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25 Years of Session Rating of Perceived Exertion: Historical Perspective and Development
Abstract
The session rating of perceived exertion (sRPE) method was developed 25 years ago as a modification of the Borg concept of rating of perceived exertion (RPE), designed to estimate the intensity of an entire training session. It appears to be well accepted as a marker of the internal training load. Early studies demonstrated that sRPE correlated well with objective measures of internal training load, such as the percentage of heart rate reserve and blood lactate concentration. It has been shown to be useful in a wide variety of exercise activities ranging from aerobic to resistance to games. It has also been shown to be useful in populations ranging from patients to elite athletes. The sRPE is a reasonable measure of the average RPE acquired across an exercise session. Originally designed to be acquired ∼30 minutes after a training bout to prevent the terminal elements of an exercise session from unduly influencing the rating, sRPE has been shown to be temporally robust across periods ranging from 1 minute to 14 days following an exercise session. Within the training impulse concept, sRPE, or other indices derived from sRPE, has been shown to be able to account for both positive and negative training outcomes and has contributed to our understanding of how training is periodized to optimize training outcomes and to understand maladaptations such as overtraining syndrome. The sRPE as a method of monitoring training has the advantage of extreme simplicity. While it is not ideal for the precise recording of the details of the external training load, it has large advantages relative to evaluating the internal training load.
... Measures of sRPE have been shown to be a valid and reliable assessment of training load, and has been used previously in soccer (Impellizzeri et al., 2004). Another benefit of using sRPE to monitor training load is its affordability in comparison to other methods (Foster et al., 2021). ...
... Whilst sRPE, and sRPE-TL, have been proposed as suitable methods for measuring training load it has been suggested that, due to it being a global measure of load, it may lack the sensitivity to appreciate changes in load profiles. However, sRPE may be an attractive option to practitioners who do not have the financial budget to invest in technologies which allow the assessment of objective measures of load (Foster et al., 2021). Therefore, the broad aim of the subsequent experimental portion of this thesis is to better understand the relationships between objective and subjective measures of load in professional youth soccer players within the specific context of a professional soccer club. ...
... Despite this, little quantitative research has been carried out comparing youth and senior load profiles. Whilst sRPE-TL has been shown to be a valid, reliable, and costeffective measure of monitoring training load (Foster et al., 2021, Impellizzeri et al., 2004, its ability to detect changes in load across transitions is unclear. Considering this, the aim of this thesis is firstly to quantify and describe the relationships between subjective and objective training load measures to assess their suitability for monitoring load. ...
... Likewise, because it presents a high correspondence, RPE is used as a complementary or alternative measurement of physiological parameters (16), including maximum oxygen uptake (VO 2max ) (17), blood lactate (BL) (18), ventilatory thresholds, and heart rate (HR) (19). In addition, RPE allows quantification of exercise load (20), becoming an alternative to measure fatigue levels (21) and the state of post-exertion recovery (22). ...
... Therefore, in light of the results, it is possible to infer that supplementation with 45 mg BA·kg -1 increases physical performance in middle-distance athletes, allowing better performance in HIDZ. 20 Concerning the distance obtained in the 6-MRT by the three intervention groups, "excellent" performance was observed in physically active males between 18-25 years of age (32). From these results, the high dose of BA (45 mg BA·kg -1 ) stands out, evidencing the highest performance in the 6-MRT (1,861.8 ...
... Consequently, it has been shown that RPE can be a helpful tool to prescribe and control training intensity practically and economically since it reliably represents physiological parameters involved in exercise (16,46). Furthermore, RPE allows the quantification of exercise load (19,20), becoming an alternative to measure fatigue levels (21) and the state of post-exertion recovery (22). 23 ...
Background:
the use of beta-alanine (BA) to increase physical performance in the heavy-intensity domain zone (HIDZ) is widely documented. However, the effect of this amino acid on the post-exertion rating of perceived exertion (RPE), heart rate (HR), and blood lactate (BL) is still uncertain.
Objectives:
a) to determine the effect of acute BA supplementation on post-exertion RPE, HR, and BL in middle-distance athletes; and b) to determine the effect of acute BA supplementation on physical performance on the 6-minute race test (6-MRT).
Material and methods:
the study included 12 male middle-distance athletes. The de-sign was quasi-experimental, intrasubject, double-blind & crossover. It had two treat-ments (low-dose BA [30 mg·kg-1] and high-dose BA [45 mg·kg-1]) and a placebo, 72 hours apart. The effect of BA was evaluated at the end of the 6-MRT and post-exertion. The variables were RPE, HR and BL, and 6-MRT (m) distance. The statistical analysis included a repeated-measures ANOVA (p < 0.05).
Results:
the analysis evidenced no significant differences at the end of 6-MRT for all variables (p ˃ 0.05). However, both doses of BA generated a lower post-exertion RPE. The high dose of BA caused significant increases in post-exertion BL (p ˂ 0.05).
Conclusion:
acute supplementation with BA generated a lower post-exertion RPE. This decrease in RPE and the post-exertion BL increase could be related to an increase in physical performance in HIDZ.
... Throughout the season, the soccer player was monitored by the session rating of perceived exertion (sRPE) [25,26], with the minutes completed in every session and during matches also recorded. The daily TL was subsequently determined (TL [AU] = sRPE × time) [25,26]. ...
... Throughout the season, the soccer player was monitored by the session rating of perceived exertion (sRPE) [25,26], with the minutes completed in every session and during matches also recorded. The daily TL was subsequently determined (TL [AU] = sRPE × time) [25,26]. In addition, TL was analysed by using coupled ACWR as rolling averages by dividing the TL of the last week by the average of the TL of the 4 previous weeks (coupled ACWR = 1:4), and also by using EWMA [21,26]. ...
... In the current study, acute fatigue emerges as an important factor that may be related to the EAMC episode. When the soccer player returned to the normal training process after the medical department period, he exhibited several times an ACWR (both rolling averages and EWMA) above the threshold of 1.25, which is considered to be related to an augmented injury risk [25]. The main factor contributing to this value was the absence of training activities during the period of rehabilitation from the injury, when he showed a low chronic workload. ...
Purpose. Exercise-associated muscle cramps (EAMC) are characterized by intense pain and involuntary contractions of a single muscle or muscle group. While EAMCs may occur during and after exercise, their precise aetiology remains unknown. However, there are some potential risk factors, as the workload of physical training previously performed. The purpose of this case report was to evaluate the acute:chronic workload ratio (ACWR) and creatine kinase (CK) concentrations in a professional soccer player to verify the potential influence of recent training history on an extreme EAMC episode and subsequent muscle damage. Methods. A 21-year-old professional soccer player (body fat: 6.5%; body mass: 76 kg; height: 1.76 m) who experienced an extreme EAMC episode after the end of an official soccer match was monitored with session rating of perceived exertion before and after the EAMC episode and with post-match CK concentrations. Results. ACWR revealed several spikes on the days before the match, with the highest one observed on the match day. The CK concentrations recorded 35 and 53 hours after the EAMC episode were 262% and 182% higher, respectively, than the maximal CK concentrations recorded during the season (703 U/l). Conclusions. This case report illustrates, for the first time, how workload spikes, monitored with ACWR, preceded an extreme EAMC episode that was followed by an exacerbated muscle damage response. Some insights are provided in this case report for practitioners working in professional soccer to help them better manage similar cases.
... Foster et al. [9] recommend keeping it simple, which may be the most crucial element of training monitoring. Thus, the use of RPE and sRPE is considered an easy-to-use, non-invasive, accessible, valid, and reliable method for coaches to assess the training load applied to athletes daily, improving the control of training variables [2,[10][11][12][13]. ...
... The sRPE method uses an objective measure of training load (time) interacting with a subjective one (RPE), thus giving a training load index in arbitrary units (a.u.) [2,14] extensively accepted as a marker of the internal training load [13]. In addition, the sRPE has been used to assess the agreement between coach and athlete for load planned and perceived [5]. ...
... Coaches should be aware that athletes could interpret the same training differently. A simple and subjective method to quantify the internal load of the designed and executed training programs could serve as a tool to optimize the training process [9,13]. Therefore, this systematic review and meta-analysis of the literature aimed to investigate whether there are differences between the training load perceived by athletes and that prescribed/intended/observed by coaches. ...
Background
Rating of perceived exertion (RPE) and session RPE (sRPE) has been widely used to verify the internal load in athletes. Understanding the agreement between the training load prescribed by coaches and that perceived by athletes is a topic of great interest in sport science.
Objective
This systematic review and meta-analysis aimed to investigate differences between the training/competition load perceived by athletes and prescribed/intended/observed by coaches.
Methods
A literature search (September 2020 and updated in November 2021) was conducted using PubMed, Web of Science, Embase, and SPORTDiscus databases. The protocol was registered in the Open Science Framework (osf.io/wna4x). Studies should include athletes and coaches of any sex, age, or level of experience. The studies should present outcomes related to the RPE or sRPE for any scale considering overall training/competition sessions (physical, strength, tactical, technical, games) and/or classified into three effort categories: easy, moderate, and hard.
Results
Twenty-seven studies were included in the meta-analysis. No difference was found between coaches and athletes for overall RPE (SMD = 0.19, P = 0.10) and overall sRPE (SMD = 0.05, P = 0.75). There was a difference for easy RPE (SMD = − 0.44, small effect size, P = 0.04) and easy sRPE (SMD = − 0.54, moderate effect size, P = 0.04). No differences were found for moderate RPE (SMD = 0.05, P = 0.74) and hard RPE (SMD = 0.41, P = 0.18). No difference was found for moderate (SMD = -0.15, P = 0.56) and hard (SMD = 0.20, P = 0.43) sRPE.
Conclusion
There is an agreement between coaches and athletes about overall RPE and sRPE, and RPE and sRPE into two effort categories (moderate and hard). However, there were disagreements in RPE and sRPE for easy effort category. Thus, despite a small disagreement, the use of these tools seems to be adequate for training monitoring.
... All exercise was recorded in Training Peaks software (Train-ingPeaks, Louisville, CO, USA). Each session was noted for modality (e.g., bike, run, swim), duration, and session rating of perceived exertion (sRPE [14]) using the Borg CR100 ® scale, which offers additional precision compared with the CR10 scale [10]. Participants were instructed to rate their perceived effort for the whole training session within 1-h of exercise, although sRPE scores are temporally robust from minutes to days following a bout of exercise [14]. ...
... Each session was noted for modality (e.g., bike, run, swim), duration, and session rating of perceived exertion (sRPE [14]) using the Borg CR100 ® scale, which offers additional precision compared with the CR10 scale [10]. Participants were instructed to rate their perceived effort for the whole training session within 1-h of exercise, although sRPE scores are temporally robust from minutes to days following a bout of exercise [14]. ...
Purpose
Research findings are typically reported at the group level but applied to individuals. However, an emerging issue in sports science concerns nonergodicity—whereby group-level data cannot be generalized to individuals. The purpose of this study was to determine if the relationship between daily carbohydrate intake and perceived recovery status displays nonergodicity.
Methods
Fifty-five endurance athletes recorded daily measures of self-selected dietary intake, training, sleep, and subjective wellbeing for 12 weeks. We constructed linear models to measure the influence of daily carbohydrate intake on perceived recovery status while accounting for training load, sleep duration, sleep quality, and muscle soreness. Using linear model coefficients for carbohydrate intake we tested whether the distributions (mean and SD) differed at the group and individual levels (indicating nonergodicity). Additionally, a decision tree was created to explore factors that could provide an indication of an individual athlete’s relationship between carbohydrate intake and perceived recovery status.
Results
Mean values were not different between group- and individual-level analyses, but SDs at the individual level were ~2.4 times larger than at the group level, indicating nonergodicity. Model coefficients for carbohydrate intake were negative for three participants, positive for four participants, and non-significant for 37 participants. The κ value measuring accuracy of the decision tree was 0.52, indicating moderate prediction accuracy.
