scholarly journals Training Load and Recovery During a Pre-Olympic Season in Professional Rhythmic Gymnasts

2020 ◽  
Vol 55 (9) ◽  
pp. 977-983
Author(s):  
Paula Barreiros Debien ◽  
Bernardo Miloski ◽  
Francisco Zacaron Werneck ◽  
Thiago Ferreira Timoteo ◽  
Camila Ferezin ◽  
...  
Keyword(s):  
Perceived Exertion ◽  
Outcome Measure ◽  
Training Load ◽  
Rating Of Perceived Exertion ◽  
Total Quality ◽  
Rhythmic Gymnastics ◽  
National Training ◽  
High Level ◽  
National Training Center ◽  
Rhythmic Gymnasts

Context Rhythmic gymnastics requires a high level of complexity and perfection of technical gestures, associated with well-developed physical and artistic capacities. The training-load and recovery profiles of rhythmic gymnasts across a season are unknown. Objective To analyze the training load and recovery of professional rhythmic gymnasts during 1 season. Design Cohort study. Setting Brazilian National Training Center of Rhythmic Gymnastics and competition facilities. Patients or Other Participants Eight gymnasts from the Brazilian national senior rhythmic gymnastics group. Main Outcome Measure(s) Session rating of perceived exertion (session-RPE) and total quality recovery (TQR) scores were collected daily for 43 weeks. We obtained the session-RPE after each session and TQR score before the first session of the day. Performances during 5 competitions were also recorded. The season was divided into 8 periods. Total weekly internal training load (wITL), training intensity, frequency, duration, recovery, and acute : chronic workload ratio were calculated for analysis. Results The season mean wITL was 10 381 ± 4894 arbitrary units, mean session-RPE score was 5.0 ± 1.6, and mean TQR score was 12.8 ± 1.3. The gymnasts trained an average of 8.7 ± 2.9 sessions per week, with a mean duration of 219 ± 36 minutes. Each competitive period showed increased wITL compared with the previous period. Training-load variables (wITL and session-RPE) and recovery were inversely correlated. Gymnasts were poorly recovered (TQR < 13) during 50.9% of the season (n = 167 times), especially during competitive weeks. Spikes in load (acute : chronic workload ratio ≥ 1.5) occurred across 18.1% of the season (n = 55 times). Conclusions The training-load variables and recovery changed throughout a professional rhythmic gymnastics group season, mainly during competitive periods. The correct distribution of training load is critical to ensure that gymnasts are entering competitions in a recovered state.

scholarly journals Training Loads, Wellness And Performance Before and During Tapering for a Water-Polo Tournament

2019 ◽  
Vol 66 (1) ◽  
pp. 131-141
Author(s):  
Petros G. Botonis ◽  
Argyris G. Toubekis ◽  
Theodoros I. Platanou
Keyword(s):  
Muscle Soreness ◽  
Perceived Exertion ◽  
Swimming Performance ◽  
Training Load ◽  
Rating Of Perceived Exertion ◽  
Training Period ◽  
Training Strategy ◽  
Water Polo ◽  
And Performance ◽  
High Level

AbstractWe investigated the effectiveness of a short-duration training period including an overloaded (weeks 1 and 2) and a reduced training load period (weeks 3 and 4) on wellness, swimming performance and a perceived internal training load in eight high-level water-polo players preparing for play-offs. The internal training load was estimated daily using the rating of perceived exertion (RPE) and session duration (session-RPE). Perceived ratings of wellness (fatigue, muscle soreness, sleep quality, stress level and mood) were assessed daily. Swimming performance was evaluated through 400-m and 20-m tests performed before (baseline) and after the end of weeks 2 and 4. In weeks 3 and 4, the internal training load was reduced by 19.0 ± 3.8 and 36.0 ± 4.7%, respectively, compared to week 1 (p = 0.00). Wellness was improved in week 4 (20.4 ± 2.8 AU) compared to week 1 and week 2 by 16.0 ± 2.2 and 17.3 ± 2.9 AU, respectively (p =0.001). At the end of week 4, swimming performance at 400-m and 20-m tests (299.0 ± 10.2 and 10.2 ± 0.3 s) was improved compared to baseline values (301.4 ± 10.9 and 10.4 ± 0.4 s, p < 0.05) and the overloading training period (week 2; 302.9 ± 9.0 and 10.4 ± 0.4 s, p < 0.05). High correlations were observed between the percentage reduction of the internal training load from week 4 to week 1 (-25.3 ± 5.5%) and the respective changes in 20-m time (-2.1 ± 2.2%, r = 0.88, p < 0.01), fatigue perception (39.6 ± 27.1%), muscle soreness (32.5 ± 26.6%), stress levels (25.6 ± 15.1%) and the overall wellness scores (28.6 ± 21.9%, r = 0.74-0.79, p < 0.05). The reduction of the internal training load improved the overall perceived wellness and swimming performance of players. The aforementioned periodization approach may be an effective training strategy in the lead-up to play-off tournaments.

