Sport-Specific Outdoor Rehabilitation in a Group Setting: Do the Intentions Match Actual Training Load?

2018 ◽  
Vol 27 (2) ◽  
pp. 151-156 ◽  
Author(s):  
Jeroen de Bruijn ◽  
Henk van der Worp ◽  
Mark Korte ◽  
Astrid de Vries ◽  
Rick Nijland ◽  
...  

Context: Previous research has shown a weak relationship between intended and actual training load in various sports. Due to variety in group and content, this relationship is expected to be even weaker during group rehabilitation. Objective: The goal of this study was to examine the relationship between intended and actual training load during sport-specific rehabilitation in a group setting. Design: Observational study. Setting: Three outdoor rehabilitation sessions. Participants: Nine amateur soccer players recovering from lower limb injury participated in the study (age 22 ± 3 y, height 179 ± 9 cm, body mass 75 ± 13 kg). Main Outcome Measures: We collected physiotherapists’ ratings of intended exertion (RIE) and players’ ratings of perceived exertion (RPE). Furthermore, Zephyr Bioharness 3 equipped with GPS-trackers provided heart rate and distance data. We computed heart rate–based training loads using Edwards’ method and a modified TRIMP. Results: Overall, we found weak correlations (N = 42) between RIE and RPE (r = 0.35), Edwards’ (r = 0.34), TRIMPMOD (r = 0.07), and distance (r = 0.26). Conclusions: In general, physiotherapists tended to underestimate training loads. To check whether intended training loads are met, it is thus recommended to monitor training loads during rehabilitation.

Sports ◽  
2021 ◽  
Vol 9 (8) ◽  
pp. 109
Author(s):  
Tom Douchet ◽  
Allex Humbertclaude ◽  
Carole Cometti ◽  
Christos Paizis ◽  
Nicolas Babault

Accelerations (ACC) and decelerations (DEC) are important and frequent actions in soccer. We aimed to investigate whether ACC and DEC were good indicators of the variation of training loads in elite women soccer players. Changes in the training load were monitored during two different selected weeks (considered a “low week” and a “heavy week”) during the in-season. Twelve elite soccer women playing in the French first division wore a 10-Hz Global Positioning System unit recording total distance, distance within speed ranges, sprint number, ACC, DEC, and a heart rate monitor during six soccer training sessions and rated their perceived exertion (RPE). They answered the Hooper questionnaire (sleep, stress, fatigue, DOMS) to get an insight of their subjective fitness level at the start (Hooper S) and at the end of each week (Hooper E). A countermovement jump (CMJ) was also performed once a week. During the heavy week, the training load was significantly greater than the low week when considering number of ACC >2 m·s−2 (28.2 ± 11.9 vs. 56.1 ± 10.1, p < 0.001) and number of DEC < −2 m·s−2 (31.5 ± 13.4 vs. 60.9 ± 14.4, p < 0.001). The mean heart rate percentage (HR%) (p < 0.05), RPE (p < 0.001), and Hooper E (p < 0.001) were significantly greater during the heavy week. ACC and DEC showed significant correlations with most outcomes: HR%, total distance, distance per min, sprint number, Hooper index of Hooper E, DOMS E, Fatigue E, RPE, and session RPE. We concluded that, for elite women soccer players, quantifying ACC and DEC alongside other indicators seemed to be essential for a more complete training load monitoring. Indeed, it could lead to a better understanding of the reasons why athletes get fatigued and give insight into neuromuscular, rather than only energetic, fatigue.


2019 ◽  
Vol 9 (23) ◽  
pp. 5174
Author(s):  
Alessio Rossi ◽  
Enrico Perri ◽  
Luca Pappalardo ◽  
Paolo Cintia ◽  
F. Iaia

The use of machine learning (ML) in soccer allows for the management of a large amount of data deriving from the monitoring of sessions and matches. Although the rate of perceived exertion (RPE), training load (S-RPE), and global position system (GPS) are standard methodologies used in team sports to assess the internal and external workload; how the external workload affects RPE and S-RPE remains still unclear. This study explores the relationship between both RPE and S-RPE and the training workload through ML. Data were recorded from 22 elite soccer players, in 160 training sessions and 35 matches during the 2015/2016 season, by using GPS tracking technology. A feature selection process was applied to understand which workload features influence RPE and S-RPE the most. Our results show that the training workloads performed in the previous week have a strong effect on perceived exertion and training load. On the other hand, the analysis of our predictions shows higher accuracy for medium RPE and S-RPE values compared with the extremes. These results provide further evidence of the usefulness of ML as a support to athletic trainers and coaches in understanding the relationship between training load and individual-response in team sports.


