scholarly journals Training-Intensity Distribution in Road Cyclists: Objective Versus Subjective Measures

2017 ◽  
Vol 12 (9) ◽  
pp. 1232-1237 ◽  
Author(s):  
Dajo Sanders ◽  
Tony Myers ◽  
Ibrahim Akubat
Keyword(s):  
Intensity Distribution ◽  
Lactate Threshold ◽  
Perceived Exertion ◽  
Rating Of Perceived Exertion ◽  
Training Data ◽  
Training Intensity ◽  
Intensity Measure ◽  
Intensity Measures ◽  
Evaluation Of Training ◽  
Road Cyclists

Purpose:To evaluate training-intensity distribution using different intensity measures based on rating of perceived exertion (RPE), heart rate (HR), and power output (PO) in well-trained cyclists. Methods:Fifteen road cyclists participated in the study. Training data were collected during a 10-wk training period. Training-intensity distribution was quantified using RPE, HR, and PO categorized in a 3-zone training-intensity model. Three zones for HR and PO were based around a 1st and 2nd lactate threshold. The 3 RPE zones were defined using a 10-point scale: zone 1, RPE scores 1–4; zone 2, RPE scores 5–6; zone 3, RPE scores 7–10. Results:Training-intensity distributions as percentages of time spent in zones 1, 2, and 3 were moderate to very largely different for RPE (44.9%, 29.9%, 25.2%) compared with HR (86.8%, 8.8%, 4.4%) and PO (79.5%, 9.0%, 11.5%). Time in zone 1 quantified using RPE was largely to very largely lower for RPE than PO (P < .001) and HR (P < .001). Time in zones 2 and 3 was moderately to very largely higher when quantified using RPE compared with intensity quantified using HR (P < .001) and PO (P < .001). Conclusions:Training-intensity distribution quantified using RPE demonstrates moderate to very large differences compared with intensity distributions quantified based on HR and PO. The choice of intensity measure affects intensity distribution and has implications for training-load quantification, training prescription, and the evaluation of training characteristics.

scholarly journals Methods of Monitoring Training Load and Their Relationships to Changes in Fitness and Performance in Competitive Road Cyclists

2017 ◽  
Vol 12 (5) ◽  
pp. 668-675 ◽  
Author(s):  
Dajo Sanders ◽  
Grant Abt ◽  
Matthijs K.C. Hesselink ◽  
Tony Myers ◽  
Ibrahim Akubat
Keyword(s):  
Dose Response ◽  
Aerobic Fitness ◽  
Perceived Exertion ◽  
Training Load ◽  
Rating Of Perceived Exertion ◽  
Training Data ◽  
Training Period ◽  
Competitive Cyclists ◽  
Road Cyclists ◽  
And Performance

Purpose:To assess the dose-response relationships between different training-load methods and aerobic fitness and performance in competitive road cyclists.Methods:Training data from 15 well-trained competitive cyclists were collected during a 10-wk (December–March) preseason training period. Before and after the training period, participants underwent a laboratory incremental exercise test with gas-exchange and lactate measures and a performance assessment using an 8-min time trial (8MT). Internal training load was calculated using Banister TRIMP, Edwards TRIMP, individualized TRIMP (iTRIMP), Lucia TRIMP (luTRIMP), and session rating of perceived exertion (sRPE). External load was measured using Training Stress Score (TSS).Results:Large to very large relationships (r = .54–.81) between training load and changes in submaximal fitness variables (power at 2 and 4 mmol/L) were observed for all training-load calculation methods. The strongest relationships with changes in aerobic fitness variables were observed for iTRIMP (r = .81 [95% CI .51–.93, r = .77 [95% CI .43–.92]) and TSS (r = .75 [95% CI .31–.93], r = .79 [95% CI .40–.94]). The strongest dose-response relationships with changes in the 8MT test were observed for iTRIMP (r = .63 [95% CI .17–.86]) and luTRIMP (r = .70 [95% CI .29–.89).Conclusions:Training-load quantification methods that integrate individual physiological characteristics have the strongest dose-response relationships, suggesting this to be an essential factor in the quantification of training load in cycling.