Training-Load Management in Rhythmic Gymnastics: Practices and Perceptions of Coaches, Medical Staff, and Gymnasts

2021 ◽  
pp. 1-11
Author(s):  
Paula B. Debien ◽  
Thiago F. Timoteo ◽  
Tim J. Gabbett ◽  
Maurício G. Bara Filho
Keyword(s):  
Medical Staff ◽  
Perceived Exertion ◽  
Daily Basis ◽  
Training Load ◽  
Rating Of Perceived Exertion ◽  
Load Management ◽  
Specific Training ◽  
Rhythmic Gymnastics ◽  
Effective Training ◽  
And Performance

Purpose: This study described and analyzed practices and perceptions of rhythmic gymnastics coaches, medical staff, and athletes on training-load management. Methods: Online surveys were distributed among professionals and gymnasts involved in rhythmic gymnastics training across the world. One hundred (50 coaches, 12 medical staff, and 38 gymnasts) participants from 25 different countries completed the surveys. Results: Respondents stated using coaches’ perception on a daily basis as a method of monitoring external (57%) and internal (58%) load, recovery/fatigue (52%), and performance (64%). Variables and methods (eg, wearable devices, athlete self-reported measures, session rating of perceived exertion), and metrics (eg, acute and chronic load) commonly reported in the training-load literature and other sports were not frequently used in rhythmic gymnastics. The majority of coaches (60.3% [17%]) perceived that maladaptation rarely or never occurred. Medical staff involvement in sharing and discussing training-load information was limited, and they perceived that the measurement of athletes’ recovery/fatigue was poor. Gymnasts noted good quality in relation to the measurement of performance. Most participants (≥85%) believed that a specific training-load management model for rhythmic gymnastics could be very or extremely effective. Conclusions: In conclusion, rhythmic gymnastics coaches’ perception is the most commonly used strategy to monitor load, recovery/fatigue, and performance; although, this could be a limited method to guarantee effective training-load management in this sport.

Monitoring Training Load, Recovery, and Performance of Brazilian Professional Volleyball Players During a Season

2018 ◽  
Vol 13 (9) ◽  
pp. 1182-1189 ◽  
Author(s):  
Paula B. Debien ◽  
Marcelly Mancini ◽  
Danilo R. Coimbra ◽  
Daniel G.S. de Freitas ◽  
Renato Miranda ◽  
...  
Keyword(s):  
Physical Performance ◽  
Perceived Exertion ◽  
Training Session ◽  
Training Load ◽  
Rating Of Perceived Exertion ◽  
Total Quality ◽  
Volleyball Players ◽  
Monitoring Training ◽  
And Performance ◽  
Difficulty Score