1995 ◽  
Vol 81 (2) ◽  
pp. 691-700
Author(s):  
Sarah A. Schaefeer ◽  
Lynn A. Darby ◽  
Kathy D. Browder ◽  
Brenda D. Reeves

The relationship between ratings of perceived exertion (RPE) and metabolic responses was examined during aerobic dance exercise with combined arm and leg movements. 16 women with previous aerobic dance instructional experience performed three consecutive trials of 8 min. each of aerobic dance exercise at a cadence of 124 and 138 beats • min.-1 Estimates of RPE reported at the end of each trial were significantly different across the trials while heart rate and % maximum heart rate were significantly different between Trials 1 and 3. Correlations and partial correlations between RPE and all metabolic variables were not significant across trials and with trials combined except for ventilation. Results indicated that RPE should not be used singularly as an indicator of exercise intensity during aerobic dance exercise.


2018 ◽  
Vol 10 (1) ◽  
pp. 157-162 ◽  
Author(s):  
Andrew Scott Perrotta ◽  
Darren E. R. Warburton

Abstract Study aim: Recent evidence has revealed a reduction in the strength of correlation between ratings of perceived exertion and a heart rate (HR) derived training load in elite field hockey players during competition. These competitive periods involve sustained levels of cardiovascular performance coupled with considerable time performing above the anaerobic threshold. As such, the purpose of this investigation was to examine the magnitude of correlation between ratings of perceived exertion and time spent above threshold and two HR derived training loads.Material and methods: Seventeen (n = 17) international caliber female field hockey players competing as a national team were monitored over four matches during a seven-day competition period within the 2016 Olympic Cycle. Cardiovascular indices of exercise intensity were derived from HR dynamics and were quantified through estimating time spent above anaerobic threshold (LT2), the Edwards training load model (TLED) and the Polar Training Load (TLPOL). Sessional ratings of perceived exertion (sRPE) were recorded after each match.Results: 64 samples were recorded for analysis. HR derived (TLED& TL POL) and sRPE training loads remained comparable between matches. A large correlation (p = 0.01) was observed between sRPE and each heart rate derived training load (TLED& TLPOL). An unremarkable relationship (p = 0.06) was revealed between time spent above LT2 and sRPE.Conclusions: Our results demonstrate HR derived training loads (TLPOL& TLED) exhibit a stronger correlation with sRPE than time spent above LT2 in elite field hockey players during competition.


2008 ◽  
Vol 3 (1) ◽  
pp. 16-30 ◽  
Author(s):  
Jill Borresen ◽  
Michael I. Lambert

Purpose:To establish the relationship between a subjective (session rating of perceived exertion [RPE]) and 2 objective (training impulse [TRIMP]) and summated-heart-rate-zone (SHRZ) methods of quantifying training load and explain characteristics of the variance not accounted for in these relationships.Methods:Thirty-three participants trained ad libitum for 2 wk, and their heart rate (HR) and RPE were recorded to calculate training load. Subjects were divided into groups based on whether the regression equations over- (OVER), under- (UNDER), or accurately predicted (ACCURATE) the relationship between objective and subjective methods.Results:A correlation of r = .76 (95% CI: .56 to .88) occurred between TRIMP and session-RPE training load. OVER spent a greater percentage of training time in zone 4 of SHRZ (ie, 80% to 90% HRmax) than UNDER (46% ± 8% vs 25% ± 10% [mean ± SD], P = .008). UNDER spent a greater percentage of training time in zone 1 of SHRZ (ie, 50% to 60% HRmax) than OVER (15% ± 8% vs 3% ± 3%, P = .005) and ACCURATE (5% ± 3%, P = .020) and more time in zone 2 of SHRZ (ie, 60% to 70%HRmax) than OVER (17% ± 6% vs 7% ± 6%, P = .039). A correlation of r = .84 (.70 to .92) occurred between SHRZ and session-RPE training load. OVER spent proportionally more time in Zone 4 than UNDER (45% ± 8% vs 25% ± 10%, P = .018). UNDER had a lower training HR than ACCURATE (132 ± 10 vs 148 ± 12 beats/min, P = .048) and spent more time in zone 1 than OVER (15% ± 8% vs 4% ± 3%, P = .013) and ACCURATE (5% ± 3%, P = .015).Conclusions:The session-RPE method provides reasonably accurate assessments of training load compared with HR-based methods, but they deviate in accuracy when proportionally more time is spent training at low or high intensity.