Conclusion
For most individuals, carbohydrate intake did not influence recovery status. However, the influence of dietary carbohydrate intake on daily recovery differs at the group and individual level. Therefore, practical recommendations should be based on individual-level analysis.
... Training impulse (TRIMP) and rating of perceived exertion (RPE) [12] are currently the most common methods to evaluate internal loads. TRIMP was first produced by Banister et al. [13] in 1975 and the Banister's TRIMP [13] was calculated by training time and training intensity based on heart rate reserve. ...
... The MINORS is suitable for single-arm tests and is used to access the methodological quality of criterion-related validity studies. The total score for each study was used to rank the risk of bias as low (13)(14)(15)(16), moderate (9)(10)(11)(12), or high (0-8). ...
Background The objective of this study was to establish the criterion-related validity of the session-rating of perceived exertion (s-RPE) method in adolescent athletes.
Methods According to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA 2020) guidelines, a meta-analysis (PROSPERO ID: CRD42022373126) was performed using Stata 15.1 software. Eight data�bases using the following terms: (‘s-RPE’ OR ‘Rating Perceived Exertion session’ OR ‘RPE session’ OR ‘RPE’ OR ‘Rate of Perceived Exertion’ OR ‘Rated of Perceived Exertion’) AND (‘Adolescen*’ OR ‘Youth*’ OR ‘Teen*’) AND (‘validity’ OR ‘cor�relation’ OR ‘concurrent validity’) were searched up to 2022. Articles meeting the inclusion criteria were screened and adopted the “Methodological Index for Non-Randomized Studies (MINORS)” to evaluate the risk of bias.
Results An initial 1798 studies using the s-RPE method were identifed and fnally, a total of 16 studies were included for further analysis. The relationship between assessment instruments CR-10 or CR-100 modifed methods of s-RPE and the heart rate measures of these selected studies were calculated using correlation coefcient (r values) and Fish�er’s z-score. A strong to very strong correlation between s-RPE and HR was observed (overall: r=0.74; CR-10: r=0.69; CR-100: r=0.80). CR-100 scale (Fisher’s z=1.09) was shown to have a higher criterion validity than that of the CR-10
scale (Fisher’s z=0.85).
Conclusion Preliminary fndings showed that s-RPE using either CR-10 or CR-100 scales can be used "stand�alone" for monitoring internal training load for children and adolescent athletes. Future studies should focus on whether CR-100 could better perform than CR-10 for junior and children athletes in diferent age groups
and sports as well as the causes leading to potential scoring biases.
... This method helped minimize factors that may influence a player's RPE score, such as peer pressure and replicating other player's ratings. 28,29 Each individual RPE value was multiplied by the session duration to generate a session RPE (sRPE) value. 28,29 The total weekly ITL (wITL) consisted of the sum of the ITLs of all training sessions during that week. ...
... 28,29 Each individual RPE value was multiplied by the session duration to generate a session RPE (sRPE) value. 28,29 The total weekly ITL (wITL) consisted of the sum of the ITLs of all training sessions during that week. Monotony (calculated as daily load divided by the daily load SD) and strain (calculated as the product of monotony and load) were also obtained. ...
Purpose:
Most high-intensity bouts of exercise in volleyball consist of jumping activities, which are responsible for inducing muscle damage, high levels of fatigue, and muscle soreness. Therefore, the aim of the current study was to quantify and analyze the training loads, neuromuscular fatigue, and perceptual well-being of a 5-week in-season mesocycle carried out by a professional male volleyball team.
Methods:
Fifteen volleyball players (age 28.51 [5.39] y; height 193.19 [9.87] cm; body mass 88.46 [13.18] kg) participated in this study. Internal training load assessed through the rating of perceived exertion, external training load (ETL; evaluated using an inertial motion unit), countermovement jump (CMJ) height and peak power, and wellness questionnaire responses were obtained from all athletes.
Results:
Results indicated a progressive decrease of the internal training load during the week and by the undulatory pattern of the ETL during the microcycles. Moreover, training monotony increased across the microcycles and was negatively associated with CMJ peak power (r = -.681, P < .05). Finally, sleep quality (ρ = -.747, P < .01) and fatigue (ρ = -.789, P < .01) were negatively associated with weekly ETL.
Conclusions:
This study indicated that sleep quality and fatigue were negatively associated with weekly ETL. Therefore, decreases in weekly ETL might be needed to improve sleep quality and decrease fatigue in professional volleyball players. Plus, higher values of training monotony were associated with lower values of CMJ peak power. Consequently, avoiding training monotony might be important to improve jumping performance in professional volleyball athletes.
... Typically, RPE scores are obtained using the Borg's 6-20 RPE scale (3) or the modified Borg's category-ratio 10-point scale (CR10 (14)), which can be used interchangeably (1). Besides its simplicity, the session RPE (i.e., RPE based on CR10 3 duration) is considered to be a very useful tool for monitoring internal training load because it reflects periodization of internal training load as well as positive and negative training outcomes (15). Additional information can be derived from complementary indices that are calculated from session RPE scores, such as monotony and strain, reflecting day-to-day training variability and total stress on the body (17). ...
... In the first week, subjects performed a maximal incremental ramp test to voluntary exhaustion on an electromagnetically braked cycle ergometer (Excalibur or Excalibur Sport, Lode, Groningen, The Netherlands). After pedaling at 0 W for one minute, power output was increased continuously by 15 . During the test, heart rate was continuously monitored using a heart rate sensor chest strap (H9, Polar Electro Oy, Finland). ...
van der Zwaard, S, Hooft Graafland, F, van Middelkoop, C, and Lintmeijer, LL. Validity and reliability of facial rating of perceived exertion scales for training load monitoring. J Strength Cond Res XX(X): 000-000, 2022-Rating of perceived exertion (RPE) is often used by coaches and athletes to indicate exercise intensity, which facilitates training load monitoring and prescription. Although RPE is typically measured using the Borg's category-ratio 10-point scale (CR10), digital sports platforms have recently started to incorporate facial RPE scales, which potentially have a better user experience. The aim of this study was to evaluate the validity and reliability of a 5-point facial RPE scale (FCR5) and a 10-point facial RPE scale (FCR10), using the CR10 as a golden standard and to assess their use for training load monitoring. Forty-nine subjects were grouped into 17 untrained (UT), 19 recreationally trained (RT), and 13 trained (T) individuals Subjects completed 9 randomly ordered home-based workout sessions (3 intensities × 3 RPE scales) on the Fitchannel.com platform. Heart rate was monitored throughout the workouts. Subjects performed 3 additional workouts to assess reliability. Validity and reliability of both facial RPE scales were low in UT subjects (intraclass correlation [ICC] ≤ 0.44, p ≤ 0.06 and ICC ≤ 0.43, p ≥ 0.09). In RT and T subjects, validity was moderate for FCR5 (ICC ≥ 0.72, p < 0.001) and good for FCR10 (ICC ≥ 0.80, p < 0.001). Reliability for these groups was rather poor for FCR5 (ICC = 0.51, p = 0.006) and moderate for FCR10 (ICC = 0.74, p < 0.001), but it was excellent for CR10 (ICC = 0.92, p < 0.001). In RT and T subjects, session RPE scores were also strongly related to Edward's training impulse scores (r ≥ 0.70, p < 0.001). User experience was best supported by the FCR10 scale. In conclusion, researchers, coaches, strength and conditioning professionals, and digital sports platforms are encouraged to incorporate the valid and reliable FCR10 and not FCR5 to assess perceived exertion and internal training load of recreationally trained and trained individuals.
... All exercise was recorded in Training Peaks software (TrainingPeaks, Louisville, CO, USA). Each session was noted for modality (e.g., bike, run, swim), duration, and session rating of perceived exertion (sRPE (Foster et al., 2021)) using the Borg CR100® scale, which offers additional precision compared with the CR10 scale (Clemente et al., 2019). Participants were instructed to rate their perceived effort for the whole training session within 1-h of exercise, although sRPE scores are temporally robust from minutes to days following a bout of exercise (Foster et al., 2021). ...
... Each session was noted for modality (e.g., bike, run, swim), duration, and session rating of perceived exertion (sRPE (Foster et al., 2021)) using the Borg CR100® scale, which offers additional precision compared with the CR10 scale (Clemente et al., 2019). Participants were instructed to rate their perceived effort for the whole training session within 1-h of exercise, although sRPE scores are temporally robust from minutes to days following a bout of exercise (Foster et al., 2021). ...
... De plus, la fatigue perçue à la fin des tâches sur ordinateur est significativement plus faible que la fatigue perçue après le protocole de badminton. Or, les mesures de fatigue perçue sont en lien étroit avec l'intensité de l'exercice (Alder et al., 2019 ;Foster et al., 2021 ;Van Cutsem et al., 2017). On peut donc remettre en question l'état de fatigue des participants au moment des tâches sur ordinateur. ...
... Girard et Millet (2009) montrent une moyenne entre 75 et 90%FCMax. Les résultats des mesures auto rapportées des échelles numériques sont en adéquation avec la littérature montrant un lien étroit entre la fatigue perçue / l'effort perçu et l'intensité de l'exercice(Alder et al., 2019 ;Foster et al., 2021 ;Van Cutsem et al., 2017). Ainsi, nos résultats sont en adéquation avec certaines études de la littérature et nous permettent de vérifier notre procédure expérimentale : le protocole de fatigue induit bien de la fatigue mesurée à partir de ces trois marqueurs d'intensité et de fatigue. ...
Among the sensory information used by a player in a net-mediated opposition sport, visual information represents the most used information. Collecting relevant visual information under temporal pressure is one of the determinants of badminton performance. Anticipation, as judgment and attention, as perceptivo-cognitive skill, is defined from the acquisition of visual information. Anticipation involves visual information pick-up and attention allows this information pick-up. Fatigue, as an inherent constraint in practice, can affect anticipation, attention, visual search and performance in sport. However, the links between these variables remain poorly described and understood in real badminton settings. Thus, first scientific aim of this thesis is, from the expertise model, to bring descriptive and explanatory knowledge on anticipation judgment from four determinants: motor, visual, attentional and knowledge determinants for badminton players in real game settings. The second goal is to assess effects of fatigue on this judgment. The main results of this thesis show a difference in anticipation/reaction motor and visual responses according to the level of expertise (Study 1). Regarding effects of fatigue, motor and visual responses are little impacted by fatigue for novice players (Study 2) but are impacted for expert players (Study 3). More specifically, in a defensive force ratio, fatigue impacts gaze and motor behaviors (Study 4). These first results in ecological situations of badminton allow descriptive and explanatory contribution according to two levels of expertise (beginners and high-level athletes) and an understanding of the fatigue constraint on anticipation judgment. Finally, the understanding of attentional and anticipation mechanisms in a controlled situation shows an effect of expertise and fatigue (Study 5). This thesis project opens up practical perspectives of training and perspectives of complementary research on the understanding of the mechanisms of anticipation observed from the determinants of the anticipation judgment. Indeed, the contributions of this project allow an accessible rendering of knowledge for educational purposes in order to optimize the training programs (written feedback, instructions, training situations) and new research questions around the neuronal mechanisms and the fatigue-performance link involved in the anticipation judgment in situations and around factors (commitment, type of games) that can impact this judgment.
Keywords: visual perception, information pick-up, visual search, attention.
... Saw et al. [18] showed through a systematic review that self-reported measures may report acute and chronic training loads with superior sensitivity and consistency than common objective measures (e.g., blood markers, oxygen consumption, heart rate). In fact, subjective monitoring is sensitive to change, not only related to training loads [90][91][92][93], but also to overtraining status [18,94,95], injuries [96][97][98], illness [99,100] or even the rhythms in the earth's magnetic field [101]. In addition, it may also provide relevant information for predicting individuals' health-related behaviour and decision-making [102] or performance status [103,104]. ...