Purpose: To describe and analyze the distribution of internal training load (ITL), recovery, and physical performance of professional volleyball players throughout 1 season. Methods: Fifteen male professional Brazilian volleyball players participated in this study. The session rating of perceived exertion (s-RPE) and Total Quality Recovery (TQR) score were collected daily for 36 wk. s-RPE was collected after each training session, and TQR, before the first session of the day. The sum of the ITL of each session during the week, training monotony, strain, acute∶chronic workload ratio, match difficulty score, and average of the TQR scores were recorded for the analysis. In addition, the athletes performed countermovement-jump (CMJ) tests with and without the use of the arms 4 times over the season. Results: The season mean weekly ITL was 3733 (1228) AU and the TQR was 15.02 (0.71). The ITL and recovery demonstrated undulating dynamics over the 36 wk, with higher weekly ITL in the preparatory periods (F = 50.32; P < .001) and worse recovery during the main competition (F = 6.47; P = .004). Negative correlations were found between TQR and ITL variables (P < .05). There was improvement and maintenance in CMJ tests without (F = 11.88; P < .001) and with (F = 16.02; P < .001) the use of the arms after the preparatory periods. Conclusions: The ITL variables, recovery, and physical performance changed significantly throughout a professional volleyball season. Despite the decrease in ITL during the main competitive period, the correct distribution of weekly ITL seems to be very important to guarantee the best recovery of athletes.

scholarly journals Influence of Faster and Slower Recovery-Profile Classifications, Self-Reported Sleep, Acute Training Load, and Phase of the Microcycle on Perceived Recovery in Futsal Players

2020 ◽  
Vol 15 (5) ◽  
pp. 648-653 ◽  
Author(s):  
Carolina F. Wilke ◽  
Samuel P. Wanner ◽  
Weslley H.M. Santos ◽  
Eduardo M. Penna ◽  
Guilherme P. Ramos ◽  
...  
Keyword(s):  
Sleep Quality ◽  
Perceived Exertion ◽  
Mixed Model ◽  
Linear Mixed Model ◽  
Training Load ◽  
Rating Of Perceived Exertion ◽  
Total Quality ◽  
Training Impulse

Purpose: To determine whether daily perceived recovery is explained from a multifactorial single-session classification of recovery (ie, faster vs slower) or other circumstantial factors (ie, previous training load, self-reported sleep, or phase of the microcycle). Methods: Nineteen elite male futsal players were initially allocated to a recovery-classification group (faster recovery, slower physiological, or slower perceptual) based on previous research using a multifactorial cluster-analysis technique. During 4 ensuing weeks of preseason, training loads were monitored via player load, training impulse, and session rating of perceived exertion. Before each day’s training, players reported their perception of recovery (Total Quality of Recovery scale [TQR]) and the number of hours and perceived quality of sleep the night prior. A hierarchical linear mixed model was used to analyze the effect of the different recovery profiles, training load, sleep, and phase of the microcycle (ie, start, middle, end) on daily TQR. Results: The recovery classification of players (P = .20), training load (training impulse, P = .32; player load, P = .23; session rating of perceived exertion, P = .46), and self-reported hours slept the night before (P = .45) did not significantly influence TQR. However, perceived sleep quality (P < .01) and phase of the microcycle (P < .01) were significantly associated with TQR (r2 = .41). Conclusions: Neither recovery classification nor prior training load influenced perceived recovery during the preseason. However, higher TQR was evident with better self-reported sleep quality, whereas lower values were associated with phases of the training week.

scholarly journals TRAINING LOAD IMPACT ON RECOVERY STATUS IN PROFESSIONAL VOLLEYBALL ATHLETES

2020 ◽  
Vol 26 (2) ◽  
pp. 158-161
Author(s):  
Thiago Andrade Goulart Horta ◽  
Pedro Henrique Prazeres de Lima ◽  
Guilherme Garcia Matta ◽  
Jefferson Verbena de Freitas ◽  
Bernardo Miloski Dias ◽  
...  
Keyword(s):  
Perceived Exertion ◽  
Positive Impact ◽  
Mood State ◽  
Training Load ◽  
Rating Of Perceived Exertion ◽  
Diagnostic Study ◽  
Total Quality ◽  
Monitoring Methods ◽  
Level Of Evidence ◽  
Recovery Status