Author(s):  
Cristian Ieno ◽  
Roberto Baldassarre ◽  
Maddalena Pennacchi ◽  
Antonio La Torre ◽  
Marco Bonifazi ◽  
...  

Purpose: To analyze training-intensity distribution (TID) using different independent monitoring systems for internal training load in a group of elite open-water swimmers. Methods: One hundred sixty training sessions were monitored in 4 elite open-water swimmers (2 females and 2 males: 23.75 [4.86] y, 62.25 [6.18] kg, 167 [6.68] cm) during 5 weeks of regular training. Heart-rate-based methods, such as time in zone (TIZ), session goal (SG), and hybrid (SG/TIZ), were used to analyze TID. Similarly to SG/TIZ, a new hybrid approach, the rating of perceived exertion (RPE)/TIZ for a more accurate analysis of TID was used. Moreover, based on the 3-zone model, the session ratings of perceived exertion of the swimmers and the coach were compared. Results: Heart-rate- and RPE-based TID methods were significantly different in quantifying Z1 (P = .012; effect size [ES] = 0.490) and Z2 (P = .006; ES = 0.778), while no difference was observed in the quantification of Z3 (P = .428; ES = 0.223). The heart-rate-based data for Z1, Z2, and Z3 were 83.2%, 7.4%, and 8.1% for TIZ; 80.8%, 8.3%, and 10.8% for SG/TIZ; and 55%, 15.6%, and 29.4% for SG. The RPE-based data were 70.9%, 19.9%, and 9.2% for RPE/TIZ% and 41.2%, 48.9%, and 9.7% for the session rating of perceived exertion. No differences were observed between the coach’s and the swimmers’ session ratings of perceived exertion in the 3 zones (Z1: P = .663, ES = −0.187; Z2: P = .110, ES = 0.578; Z3: P = .149, ES = 0.420). Conclusion: Using RPE-based TID methods, Z2 was significantly larger compared with Z1. These results show that RPE-based TID methods in elite open-water swimmers are affected by both intensity and volume.


2020 ◽  
Vol 185 (5-6) ◽  
pp. e847-e852
Author(s):  
Maria C Canino ◽  
Stephen A Foulis ◽  
Bruce S Cohen ◽  
Leila A Walker ◽  
Kathryn M Taylor ◽  
...  