... Despite the increasing availability of high-tech-based objective tools, the use of subjective monitoring has recently increased in specific sport contexts [74,108]. Typically, the RPE remains one of the most popular objective measures of subjective information in sport (e.g., in professional football, [109]) [94,110,111]. Other measures to evaluate constructs such as fatigue, pain or internal training loads have also been validated [73,92,[112][113][114][115]. ...
Current trends in sports monitoring are characterized by the massive collection of tech-based biomechanical, physiological and performance data, integrated through mathematical algorithms. However, the application of algorithms, predicated on mechanistic assumptions of how athletes operate, cannot capture, assess and adequately promote athletes’ health and performance. The objective of this paper is to reorient the current integrative proposals of sports monitoring by re-conceptualizing athletes as complex adaptive systems (CAS). CAS contain higher-order perceptual units that provide continuous and multilevel integrated information about performer–environment interactions. Such integrative properties offer exceptional possibilities of subjective monitoring for outperforming any objective monitoring system. Future research should investigate how to enhance this human potential to contribute further to athletes’ health and performance. This line of argument is not intended to advocate for the elimination of objective assessments, but to highlight the integrative possibilities of subjective monitoring.
... The session rating of perceived exertion (sRPE) is a scale used to control the perceived training load (Freitas et al., 2014;Hernández-Cruz et al., 2017). This scale has been suggested as a non-expensive and effective tool for controlling training load in an easier and less invasive way, being widely used to assess changes in team and individual sports, both in training and in competition (Foster et al., 2021;Halson, 2014). ...
Objectives. – The aim of the study was to analyze the behavior of the modified total quality recovery (TQR) scale during four microcycles of accumulation in volleyball players and its relationship with physiological markers as heart rate variability (HRV) and training impulse (TRIMP), as well as load perception by the session rating of perceived exertion (s-RPE), and perceived recovery-stress state using the RESTQ-Sport questionnaire. Equipment and methods. – Seven female players of a national volleyball team (age: 24.26 ± 3.37 years; weight: 71.63 ± 6.84 kg; height: 176.97 ± 8.04 cm; % fat: 32.64 ± 1.57%) were evaluated during a pre-competitive camp. HRV, TRIMP, TQR scale, and the s-RPE were assessed daily. While the RESTQ-Sport was applied at the beginning and at the end of the concentration camp. The Spearman correlation for all variables, as well as Friedman Test for HRV, TRIMP, TQR and S-RPE and Wilcoxon test for RESTQ-Sport were performed. Furthermore, the smallest worthwhile change (SWC) was applied to identify the magnitudes of change in the intra-subject data. Results. – The TQR scale showed significant correlations (p < .05) with HRV parameters (LnrMSSD and Stress Score), S-RPE and RESTQ-Sport dimensions. Conclusion. – The TQR scale shows to be sensitivity to microcycles of accumulation in female volleyball players. In addition, the study proves the TQR concurrent validity by correlating with different physiological and psychological parameters for monitoring load and recovery. Keywords: assessment; recovery; sports performance; volleyball; internal training load
... Thus, an equilibrium between simplicity and complexity should be warranted to allow the correct flux of information for appropriate diagnosis and decision making. For instance, while the session RPE (sRPE) is a valid and simple monitoring tool including both the volume and intensity in a single metric, 18 this simplicity would not allow the differentiation of what physiological system is more taxed (eg, cardiometabolic vs neuromuscular). Thus, depending on specific requirements of each sport, additional measures are needed for fine-tuning the athlete's training adaptations. ...
Purpose:
Monitoring is a fundamental part of the training process to guarantee that the programmed training loads are executed by athletes and result in the intended adaptations and enhanced performance. A number of monitoring tools have emerged during the last century in sport. These tools capture different facets (eg, psychophysiological, physical, biomechanical) of acute training bouts and chronic adaptations while presenting specific advantages and limitations. Therefore, there is a need to identify what tools are more efficient in each sport context for better monitoring of training process.
Methods and results:
We present and discuss the fine-tuning approach for training monitoring, which consists of identifying and combining the best monitoring tools with experts' knowledge in different sport settings, designed to improve (1) the control of actual training loads and (2) understanding of athletes' training adaptations. Instead of using single-tool approaches or merely subjective decision making, the identification of the best combination of monitoring tools to assist experts' decisions in each specific context (ie, triangulation) is necessary to better understand the link between acute and chronic adaptations and their impact on health and performance. Future studies should elaborate on the identification of the best combination of monitoring tools for each specific sport setting.
Conclusion:
The fine-tuning monitoring approach requires the simultaneous use of several valid and practical tools, instead of a single tool, to improve the effectiveness of monitoring practices when added to experts' knowledge.
... Kini, model manajemen persediaan tradisional sudah dianggap tertinggal apabila dibandingkan dengan manajemen persediaan di tengah era informasi karena kurangnya konsep rantai pasok (Foster et al., 2021). Kehadiran ERP yang berperan dalam memberikan informasi mengenai manajemen dan pengendalian persediaan merupakan cara yang efektif untuk memecahkan masalah model manajemen persediaan tradisional (Zhao & Tu, 2021). ...
Penelitian ini bertujuan untuk menganalisis supply chain management berbasis ERP pada persediaan Minimarket Lok Jaya. Adapun teknik analisis data yang digunakan dalam penelitian ini berupa teknik analisis data kualitatif. Hasil penelitian menunjukkan bahwa metode pengendalian persediaan yang diterapkan oleh pemilik usaha Minimarket Lok Jaya adalah perpetual inventory system. Kegiatan pengendalian persediaan yang dilakukan oleh pemilik usaha tersebut dapat melacak inventaris secara real time apabila dikelola dengan baik. Namun, jenis pengendalian persediaan yang diterapkan membutuhkan fokus, waktu, dan tenaga dalam jumlah yang besar. Oleh karena itu, tim penulis menyarankan pemilik Minimarket Lok Jaya untuk menerapkan metode EOQ agar dapat mengetahui kuantitas jumlah dan waktu yang tepat dalam melaksanakan pesanan sehingga pemantauan tidak harus dilakukan setiap hari untuk memastikan ketersediaan stok.
... Athlete A3 reported RPE consistently lower than their peers; athlete A2 mainly rated sessions as moderate to hard; finally, athlete A1 reported RPE across the whole scale of values available. These individual tendencies have been observed in previous athlete cohorts as well (34), and could be explained by environmental factors, accumulated fatigue that propagates from day to day or even athletes' interpretation of the scale (35). In contrast, IMU playerload showed no significant differences across participants (p = 0.81). ...
INTRODUCTION: Measurement of training in water polo goalkeepers has focused first on psycho-physiological variables, but also on external volume estimated with wearable sensors. However, there are limited studies exploring training monitoring in water polo goalkeepers longitudinally.
METHODS: Three female senior national team goalkeepers participated in this study from May to August 2021. Internal loads were defined using session rating of perceived exertion (sRPE). Tri-axial accelerations and angular velocities were measured with an inertial measurement unit (IMU) placed on the lower back to measure external loads. Relationships between self-reported and IMU-derived metrics were explored using Spearman correlations. Two-way ANOVAs were used to assess differences between session types and between athletes.
RESULTS: In total, 247 sessions were collected (159 practices, 67 matches and 21 game warm up), with 155 sessions having complete data. IMU metrics, such as number of kicks, number of jumps or player-load showed high correlation with each other (rho=0.80 to 0.88). There was also a moderate correlation (rho=0.47, 95%CI=0.33 to 0.58) between sRPE and player-load measured with the IMU. ANOVA tests showed that there were significant differences between athletes for sRPE (p<0.01) but not for player load (p=0.47). There were no interactions between athletes and training types, except for index score (p<0.01).
CONCLUSIONS: This study shows that monitoring of training loads can be performed successfully in water polo goalkeepers using a combination of self-reported and IMU measures. Self-reported outcomes can be expected to vary significantly across athletes within the same session, while IMU metrics vary across training situations. Finally, coaches should be mindful of missing data, as they can skew the interpretation of training loads.
... The exposure to acceleration and deceleration efforts was significantly lower during LSG formats compared to Possession 6vs4 (p < 0.01, moderate). In addition to the use of external load parameters, practitioners can assess the players' internal load using an RPE scale, which is cheap and easy to implement (28,29). RPE enables for a subjective quantification of the overall load that the players have perceived during the sided-games (7,16). ...
This study aims to quantify and compare the external and internal training load demands of sided-game drills in professional team players during the competitive season. Twenty-four male professional soccer players of the same club were enrolled in this study. Drills were categorized as large-sided games (LSG): 10vs10 (84 × 60 m or 72 × 60 m), Hexagon possession 9vs9 + 3 (36 × 48 m), Possession gate 8vs8 + 2 (36 × 44 m), Possession 7vs7 + 3 (30 × 32 m) or as Small-sided games (SSG): 6vs6 (48 × 42 m), and Possession 6vs4 (30 × 60 m). A total of 7 drills and 279 individual data points were included in this analysis. Distance covered, high-speed running (HSR), and sprinting distance were all calculated in meters per minute (m.min−1) while total accelerations (>3 m.s−2) and total decelerations (− < 3 m.s−2) were calculated in number of actions per minute (n.min−1). All external load was measured with global navigation satellite systems (GNSS) STATSports Apex units. Players’ internal load was quantified using their rating of perceived exertion (RPE). We found that distance covered (p < 0.01, large), HSR (p < 0.01, large), and sprinting distance (p < 0.01, large) changed between drills (e.g., greater in LSG formats), acceleration (p < 0.01, large) and deceleration (p < 0.01, large) demands were greater in smaller formats (e.g., SSG 6vs6, and Possession 6vs4), while RPE was lower in the Possession gate 8vs8 + 2 format (p < 0.01, large). This study found that sided-games can replicate and sometimes exceed some match-specific intensity parameters, however, HSR and sprinting were consistently lower compared to official matches.
... Training impulse (TRIMP) and rating of perceived exertion (RPE) (12) are currently the most common methods to evaluate internal loads. TRIMP was rst produced by Banister et al. (13) in 1975 and the Banister's TRIMP (13) was calculated by training time and training intensity based on heart rate reserve. ...
Background: The objective of this study was to establish the criterion-related validity of the session-rating of perceived exertion (s-RPE) method in adolescent athletes.
Methods: According to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA 2020) guidelines, a meta-analysis (PROSPERO ID: CRD42022373126) was performed using Stata 15.1 software. Eight databases using the following terms: (‘s-RPE’ OR ‘Rating Perceived Exertion session’ OR ‘RPE session’ OR ‘RPE’ OR ‘Rate of Perceived Exertion’ OR ‘Rated of Perceived Exertion’) AND (‘Adolescen*’ OR ‘Youth*’ OR ‘Teen*’) AND (‘validity’ OR ‘correlation’ OR ‘concurrent validity’) were searched up to 2022. Articles meeting the inclusion criteria were screened and adopted the “Methodological Index for Non-Randomized Studies (MINORS)” to evaluate the risk of bias.
Results: An initial 1798 studies using the s-RPE method were identified and finally, a total of 16 studies were included for further analysis. The relationship between assessment instruments CR-10 or CR-100 modified methods of s-RPE and the heart rate measures of these selected studies were calculated using correlation coefficient (r values) and Fisher’s z-score. A strong to very strong correlation between s-RPE and HR was observed (overall: r=0.74; CR-10: r=0.69; CR-100: r=0.80). CR-100 scale (Fisher’s z=1.09) was shown to have a higher criterion validity than that of the CR-10 scale (Fisher’s z=0.85).
Conclusion: Preliminary findings showed that s-RPE using either CR-10 or CR-100 scales can be used "stand-alone" for monitoring internal training load for children and adolescent athletes. Future studies should focus on whether CR-100 could better perform than CR-10 for junior and children athletes in different age groups and sports as well as the causes leading to potential scoring biases.