ABSTRACT Introduction: The success of training depends on the balance between training load magnitude and recovery. Objective: Verify the effect of training load distribution on recovery status, vigor and fatigue in volleyball players during a season. Methods: Nine male athletes from a professional volleyball team participated in the study. During 19 weeks of the season, quantification of the training load was performed through the session rating of perceived exertion (RPE) method, evaluation of the athletes' recovery status through the Total Quality Recovery (TQR) scale, and evaluation of the profile of mood state through the POMS questionnaire, with research focus for the subscales vigor and fatigue. Results: The average total weekly training load (TWTL) was 3206 ± 685.5 A. Us and the average recovery of the whole season was 15.3 ± 0.57. The mean values of fatigue and vigor were 11 ± 3.05 and 19.4 ± 2.84, respectively. Significant differences were found for the variables RPE, fatigue and Energy Index (Vigor - Fatigue) in the three different periods of the season (Preparatory Period, Competitive Period I and Competitive Period II). Conclusion: It was concluded that the training load and recovery monitoring methods used throughout the season were effective in controlling the variables, with a positive impact of training loads verified on the recovery values presented by the athletes. Level of Evidence III; Diagnostic study.

Training Load and Player Monitoring in High-Level Football: Current Practice and Perceptions

2016 ◽  
Vol 11 (5) ◽  
pp. 587-593 ◽  
Author(s):  
Richard Akenhead ◽  
George P. Nassis
Keyword(s):  
Heart Rate ◽  
Human Resources ◽  
Perceived Exertion ◽  
Performance Enhancement ◽  
The United States ◽  
Training Load ◽  
Assessment Tools ◽  
Rating Of Perceived Exertion ◽  
Actual Effectiveness ◽  
High Level

Training load (TL) is monitored with the aim of making evidence-based decisions on appropriate loading schemes to reduce injuries and enhance team performance. However, little is known in detail about the variables of load and methods of analysis used in high-level football. Therefore, the aim of this study was to provide information on the practices and practitioners’ perceptions of monitoring in professional clubs. Eighty-two high-level football clubs from Europe, the United States, and Australia were invited to answer questions relating to how TL is quantified, how players’ responses are monitored, and their perceptions of the effectiveness of monitoring. Forty-one responses were received. All teams used GPS and heart-rate monitors during all training sessions, and 28 used rating of perceived exertion. The top-5-ranking TL variables were acceleration (various thresholds), total distance, distance covered above 5.5 m/s, estimated metabolic power, and heart-rate exertion. Players’ responses to training are monitored using questionnaires (68% of clubs) and submaximal exercise protocols (41%). Differences in expected vs actual effectiveness of monitoring were 23% and 20% for injury prevention and performance enhancement, respectively (P < .001 d = 1.0−1.4). Of the perceived barriers to effectiveness, limited human resources scored highest, followed by coach buy-in. The discrepancy between expected and actual effectiveness appears to be due to suboptimal integration with coaches, insufficient human resources, and concerns over the reliability of assessment tools. Future approaches should critically evaluate the usefulness of current monitoring tools and explore methods of reducing the identified barriers to effectiveness.

scholarly journals Increases in RPE Rating Predict Fatigue Accumulation Without Changes in Heart Rate Zone Distribution After 4-Week Low-Intensity High-Volume Training Period in High-Level Rowers

2021 ◽  
Vol 12 ◽  
Author(s):  
Rasmus Pind ◽  
Peter Hofmann ◽  
Evelin Mäestu ◽  
Eno Vahtra ◽  
Priit Purge ◽  
...  
Keyword(s):  
Heart Rate ◽  
Perceived Exertion ◽  
Training Load ◽  
Rating Of Perceived Exertion ◽  
Training Data ◽  
Training Period ◽  
Zone Method ◽  
Low Intensity ◽  
High Level ◽  
Intensity Training