Training intensity distribution in young tennis players

2016 ◽  
Vol 11 (6) ◽  
pp. 880-886 ◽  
Author(s):  
Alexandre Moreira ◽  
Rodrigo V Gomes ◽  
Caroline D Capitani ◽  
Charles R Lopes ◽  
Audrei R Santos ◽  
...  
Keyword(s):  
Heart Rate ◽  
Intensity Distribution ◽  
Perceived Exertion ◽  
Rating Of Perceived Exertion ◽  
Moderate Intensity ◽  
Training Intensity ◽  
Match Play ◽  
Training Time ◽  
Tennis Players ◽  
Professional Tennis

The aim of this study was to describe the training intensity distribution of elite young tennis players, based on the session rating of perceived exertion and heart rate methods. Twelve professional tennis players participated in this study. Heart rate and session rating of perceived exertion were collected in 384 tennis training sessions, 23 simulated matches, and 17 official matches. The total training time spent in the heart rate zone-1 (52.00%) and zone-2 (37.10%) was greater than the time spent in zone-3 (10.90%) during the 5-week training period ( p < 0.05). Similarly, the total training time spent in the session rating of perceived exertion zone-1 (42.00%) and zone-2 (47.50%) was also greater than the time in zone-3 (10.50%) ( p < 0.05). The data of the present study suggest that the majority of the training sessions of these young tennis players were performed at low-to-moderate intensity zone and, therefore, under the intensity performed during actual tennis match play.

scholarly journals The Training Characteristics of Recreational-Level Triathletes: Influence on Fatigue and Health

Sports ◽  
2021 ◽  
Vol 9 (7) ◽  
pp. 94
Author(s):  
João Henrique Falk Neto ◽  
Eric C. Parent ◽  
Veronica Vleck ◽  
Michael D. Kennedy
Keyword(s):  
Intensity Distribution ◽  
Perceived Exertion ◽  
Rating Of Perceived Exertion ◽  
Recovery Stress ◽  
Health Questionnaire ◽  
Training Intensity ◽  
Recreational Athletes ◽  
Competition Period ◽  
Daily Training ◽  
Distress Scale

Little is known about how recreational triathletes prepare for an Olympic distance event. The aim of this study was to identify the training characteristics of recreational-level triathletes within the competition period and assess how their preparation for a triathlon influences their health and their levels of fatigue. During the 6 weeks prior to, and the 2 weeks after, an Olympic distance triathlon, nine recreational athletes (five males, four females) completed a daily training log. Participants answered the Daily Analysis of Life Demands Questionnaire (DALDA), the Training Distress Scale (TDS) and the Alberta Swim Fatigue and Health Questionnaire weekly. The Recovery-Stress Questionnaire (REST-Q) was completed at the beginning of the study, on the day before the competition, and at the end of week 8. Training loads were calculated using session-based rating of perceived exertion (sRPE). The data from every week of training was compared to week 1 to determine how athletes’ training and health changed throughout the study. No changes in training loads, duration or training intensity distribution were seen in the weeks leading up to the competition. Training duration was significantly reduced in week 6 (p = 0.041, d = 1.58, 95% CI = 6.9, 421.9), while the number of sessions was reduced in week 6 (Z = 2.32, p = 0.02, ES = 0.88) and week 7 (Z = 2.31, p = 0.02, ES = 0.87). Training was characterized by large weekly variations in training loads and a high training intensity. No significant changes were seen in the DALDA, TDS or REST-Q questionnaire scores throughout the 8 weeks. Despite large spikes in training load and a high overall training intensity, these recreational-level triathletes were able to maintain their health in the 6 weeks of training prior to an Olympic distance triathlon.

