scholarly journals Impaired Player–Coach Perceptions of Exertion and Recovery During Match Congestion

2017 ◽  
Vol 12 (9) ◽  
pp. 1151-1156 ◽  
Author(s):  
Steven H. Doeven ◽  
Michel S. Brink ◽  
Wouter G.P. Frencken ◽  
Koen A.P.M. Lemmink
Keyword(s):  
Perceived Exertion ◽  
Training Session ◽  
Rating Of Perceived Exertion ◽  
Total Quality ◽  
Basketball Players ◽  
Subsequent Recovery ◽  
Professional Basketball ◽  
Quality Of Recovery ◽  
Degree Of Recovery

During intensified phases of competition, attunement of exertion and recovery is crucial to maintain performance. Although a mismatch between coach and player perceptions of training load is demonstrated, it is unknown if these discrepancies also exist for match exertion and recovery. Purpose:To determine match exertion and subsequent recovery and to investigate the extent to which the coach is able to estimate players’ match exertion and recovery. Methods:Rating of perceived exertion (RPE) and total quality of recovery (TQR) of 14 professional basketball players (age 26.7 ± 3.8 y, height 197.2 ± 9.1 cm, weight 100.3 ± 15.2 kg, body fat 10.3% ± 3.6%) were compared with observations of the coach. During an in-season phase of 15 matches within 6 wk, players gave RPEs after each match. TQR scores were filled out before the first training session after the match. The coach rated observed exertion (ROE) and recovery (TQ-OR) of the players. Results:RPE was lower than ROE (15.6 ± 2.3 and 16.1 ± 1.4; P = .029). Furthermore, TQR was lower than TQ-OR (12.7 ± 3.0 and 15.3 ± 1.3; P < .001). Correlations between coach- and player-perceived exertion and recovery were r = .25 and r = .21, respectively. For recovery within 1 d the correlation was r = .68, but for recovery after 1–2 d no association existed. Conclusion:Players perceive match exertion as hard to very hard and subsequent recovery reasonable. The coach overestimates match exertion and underestimates degree of recovery. Correspondence between coach and players is thus not optimal. This mismatch potentially leads to inadequate planning of training sessions and decreases in performance during fixture congestion in basketball.

Effect of Training-Session Intensity Distribution on Session Rating of Perceived Exertion in Soccer Players

2015 ◽  
Vol 10 (4) ◽  
pp. 426-430 ◽  
Author(s):  
Maurizio Fanchini ◽  
Roberto Ghielmetti ◽  
Aaron J. Coutts ◽  
Federico Schena ◽  
Franco M. Impellizzeri
Keyword(s):  
Exercise Intensity ◽  
Perceived Exertion ◽  
Training Session ◽  
Random Order ◽  
Rating Of Perceived Exertion ◽  
Lower Limbs ◽  
Total Quality ◽  
Quality Of Recovery ◽  
Rate Maximum

Purpose:To examine the effect of different exercise-intensity distributions within a training session on the session rating of perceived exertion (RPE) and to examine the timing of measure on the rating.Methods:Nineteen junior players (age 16 ± 1 y, height 173 ± 5 cm, body mass 64 ± 6 kg) from a Swiss soccer team were involved in the study. Percentage of heart rate maximum (%HR) and RPE (Borg CR100®) were collected in 4 standardized training sessions (conditions). The Total Quality of Recovery scale (TQR) and a visual analogue scale (VAS) for pain of the lower limbs were used to control for the effect of pretraining fatigue. Every session consisted of three 20-min blocks of different intensities (ie, low-moderate-high) performed in a random order. RPE was collected after every block (RPE5), immediately after the session (RPE-end), and 30 min after the session (RPE30).Results:RPE5s of each block were different depending on the distribution sequence (P < .0001). RPE-end, TQR, and VAS values were not different between conditions (P = .57, P = .55, and P = .96, respectively). The %HR was significantly different between conditions (P = .008), with condition 3 higher than condition 2 (74.1 vs 70.2%, P = .02). Edwards training loads were not significantly different between conditions (P = .09). RPE30 was not different from RPE-end (P > .05).Conclusions:The current results show that coaches can design training sessions without concern about the influence of the within-session distribution of exercise intensity on session-RPE and that RPE can be collected at the end of the session or 30 min later.