... According to the relevant literature, there is not a single or gold standard method to measure the external and internal loads [16]. Although the importance of using other subjective measures cannot be underestimated, one of the most used methods to assess the internal load is through the rating of perceived exertion (RPE) [10,17]. Based on the RPE measure, Foster et al. [18] developed the session-RPE method, which considers the intensity and duration of the training/competition sessions to calculate the training and competition loads [19]. ...
This study aimed to investigate the effects of playing position and contextual factors (match outcome, final score difference, match location, travel duration, number of scored and conceded goals) on the internal match load, players’ perceived recovery and players’ well-being. The session-RPE (s-RPE), Perceived Recovery Scale (PRS) and Hooper Index (HI) of 17 male elite water polo players were monitored during all matches (regular season and play-out) of the 2021/22 Italian Serie A1 championship. Three separate, mixed linear models for repeated measures showed significant main effects: drawn compared to won matches led to higher s-RPE values (mean ± SE = 277 ± 17.6 vs. 237.3 ± 20.6), while longer travel duration (estimate = −0.148) and goals scored (estimate = −3.598) led to lower s-RPE values; balanced compared to unbalanced matches led to higher PRS values (mean ± SE = 6.8 ± 0.3 vs. 5.1 ± 0.4), while playing time (estimate = −0.041) and goals scored (estimate = −0.180) led to lower PRS values; higher scores of the HI were registered for regular season compared to the play-out (mean ± SE = 15.6 ± 0.9 vs. 13.5 ± 0.8). This study marks the importance of ecological and non-invasive monitoring tools to assess internal match load, recovery and the well-being of elite water polo players.
... One way of understanding the adaptive response to training is using the 'training impulse' (TRIMP) model of Banister et al. [3], who discovered that exercise training produces changes in both fitness and fatigue [4,5]. The TRIMP model was originally designed to work using training heart rate (HR) and time, but more recent studies have shown that it could work using RPE and time, resulting in the session RPE (sRPE) [6][7][8][9]. More recent studies have suggested that it could be understood using responses during the warm-up for subsequent exercise bouts [10], questionnaires [11], HR variability (HRV) [12][13][14], or training intensity distribution [15][16][17]. ...
In the first volume of “Exercise Evaluation and Prescription” in the Journal of Functional Morphology and Kinesiology [...]
... Internal load (IL) data were obtained through the RPE-based method (arbitrary units, au) [28,29] at 10-30 minutes following every handball training session and game. ...
In this research, we aimed to (1) describe the differences in internal and external load between playing positions and (2) characterize the training demands of the days before competitive events for professional handball players. Fifteen players (5 wings, 2 centre backs, 4 backs, and 2 pivots) were equipped with a local positioning system device during training and 11 official matches. External (total distance, high-speed running, player load) and internal loads (rating of perceived exertion) were computed. Substantial differences were recorded between the external load variables depending on each playing position and depending on whether it was a training day (high-speed running: effect size (ES) ≥ 2.07; player load: ES ≥ 1.89) or a match (total distance: ES ≥ 1.27; high-speed running: ES ≥ 1.42; player load: ES ≥ 1.33). Differences in internal load were not substantial. The rating of perceived exertion, at this competitive level, does not seem to discriminate the differences registered in the external load, probably due to the degree of adaptation to the specific effort of these players. The large differences observed in external load variables should be used to tailor practices and better adjust the training demands in professional handball settings.
... The s-RPE (session RPE) is the measure of quantitative internal load proposed by Foster on the basis of RPE. The training load is the RPE value 15~30 min after a training session or a game multiplied by the exercise duration (minutes) in AU (arbitrary units) [50]. In general, the loads of a low-intensity and high-intensity soccer training session are 300-500 AU and 700-1000 AU, respectively. ...
The number of studies on the relationship between training and competition load and injury has increased exponentially in recent years, and it is also widely studied by researchers in the field of professional soccer. In order to provide practical guidance for workload management and injury prevention in professional athletes, this study provides a review of the literature on the effect of load on injury risk, injury prediction, and interpretation mechanisms. The results of the research show that: (1) It appears that short-term fixture congestion may increase the match injury incidence, while long-term fixture congestion may have no effect on both the overall injury incidence and the match injury incidence. (2) It is impossible to determine conclusively whether any global positioning system (GPS)-derived metrics (total distance, high-speed running distance, and acceleration) are associated with an increased risk of injury. (3) The acute:chronic workload ratio (ACWR) of the session rating of perceived exertion (s-RPE) may be significantly associated with the risk of non-contact injuries, but an ACWR threshold with a minimum risk of injury could not be obtained. (4) Based on the workload and fatigue recovery factors, artificial intelligence technology may possess good predictive power regarding injury risk.
... Power training (PWT) is characterized by performing the concentric phase of the movement at the maximum amount of force as fast as possible with loads of no more than 60% of 1 RM. According to different studies, power training (PWT) is important for functional improvements in ADL and balance and can promote more power at lower external resistances, which will result in a higher velocity of power to perform any task [6,7,10,17]. ...
Background:
Physical activity (PA) and physical fitness are key factors for quality of life (QoL) for older women. The aging process promotes the decrease in some capacities such as strength, which affect the activities of daily life. This loss of strength leads to a reduction in balance and an increased risk of falls as well as a sedentary lifestyle. Resistance Training (RT) is an effective method to improve balance and strength but different RT protocols can promote different responses. Power training has a higher impact on the performance of activities of daily life. Therefore, our study aimed to analyze if different RT protocols promote individual responses in balance, QoL and PA levels of older women and which are more effective for the older women.
Methods:
Ninety-four older women were divided into four RT groups (relative strength endurance training, SET; Traditional strength training, TRT; absolute strength training, AST; power training, PWT) and one control group (CG). Each RT group performed a specific protocol for 16 weeks. At baseline and after 8 and 16 weeks, we assessed balance through the Berg balance scale; PA levels with a modified Baecke questionnaire and QoL with World Health Organization Quality of Life-BREF (WHOQOL-BREF) and World Health Organization Quality of Life-OLD module (WHOQOL-OLD).
Results:
Balance improved after 16 weeks (baseline vs. 16 weeks; p < 0.05) without differences between all RT groups. PWT (2.82%) and TRT (3.48%) improved balance in the first 8 weeks (baseline vs. 8 weeks; p < 0.05). PA levels increased in PWT, TRT and AST after 16 weeks (baseline vs. 16 weeks; p < 0.05).
Conclusion:
All RT protocols improved PA levels and QoL after 16 weeks of training. For the improvement of balance, QoL and PA, older women can be subjected to PWT, AST and SET, and not be restricted to TRT.
... We modified the verbal anchors so that they would refer only to velocity, substituting the existing "power zone" with "Somewhat Fast". When verbal descriptors are used, the terminology used is very important, as these serve to better understand the purpose of the scale and the different terminology used can influence the interpretation of the scale [35,36]. It is also important to have coherent verbal anchors positioned correctly according to their quantitative meaning [37]. ...
Background:
the aim of the study was to develop and validate a specific perception velocity scale for the Back Squat exercise to discriminate the velocity of each repetition during a set.
Methods:
31 resistance trained participants completed 3 evaluation sessions, consisting of 3 blinded loads (light, medium, heavy). For each repetition, barbell mean velocity (Vr) was measured with a linear position transducer while perceived velocity (Vp) was reported using the Squat Perception of Velocity (PV) Scale.
Results:
Pearson correlation coefficients (r) showed very high values for each intensity in the 3 different days (range r = 0.73-0.83) and practically perfect correlation for all loads (range r = 0.97-0.98). The simple linear regression analysis between Vp and Vr revealed values ranging from R2 = 0.53 to R2 = 0.69 in the 3 intensities and values ranging from R2 = 0.95 to R2 = 0.97 considering all loads. The reliability (ICC2.1, SEM) of Vp was tested for light (0.85, 0.03), medium Please do not modify the format of the manuscript (type and size of font, margin size, paragraph spacing, etc.), only what is indicated with comments or highlighted, as it follows the standard style of MDPI. We would appreciate if you could mark all the modifications with the Track Changes tool and thoroughly address all the comments.(0.90, 0.03) and heavy loads (0.86, 0.03) and for all loads (0.99, 0.11). The delta score (ds = Vp - Vr) showed higher accuracy of the PV at heavy loads.
Conclusions:
these results show that the PV Squat Scale is a valid and reliable tool that can be used to accurately quantify exercise intensity.
... A reliable, valid, and also easy way to monitor internal training load is by logging session Ratings of Perceived Exertion (sRPE) and duration for each training session [12]. This method has shown to be useful for a wide variety of training modalities, such as endurance, interval, and strength training [13]. It can be used for both the prescribed training sessions (intended load) by the coach and the perception of actual training sessions (perceived load) by the athlete so that a comparison can be made [14]. ...
The aim of this observational study was to examine the differences between training variables as intended by coaches and perceived by junior speed skaters and to explore how these relate to changes in stress and recovery. During a 4-week preparatory period, intended and perceived training intensity (RPE) and duration (min) were monitored for 2 coaches and their 23 speed skaters, respectively. The training load was calculated by multiplying RPE by duration. Changes in perceived stress and recovery were measured using RESTQ-sport questionnaires before and after 4 weeks. Results included 438 intended training sessions and 378 executed sessions of 14 speed skaters. A moderately higher intended (52:37 h) versus perceived duration (45:16 h) was found, as skaters performed fewer training sessions than anticipated (four sessions). Perceived training load was lower than intended for speed skating sessions (−532 ± 545 AU) and strength sessions (−1276 ± 530 AU) due to lower RPE scores for skating (−0.6 ± 0.7) or shorter and fewer training sessions for strength (−04:13 ± 02:06 hh:mm). All training and RESTQ-sport parameters showed large inter-individual variations. Differences between intended–perceived training variables showed large positive correlations with changes in RESTQ-sport, i.e., for the subscale’s success (r = 0.568), physical recovery (r = 0.575), self-regulation (r = 0.598), and personal accomplishment (r = 0.589). To conclude, speed skaters that approach or exceed the coach’s intended training variables demonstrated an increased perception of success, physical recovery, self-regulation, and personal accomplishment.
... 14 Participants were instructed to rate their perceived effort for the whole training session within 1-h of exercise, although sRPE scores are temporally robust from minutes to days following a bout of exercise. 13 As an indicator of the type of feedback that occurs between athletes and coaches on a daily basis, participants also rated a subjective (TF) score from 0-100 using a customized scale based on the Perceived Recovery Status (PRS) scale 15 (supplemental Fig. 1). Athletes were instructed to consider how they felt during the training session, which was distinct from the sRPE. ...
... Internal load was primarily derived from HR measures or corresponding subjective measures such as sRPE (10). In the current data, mean and max HR were evaluated (20). ...
A scoping review methodology was used to assess player readiness via indicators of neuromuscular function in response to training load. Literature search included PubMed, Web of Science, SportDiscus, and CINAHL. Search strategy was based on Population-Concept-Context framework evaluating football code athletes with the focus on player readiness in the context of longitudinal monitoring across quantified training loads with an emphasis on neuromuscular function. Demographics, frequency of data collection, methods of monitoring readiness, neuromuscular function, duration of monitoring period, and quantification of training loads were reported. Authors independently reviewed articles and, in the case of disagreement, a vote determined inclusion. The sports of rugby ( n = 13) and soccer ( n = 11) were most frequently examined, followed by Australian Rules Football ( n = 6) and American Football ( n = 1). The most common methods assessed systemic readiness with the primary focus on jump and sprint testing. Findings identified limited evidence supporting structural and tissue-specific monitoring tools. Player readiness assessment strategies have evolved with advances in technology and analytics. It is recommended that future research focus on a variety of populations, including youth and women athletes. This review is the first to summarize methods of assessing player readiness using indicators of neuromuscular function in football code athletes.