Factors Affecting Perception of Effort (Session Rating of Perceived Exertion) During Rugby League Training

2013 ◽  
Vol 8 (1) ◽  
pp. 62-69 ◽  
Author(s):  
Thomas W.J. Lovell ◽  
Anita C. Sirotic ◽  
Franco M. Impellizzeri ◽  
Aaron J. Coutts
Keyword(s):  
Exercise Intensity ◽  
Perceived Exertion ◽  
Rugby League ◽  
Rating Of Perceived Exertion ◽  
Stepwise Multiple Regression ◽  
Training Intensity ◽  
Intensity Measures ◽  
Positioning Systems ◽  
Body Load ◽  
Training Impulse

Purpose:The purpose of this study was to examine the validity of session rating of perceived exertion (sRPE) for monitoring training intensity in rugby league.Methods:Thirty-two professional rugby league players participated in this study. Training-load (TL) data were collected during an entire season and assessed via microtechnology (heart-rate [HR] monitors, global positioning systems [GPS], and accelerometers) and sRPE. Within-individual correlation analysis was used to determine relationships between sRPE and various other measures of training intensity and load. Stepwise multiple regressions were used to determine a predictive equation to estimate sRPE during rugby league training.Results:There were significant within-individual correlations between sRPE and various other internal and external measures of intensity and load. The stepwise multiple-regression analysis also revealed that 62.4% of the adjusted variance in sRPE-TL could be explained by TL measures of distance, impacts, body load, and training impulse (y = 37.21 + 0.93 distance − 0.39 impacts + 0.18 body load + 0.03 training impulse). Furthermore, 35.2% of the adjusted variance in sRPE could be explained by exercise-intensity measures of percentage of peak HR (%HRpeak), impacts/min, m/min, and body load/min (y = −0.01 + 0.37%HRpeak + 0.10 impacts/min + 0.17 m/min + 0.09 body load/min).Conclusion:A combination of internal and external TL factors predicts sRPE in rugby league training better than any individual measures alone. These findings provide new evidence to support the use of sRPE as a global measure of exercise intensity in rugby league training.

scholarly journals Quantifying the Training-Intensity Distribution in Middle-Distance Runners: The Influence of Different Methods of Training-Intensity Quantification

2020 ◽  
Vol 15 (3) ◽  
pp. 319-323
Author(s):  
Phillip Bellinger ◽  
Blayne Arnold ◽  
Clare Minahan
Keyword(s):  
Intensity Distribution ◽  
Perceived Exertion ◽  
Rating Of Perceived Exertion ◽  
Training Intensity ◽  
Distance Runners ◽  
Running Speed ◽  
Training Time ◽  
Reduced Time ◽  
Continuous Running ◽  
Gas Exchange Threshold

Purpose: To compare the training-intensity distribution (TID) across an 8-week training period in a group of highly trained middle-distance runners employing 3 different methods of training-intensity quantification. Methods: A total of 14 highly trained middle-distance runners performed an incremental treadmill test to exhaustion to determine the heart rate (HR) and running speed corresponding to the ventilatory thresholds (gas-exchange threshold and respiratory-compensation threshold), as well as fixed rating of perceived exertion (RPE) values, which were used to demarcate 3 training-intensity zones. During the following 8 weeks, the TID (total and percentage of time spent in each training zone) of all running training sessions (N = 695) was quantified using continuous running speed, HR monitoring, and RPE. Results: Compared with the running-speed-derived TID (zone 1, 79.9% [7.3%]; zone 2, 5.3% [4.9%]; and zone 3, 14.7% [7.3%]), HR-demarcated TID (zone 1, 79.6% [7.2%]; zone 2, 17.0% [6.3%]; and zone 3, 3.4% [2.0%]) resulted in a substantially higher training time in zone 2 (effect size ± 95% confidence interval: −1.64 ± 0.53; P < .001) and lower training time in zone 3 (−1.59 ± 0.51; P < .001). RPE-derived TID (zone 1, 39.6% [8.4%]; zone 2, 31.9% [8.7%]; and zone 3, 28.5% [11.6%]) reduced time in zone 1 compared with both HR (−5.64 ± 1.40; P < .001) and running speed (−5.69 ± 1.9; P < .001), whereas time in RPE training zones 2 and 3 was substantially higher than both HR- and running-speed-derived zones. Conclusion: The results show that the method of training-intensity quantification substantially affects computation of TID.

