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With innovative portable force plate systems being widely implemented for lower-body neuromuscular performance assessment in an applied sports setting and the existing gap in the scientific literature regarding player performance during in-game competitive scenarios, the purpose of the present study was to compare changes in countermovement vertical jump (CVJ) performance pre-post a simulated 3×3 basketball tournament. Seven current or former members of a 3×3 national basketball team volunteered to participate in the present investigation. Upon completing standardized warm-up procedures, athletes stepped on a uni-axial force plate system sampling at 1,000 Hz and performed three maximal-effort CVJs with no arm swing. Then, the athletes proceeded to play a simulated 3×3 basketball tournament composed of two consecutive games, separated by a 15-min rest interval. Immediately following the completion of the second game, the identical CVJ testing procedures were repeated. Paired sample t-tests were used to examine prepost-tournament differences in nineteen CVJ performance metrics (p < 0.05). The results reveal that force-time metrics during both eccentric and concentric phases of the CVJ remain relatively unchanged pre-post simulated 3×3 basketball tournament. However, multiple force-time metrics within the eccentric phase of the CVJ changed by 12.1%-19.1% (e.g., eccentric peak power and peak velocity, eccentric duration), suggesting that the eccentric phase of CVJ might be responsive to performance stimulus to a greater extent than the concentric phase. Overall, these findings further support the importance of comprehensive CVJ analysis when intending to measure changes in neuromuscular performance. [ABSTRACT FROM AUTHOR]

With innovative portable force plate systems being widely implemented for lower-body neuromuscular performance assessment in an applied sports setting and the existing gap in the scientific literature regarding player performance during in-game competitive scenarios, the purpose of the present study was to compare changes in countermovement vertical jump (CVJ) performance pre-post a simulated 3×3 basketball tournament. Seven current or former members of a 3×3 national basketball team volunteered to participate in the present investigation. Upon completing standardized warm-up procedures, athletes stepped on a uni-axial force plate system sampling at 1,000 Hz and performed three maximal-effort CVJs with no arm swing. Then, the athletes proceeded to play a simulated 3×3 basketball tournament composed of two consecutive games, separated by a 15-min rest interval. Immediately following the completion of the second game, the identical CVJ testing procedures were repeated. Paired sample t-tests were used to examine pre-post-tournament differences in nineteen CVJ performance metrics (p < 0.05). The results reveal that force-time metrics during both eccentric and concentric phases of the CVJ remain relatively unchanged pre-post simulated 3×3 basketball tournament. However, multiple force-time metrics within the eccentric phase of the CVJ changed by 12.1%–19.1% (e.g., eccentric peak power and peak velocity, eccentric duration), suggesting that the eccentric phase of CVJ might be responsive to performance stimulus to a greater extent than the concentric phase. Overall, these findings further support the importance of comprehensive CVJ analysis when intending to measure changes in neuromuscular performance.

Purpose: The purposes of this study were to quantify the external load for female and male varsity ice hockey players during regular season games using a local positioning system (LPS), compare LPS-derived external load between sexes and positions, and compare skating distances in absolute and relative speed zones. Methods: Data were collected for 21 female (7 defense, 14 forwards; 20.0 ± 1.4 yrs., 69.1 ± 6.7 kg, 167.1 ± 5.4 cm) and 25 male (8 defense, 17 forwards; 21.9 ± 1.1 yrs., 85.9 ± 5.4 kg, 181.1 ± 5.2 cm) varsity ice hockey players. Measures included skating distance (total, and in absolute and relative speed zones), peak skating speed, peak acceleration and deceleration, accumulative acceleration load, and number of accelerations, decelerations, turns, skating transitions, direction changes, and impacts. Results: Female and male players had a high external load during games, with average peak skating speeds >28 km/h and average skating distances >4.4 km. Most LPS-derived measures showed greater external load in males than females (p < 0.05). Forwards skated further at higher speeds compared to defense in both sexes (p < 0.001). Skating distances were significantly different when comparing absolute and relative speed zones (p < 0.001), with absolute speed zones potentially overestimating skating at very slow, very fast, and sprint speeds and underestimating skating at slow and moderate speeds. Conclusion: This was the first study to measure external load in female ice hockey players with a LPS. Both female and male varsity players had high external loads during games, with forwards having greater external load at higher intensities and defense having greater external load at lower intensities. Sex and positional differences outline the importance of individualized athlete monitoring. [ABSTRACT FROM AUTHOR]

