Twenty healthy male participants volunteered for this study. They performed two randomly assigned trials (with or without music) of a 6-MSPRT three days apart. Mean running speed, the adopted pacing strategy, total distance covered (TDC), peak and mean heart rate (HRpeak, HRmean), blood lactate (3 min after the test), and rate of perceived exertion (RPE) were measured. Listening to preferred music during the 6-MSPRT resulted in significant TDC improvement (?10%; p = 0.016; effect size (ES) = 0.80). A significantly faster mean running speed was observed when listening to music compared with no music. The improvement of TDC in the present study is explained by a significant overall increase in speed (main effect for conditions) during the music trial. Music failed to modify pacing patterns as suggested by the similar reversed “J-shaped” profile during the two conditions. Blood-lactate concentrations were significantly reduced by 9% (p = 0.006, ES = 1.09) after the 6-MSPRT with music compared to those in the control condition. No statistically significant differences were found between the test conditions for HRpeak, HRmean, and RPE. Therefore, listening to preferred music can have positive effects on exercise performance during the 6-MSPRT, such as greater TDC, faster running speeds, and reduced blood lactate levels but has no effect on the pacing strategy.
How We Found Our IMU
(2020)
Inertial measurement units (IMUs) are commonly used for localization or movement tracking in pervasive healthcare-related studies, and gait analysis is one of the most often studied topics using IMUs. The increasing variety of commercially available IMU devices offers convenience by combining the sensor modalities and simplifies the data collection procedures. However, selecting the most suitable IMU device for a certain use case is increasingly challenging. In this study, guidelines for IMU selection are proposed. In particular, seven IMUs were compared in terms of their specifications, data collection procedures, and raw data quality. Data collected from the IMUs were then analyzed by a gait analysis algorithm. The difference in accuracy of the calculated gait parameters between the IMUs could be used to retrace the issues in raw data, such as acceleration range or sensor calibration. Based on our algorithm, we were able to identify the best-suited IMUs for our needs. This study provides an overview of how to select the IMUs based on the area of study with concrete examples, and gives insights into the features of seven commercial IMUs using real data.
Gait analysis is an important tool for the early detection of neurological diseases and for the assessment of risk of falling in elderly people. The availability of low-cost camera hardware on the market today and recent advances in Machine Learning enable a wide range of clinical and health-related applications, such as patient monitoring or exercise recognition at home. In this study, we evaluated the motion tracking performance of the latest generation of the Microsoft Kinect camera, Azure Kinect, compared to its predecessor Kinect v2 in terms of treadmill walking using a gold standard Vicon multi-camera motion capturing system and the 39 marker Plug-in Gait model. Five young and healthy subjects walked on a treadmill at three different velocities while data were recorded simultaneously with all three camera systems. An easy-to-administer camera calibration method developed here was used to spatially align the 3D skeleton data from both Kinect cameras and the Vicon system. With this calibration, the spatial agreement of joint positions between the two Kinect cameras and the reference system was evaluated. In addition, we compared the accuracy of certain spatio-temporal gait parameters, i.e., step length, step time, step width, and stride time calculated from the Kinect data, with the gold standard system. Our results showed that the improved hardware and the motion tracking algorithm of the Azure Kinect camera led to a significantly higher accuracy of the spatial gait parameters than the predecessor Kinect v2, while no significant differences were found between the temporal parameters. Furthermore, we explain in detail how this experimental setup could be used to continuously monitor the progress during gait rehabilitation in older people.
Effects of the barbell load on the acceleration phase during the snatch in Olympic weightlifting
(2020)
The load-depended loss of vertical barbell velocity at the end of the acceleration phase limits the maximum weight that can be lifted. Thus, the purpose of this study was to analyze how increased barbell loads affect the vertical barbell velocity in the sub-phases of the acceleration phase during the snatch. It was hypothesized that the load-dependent velocity loss at the end of the acceleration phase is primarily associated with a velocity loss during the 1st pull. For this purpose, 14 male elite weightlifters lifted seven load-stages from 70–100% of their personal best in the snatch. The load–velocity relationship was calculated using linear regression analysis to determine the velocity loss at 1st pull, transition, and 2nd pull. A group mean data contrast analysis revealed the highest load-dependent velocity loss for the 1st pull (t = 1.85, p = 0.044, g = 0.49 [−0.05, 1.04]) which confirmed our study hypothesis. In contrast to the group mean data, the individual athlete showed a unique response to increased loads during the acceleration sub-phases of the snatch. With the proposed method, individualized training recommendations on exercise selection and loading schemes can be derived to specifically improve the sub-phases of the snatch acceleration phase. Furthermore, the results highlight the importance of single-subject assessment when working with elite athletes in Olympic weightlifting.