Quantifying Training Intensity Distribution in a Group of Norwegian Professional Soccer Players

2011 ◽  
Vol 6 (1) ◽  
pp. 70-81 ◽  
Author(s):  
Erling A. Algrøy ◽  
Ken J. Hetlelid ◽  
Stephen Seiler ◽  
Jørg I. Stray Pedersen
Keyword(s):  
Heart Rate ◽  
Standardized Testing ◽  
Intensity Distribution ◽  
Perceived Exertion ◽  
Maximal Oxygen Consumption ◽  
Rating Of Perceived Exertion ◽  
Soccer Players ◽  
Maximal Heart Rate ◽  
Training Intensity ◽  
Professional Soccer

Purpose:This study was designed to quantify the daily distribution of training intensity in a group of professional soccer players in Norway based on three different methods of training intensity quantification.Methods:Fifteen male athletes (age, 24 ± 5 y) performed treadmill test to exhaustion to determine heart rate and VO2 corresponding to ventilatory thresholds (VT1, VT2), maximal oxygen consumption (VO2max) and maximal heart rate. VT1 and VT2 were used to delineate three intensity zones based on heart rate. During a 4 wk period in the preseason (N = 15), and two separate weeks late in the season (N = 11), all endurance and on-ball training sessions (preseason: N = 378, season: N= 78) were quantified using continuous heart rate registration and session rating of perceived exertion (sRPE). Three different methods were used to quantify the intensity distribution: time in zone, session goal and sRPE.Results:Intensity distributions across all sessions were similar when based on session goal or by sRPE. However, intensity distribution based on heart rate cut-offs from standardized testing was significantly different (time in zone).Conclusions:Our findings suggest that quantifying training intensity by using heart rate based total time in zone is not valid for describing the effective training intensity in soccer. The results also suggest that the daily training intensity distribution in this representative group of high level Norwegian soccer players is organized after a pattern where about the same numbers of training sessions are performed in low lactate, lactate threshold, and high intensity training zones.

Training-intensity Distribution on Middle- and Long-distance Runners: A Systematic Review

2021 ◽  
Author(s):  
Yuri Campos ◽  
Arturo Casado ◽  
João Guilherme Vieira ◽  
Miller Guimarães ◽  
Leandro Sant’Ana ◽  
...  
Keyword(s):  
Systematic Review ◽  
Intensity Distribution ◽  
Perceived Exertion ◽  
Endurance Performance ◽  
High Volume ◽  
Rating Of Perceived Exertion ◽  
Training Intensity ◽  
Distance Runners ◽  
Long Distance ◽  
Low Intensity

AbstractTraining-intensity distribution (TID) is considered the key factor to optimize performance in endurance sports. This systematic review aimed to: I) characterize the TID typically used by middle-and long-distance runners; II) compare the effect of different types of TID on endurance performance and its physiological determinants; III) determine the extent to which different TID quantification methods can calculate same TID outcomes from a given training program. The keywords and search strategy identified 20 articles in the research databases. These articles demonstrated differences in the quantification of the different training-intensity zones among quantification methods (i. e. session-rating of perceived exertion, heart rate, blood lactate, race pace, and running speed). The studies that used greater volumes of low-intensity training such as those characterized by pyramidal and polarized TID approaches, reported greater improvements in endurance performance than those which used a threshold TID. Thus, it seems that the combination of high-volume at low-intensity (≥ 70% of overall training volume) and low-volume at threshold and high-intensity interval training (≤ 30%) is necessary to optimize endurance training adaptations in middle-and long-distance runners. Moreover, monitoring training via multiple mechanisms that systematically encompasses objective and subjective TID quantification methods can help coaches/researches to make better decisions.