scholarly journals Nonergodicity in Load and Recovery: Group Results Do Not Generalize to Individuals

2021 ◽  
pp. 1-9
Author(s):  
Niklas D. Neumann ◽  
Nico W. Van Yperen ◽  
Jur J. Brauers ◽  
Wouter Frencken ◽  
Michel S. Brink ◽  
...  
Keyword(s):  
Perceived Exertion ◽  
Rating Of Perceived Exertion ◽  
Group Level ◽  
Total Quality ◽  
Individual Level ◽  
Quality Of Recovery ◽  
Level Statistics ◽  
The Individual ◽  
Level Analysis

Purpose: The study of load and recovery gained significant interest in the last decades, given its important value in decreasing the likelihood of injuries and improving performance. So far, findings are typically reported on the group level, whereas practitioners are most often interested in applications at the individual level. Hence, the aim of the present research is to examine to what extent group-level statistics can be generalized to individual athletes, which is referred to as the “ergodicity issue.” Nonergodicity may have serious consequences for the way we should analyze, and work with, load and recovery measures in the sports field. Methods: The authors collected load, that is, rating of perceived exertion × training duration, and total quality of recovery data among youth male players of a professional football club. This data were collected daily across 2 seasons and analyzed on both the group and the individual level. Results: Group- and individual-level analysis resulted in different statistical outcomes, particularly with regard to load. Specifically, SDs within individuals were up to 7.63 times larger than SDs between individuals. In addition, at either level, the authors observed different correlations between load and recovery. Conclusions: The results suggest that the process of load and recovery in athletes is nonergodic, which has important implications for the sports field. Recommendations for training programs of individual athletes may be suboptimal, or even erroneous, when guided by group-level outcomes. The utilization of individual-level analysis is key to ensure the optimal balance of individual load and recovery.

High Match Load’s Relation to Decreased Well-Being During an Elite Women’s Rugby Sevens Tournament

2019 ◽  
Vol 14 (8) ◽  
pp. 1036-1042 ◽  
Author(s):  
Steven H. Doeven ◽  
Michel S. Brink ◽  
Barbara C.H. Huijgen ◽  
Johan de Jong ◽  
Koen A.P.M. Lemmink
Keyword(s):  
High Intensity ◽  
Muscle Soreness ◽  
Perceived Exertion ◽  
Well Being ◽  
Rating Of Perceived Exertion ◽  
Total Quality ◽  
Quality Of Recovery ◽  
Time Motion ◽  
Stress Levels

During rugby sevens tournaments, it is crucial to balance match load and recovery to strive for optimal performance. Purpose: To determine changes in well-being, recovery, and neuromuscular performance during and after an elite women’s rugby sevens tournament and assess the influence of match-load indicators. Methods: Twelve elite women rugby sevens players (age = 25.3 [4.1]y, height = 169.0 [4.0] cm, weight = 63.9 [4.9] kg, and body fat = 18.6% [2.7%]) performed 5 matches during a 2-d tournament of the Women’s Rugby Sevens World Series. Perceived well-being (fatigue, sleep quality, general muscle soreness, stress levels, and mood), total quality of recovery, and countermovement-jump flight time were measured on match days 1 and 2, 1 d posttournament, and 2 d posttournament. Total distance; low-, moderate-, and high-intensity running; and physical contacts during matches were derived from global positioning system–based time–motion analysis and video-based notational analysis, respectively. Internal match load was calculated by session rating of perceived exertion and playing time (rating of perceived exertion × duration). Results: Well-being (P < .001), fatigue (P < .001), general muscle soreness (P < .001), stress levels (P < .001), mood (P = .005), and total quality of recovery (P < .001) were significantly impaired after match day 1 and did not return to baseline values until 2 d posttournament. More high-intensity running was related to more fatigue (r = −.60, P = .049) and a larger number of physical contacts with more general muscle soreness (r = −.69, P = .013). Conclusion: Perceived well-being and total quality of recovery were already impaired after match day 1, although performance was maintained. High-intensity running and physical contacts were predominantly related to fatigue and general muscle soreness, respectively.