PurposeThe purposes of this study were to quantify the external load for female and male varsity ice hockey players during regular season games using a local positioning system (LPS), compare LPS-derived external load between sexes and positions, and compare skating distances in absolute and relative speed zones.MethodsData were collected for 21 female (7 defense, 14 forwards; 20.0 ± 1.4 yrs., 69.1 ± 6.7 kg, 167.1 ± 5.4 cm) and 25 male (8 defense, 17 forwards; 21.9 ± 1.1 yrs., 85.9 ± 5.4 kg, 181.1 ± 5.2 cm) varsity ice hockey players. Measures included skating distance (total, and in absolute and relative speed zones), peak skating speed, peak acceleration and deceleration, accumulative acceleration load, and number of accelerations, decelerations, turns, skating transitions, direction changes, and impacts.ResultsFemale and male players had a high external load during games, with average peak skating speeds >28 km/h and average skating distances >4.4 km. Most LPS-derived measures showed greater external load in males than females (p

PurposeThe aim of this study was to compare the energy contributions and workloads in men and women during badminton matches versus frequently used multi-ball smash practices.MethodsFourteen badminton players performed one badminton singles game and one session of smashing practice on separate days. The energy contributions were examined in terms of each individual’s three energy systems and substrate oxidation, while workloads included heart rate (HR), Player Load (PL), accelerations, decelerations, changes of direction, and jumps.Results(1) During games, male players exhibited higher adenosine triphosphate–phosphocreatine system contribution (EPCr, kJ) (p = 0.008) and average rate of carbohydrate oxidation (RCHO, g/min) (p = 0.044) than female players, while female players showed greater absolute PL (p = 0.029) and more accelerations (p = 0.005) than male players. Furthermore, players who lost performed higher relative PL (p = 0.017) than those who won. (2) Higher energy system contributions, including EPCr (kJ) (p = 0.028), EHLa (kJ) (p = 0.024), EAer (kJ) (p = 0.012), ETot (kJ) (p = 0.007), and RCHO (g/min) (p = 0.0002), were seen in male players during repetitive spike practices. Male players also made greater number of jumps (p = 0.0002). (3) Players exhibited higher aerobic energy contribution (p < 0.001), mean HR (p = 0.002), and HRmax (p = 0.029) during games, while exhibiting greater anaerobic energy contribution (p < 0.001) and relative PL (p = 0.001) during repetitive practices.ConclusionThe similarities between male and female badminton players in proportional use of the three energy systems during games and repetitive spike training indicate similar relative energy demands for both genders. However, considering the need for higher aerobic capacity in competition, it might be advisable to design appropriate work:rest ratios for repetitive practices in daily training.