Lactate Threshold Prediction by Blood Glucose and Rating of Perceived Exertion in People with Type 2 Diabetes

2010 ◽  
Vol 111 (2) ◽  
pp. 365-378 ◽  
Author(s):  
Herbert Gustavo Simões ◽  
Wolysson Carvalho Hiyane ◽  
Ronaldo Esch Benford ◽  
Bibiano Madrid ◽  
Francisco Andriotti Prada ◽  
...  
Keyword(s):  
Type 2 Diabetes ◽  
Blood Glucose ◽  
Lactate Threshold ◽  
Perceived Exertion ◽  
Rating Of Perceived Exertion

Training Characteristics of Male and Female Professional Road Cyclists: A 4-Year Retrospective Analysis

2020 ◽  
Vol 15 (4) ◽  
pp. 534-540 ◽  
Author(s):  
Teun van Erp ◽  
Dajo Sanders ◽  
Jos J. de Koning
Keyword(s):  
Heart Rate ◽  
Retrospective Analysis ◽  
Perceived Exertion ◽  
Training Load ◽  
Rating Of Perceived Exertion ◽  
Training Intensity ◽  
Male And Female ◽  
Stress Score ◽  
Training Stress ◽  
Training Impulse

Purpose: To describe the training intensity and load characteristics of professional cyclists using a 4-year retrospective analysis. Particularly, this study aimed to describe the differences in training characteristics between men and women professional cyclists. Method: For 4 consecutive years, training data were collected from 20 male and 10 female professional cyclists. From those training sessions, heart rate, rating of perceived exertion, and power output (PO) were analyzed. Training intensity distribution as time spent in different heart rate and PO zones was quantified. Training load was calculated using different metrics such as Training Stress Score, training impulse, and session rating of perceived exertion. Standardized effect size is reported as Cohen’s d. Results: Small to large higher values were observed for distance, duration, kilojoules spent, and (relative) mean PO in men’s training (d = 0.44–1.98). Furthermore, men spent more time in low-intensity zones (ie, zones 1 and 2) compared with women. Trivial differences in training load (ie, Training Stress Score and training impulse) were observed between men’s and women’s training (d = 0.07–0.12). However, load values expressed per kilometer were moderately (d = 0.67–0.76) higher in women compared with men’s training. Conclusions: Substantial differences in training characteristics exist between male and female professional cyclists. Particularly, it seems that female professional cyclists compensate their lower training volume, with a higher training intensity, in comparison with male professional cyclists.

Heart-Rate Variability and Training-Intensity Distribution in Elite Rowers

2014 ◽  
Vol 9 (6) ◽  
pp. 1026-1032 ◽  
Author(s):  
Daniel J. Plews ◽  
Paul B. Laursen ◽  
Andrew E. Kilding ◽  
Martin Buchheit
Keyword(s):  
Heart Rate ◽  
Heart Rate Variability ◽  
Intensity Distribution ◽  
Lactate Threshold ◽  
Training Intensity ◽  
Training Time ◽  
Low Intensity ◽  
Elite Rowers ◽  
And Training ◽  
Intensity Training

Purpose:Elite endurance athletes may train in a polarized fashion, such that their training-intensity distribution preserves autonomic balance. However, field data supporting this are limited.Methods:The authors examined the relationship between heart-rate variability and training-intensity distribution in 9 elite rowers during the 26-wk build-up to the 2012 Olympic Games (2 won gold and 2 won bronze medals). Weekly averaged log-transformed square root of the mean sum of the squared differences between R-R intervals (Ln rMSSD) was examined, with respect to changes in total training time (TTT) and training time below the first lactate threshold (>LT1), above the second lactate threshold (LT2), and between LT1 and LT2 (LT1–LT2).Results:After substantial increases in training time in a particular training zone or load, standardized changes in Ln rMSSD were +0.13 (unclear) for TTT, +0.20 (51% chance increase) for time >LT1, –0.02 (trivial) for time LT1–LT2, and –0.20 (53% chance decrease) for time >LT2. Correlations (±90% confidence limits) for Ln rMSSD were small vs TTT (r = .37 ± .80), moderate vs time >LT1 (r = .43 ± .10), unclear vs LT1–LT2 (r = .01 ± .17), and small vs >LT2 (r = –.22 ± .50).Conclusion:These data provide supportive rationale for the polarized model of training, showing that training phases with increased time spent at high intensity suppress parasympathetic activity, while low-intensity training preserves and increases it. As such, periodized low-intensity training may be beneficial for optimal training programming.

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