scholarly journals Perceived training load and jumping responses following nine weeks of a competitive period in young female basketball players

PeerJ ◽  
2018 ◽  
Vol 6 ◽  
pp. e5225 ◽  
Author(s):  
Igor de Freitas Cruz ◽  
Lucas Adriano Pereira ◽  
Ronaldo Kobal ◽  
Katia Kitamura ◽  
Cristiano Cedra ◽  
...  
Keyword(s):  
Perceived Exertion ◽  
Training Session ◽  
Young Female ◽  
Rating Of Perceived Exertion ◽  
Multivariate Approach ◽  
Total Quality ◽  
Countermovement Jump ◽  
Young Athletes ◽  
Basketball Players ◽  
Weekly Training

The aims of this study were to describe the session rating of perceived exertion (sRPE), total quality recovery (TQR), and variations in countermovement jump (CMJ) height throughout nine weeks of a competitive period in young female basketball players. In total, 10 young female basketball players (17.2 ± 0.4 years; 71.8 ± 15.0 kg; 177.2 ± 9.5 cm) participated in this study. The sRPE and TQR were assessed in each training session, whereas the CMJ height was assessed prior to the first weekly training session. The magnitude-based inferences method was used to compare the sRPE, TQR, and CMJ height across the nine weeks of training. The training loads accumulated in weeks 1, 2, and 3 were likely to almost certainly be higher than in the following weeks (ES varying from 0.67 to 2.55). The CMJ height in week 1 was very likely to be lower than in weeks 2, 5, 7, and 8 (ES varying from 0.24 to 0.34), while the CMJ height of the 9th week was likely to almost certainly be higher than all previous weeks of training (ES varying from 0.70 to 1.10). Accordingly, it was observed that when higher training loads were accumulated, both CMJ and TQR presented lower values than those presented during periods with lower internal training loads. These results highlight the importance of using a comprehensive and multivariate approach to effectively monitor the physical performance of young 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.

Monitoring Workload in Elite Female Basketball Players During the In-Season Phase: Weekly Fluctuations and Effect of Playing Time

2019 ◽  
Vol 14 (7) ◽  
pp. 941-948 ◽  
Author(s):  
Henrikas Paulauskas ◽  
Rasa Kreivyte ◽  
Aaron T. Scanlan ◽  
Alexandre Moreira ◽  
Laimonas Siupsinskas ◽  
...  
Keyword(s):  
Perceived Exertion ◽  
Linear Models ◽  
Training Session ◽  
Rating Of Perceived Exertion ◽  
Basketball Players ◽  
Significant Difference ◽  
Women's Basketball ◽  
Playing Time ◽  
And Training ◽  
Basketball Teams

Purpose:To assess the weekly fluctuations in workload and differences in workload according to playing time in elite female basketball players.Methods:A total of 29 female basketball players (mean [SD] age 21 [5] y, stature 181 [7] cm, body mass 71 [7] kg, playing experience 12 [5] y) belonging to the 7 women’s basketball teams competing in the first-division Lithuanian Women’s Basketball League were recruited. Individualized training loads (TLs) and game loads (GLs) were assessed using the session rating of perceived exertion after each training session and game during the entire in-season phase (24 wk). Percentage changes in total weekly TL (weekly TL + GL), weekly TL, weekly GL, chronic workload, acute:chronic workload ratio, training monotony, and training strain were calculated. Mixed linear models were used to assess differences for each dependent variable, with playing time (low vs high) used as fixed factor and subject, week, and team as random factors.Results:The highest changes in total weekly TL, weekly TL, and acute:chronic workload ratio were evident in week 13 (47%, 120%, and 49%, respectively). Chronic workload showed weekly changes ≤10%, whereas monotony and training strain registered highest fluctuations in weeks 17 (34%) and 15 (59%), respectively. A statistically significant difference in GL was evident between players completing low and high playing times (P = .026, moderate), whereas no significant differences (P > .05) were found for all other dependent variables.Conclusions:Coaches of elite women’s basketball teams should monitor weekly changes in workload during the in-season phase to identify weeks that may predispose players to unwanted spikes and adjust player workload according to playing time.