The aim of this study was to investigate the convergent validity of session rating of perceived exertion (s-RPE) with objective measures of internal training load (TL) in professional classical ballet dancers. Heart rate and s-RPE data were collected in 22 professional classical ballet dancers across a total of 218 ballet class or rehearsal sessions. Eleven participants completed at least 9 sessions, and were therefore included in analyses of individual relationships between s-RPE and objective measures. To calculate s-RPE, the session duration was multiplied by the RPE, measured using the modified Borg CR-10 scale. The Edwards summated heart rate zones (Edwards TRIMP) and Banister training impulse (Banister TRIMP) methods were used as criterion measures of internal TL. Pearson product-moment correlation coefficients were used to determine intra-individual relationships between s-RPE and objective measures. Repeated measures correlations were used to identify intra-individual relationships common across the cohort. Positive linear relationships were seen between s-RPE and objective measures across all session types [Edwards TRIMP: rrm (195) = 0.81, p < 0.001; Banister TRIMP: rrm (195) = 0.79, p < 0.001], in ballet class [Edwards TRIMP: rrm (58) = 0.64, p < 0.001; Banister TRIMP: rrm (58) = 0.59, p < 0.001], and in rehearsals [Edwards TRIMP: rrm (119) = 0.82, p < 0.001; Banister TRIMP: rrm (119) = 0.80, p < 0.001], as well as across both males [Edwards TRIMP: rrm (136) = 0.82, p < 0.001; Banister TRIMP: rrm (136) = 0.80, p < 0.001], and females [Edwards TRIMP: rrm (57) = 0.80, p < 0.001; Banister TRIMP: rrm (57) = 0.78, p < 0.001]. Intra-individual correlation coefficients ranged from 0.46–0.96 [Edwards TRIMP: mean r = 0.81 ± 0.11, p = 0.051 – < 0.001; Banister TRIMP: mean r = 0.78 ± 0.14, p = 0.13– < 0.001]. These results demonstrate that s-RPE is a valid and practical method for measuring internal TL in professional classical ballet dancers.

The aim of this study was to investigate the convergent validity of session rating of perceived exertion (s-RPE) with objective measures of internal training load (TL) in professional classical ballet dancers. Heart rate and s-RPE data were collected in 22 professional classical ballet dancers across a total of 218 ballet class or rehearsal sessions. Eleven participants completed at least 9 sessions, and were therefore included in analyses of individual relationships between s-RPE and objective measures. To calculate s-RPE, the session duration was multiplied by the RPE, measured using the modified Borg CR-10 scale. The Edwards summated heart rate zones (Edwards TRIMP) and Banister training impulse (Banister TRIMP) methods were used as criterion measures of internal TL. Pearson product-moment correlation coefficients were used to determine intra-individual relationships between s-RPE and objective measures. Repeated measures correlations were used to identify intra-individual relationships common across the cohort. Positive linear relationships were seen between s-RPE and objective measures across all session types [Edwards TRIMP: r rm (195) = 0.81, p < 0.001; Banister TRIMP: r rm (195) = 0.79, p < 0.001], in ballet class [Edwards TRIMP: r rm (58) = 0.64, p < 0.001; Banister TRIMP: r rm (58) = 0.59, p < 0.001], and in rehearsals [Edwards TRIMP: r rm (119) = 0.82, p < 0.001; Banister TRIMP: r rm (119) = 0.80, p < 0.001], as well as across both males [Edwards TRIMP: r rm (136) = 0.82, p < 0.001; Banister TRIMP: r rm (136) = 0.80, p < 0.001], and females [Edwards TRIMP: r rm (57) = 0.80, p < 0.001; Banister TRIMP: r rm (57) = 0.78, p < 0.001]. Intra-individual correlation coefficients ranged from 0.46–0.96 [Edwards TRIMP: mean r = 0.81 ± 0.11, p = 0.051 – < 0.001; Banister TRIMP: mean r = 0.78 ± 0.14, p = 0.13– < 0.001]. These results demonstrate that s-RPE is a valid and practical method for measuring internal TL in professional classical ballet dancers. [ABSTRACT FROM AUTHOR]