Purpose: The aim of this study was to investigate the interaction of training load quantification using heart rate (HR) and rating of perceived exertion (RPE)-based methodology, and the relationship between internal training load parameters and subjective training status (Fatigue) in high-level rowers during volume increased low-intensity training period.Methods: Training data from 19 high-level rowers (age 23.5 ± 5.9 years; maximal oxygen uptake 58.9 ± 5.8 ml·min−1·kg−1) were collected during a 4-week volume increased training period. All individual training sessions were analyzed to quantify training intensity distribution based on the HR time-in-zone method (i.e., HR Z1, HR Z2, and HR Z3) determined by the first and second ventilatory thresholds (VT1/VT2). Internal training load was calculated using session RPE (sRPE) to categorize training load by effort (i.e., sRPE1, sRPE2, and sRPE3). The Recovery-Stress Questionnaire for Athletes (RESTQ-Sport) questionnaire was implemented after every week of the study period.Results: No differences were found between the respective HR and effort-based zone distributions during the baseline week (p &gt; 0.05). Compared to HR Z1, sRPE1 was significantly lower in weeks 2–4 (p &lt; 0.05), while sRPE2 was higher in weeks 2–3 compared to HR Z2 (p &lt; 0.05) and, in week 4, the tendency (p = 0.06) of the higher amount of sRPE3 compared to HR Z3 was found. There were significant increases in RESTQ-Sport stress scales and decreases in recovery scales mostly during weeks 3 and 4. Increases in the Fatigue scale were associated with the amounts of sRPE2 and sRPE3 (p = 0.011 and p = 0.008, respectively), while no associations with Fatigue were found for HR-based session quantification with internal or external training load variables.Conclusion: During a low-intensity 4-week training period with increasing volume, RPE-based training quantification indicated a shift toward the harder rating of sessions with unchanged HR zone distributions. Moderate and Hard rated sessions were related to increases in Fatigue. Session rating of perceived exertion and effort-based training load could be practical measures in combination with HR to monitor adaptation during increased volume, low-intensity training period in endurance athletes.

scholarly journals Managing Load to Optimize Well-Being and Recovery During Short-Term Match Congestion in Elite Basketball

2021 ◽  
Vol 16 (1) ◽  
pp. 45-50
Author(s):  
Steven H. Doeven ◽  
Michel S. Brink ◽  
Barbara C.H. Huijgen ◽  
Johan de Jong ◽  
Koen A.P.M. Lemmink
Keyword(s):  
Perceived Exertion ◽  
Training Session ◽  
Well Being ◽  
Training Load ◽  
Rating Of Perceived Exertion ◽  
Total Quality ◽  
Short Term ◽  
Basketball Players ◽  
Total Load ◽  
And Training

In elite basketball, players are exposed to intensified competition periods when participating in both national and international competitions. How coaches manage training between matches and in reference to match scheduling for a full season is not yet known. Purpose: First, to compare load during short-term match congestion (ie, ≥2-match weeks) with regular competition (ie, 1-match weeks) in elite male professional basketball players. Second, to determine changes in well-being, recovery, neuromuscular performance, and injuries and illnesses between short-term match congestion and regular competition. Methods: Sixteen basketball players (age 24.8 [2.0] y, height 195.8 [7.5] cm, weight 94.8 [14.0] kg, body fat 11.9% [5.0%], VO2max 51.9 [5.3] mL·kg−1·min−1) were monitored during a full season. Session rating of perceived exertion (s-RPE) was obtained, and load was calculated (s-RPE × duration) for each training session or match. Perceived well-being (fatigue, sleep quality, general muscle soreness, stress levels, and mood) and total quality of recovery were assessed each training day. Countermovement jump height was measured, and a list of injuries and illnesses was collected weekly using the adapted Oslo Sports Trauma Research Center Questionnaire on Health Problems. Results: Total load (training sessions and matches; P < .001) and training load (P < .001) were significantly lower for ≥2-match weeks. Significantly higher well-being (P = .01) and less fatigue (P = .001) were found during ≥2-match weeks compared with 1-match weeks. Conclusion: Total load and training load were lower during short-term match congestion compared with regular competition. Furthermore, better well-being and less fatigue were demonstrated within short-term match congestion. This might indicate that coaches tend to overcompensate training load in intensified competition.

scholarly journals Quantifying Sub-Elite Youth Football Weekly Training Load and Recovery Variation

2021 ◽  
Vol 11 (11) ◽  
pp. 4871
Author(s):  
José E. Teixeira ◽  
Pedro Forte ◽  
Ricardo Ferraz ◽  
Miguel Leal ◽  
Joana Ribeiro ◽  
...  
Keyword(s):  
Perceived Exertion ◽  
Training Load ◽  
Rating Of Perceived Exertion ◽  
Future Research ◽  
Total Quality ◽  
Youth Football ◽  
Age Related ◽  
Weekly Training ◽  
External Training ◽  
Recovery Status