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 Differences in Weekly Load Distribution Over Two Euroleague Seasons with a Different Head Coach

2020 ◽  
Vol 17 (8) ◽  
pp. 2812
Author(s):  
Hugo Salazar ◽  
Luka Svilar ◽  
Ane Aldalur-Soto ◽  
Julen Castellano
Keyword(s):  
External Load ◽  
Perceived Exertion ◽  
Management Program ◽  
Rating Of Perceived Exertion ◽  
Load Management ◽  
Head Coach ◽  
Basketball Players ◽  
Professional Basketball ◽  
Coaching Strategies ◽  
Weekly Training

The weekly training management and competition loads are important aspects to optimize the performance of professional basketball players. The objectives of the study were (a) to describe the weekly external load (EL), as well as the internal response (IR), of elite basketball players over two consecutive seasons with a different head coach and (b) to compare weekly loads of different competitive densities. The data were collected from 27 elite players from the same team competing in the Spanish first division league (ACB) and EuroLeague during 2017–2018 and 2018–2019 seasons. EL was measured using microsensor technology to determine PlayerLoad values, expressed in arbitrary units (AU). Session rating of perceived exertion (sRPE) was used for IR quantification. Comparisons between the two seasons and of weeks with different competitive densities were made. The inter-week load variability was moderate-high for both seasons. The highest EL values were measured during the weeks with three games (W3) (W3 > W0 > W2 > W1), while the most demanding week for players’ IR was observed during weeks with no competition (W0). Additionally, higher EL (d = 0.31) and IR (d = 0.37) values were observed in season 2018–2019 compared to 2017–2018. The results obtained in this study contributed new data on the internal and external load required by professional basketball players in weeks with different number of games and showed that different coaching strategies may demand a different external and internal workload in consecutive seasons. Furthermore, the results highlighted the need to carry out an adequate load management program.

The Relationship Between Training Load and Injury in Men’s Professional Basketball

2017 ◽  
Vol 12 (9) ◽  
pp. 1238-1242 ◽  
Author(s):  
Kaitlyn J. Weiss ◽  
Sian V. Allen ◽  
Mike R. McGuigan ◽  
Chris S. Whatman
Keyword(s):  
Regression Model ◽  
Perceived Exertion ◽  
Training Load ◽  
Rating Of Perceived Exertion ◽  
Self Report ◽  
Basketball Players ◽  
Professional Basketball ◽  
Trauma Research ◽  
Mean Differences ◽  
The Relationship

Purpose:To establish the relationship between the acute:chronic workload ratio and lower-extremity overuse injuries in professional basketball players over the course of a competitive season. Methods:The acute:chronic workload ratio was determined by calculating the sum of the current week’s session rating of perceived exertion of training load (acute load) and dividing it by the average weekly training load over the previous 4 wk (chronic load). All injuries were recorded weekly using a self-report injury questionnaire (Oslo Sports Trauma Research Center Injury Questionnaire20). Workload ratios were modeled against injury data using a logistic-regression model with unique intercepts for each player. Results:Substantially fewer team members were injured after workload ratios of 1 to 1.49 (36%) than with very low (≤0.5; 54%), low (0.5–0.99; 51%), or high (≥1.5; 59%) workload ratios. The regression model provided unique workload–injury trends for each player, but all mean differences in likelihood of being injured between workload ratios were unclear. Conclusions:Maintaining workload ratios of 1 to 1.5 may be optimal for athlete preparation in professional basketball. An individualized approach to modeling and monitoring the training load–injury relationship, along with a symptom-based injury-surveillance method, should help coaches and performance staff with individualized training-load planning and prescription and with developing athlete-specific recovery and rehabilitation strategies.

Sign in / Sign up

Export Citation Format

Share Document