With increased professionalism in sport there has been a greater interest in the scientific approach to training and recovery of athletes. Applying appropriate training loads along with adequate recovery, is essential in gaining maximal adaptation in athletes, while minimizing harm such as overreaching, overtraining, injury and illness. Although appropriate physical stress is essential, stress for many athletes may come from areas other than training. Stress from may arise from social or environmental pressure, and for many athletes who combine elite athletic training with university study, academic workloads create significant stress which adds to the constant pressure to perform athletically. This research aimed to determine if subjective stressors were associated with counterproductive training adaptations in university athletes. Moreover, it aimed to elucidate if, and when, such stressors are most harmful (i.e., certain times of the academic year or sports training season). We monitored subjective (mood state, energy levels, academic stress, sleep quality/quantity, muscle soreness, training load) and objective (injury and illness) markers in 182 young (18–22 years) elite athletes over a 4-year period using a commercially available software package. Athletes combined full-time university study with elite sport and training obligations. Results suggest athletes were relatively un-stressed with high levels of energy at the beginning of each university semester, however, energy levels deteriorated along with sleep parameters toward the examination periods of the year. A logistical regression indicated decreased levels of perceived mood (0.89, 0.85–0.94, Odds Ratio and 95% confidence limits), sleep duration (0.94, 0.91–0.97) and increased academic stress (0.91, 0.88–0.94) and energy levels (1.07, 1.01–1.14) were able to predict injury in these athletes. Examination periods coincided with the highest stress levels and increased likelihood of illness. Additionally, a sudden and high increase in training workload during the preseason was associated with an elevated incidence of injury and illness (r = 0.63). In conclusion, young elite athletes undertaking full-time university study alongside their training and competition loads were vulnerable to increased levels of stress at certain periods of the year (pre-season and examination time). Monitoring and understanding these stressors may assist coaches and support staff in managing overall stress in these athletes.

Aim: Relationships between athlete monitoring-derived variables and injury risk have been investigated predominantly in isolation. The aim of this study was to evaluate the individual and combined effects of multiple factors on the risk of soft-tissue non-contact injuries in elite team sport athletes.Methods: Fifty-five elite Australian footballers were prospectively monitored over two consecutive seasons. Internal and external training load was quantified using the session rating of perceived exertion and GPS/accelerometry, respectively. Cumulative load and acute-to-chronic workload ratios were derived using rolling averages and exponentially weighted moving averages. History of injuries in the current and previous seasons was recorded along with professional experience, weekly musculoskeletal screening, and subjective wellness scores for individual athletes. Individual and combined effects of these variables on injury risk were evaluated with generalized linear mixed models.Results: High cumulative loads and acute-to-chronic workload ratios were associated with increased risk of injuries. The effects for measures derived using exponentially weighted moving averages were greater than those for rolling averages. History of a recent injury, long-term experience at professional level, and substantial reductions in a selection of musculoskeletal screening and subjective wellness scores were associated with increased risk. The effects of high cumulative loads were underestimated by ~20% before adjusting for previous injuries, whereas the effects of high acute-to-chronic workload ratios were overestimated by 10–15%. Injury-prone players, identified via player identity in the mixed model, were at > 5 times higher risk of injuries compared to robust players (hazard ratio 5.4, 90% confidence limits 3.6–12) despite adjusting for training load and previous injuries. Combinations of multiple risk factors were associated with extremely large increases in risk; for example, a hazard ratio of 22 (9.7–52) was observed for the combination of high acute load, recent history of a leg injury, and a substantial reduction in the adductor squeeze test score.Conclusion: On the basis of our findings with an elite team of Australian footballers, the information from athlete monitoring practices in team sports should be interpreted collectively and used as a part of the injury prevention decision-making process along with consideration of individual differences in risk.

Aim: The sit and reach test (S&R), dorsiflexion lunge test (DLT), and adductor squeeze test (AST) are commonly used in weekly musculoskeletal screening for athlete monitoring and injury prevention purposes. The aim of this study was to determine the normal week to week variability of the test scores, individual differences in variability, and the effects of training load on the scores.Methods: Forty-four elite Australian rules footballers from one club completed the weekly screening tests on day 2 or 3 post-main training (pre-season) or post-match (in-season) over a 10 month season. Ratings of perceived exertion and session duration for all training sessions were used to derive various measures of training load via both simple summations and exponentially weighted moving averages. Data were analyzed via linear and quadratic mixed modeling and interpreted using magnitude-based inference.Results: Substantial small to moderate variability was found for the tests at both season phases; for example over the in-season, the normal variability ±90% confidence limits were as follows: S&R ±1.01 cm, ±0.12; DLT ±0.48 cm, ±0.06; AST ±7.4%, ±0.6%. Small individual differences in variability existed for the S&R and AST (factor standard deviations between 1.31 and 1.66). All measures of training load had trivial effects on the screening scores.Conclusion: A change in a test score larger than the normal variability is required to be considered a true change. Athlete monitoring and flagging systems need to account for the individual differences in variability. The tests are not sensitive to internal training load when conducted 2 or 3 days post-training or post-match, and the scores should be interpreted cautiously when used as measures of recovery.