Abstract Introduction There are many ways to quantify the training loads required to perform soldiering tasks. Although indirect calorimetry may provide the most accurate measures, the equipment can be burdensome and expensive. Simpler measures may provide sufficient data, while being more practical for measuring soldiers in the field. The purpose of this study was to examine the relationship between total relative oxygen uptake (TotalRelVO2) measured by indirect calorimetry during three soldiering tasks, with two field-expedient measures of training load: summated heart rate zone (sumHR) and session rate of perceived exertion (sRPE). Materials and Methods 33 male and 28 female soldiers performed three soldiering tasks while wearing a 32.3-kg fighting load: sandbag fill, sandbag carry, and ammunition can carry. Metabolic measurements were monitored and completion times were recorded (min). TotalRelVO2 (average relative VO2*time) and age-predicted maximal heart rate (220-age) were calculated. SumHR was calculated by multiplying time spent in each of the five heart rate zones by a multiplier factor for each zone (50–59% = 1, 60–69% = 2, 70–79% = 3, 80–89% = 4, and ≥90% = 5). RPE (Borg 6–20 scale) was collected at the end of each task, then sRPE was calculated (RPE*time). Pearson and Spearman correlations were performed to examine the relationship between TotalRelVO2, sumHR and sRPE. Wilcoxon signed rank tests were conducted to determine if there was a difference in median rankings between the three variables for each task. Linear regressions were performed to determine predictability of TotalRelVO2 from sumHR and sRPE. The study was approved by the U.S. Army Research Institute of Environmental Medicine Institutional Review Board. Results Significant, positive correlations were revealed for all three tasks between TotalRelVO2, sumHR and sRPE (r ≥ 0.67, p ≤ 0.01; rho≥0.74, p ≤ 0.01). Wilcoxon signed rank tests revealed no significant differences in rankings between TotalRelVO2, sumHR and sRPE for all three tasks (p ≥ 0.43). Both sumHR and sRPE are significant predictors of TotalRelVO2 (p ≤ 0.01). Conclusions SumHR and sRPE are acceptable alternatives to TotalRelVO2 when attempting to quantify and/or monitor training load during soldiering tasks.


2017 ◽  
Vol 12 (5) ◽  
pp. 665-676 ◽  
Author(s):  
Adam L Owen ◽  
Carlos Lago-Peñas ◽  
Miguel-Ángel Gómez ◽  
Bruno Mendes ◽  
Alexandre Dellal

Ensuring adequate levels of training and recovery at the elite level of professional soccer to maximise player performance has continued to drive the necessity to monitor the training load and physical training output of soccer players. The aim of this investigation was to analyse a training mesocycle whilst quantifying positional demands imposed on elite European soccer players. Sixteen players were assessed using global positioning systems and ratings of perceived exertion over a competitive training six-week mesocycle period. The positional demands and training loads were analysed in addition to match conditions (match location, match score) and player’s age. Results from the investigation revealed that typical daily training loads (i.e. total distance, high-intensity distance, sprint distance, average speed, ratings of perceived exertion) did not differ throughout each week of the mesocycle in-season period. Further analysis revealed training loads were significantly lower on match day-1 when compared to training loads on match day-2, match day-3 and match day-4 preceding a match ( p < 0.05). Significant differences in physical outputs were also found between match day-2, match day-3 and match day-4 highlighting a structured periodised tapered approach ( p < 0.05). Lower average speeds were reported in training post-successful matches compared to defeats ( p < 0.05), and more specifically when a match was played away compared to home fixtures ( p < 0.05). To conclude, practitioners can maintain a uniformed and structured training load mesocycle whilst inducing variation of the physical outputs during the microcycle phase. Additionally, the investigation also provides a tapering approach that may induce significant variation of the positional demands.


2019 ◽  
Vol 31 (1) ◽  
pp. 91-98 ◽  
Author(s):  
Durva Vahia ◽  
Adam Kelly ◽  
Harry Knapman ◽  
Craig A. Williams

Purpose: When exposed to the same external load, players receive different internal loads, resulting in varied adaptations in fitness. In adult soccer, internal training load is measured using heart rate (HR) and session rating of perceived exertion (sRPE) scales, but these have been underutilized in youth soccer. This study investigated the in-season variation in correlation between HR and sRPE estimations of training load for adolescent soccer players. Method: Fifteen male professional adolescent players were monitored for 7 months. Within-participant correlations and Bland–Altman agreement plots for HR and sRPE were calculated for each month to analyze variation over the season and for individual players to analyze the validity of the scale. Results: The monthly correlations ranged from r = .60 to r = .73 (P < .05) and the overall correlation was r = .64 (95% confidence interval, .60–.68; P < .001). Bland–Altman plots showed an agreement of methods. Conclusion: Results showed consistently large correlations for all months. sRPE is a consistent method of measure of internal training load for the entire season for youth soccer players. Validity analysis found no bias in sRPE measurements when compared with HR for all players in the study.


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