... Training drills and training intensity monitoring Table 2 presents the characteristics of training intervention for both SSG and HIIT groups. The rating of perceived exertion (RPE) was obtained using the category ratio scale (6-20) to calculate the internal training load (ITL) immediately after the completion of each session (Foster et al., 2021). The scale was introduced at the beginning in order to familiarise the players. ...
Background
The aim of this study was two-fold: (i) analyze the within-group physical fitness adaptations promoted by a detraining period (4 weeks) followed by an intervention period (4 weeks) using small-sided games (SSGs) or running-based high intensity interval training (HIIT); and (ii) analyze the between-group differences aiming to identify the effectiveness of each training intervention on the physical fitness of youth male soccer players.
Methods
This study followed a randomized parallel study design. Forty male soccer players (age: 16.4 ± 0.5 years old) were assessed three times: (i) baseline; (ii) after 4 weeks of detraining; and (iii) after a retraining period of 4 weeks. After returning from detraining, players were randomized to an SSG-based training intervention ( n = 20) or running-based HIIT ( n = 20). Interventions lasted 4 weeks, with a training frequency of three sessions per week. At all timepoints, players were assessed by: (i) anthropometry (height, body mass, fat mass (FM)), countermovement jump (CMJ), standing broad jump (SBJ), triple hop jump (THJ), linear sprint test (5-, 10-, and 20-m), zig-zag test with (ZZwB) and without (ZZwoB) ball, three corner run test (3CRT), Y-balance test and the Yo-Yo intermittent recovery test level 1 (YYIRT). Mixed ANOVA (time * group) was conducted for testing interactions between the three timepoints of repeated measures and the two groups. Effect size (ES) for pairwise comparisons was calculated using Cohen’s.
Results
Between-group analysis revealed significantly smaller SBJ ( t = −2.424, p = 0.020, d = −0.767 small ES) and THT ( t = −4.353, p < 0.001, d = −1.376 large ES) in the SSG group after the retraining period. At the same time, SSG presented significantly greater FM after retraining compared to HIIT ( t = 3.736, p < 0.001, d = 1.181 large ES). Additionally, SSG had significantly smaller values than HIIT in the ZZwB ( t = −3.645, p < 0.001, d = −1.153 large ES), but greater times in the ZZwoB ( t = 2.679, p = 0.011, d = 0.847 large ES) and 3CRT ( t = 3.126, p = 0.003, d = 0.989 large ES).
Conclusions
Although SSG and HIIT interventions improved physical fitness outcomes after a period of detraining, they were not able to effectively restore body composition, CMJ, 20-m sprint, ZZwB, and YYIRT compared with the baseline assessments (before detraining). Only HIIT was significantly effective for restoring SBJ, short linear sprin speed, and change-of-direction compared with baseline. HIIT was also significantly better than SSG in improving SBJ and ZZwoB. Although the small sample, the non determination of maturation status and the need to be cautious regarding generalization, HIIT appears to be more beneficial than SSG after a detraining period for recovery of body composition and physical fitness qualities in this specific context of youth soccer players.
... Ratings were reported at 8 p.m., ∼15-30 min following the end of the session. In youth team sports, sRPE has been shown to possess acceptable construct validity as a measure of exercise intensity and internal load (Foster et al., 2021). ...
PurposeThe aim of this study was to assess the short-term responsiveness of measurement instruments aiming at quantifying the acute psycho-physiological response to load in high-level adolescent soccer players.Methods
Data were collected from 16 high-level male youth soccer players from the Under 15 age group. Players were assessed on two occasions during the week: after 2 days of load accumulation (“high load”) and after at least 48 h of rest. Measurements consisted of the Short Recovery and Stress Scale (SRSS), a countermovement jump (CMJ) and a sub-maximal run to assess exercise heart-rate (HRex) and heart-rate recovery (HRR60s). Training load was quantified using total distance and high-speed running distance to express external and sRPE training load to express internal load. It was expected that good instruments can distinguish reliably between high load and rest.ResultsOdd ratios (0.74–1.73) of rating one unit higher or lower were very low for athlete-reported ratings of stress and recovery of the SRSS. Standardized mean high load vs. rest differences for CMJ parameters were trivial to small (−0.31 to 0.34). The degree of evidence against the null hypothesis that changes are interchangeable ranged from p = 0.04 to p = 0.83. Moderate changes were observed for HRex (−0.62; 90% Cl −0.78 to −0.47; p = 3.24 × 10−9), while small changes were evident for HRR60s (0.45; 90% Cl 0.08–0.80; p = 0.04). Only small to moderate repeated-measures correlations were found between the accumulation of load and acute responses across all measurement instruments. The strongest relationships were observed between HRex and total distance (rm-r = −0.48; 90% Cl −0.76 to −0.25).Conclusion
Results suggest that most of the investigated measurement instruments to assess acute psycho-physiological responses in adolescent soccer players have limited short-term responsiveness. This questions their potential usefulness to detect meaningful changes and manage subsequent training load and program adequate recovery.
... [4][5][6] A commonly used method is to ask players to rate their perceived exertion at the end of a session (sRPE). 7,8 This rating should indicate the average internal intensity experienced throughout the session and can be multiplied by the DUR (in minutes) to reflect the internal load (sRPE-TL). Previous studies have shown that sRPE-TL is strongly associated with other internal intensity and load variables based on heart rate, blood lactate concentration, and muscle activity in different exercise activities. ...
Purpose:
To examine the utility of differential ratings of perceived exertion (dRPE) for monitoring internal intensity and load in association football.
Methods:
Data were collected from 2 elite senior male football teams during 1 season (N = 55). External intensity and load data (duration × intensity) were collected during each training and match session using electronic performance and tracking systems. After each session, players rated their perceived breathlessness and leg-muscle exertion. Descriptive statistics were calculated to quantify how often players rated the 2 types of rating of perceived exertion differently (dRPEDIFF). In addition, the association between dRPEDIFF and external intensity and load was examined. First, the associations between single external variables and dRPEDIFF were analyzed using a mixed-effects logistic regression model. Second, the link between dRPEDIFF and session types with distinctive external profiles was examined using the Pearson chi-square test of independence.
Results:
On average, players rated their session perceived breathlessness and leg-muscle exertion differently in 22% of the sessions (range: 0%-64%). Confidence limits for the effect of single external variables on dRPEDIFF spanned across largely positive and negative values for all variables, indicating no conclusive findings. The analysis based on session type indicated that players differentiated more often in matches and intense training sessions, but there was no pattern in the direction of differentiation.
Conclusions:
The findings of this study provide no evidence supporting the utility of dRPE for monitoring internal intensity and load in football.
... There are methods of quantifying internal training loads without the use of expensive laboratory equipment. Session ratings of perceived exertion (sRPE = RPE*session duration) may be useful [121]. An example of such methodology is represented by Spineti et al. [24], who compared CNT to traditional strength training and reported their findings with sRPE from both experimental groups (controlling for sport-specific training). ...
The primary aim of this narrative review was to outline the historical genesis of resistance training strategies that incorporate high-load, low-velocity exercises and low-load, high-velocity exercises in the same training session allowing for different "exercise sequences" to be simultaneously implemented. Discrepancies between scientific works and the terminology used within contemporary sport science publications are identified. Upon review of the literature, we propose "complex training" to be considered an umbrella term with 4 different implementations, generally used to indicate a method in which movement velocity or load is altered between sets and/or exercises within the same session with the aim of improving slow and fast force expression. We propose the following terminology for said implementations: contrast training-exercise sequence with alternating high-load and low-load (higher-velocity) exercises in a set-by-set fashion within the same session (corresponding with 'intra-contrast pairs' and 'intra-contrast rest'); descending training-several sets of high-load (e.g., back squat) exercises completed before the execution of several sets of low-load, higher-velocity (e.g., vertical jump) exercises within the same session; ascending training-several sets of low-load, higher-velocity exercises completed before several sets of high-load exercises within the same session; and French contrast training-subset of contrast training in which a series of exercises are performed in sequence within a single session: heavy compound exercise, plyometric exercise, light-to-moderate load compound exercise that maximizes movement speed (i.e., external power), and a plyometric exercise (often assisted). Finally, practical applications and training considerations are presented.
... Common external load measurements include power output, speed, acceleration, time-motion analysis, global positioning system parameters and accelerometer-derived parameters [37]. In addition, quantifying the load and controlling it is fundamental to identify the magnitude of different physical skills during training [38], and one of the ways to control the internal load is the use of the RPE (it has large advantages relative to evaluating the internal training load [39]), which was used in this intervention. ...
Background: The main aim of this study was to evaluate the relationships between training workload (WL) parameters with variations in the change of direction (COD) in under-16 soccer players. Methods: Twenty-seven under-16 elite soccer players were daily monitored for their WL across 15 weeks during the competitive soccer season. Additionally, players were assessed two times for anthropometric measures (weight, height, sitting height and leg length), COD performance (modified 505 test) and maturity offset measured using the peak height velocity (PHV). Results: A correlational analysis was performed to determine the relationship between the variation in COD performance and accumulated WL parameters. Moreover, a regression analysis was executed to explain the variations in the percentage of COD performance considering the accumulated WL parameters and PHV of the season (r = 0.93; p ≤ 0.01) and training monotony during the early-season (r = 0.53; p ≤ 0.05). There were associations between the acute workload during the start of the season and the COD during the end of the season (r = 0.47; p ≤ 0.05). The multiple linear regression analysis showed that 55% of the variation in COD performance between the early and end of season could be explained by the acute or chronic WL, training monotony or strain and the PHV. Conclusions: This information might be useful for practitioners and coaches aiming to improve the COD performance in youth soccer players during an entire competitive season.
... Training load (TL) monitoring is normally applied to assess the physical work an athlete performs in training (i.e., external load) and the athlete's within-training response to that physical work (i.e., internal load) [1,2]. Sessional ratings of perceived exertion (sRPE) and differential ratings of perceived exertion (dRPE) are both subjective measures of the intensity of internal TL [1,3]. Sessional ratings of perceived exertion, which are seen as a global measure of perceived exercise intensity [4,5], seem to be the most used measure in practice; being often recommended as the primary TL measure in team sports and being widely employed in endurance sports [6][7][8]. ...
This article addresses several key issues that have been raised related to subjective training load (TL) monitoring. These key issues include how TL is calculated if subjective TL can be used to model sports performance and where subjective TL monitoring fits into an overall decision-making framework for practitioners. Regarding how TL is calculated, there is conjecture over the most appropriate (1) acute and chronic period lengths, (2) smoothing methods for TL data and (3) change in TL measures (e.g., training stress balance (TSB), differential load, acute-to-chronic workload ratio). Variable selection procedures with measures of model-fit, like the Akaike Information Criterion, are suggested as a potential answer to these calculation issues with examples provided using datasets from two different groups of elite athletes prior to and during competition at the 2016 Olympic Games. Regarding using subjective TL to model sports performance, further examples using linear mixed models and the previously mentioned datasets are provided to illustrate possible practical interpretations of model results for coaches (e.g., ensuring TSB increases during a taper for improved performance). An overall decision-making framework for determining training interventions is also provided with context given to where subjective TL measures may fit within this framework and the determination if subjective measures are needed with TL monitoring for different sporting situations. Lastly, relevant practical recommendations (e.g., using validated scales and training coaches and athletes in their use) are provided to ensure subjective TL monitoring is used as effectively as possible along with recommendations for future research.
... Some other methods commonly rely either on products of volume and intensity parameters, being physiology-based (e.g. using heart-rate variations) [18] or not [19]. When exercise intensity cannot be objectively measured, the session TL is usually estimated using an ex post rating of perceived exertion multiplied by the session's duration [20,21]. Exercise intensity can also be measured in arbitrary units, especially in cases of technical sport disciplines [22]. ...