Monitoring the training load in football is an important strategy to improve athletic performance and an effective training periodization. The aim of this study was two-fold: (1) to quantify the weekly training load and recovery status variations performed by under-15, under-17 and under-19 sub-elite young football players; and (2) to analyze the influence of age, training day, weekly microcycle, training and playing position on the training load and recovery status. Twenty under-15, twenty under-17 and twenty under-19 players were monitored over a 2-week period during the first month of the 2019–2020 competitive season. Global positioning system technology (GPS) was used to collect external training loads: total distance covered, average speed, maximal running speed, relative high-speed running distance, high metabolic load distance, sprinting distance, dynamic stress load, accelerations and decelerations. Internal training load was monitored using ratings of perceived exertion (RPE) and session rating of perceived exertion (sRPE). Recovery status was obtained using the total quality recovery (TQR) scale. The results show an age-related influence for external training load (p ≤ 0.001; d = 0.29–0.86; moderate to strong effect), internal training load (p ≤ 0.001, d = 0.12–0.69; minimum to strong effect) and recovery status (p ≤ 0.001, d = 0.59; strong effect). The external training load presented differences between training days (p < 0.05, d = 0.26–0.95; moderate to strong effect). The playing position had a minimum effect on the weekly training load (p < 0.05; d = 0.06–0.18). The weekly microcycle had a moderate effect in the TD (p < 0.05, d = 0.39), RPE (p < 0.05; d = 0.35) and sRPE (p < 0.05, d = 0.35). Interaction effects were found between the four factors analyzed for deceleration (F = 2.819, p = 0.017) and between inter-day, inter-week and age for total covered distance (F = 8.342, p = 0.008). This study provided specific insights about sub-elite youth football training load and recovery status to monitor training environments and load variations. Future research should include a longer monitoring period to assess training load and recovery variations across different season phases.

scholarly journals Internal and External Training Load in Under-19 versus Professional Soccer Players during the In-Season Period

2021 ◽  
Vol 18 (2) ◽  
pp. 558
Author(s):  
Sullivan Coppalle ◽  
Guillaume Ravé ◽  
Jason Moran ◽  
Iyed Salhi ◽  
Abderraouf Ben Abderrahman ◽  
...  
Keyword(s):  
Perceived Exertion ◽  
Training Session ◽  
Training Load ◽  
Rating Of Perceived Exertion ◽  
Soccer Players ◽  
Time Intervals ◽  
Professional Soccer ◽  
Global Positioning ◽  
External Training ◽  
Soccer Team

This study aimed to compare the training load of a professional under-19 soccer team (U-19) to that of an elite adult team (EAT), from the same club, during the in-season period. Thirty-nine healthy soccer players were involved (EAT [n = 20]; U-19 [n = 19]) in the study which spanned four weeks. Training load (TL) was monitored as external TL, using a global positioning system (GPS), and internal TL, using a rating of perceived exertion (RPE). TL data were recorded after each training session. During soccer matches, players’ RPEs were recorded. The internal TL was quantified daily by means of the session rating of perceived exertion (session-RPE) using Borg’s 0–10 scale. For GPS data, the selected running speed intensities (over 0.5 s time intervals) were 12–15.9 km/h; 16–19.9 km/h; 20–24.9 km/h; >25 km/h (sprint). Distances covered between 16 and 19.9 km/h, > 20 km/h and >25 km/h were significantly higher in U-19 compared to EAT over the course of the study (p =0.023, d = 0.243, small; p = 0.016, d = 0.298, small; and p = 0.001, d = 0.564, small, respectively). EAT players performed significantly fewer sprints per week compared to U-19 players (p = 0.002, d = 0.526, small). RPE was significantly higher in U-19 compared to EAT (p =0.001, d = 0.188, trivial). The external and internal measures of TL were significantly higher in the U-19 group compared to the EAT soccer players. In conclusion, the results obtained show that the training load is greater in U19 compared to EAT.

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