With increased professionalism in sport there has been a greater interest in the scientific approach to training and recovery of athletes. Applying appropriate training loads along with adequate recovery, is essential in gaining maximal adaptation in athletes, while minimizing harm such as overreaching, overtraining, injury and illness. Although appropriate physical stress is essential, stress for many athletes may come from areas other than training. Stress from may arise from social or environmental pressure, and for many athletes who combine elite athletic training with university study, academic workloads create significant stress which adds to the constant pressure to perform athletically. This research aimed to determine if subjective stressors were associated with counterproductive training adaptations in university athletes. Moreover, it aimed to elucidate if, and when, such stressors are most harmful (i.e., certain times of the academic year or sports training season). We monitored subjective (mood state, energy levels, academic stress, sleep quality/quantity, muscle soreness, training load) and objective (injury and illness) markers in 182 young (18–22 years) elite athletes over a 4-year period using a commercially available software package. Athletes combined full-time university study with elite sport and training obligations. Results suggest athletes were relatively un-stressed with high levels of energy at the beginning of each university semester, however, energy levels deteriorated along with sleep parameters toward the examination periods of the year. A logistical regression indicated decreased levels of perceived mood (0.89, 0.85–0.94, Odds Ratio and 95% confidence limits), sleep duration (0.94, 0.91–0.97) and increased academic stress (0.91, 0.88–0.94) and energy levels (1.07, 1.01–1.14) were able to predict injury in these athletes. Examination periods coincided with the highest stress levels and increased likelihood of illness. Additionally, a sudden and high increase in training workload during the preseason was associated with an elevated incidence of injury and illness (r = 0.63). In conclusion, young elite athletes undertaking full-time university study alongside their training and competition loads were vulnerable to increased levels of stress at certain periods of the year (pre-season and examination time). Monitoring and understanding these stressors may assist coaches and support staff in managing overall stress in these athletes. [ABSTRACT FROM AUTHOR]

The article discusses the potential use of sleep as indicator of overreaching or overtraining in athletes. Topics discussed include the causes of overreaching and the role of sleep in physical and mental recovery from exercise, sleep disturbances as symptoms of overreaching or overtraining, and the studies suggesting reduced sleep as a result or the cause of overreaching or overtraining. It also suggests the significance of measures of sleep such as polysomnography as predictor of overtraining.

Aim: The sit and reach test (S&R), dorsiflexion lunge test (DLT), and adductor squeeze test (AST) are commonly used in weekly musculoskeletal screening for athlete monitoring and injury prevention purposes. The aim of this study was to determine the normal week to week variability of the test scores, individual differences in variability, and the effects of training load on the scores. Methods: Forty-four elite Australian rules footballers from one club completed the weekly screening tests on day 2 or 3 post-main training (pre-season) or post-match (in-season) over a 10 month season. Ratings of perceived exertion and session duration for all training sessions were used to derive various measures of training load via both simple summations and exponentially weighted moving averages. Data were analyzed via linear and quadratic mixed modeling and interpreted using magnitude-based inference. Results: Substantial small to moderate variability was found for the tests at both season phases; for example over the in-season, the normal variability ±90% confidence limits were as follows: S&R ±1.01 cm, ±0.12; DLT ±0.48 cm, ±0.06; AST ±7.4%, ±0.6%. Small individual differences in variability existed for the S&R and AST (factor standard deviations between 1.31 and 1.66). All measures of training load had trivial effects on the screening scores. Conclusion: A change in a test score larger than the normal variability is required to be considered a true change. Athlete monitoring and flagging systems need to account for the individual differences in variability. The tests are not sensitive to internal training load when conducted 2 or 3 days post-training or post-match, and the scores should be interpreted cautiously when used as measures of recovery. [ABSTRACT FROM AUTHOR]