The emergence of the first Fitness-Fatigue impulse responses models (FFMs) have allowed the sport science community to investigate relationships between the effects of training and performance. In the models, athletic performance is described by first order transfer functions which represent Fitness and Fatigue antagonistic responses to training. On this basis, the mathematical structure allows for a precise determination of optimal sequence of training doses that would enhance the greatest athletic performance, at a given time point. Despite several improvement of FFMs and still being widely used nowadays, their efficiency for describing as well as for predicting a sport performance remains mitigated. The main causes may be attributed to a simplification of physiological processes involved by exercise which the model relies on, as well as a univariate consideration of factors responsible for an athletic performance. In this context, machine-learning perspectives appear to be valuable for sport performance modelling purposes. Weaknesses of FFMs may be surpassed by embedding physiological representation of training effects into non-linear and multivariate learning algorithms. Thus, ensemble learning methods may benefit from a combination of individual responses based on physiological knowledge within supervised machine-learning algorithms for a better prediction of athletic performance.
In conclusion, the machine-learning approach is not an alternative to FFMs, but rather a way to take advantage of models based on physiological assumptions within powerful machine-learning models.
... Each team in SSGs was selected by their coach to avoid having unbalanced groups, especially in regard to physical fitness and technical abilities, and these teams remained stable during the study. The rating of perceived exertion (RPE) was obtained using the category ratio scale (CR-10) to calculate internal training load (ITL) immediately after the completion of each session [31]. The scale was introduced at the beginning to familiarize the players. ...
This study aimed to investigate the effects of the 6-week small-sided games training (SSGs) vs. high-intensity interval training (HIIT) on the psychophysiological and performance responses, and technical skills of young basketball players. Thirty-two male players (age: 14.5 0.5 years of age) were randomly divided into SSGs group (n = 16) and HIIT group (n = 16) training methods thrice per week for 6 weeks. The players in the SSGs group performed two 5–8 min of 2 vs. 2 with 2 min rest periods, while the players in HIIT performed 12–18 min of runs at intensities (90 to 95%) related to the velocity obtained in the 30-15 intermittent fitness test (IFT). Pre-testing and post-testing sessions involved assessments of Yo-Yo Intermittent Recovery Test level 1, 30-15 intermittent fitness test, 5 and 30 m sprint times, vertical jump height, repeated sprint ability, defensive and offensive agility, and technical skills. The SSGs group demonstrated significantly higher agility-based technical responses in terms of the control dribbling and shooting skills (d = 1.71 vs. 0.20, d = 1.41 vs. 0.35, respectively) compared with the HIIT group. Conversely, the HIIT induced greater improvements in 30 m sprint times (d = 3.15 vs. 0.68). These findings provided that SSGs in youth basketball players may allow similar positive physical adaptations to HIIT, with an extra advantage of improving technical skills while improving enjoyability.
... METP intensity used was progressive; for the aerobic exercise, in the first month, we maintained it at 2-3, and in the next months we increased it up to 4-5 according to Rating of Perceived Exertion adapted scale [26], and for the resistance exercises, the first month was used for familiarization with and adaptation to the exercises and their techniques, and the next months we increased the series and repetitions from 2 to 4 and from 16 to 30, respectively. ...
Background:
Chronic diseases are the leading causes of death and disability in older women. Physical exercise training programs promote beneficial effects for health and quality of life. However, exercise interruption periods may be detrimental for the hemodynamic and lipidic profiles of hypertensive older women with dyslipidemia.
Methods:
Nineteen hypertensive older women with dyslipidemia (exercise group: 67.5 ± 5.4 years, 1.53 ± 3.42 m, 71.84 ± 7.45 kg) performed a supervised multicomponent exercise training program (METP) during nine months, followed by a one-year detraining period (DT), while fourteen hypertensive older women (control group: 66.4 ± 5.2 years, 1.56 ± 3.10 m, 69.38 ± 5.24 kg) with dyslipidemia kept their continued daily routine without exercise. For both groups, hemodynamic and lipidic profiles and functional capacities (FCs) were assessed four times: before and after the METP and after 3 and 12 months of DT (no exercise was carried out).
Results:
The METP improved hemodynamic and lipidic profiles (p < 0.05), while three months of DT decreased all (p < 0.05) parameters, with the exception of diastolic blood pressure (DBP). One year of DT significantly (p < 0.01) decreased systolic blood pressure (7.85%), DBP (2.29%), resting heart rate (7.95%), blood glucose (19.14%), total cholesterol (10.27%), triglycerides (6.92%) and FC-agility (4.24%), lower- (-12.75%) and upper-body strength (-12.17%), cardiorespiratory capacity (-4.81%) and lower- (-16.16%) and upper-body flexibility (-11.11%).
Conclusion:
Nine months of the exercise program significantly improved the hemodynamic and lipid profiles as well as the functional capacities of hypertensive older women with dyslipidemia. Although a detraining period is detrimental to these benefits, it seems that the first three months are more prominent in these alterations.
... In addition, Heart rate and the RPE can be assessed to determine the internal load. After a training session, ideally within 30 min, athletes can report their RPE that is multiplied by the session duration to get the session-RPE, which provides a typical estimation of training load (Foster et al., 2001(Foster et al., , 2021. The RPE report is increasingly assessed using an online application (filling out the question on a smartphone or tablet, e.g. ...
Athletes are exposed to various psychological and physiological stressors, such as losing matches and high training loads. Understanding and improving the resilience of athletes is therefore crucial to prevent performance decrements and psychological or physical problems. In this review, resilience is conceptualized as a dynamic process of bouncing back to normal functioning following stressors. This process has been of wide interest in psychology, but also in the physiology and sports science literature (e.g. load and recovery). To improve our understanding of the process of resilience, we argue for a collaborative synthesis of knowledge from the domains of psychology, physiology, sports science, and data science. Accordingly, we propose a multidisciplinary, dynamic, and personalized research agenda on resilience. We explain how new technologies and data science applications are important future trends (1) to detect warning signals for resilience losses in (combinations of) psychological and physiological changes, and (2) to provide athletes and their coaches with personalized feedback about athletes’ resilience.
This study aimed to investigate the impact of post-activation potentiation enhancement (PAPE) on parameters of 3-minute all-out test (3MT) on non-motorized tethered running performance by applying the concept of complex networks for integrative analysis. Ten recreational sports athletes where submitted to anthropometric tests, 1RM ramp, and 3MT trials (PAPE and CONTROL conditions) across five separate test sessions. The conditioning activity model applied was two series of six back squats at 60% 1RM. Based on the complex network, graphs were constructed for each scenario (CONTROL and PAPE) to investigate the Degree, Eigenvector, Pagerank , and Betweenness centrality metrics. PAPE scenario shows greater centrality of anthropometrics and conditioning parameters related to aerobic efficiency, ranking among the top-five classified nodes. Paired Student t-test (p ≤ 0.05) results for 3MT showed differences between two conditions (PAPE vs. CONTROL) for values of EP-W (407.83 ± 119.30; 539.33 ± 177.10) and rEP-W.kg-1(5.38 ± 1.70; 6.91 ± 2.00), and mechanical parameters in absolute and relativized values of peak output power, mean output power, peak force, and mean force. Our results suggest that PAPE modifies the graphs' configuration, raising the network density, and may increase the neuromuscular functions and running economy. In addition, it seems to optimize the activation of aerobic and anaerobic metabolism.
Objectives: To investigate the effect of menstrual cycle (MC) and hormonal contraception (HC) phases in elite rowers training, performance and wellness monitoring. Methods: Twelve French elite rowers were follow-up for 4,2 cycles on average in their final preparation for the Olympics and Paralympics Games in Tokyo 2021 through an on-site longitudinal study based on repeated measures. Daily self-reported evaluation using Likert rating scales of wellness (sleep quality, fitness, mood, injuries’ pain), menstrual symptoms and training parameters (perceived exertion and self-assessment of performance) were collected (n = 1,281) in parallel to a coach evaluation of rowers’ performance (n = 136), blinded to theirs MC and HC phases. Salivary samples of estradiol and progesterone were collected in each cycle to help to classify the MC into 6 phases and HC into 2–3 phases depending on the pills’ hormone concentration. A chi-square test normalized by each rower was used to compare the upper quintile scores of each studied variable across phases. A Bayesian ordinal logistic regression was applied to model the rowers’ self-reported performance. Results: Rowers with a natural cycle, n = 6 ( + 1 amenorrhea) evaluate their performance and wellness with significant higher score indices at the middle of their cycle. Top assessments are rarer at the premenstrual and menses phases, when they more frequently experience menstrual symptoms which are negatively correlated with their performance. The HC rowers, n = 5, also better evaluate their performance when taking the pills and more frequently experience menstrual symptoms during the pill withdrawal. The athletes self-reported performance is correlated with their coach’s evaluation. Conclusion: It seems important to integrate MC and HC data in the wellness and training monitoring of female athletes since these parameters vary across hormonal phases affecting training perception of both athlete and coach.
The effect of drafting on the aerodynamic drag of a trailing cyclist has been widely investigated. However, no experimental field study has quantified under field conditions the potential benefit of this strategy on the leading cyclist, which is the purpose of the present study. Therefore, a protocol based in a previous study performed in velodrome (García-López et al., 2014) was designed. Results indicate that drafting decrease the leading cyclist’s drag area (CdA) by 2.6 and 3.3%, and the trailing cyclist’ CdA by 31.9 and 19.3%, depending on the trailing cyclist position on the bicycle (i.e., aero vs. upright position, respectively). Although Rate of Perceived Exertion (RPE) values behaved similarly to CdA (i.e., when CdA decreased RPE also decreased), quantitatively the RPE method was not sensitive enough to detect small changes in aerodynamic drag.
In general, the concept of a mechanism in biology has three distinct meanings. It may refer to a philosophical thesis about the nature of life and biology, to the internal workings of a machine-like structure, or to the causal explanation of a particular phenomenon [1].
Understanding the biological mechanisms that justify acute and chronic physiological responses to exercise interventions determines the development of training principles and training methods. A strong understanding of the effects of exercise in humans may help
researchers to identify what causes specific biological changes and to properly identify the
most adequate processes for implementing a training stimulus [1].
Despite the significant body of knowledge regarding the physiological and physical effects of different training methods (based on load dimensions), some biological causes of those changes are still unknown. Additionally, few studies have focused on natural biological variability in humans and how specific human properties may underlie different responses to the same training intervention. Thus, more original research is needed to
provide plausible biological mechanisms that may explain the physiological and physical effects of exercise and training in humans.
In this Special Issue, we discuss/demonstrate the biological mechanisms that underlie the beneficial effects of physical fitness and sports performance, as well as their importance and their role in/influences on physical health.
A total of 28 manuscripts are published here, of which 25 are original articles, two are reviews, and one is a systematic review.
Two papers are on neuromuscular training programs (NMTs), training monotony (TM), and training strain (TS) in soccer players [2,3]; five articles provide innovative findings about testosterone and cortisol [4,5], gastrointestinal hormones [6], spirulina [7], and concentrations of erythroferrone (ERFE) [8]; another five papers analyze fitness and
its association with other variables [7,9–12]; three papers examine body composition in elite female soccer players [2], adolescents [6], and obese women [7]; five articles examines the effects of high-intensity interval training (HIIT) [7,10,13–15]; one paper examines the
acute effects of different levels of hypoxia on maximal strength, muscular endurance, and cognitive function [16]; another article evaluates the efficiency of using vibrating exercise equipment (VEE) compared with using sham-VEE in women with CLBP (chronic lowback pain) [17]; one article compares the effects of different exercise modes on autonomic modulation in patients with T2D (type 2 diabetes mellitus) [14]; and another paper analyzes the changes in ABB (acid–base balance) in the capillaries of kickboxers [18]. Other studies evaluate: the effects of resistance training on oxidative stress and muscle damage in spinal cord-injured rats [19]; the effects of muscle training on core muscle performance in rhythmic
gymnasts [20]; the physiological profiles of road cyclist in different age categories [21]; changes in body composition during the COVID-19 [22]; a mathematical model capable of predicting 2000 m rowing performance using a maximum-effort 100 m indoor rowing
ergometer [23]; the effects of ibuprofen on performance and oxidative stress [24]; the associations of vitamin D levels with various motor performance tests [12]; the level of knowledge on FM (Fibromyalgia) [25]; and the ability of a specific BIVA (bioelectrical
impedance vector analysis) to identify changes in fat mass after a 16-week lifestyle program in former athletes [26]. Finally, one review evaluates evidence from published systematic reviews and meta-analyses about the efficacy of exercise on depressive symptoms in cancer patients [27]; another review presents the current state of knowledge on satellite cell dependent skeletal muscle regeneration [28]; and a systematic review evaluates the effects of exercise on depressive symptoms among women during the postpartum period [29]
Purpose:
This study aimed to examine the responsiveness of commonly used measurement instruments to a short training camp by examining the time course of psychophysiological responses in high-level youth soccer players.
