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.

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 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.

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.

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.

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.

scholarly journals Consecutive Days of Prolonged Tennis Match Play: Performance, Physical, and Perceptual Responses in Trained Players

2015 ◽  
Vol 10 (7) ◽  
pp. 913-920 ◽  
Author(s):  
Danielle T. Gescheit ◽  
Stuart J. Cormack ◽  
Machar Reid ◽  
Rob Duffield
Keyword(s):  
Effect Size ◽  
Perceived Exertion ◽  
Voluntary Contraction ◽  
Rating Of Perceived Exertion ◽  
Perceptual Training ◽  
Match Play ◽  
Tennis Players ◽  
Playing Time ◽  
Distress Scale ◽  
Tennis Match

Purpose:To determine how consecutive days of prolonged tennis match play affect performance, physiological, and perceptual responses.Methods:Seven well-trained male tennis players completed 4-h tennis matches on 4 consecutive days. Pre- and postmatch measures involved tennis-specific (serve speed and accuracy), physical (20-m sprint, countermovement jump [CMJ], shoulder-rotation maximal voluntary contraction, isometric midthigh pull), perceptual (Training Distress Scale, soreness), and physiological (creatine kinase [CK]) responses. Activity profile was assessed by heart rate, 3D load (accumulated accelerations measured by triaxial accelerometers), and rating of perceived exertion (RPE). Statistical analysis compared within- and between-days values. Changes (± 90% confidence interval [CI]) ≥75% likely to exceed the smallest important effect size (0.2) were considered practically important.Results:3D load reduced on days 2 to 4 (mean effect size ± 90% CI –1.46 ± 0.40) and effective playing time reduced on days 3 to 4 (–0.37 ± 0.51) compared with day 1. RPE did not differ and total points played only declined on day 3 (–0.38 ± 1.02). Postmatch 20-m sprint (0.79 ± 0.77) and prematch CMJ (–0.43 ± 0.27) performance declined on days 2 to 4 compared with prematch day 1. Although serve velocity was maintained, compromised postmatch serve accuracy was evident compared with prematch day 1 (0.52 ± 0.58). CK increased each day, as did ratings of muscle soreness and fatigue.Conclusions:Players reduced external physical loads, through declines in movement, over 4 consecutive days of prolonged competitive tennis. This may be affected by tactical changes and pacing strategies. Alongside this, impairments in sprinting and jumping ability, perceptual and biochemical markers of muscle damage, and reduced mood states may be a function of neuromuscular and perceptual fatigue.

The Impact of 3 Different-Length Between-Matches Microcycles on Training Loads in Professional Rugby League Players

2015 ◽  
Vol 10 (6) ◽  
pp. 767-773 ◽  
Author(s):  
Alexandre Moreira ◽  
Tom Kempton ◽  
Marcelo Saldanha Aoki ◽  
Anita C. Sirotic ◽  
Aaron J. Coutts
Keyword(s):  
Perceived Exertion ◽  
Training Session ◽  
Rugby League ◽  
Training Load ◽  
Rating Of Perceived Exertion ◽  
Endurance Athletes ◽  
Moderate Intensity ◽  
High Intensity Zone ◽  
Competition Period ◽  
The Impact

Purpose: To examine the impact of varying between-matches microcycles on training characteristics (ie, intensity, duration, and load) in professional rugby league players and to report on match load related to these between-matches microcycles. Methods: Training-load data were collected during a 26-wk competition period of an entire season. Training load was measured using the session rating of perceived exertion (session-RPE) method for every training session and match from 44 professional rugby league players from the same National Rugby League team. Using the category-ratio 10 RPE scale, the training intensity was divided into 3 zones (low <4 AU, moderate ≥4-≤7 AU, and high >7 AU). Three different-length between-matches recovery microcycles were used for analysis: 5−6 d, 7−8 d, and 9−10 d. Results: A total of 3848 individual sessions were recorded. During the shorter-length between-matches microcycles (5−6 d), significantly lower training load was observed. No significant differences for subsequent match load or intensity were identified between the various match recovery periods. Overall, 16% of the training sessions were completed at the low-intensity zone, 61% at the moderate-intensity zone, and 23% at the high-intensity zone. Conclusions: The findings demonstrate that rugby league players undertake higher training load as the length of between-matches microcycles is increased. The majority of in-season training of professional rugby league players was at moderate intensity, and a polarized approach to training that has been reported in elite endurance athletes does not occur in professional rugby league.

scholarly journals The Quantification of Within-Week Session Intensity, Duration, and Intensity Distribution Across a Season in Australian Football Using the Session Rating of Perceived Exertion Method

2018 ◽  
Vol 13 (7) ◽  
pp. 940-946 ◽  
Author(s):  
Farhan Juhari ◽  
Dean Ritchie ◽  
Fergus O’Connor ◽  
Nathan Pitchford ◽  
Matthew Weston ◽  
...  
Keyword(s):  
Intensity Distribution ◽  
Mixed Models ◽  
High Intensity ◽  
Perceived Exertion ◽  
Linear Mixed Models ◽  
Training Session ◽  
Rating Of Perceived Exertion ◽  
Moderate Intensity ◽  
Low Intensity ◽  
Australian Football

Context: Team-sport training requires the daily manipulation of intensity, duration, and frequency, with preseason training focusing on meeting the demands of in-season competition and training on maintaining fitness. Purpose: To provide information about daily training in Australian football (AF), this study aimed to quantify session intensity, duration, and intensity distribution across different stages of an entire season. Methods: Intensity (session ratings of perceived exertion; CR-10 scale) and duration were collected from 45 professional male AF players for every training session and game. Each session’s rating of perceived exertion was categorized into a corresponding intensity zone, low (<4.0 arbitrary units), moderate (≥4.0 and <7.0), and high (≥7.0), to categorize session intensity. Linear mixed models were constructed to estimate session duration, intensity, and distribution between the 3 preseason and 4 in-season periods. Effects were assessed using linear mixed models and magnitude-based inferences. Results: The distribution of the mean session intensity across the season was 29% low intensity, 57% moderate intensity, and 14% high intensity. While 96% of games were high intensity, 44% and 49% of skills training sessions were low intensity and moderate intensity, respectively. Running had the highest proportion of high-intensity training sessions (27%). Preseason displayed higher training-session intensity (effect size [ES] = 0.29–0.91) and duration (ES = 0.33–1.44), while in-season game intensity (ES = 0.31–0.51) and duration (ES = 0.51–0.82) were higher. Conclusions: By using a cost-effective monitoring tool, this study provides information about the intensity, duration, and intensity distribution of all training types across different phases of a season, thus allowing a greater understanding of the training and competition demands of Australian footballers.

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