Purpose: The aim of this study was to compare the energy contributions and workloads in men and women during badminton matches versus frequently used multi-ball smash practices., Methods: Fourteen badminton players performed one badminton singles game and one session of smashing practice on separate days. The energy contributions were examined in terms of each individual's three energy systems and substrate oxidation, while workloads included heart rate (HR), Player Load (PL), accelerations, decelerations, changes of direction, and jumps., Results: (1) During games, male players exhibited higher adenosine triphosphate-phosphocreatine system contribution (E PCr , kJ) ( p = 0.008) and average rate of carbohydrate oxidation (R CHO , g/min) ( p = 0.044) than female players, while female players showed greater absolute PL ( p = 0.029) and more accelerations ( p = 0.005) than male players. Furthermore, players who lost performed higher relative PL ( p = 0.017) than those who won. (2) Higher energy system contributions, including E PCr (kJ) ( p = 0.028), E HLa (kJ) ( p = 0.024), E Aer (kJ) ( p = 0.012), E Tot (kJ) ( p = 0.007), and R CHO (g/min) ( p = 0.0002), were seen in male players during repetitive spike practices. Male players also made greater number of jumps ( p = 0.0002). (3) Players exhibited higher aerobic energy contribution ( p < 0.001), mean HR ( p = 0.002), and HRmax ( p = 0.029) during games, while exhibiting greater anaerobic energy contribution ( p < 0.001) and relative PL ( p = 0.001) during repetitive practices., Conclusion: The similarities between male and female badminton players in proportional use of the three energy systems during games and repetitive spike training indicate similar relative energy demands for both genders. However, considering the need for higher aerobic capacity in competition, it might be advisable to design appropriate work:rest ratios for repetitive practices in daily training., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2021 Fu, Liu, Chen, Li, Li, Wang, Shu and Shang.)

Aim: Relationships between athlete monitoring-derived variables and injury risk have been investigated predominantly in isolation. The aim of this study was to evaluate the individual and combined effects of multiple factors on the risk of soft-tissue non-contact injuries in elite team sport athletes. Methods: Fifty-five elite Australian footballers were prospectively monitored over two consecutive seasons. Internal and external training load was quantified using the session rating of perceived exertion and GPS/accelerometry, respectively. Cumulative load and acute-to-chronic workload ratios were derived using rolling averages and exponentially weighted moving averages. History of injuries in the current and previous seasons was recorded along with professional experience, weekly musculoskeletal screening, and subjective wellness scores for individual athletes. Individual and combined effects of these variables on injury risk were evaluated with generalized linear mixed models. Results: High cumulative loads and acute-to-chronic workload ratios were associated with increased risk of injuries. The effects for measures derived using exponentially weighted moving averages were greater than those for rolling averages. History of a recent injury, long-term experience at professional level, and substantial reductions in a selection of musculoskeletal screening and subjective wellness scores were associated with increased risk. The effects of high cumulative loads were underestimated by ~20% before adjusting for previous injuries, whereas the effects of high acute-to-chronic workload ratios were overestimated by 10-15%. Injury-prone players, identified via player identity in the mixed model, were at > 5 times higher risk of injuries compared to robust players (hazard ratio 5.4, 90% confidence limits 3.6-12) despite adjusting for training load and previous injuries. Combinations of multiple risk factors were associated with extremely large increases in risk; for example, a hazard ratio of 22 (9.7-52) was observed for the combination of high acute load, recent history of a leg injury, and a substantial reduction in the adductor squeeze test score. Conclusion: On the basis of our findings with an elite team of Australian footballers, the information from athlete monitoring practices in team sports should be interpreted collectively and used as a part of the injury prevention decision-making process along with consideration of individual differences in risk.