Methods:
Monitoring was carried out in 14 U15 male soccer players of 1 professional youth academy. Players provided data 3 days prior to (D - 3), during (D2-D4), and 1 (D + 1) and 4 days (D + 4) after the camp: 4 items for the Short Recovery and Stress Scale (SRSS), a countermovement jump (CMJ), and a submaximal run to assess exercise heart rate and heart-rate recovery. Training load during the camp followed an alternating low-high pattern, with lower training loads on D1 and D3 and higher training loads on D2 and D4.
Results:
Changes in SRSS physical performance capability, emotional balance, overall recovery, muscular stress, and overall stress were small to moderate on D3 and moderate to large on D + 1, while changes were trivial on D + 4. Some CMJ parameters related to the eccentric phase were slightly improved on D3, and these parameters were slightly impaired on D4. Changes in CMJ parameters were trivial on D + 1 and D + 4. After a moderate decrease in exercise heart rate on D3, there was a small decrease on D + 4 and a moderate increase in heart-rate recovery.
Conclusion:
Measurement instruments such as the SRSS and submaximal runs can be used to monitor acute psychophysiological responses to load, while the CMJ may provide little insight during periods of intensified training load.
Background:
This study compared the acute effects of aerobic (AE) and resistance (RE) exercise on reaction time (RT) and working memory (WM) in individuals with intellectual disability.
Methods:
RT tests and Corsi test for WM were performed before and after three intervention sessions: AE, RE, or control session consisting on watching video.
Results:
The RT values decreased significantly (p < .001) after both of AE and RE with higher extend after the RE but did not vary following the control session. Corsi scores increased significantly (p < .001) after AE but not after RE or control session.
Conclusions:
These findings suggest that the effects of acute exercise on cognitive function in individuals with intellectual disability depend on the exercise mode as well as the nature of the cognitive task. The RE seems to be more recommended for RT enhancement whereas only the aerobic one could improve WM in these individuals.
Rating of Perceived Exertion (RPE) is used to subjectively quantify the perception of physical activity, breathlessness or dyspnea, and leg discomfort (RPElegs) during exercise. However, it is unknown how dyspnea or RPElegs can be influenced by expectations. Thirty healthy, active participants (19 M, 11 F) completed five, 5-minute submaximal cycling trials at 60% peak work rate. We deceived participants by telling them they were inspiring different hypoxic and hyperoxic gases, when in fact they breathed room air. Cardiorespiratory variables were similar between the trials, however dyspnea and RPElegs evaluated with a Borg scale changed in a dose-response manner. When participants believed they were breathing 15% O2, they significantly increased dyspnea +0.70 ± 0.2 units (p=0.03) compared to room air, whereas RPElegs was unchanged +0.35 ± 0.1 units (p=0.70). When comparing 15% O2, to the 23% hyperoxic condition, where participants significantly increased their dyspnea +1.05 ± 0.4 units (p=0.003) but did not significantly change RPElegs +0.55 ± 0.2 units (p=0.46). We found that dyspnea during exercise is susceptible to expectancy, without any accompanying physiological changes. Given coaches and clinicians uses perceived exertion to prescribe exercise intensity and evaluate treatments, our finding show that the effect of expectations must be considered when interpreting sensations of breathlessness.
This study is governed by two aims: firstly, expanding the meagre knowledge store regarding the demands set by professional female road cycling and, secondly, ascertaining whether these demands vary in relation to different race-levels and race duration (single- or multi-day events). A total of 1349 female professional road races was analysed and demands (intensity, load and performance) were determined. Races were classified based on race level (i.e. Women's World Tour [WWT], level.1 and level.2 according to the International Cycling Federation) and race duration (single- or multi-day events). Differences were assessed with a multilevel random intercept model whilst the strength of said differences were indicated by Cohen’s d (0–0.19 trivial; 0.20–0.59 small; 0.60–1.1.9 moderate; 1.20–1.99 large; ≥2.00 very large). In general, no moderate differences for load and intensity were noted for the different race levels. This result contrasts with data obtained from male road cycling. Moderate higher 3 and 5 min maximal mean power (MMP) values were noted in the WWT compared to Level.2 races. More substantial differences were found to exist between single- and multi-day races with single-day races presenting small to large higher load and intensity values. In addition, single-day races presented higher MMPs overall durations (5 s–60 min) although these differences can be rated trivial to small. This study contributes to the limited knowledge store describing demands in professional female cycling. The reported data provide valuable insights which may aid practitioners and/or coaches in preparing female professional cyclists for races.
• Highlights
• Within female professional cycling, some differences were noted in the demands (load, intensity and performances) set by different race levels. However, (in general), these differences were trivial to small, which contrasts with male professional cycling.
• More pronounced differences were noted in the demands set by single- and multi-day races. The load (Work done, eTRIMP and TSS) was moderate to large higher in single-day races. Differences in load are primarily caused by a combination of small higher duration and small higher intensity.
• No moderate differences in performance measures (i.e MMPs) were noted for different race levels or between single- and multi-day races.
Background:
Elite junior Australian football players experience high training loads across levels of competition and training. This, in conjunction with impaired wellness, can predispose athletes to injury.
Hypothesis:
Elite junior Australian football players exposed to high loads with poor wellness are more likely to be at risk of injury than those with improved wellness.
Study Design:
Longitudinal prospective cohort study.
Level of Evidence:
Level 3.
Methods:
Data were collected and analyzed from 280 players across the 2014 season. Internal load was measured via session rating of perceived exertion. Player wellness was reported according to ratings of sleep quality, fatigue, soreness, stress, and mood. Week- and month-based training load measures were calculated, representing a combination of absolute and relative load variables. Principal component analysis factor loadings, based on 17 load and wellness variables, were used to calculate summed variable covariates. Injury was defined as “any injury leading to a missed training session or competitive match.” Associations between covariates and injury risk (yes/no) were determined via logistic generalized estimating equations.
Results:
A significant interaction term between load and wellness on injury was found [odds ratio (OR) 0.76; 95% CI 0.62-0.92; P < 0.01), indicating that wellness acts as a “dimmer switch” of load on injury. Further, there was evidence of moderated mediation (OR 0.71; 95% CI 0.57-0.87; P < 0.01). When wellness was low, injury risk started to increase substantially at a 1-week load of 3250 au.
Conclusions:
Subjective measures of training load are associated with injury risk through a nonlinear relationship. This relationship is further influenced by player wellness, which can amplify the risk of injury. There is evidence that higher stress is linked with injury and that soreness and sleep mediate any stress-injury relationship.
Clinical Relevance:
Coaching efforts to manage training load and player adaptive responses, including wellness, may reduce the risk of injury, with stress, soreness, and sleep particularly relevant at this level.
Background:
The programming of training protocols within a high-intensity interval training (HIIT) framework with appropriate analysis of total training load could deliver optimal training adaptations. This study aims to compare the efficiency of two low-volume HIIT protocols integrated with the regular training regime in professional soccer players.
Methods:
Twenty-five participants aged 18.4-29.7 years were randomly assigned to one of two interventions involving straight-line sprint interval training (SIT, n = 13) or small-sided games (SSG, n = 12). Periodization was divided into two 3-week phases concluded by a 7-day taper. SIT first involved two sessions·week-1 of one set of 10·45-s sprints (at maximal intensity) and then three sessions·week-1 of two sets of 10·30-s sprints with a 0.75:1 and 1:1 recovery interval (slow running and stretching exercises), respectively. SSG in the first phase involved 5·3-min games of 4 vs. 4 and in the second phase 4·4-min games of 2 vs. 2 with 3-min recovery (practice drills at 60-70% HRmax). Training load was controlled via session-RPE and HR-based methods. Pre- and post-intervention testing included: countermovement jump height, 5-m and 30-m sprints performance, anaerobic power by the 10-s Wingate Anaerobic Test, maximal oxygen uptake (V̇ O2max) and blood lactate concentration (BLa-) determined by incremental exhaustive running test.
Results:
Two-way ANOVA showed group×time interaction effects for the 30-m sprint time (F(1,23) = 3.023; p = 0.049; η2 p = 0.116), BLa- (F(1,23) = 5.250; p = 0.031; η2 p = 0.185), and V̇ O2max (F(1,23) = 4.648, p = 0.044; η2 p = 0.157). SIT elicited greater enhancements in anaerobic performance (30-m sprint time and BLa-), while SSG induced larger mprovements in V̇ O2max.
Conclusions:
Comparable effects of SIT and SSG protocols were noted, however the aerobic capacity benefits provided by SSG warrant this HIIT protocol as a highly recommended training modality in the professional soccer.
Purpose:
To assess the relationship between external and internal load during official women's rugby seven matches.
Methods:
Six backs (age = 24.2 [3.2] y; height = 161.5 [7.3] cm; body mass = 59.5 [5.0] kg; playing experience = 5.3 [1.5] y) and 8 forwards (age = 22.4 [2.7] y; height = 167.0 [4.8] cm; body mass = 70.6 [5.6] kg; playing experience = 5.0 [1.5] y) belonging to the women's rugby seven Brazilian national team were monitored across 3 international tournaments during the 2019-20 season, with 2 players excluded from the analysis since they did not participate in any investigated match. Total distance (TD), distance during high-intensity running 18.1 to 20.0 km·h-1 and >20 km·h-1 (sprinting), number of accelerations >1.8 m·s-2 (ACC), and of decelerations <1.8 m·s-2 were used as match load volume measures, while their relative values (TD per minute, high-intensity running per minute, sprinting per minute, ACC per minute, and decelerations per minute) were used as external load match intensity measures. Internal load intensity and volume were assessed using the session rating of perceived exertion (sRPE) and its value multiplied by match duration (sRPE-ML), respectively. Spearman correlations and linear mixed models were used to assess the relationships between internal and external load measures.
Results:
A very large relationship (ρ = .830, P < .001) was found between sRPE-ML and TD, with linear mixed models showing that TD statistically affected sRPE-ML (P < .001). Linear mixed models analysis showed that ACC per minute was also affecting the sRPE-ML (P = .017), while sprinting (P = .007) and ACC per minute (P = .005) were the only 2 measures statistically affecting sRPE. However, weak relationships (trivial to large) were found for these and all other measures.
Conclusions:
These results highlight that TD is the main external load measure able to anticipate the internal load responses measured via sRPE-ML in elite women's rugby sevens.
This study aimed to verify the validity of session-RPE method to monitor the internal training load (ITL) in beach volleyball players by considering sessions related to different genders, competition levels (elite or amateur), and types of session (conditioning, technical, or tactical/game). Session-RPE and Edwards’ methods were applied to quantify the ITLs of 12 elite (18 players; 197 individual sessions) and 12 amateur (18 players; 189 individual sessions) training sessions. Very large relationships between the two methods emerged for both competition level (Elite: r=.77; Amateur: r=.75) and gender (male: r=.76; female: r=.75) subgroups, and conditioning sessions (r=.75). Large relationships emerged for technical (r=.61) sessions, whereas tactical/game sessions resulted only in moderate relationships (r=.36). Beach volleyball coaches could adequately use session-RPE method to monitor training for players of different genders, competition levels, and types of session, although tactical/game sessions should be considered with some caution.
Rating of perceived exertion (RPE) and session RPE (sRPE) are reliable tools for predicting exercise intensity and are alternatives to more technological and physiological measurements, such as blood lactate (HLa) concentration, oxygen consumption and heart rate (HR). As sRPE may also convey some insights into accumulated fatigue, the purpose of this study was to examine the effects of progressive fatigue in response to heavier-than-normal training on sRPE, with absolute training intensity held constant, and determine its validity as marker of fatigue. Twelve young adults performed eight interval workouts over a two-week period. The percentage of maximal HR (%HRmax), HLa, RPE and sRPE were measured for each session. The HLa/RPE ratio was calculated as an index of fatigue. Multilevel regression analysis showed significant differences for %HRmax (p = 0.004), HLa concentration (p = 0.0001), RPE (p < 0.0001), HLa/RPE ratio (p = 0.0002) and sRPE (p < 0.0001) across sessions. Non-linear regression analysis revealed a very large negative relationship between HLa/RPE ratio and sRPE (r = −0.70, p < 0.0001). These results support the hypothesis that sRPE is a sensitive tool that provides information on accumulated fatigue, in addition to training intensity. Exercise scientists without access to HLa measurements may now be able to gain insights into accumulated fatigue during periods of increased training by using sRPE.
The Rating of Perceived Exertion (RPE) is an important measure of exercise intensity, which is useful both as a primary and adjunctive method of exercise prescription. However, there are multiple variants of
the Borg RPE scale, primarily the Borg 6-20 RPE scale (BORG-RPE) and the Borg Category-Ratio-10 scale (BORG-CR10). There are inadequate data available to address the comparability and interchangeability of
these two widely used scales. Well-trained non-athletes performed two increment cycle tests, with each scale used in a random sequence. Subjects also performed interval sessions at three intensities (50, 75 and 85% of peak power output) with each scale used in a random sequence. There were very large correlations during the incremental exercise between the conventional physiological measures (% heart rate reserve – r=0.89 & r=.87); and %VO2reserve (r=.88 & r=.90) and RPE measured by either the BORG-RPE or the BORGCR10, respectively. This pattern was also evident during the interval exercise (% heart rate reserve – r=.85 & r=.84; and blood lactate concentration – r=.74 & r=.78) and RPE measured by either the BORG-RPE or the BORG-CR10, respectively. The relationship between RPE measured by the BORG-RPE and the BORGCR10 was large and best described by a non-linear relationship for both the incremental (R2=.89) and the interval (R2=.89) exercise. The incremental and interval curves were virtually overlapping. We concluded that the two most popular versions of the RPE scale, BORG-RPE and BORG-CR10, were both highly related to the conventional physiological measures and very strongly related to each other, with an easily described conversion.
Purpose::
The relationship between various training load (TL) measures in professional cycling is not well explored. This study investigates the relationship between mechanical energy spent (in kJ), sRPE, LuTRIMP and TSS in training, races and time trials (TT).
Methods::
From 4 consecutive years field data was collected from 21 professional cyclists and categorized as being collected in training, racing or TT's. kJ spent, sRPE, LuTRIMP and TSS were calculated and the correlations between the various TL's were made.
Results::
11,655 sessions were collected from which 7,596 sessions had heart rate (HR) data and 5,445 sessions had an RPE-score available. The r between the various TL's during training was almost perfect. The r between the various TL's during racing was almost perfect or very large. The r between the various TL's during TT's was almost perfect or very large. For all relationships between TSS and one of the other measurements of TL (kJ spent, sRPE and LuTRIMP) a significant different slope was found.
Conclusions::
kJ spent, sRPE, LuTRIMP and TSS have all a large or almost perfect relationship with each other during training, racing and TT's but during racing both sRPE and LuTRIMP have a weaker relationship with kJ spent and TSS. Further, the significant different slope of TSS versus the other measurements of TL during training and racing has the effect that TSS collected in training and road-races differ by 120% while the other measurements of TL (kJ spent, sRPE and LuTRIMP) differ by only 73%, 67%, and 68% respectively).
An athlete’s pacing strategy is widely recognised as an essential determinant for performance during individual events. Previous research focussed on the importance of internal bodily state feedback, revealed optimal pacing strategies in time-trial exercise, and explored concepts such as teleoanticipation and template formation. Recently, human–environment interactions have additionally been emphasized as a crucial determinant for pacing, yet how they affect pacing is not well understood. Therefore, this literature review focussed on exploring one of the most important human–environment interactions in sport competitions: the interaction among competitors. The existing literature regarding the regulation of exercise intensity and the effect of competition on pacing and performance is critically reviewed in this paper. The PubMed, CINAHL and Web of Science electronic databases were searched for studies about pacing in sports and (interpersonal) competition between January 2000 to October 2017, using the following combination of terms: (1) Sports AND (2) Pacing, resulting in 75 included papers. The behaviour of opponents was shown to be an essential determinant in the regulation of exercise intensity, based on both observational (N = 59) and experimental (N = 16) studies. However, adjustment in the pacing response related to other competitors appears to depend on the competitive situation and the current internal state of the athlete. The findings of this review emphasize the importance of what is happening around the athlete for the outcome of the decision-making process involved in pacing, and highlight the necessity to incorporate human–environment interactions into models that attempt to explain the regulation of exercise intensity in sports and exercise.
Purpose: The aim of this review is to (1) retrieve all data validating the Session-rating of perceived exertion (RPE)-method using various criteria, (2) highlight the rationale of this method and its ecological usefulness, and (3) describe factors that can alter RPE and users of this method should take into consideration.
Method: Search engines such as SPORTDiscus, PubMed, and Google Scholar databases in the English language between 2001 and 2016 were consulted for the validity and usefulness of the session-RPE method. Studies were considered for further analysis when they used the session-RPE method proposed by Foster et al. in 2001. Participants were athletes of any gender, age, or level of competition. Studies using languages other than English were excluded in the analysis of the validity and reliability of the session-RPE method. Other studies were examined to explain the rationale of the session-RPE method and the origin of RPE.
Results: A total of 950 studies cited the Foster et al. study that proposed the session RPE-method. 36 studies have examined the validity and reliability of this proposed method using the modified CR-10.
Conclusion: These studies confirmed the validity and good reliability and internal consistency of session-RPE method in several sports and physical activities with men and women of different age categories (children, adolescents, and adults) among various expertise levels. This method could be used as “standing alone” method for training load (TL) monitoring purposes though some recommend to combine it with other physiological parameters as heart rate.
To alleviate issues arising from the over/under prescription of training load, coaches must ensure that desired athlete responses to training are being achieved. The present study aimed to assess the level of agreement between the coach intended (pre-session) and observed (post-session) rating of perceived exertion (RPE), with athlete RPE during different training intensities (easy, moderate, hard). Coach intended RPE was taken prior to all field based training sessions over an 8 week in-season period. Following training, all coaches and athletes, whom were participants in hockey, netball, rugby and soccer were asked to provide an RPE measure for the completed session. Sessions were then classified based on the coaches intended RPE, with a total of 28, 125 and 66 easy, moderate and hard training sessions collected respectively. A univariate analysis of variance was used to calculate within-participant correlations between coach intended/observed RPE and athlete RPE. Moderate correlations were found between coach intended and athlete RPE for sessions intended to be moderate and hard whilst a small correlation was found for sessions intended to be easy. The level of agreement between coach and athlete RPE improved following training with coaches altering their RPE to align with those of the athlete. Despite this, moderate and small differences between coach observed and athlete RPE persisted for sessions intended to be easy and moderate respectively. Coaches should therefore incorporate strategies to monitor training load to increase the accuracy of training periodisation and reduce potential over/under prescription of training.
Purpose:
The aim of this study was to determine the reliability and validity of several submaximal variables that can be easily obtained by monitoring cyclists' performance.
Methods:
Eighteen professional cyclists participated in this study. In a first part (n=15) the test-retest reliability of HR and RPE during a progressive maximal test was measured. Derived submaximal variables based on HR, RPE and power output (PO) responses were analyzed. In a second part (n=7) the pattern of the submaximal variables according to cyclists' training status was analyzed. Cyclists were assessed 3 times during the season: at the beginning of the season, before the Vuelta a España and the day after this Grand Tour.
Results:
Part 1: no significant differences in maximal and submaximal variables between test-retest were found. Excellent ICCs (0.81-0.98) were obtained in all variables. Part 2: the HR and RPE showed a rightward shift from early to peak season. In addition, RPE showed a left shift after the Vuelta a España. Submaximal variables based on RPE had the best relationship with both performance and changes in performance.
Conclusion:
The present study showed the reliability of different maximal and submaximal variables used to assess cyclists' performance. Submaximal variables based on RPE seem to be the best to monitor changes in training status over a season.
There have been considerable advances in monitoring training load in running-based team sports in recent years. Novel technologies nowadays offer ample opportunities to continuously monitor the activities of a player. These activities lead to internal biochemical stresses on the various physiological subsystems; however, they also cause internal mechanical stresses on the various musculoskeletal tissues. Based on the amount and periodization of these stresses, the subsystems and tissues adapt. Therefore, by monitoring external loads, one hopes to estimate internal loads to predict adaptation, through understanding the load-adaptation pathways. We propose a new theoretical framework in which physiological and biomechanical load-adaptation pathways are considered separately, shedding new light on some of the previously published evidence. We hope that it can help the various practitioners in this field (trainers, coaches, medical staff, sport scientists) to align their thoughts when considering the value of monitoring load, and that it can help researchers design experiments that can better rationalize training-load monitoring for improving performance while preventing injury.
Training monitoring is about keeping track of what athletes accomplish in training, for the purpose of improving the interaction between coach and athlete. Over history there have been several basic schemes of training monitoring. In the earliest days training monitoring was about observing the athlete during standard workouts. However, difficulty in standardizing the conditions of training made this process unreliable. With the advent of interval training, monitoring became more systematic. However, imprecision in the measurement of HR evolved interval training toward index workouts, where the main monitored parameter was average time required to complete index workouts. These measures of training load focused on the external training load, what the athlete could actually do. With the advent of interest from the scientific community, the development of the concept of metabolic thresholds, and the possibility of trackside measurement of HR, lactate, VO2 and power output, there was greater interest in the internal training load, allowing better titration of training loads in athletes of differing ability. These methods show much promise, but often require laboratory testing for calibration, and tend to produce too much information, in too slow of a time frame, to be optimally useful to coaches. The advent of the TRIMP concept by Banister suggested a strategy to combine intensity and duration elements of training into a single index concept, training LOAD. Although the original TRIMP concept was mathematically complex, the development of the Session RPE and similar low tech methods has demonstrated a way to evaluate training LOAD, along with derived variables, in a simple, responsive way. Recently, there has been interest in using wearable sensors to provide high resolution data of the external training load. These methods are promising, but problems relative to information overload and turn-around time to coaches remain to be solved.
Athlete-environment interactions are crucial factors in understanding the regulation of exercise intensity in head-to-head competitions. Previously, we have proposed a framework based on the interdependence of perception and action, which allows us to explore athletic behaviour in the more complex pacing situations occurring when athletes need to respond to actions of their opponents. In the present perspective we will further explore whether opponents, crucial external factors in competitive sports, could indeed be perceived as social invitations for action. Decisions regarding how to expend energy over the race are based on internal factors such as the physiological/biomechanical capacity of the athlete in relation to external factors such as those presented by opponents. For example: Is the athlete able to overtake competitors, or not?
We present several experimental studies that demonstrate that athletes regulate their exercise intensity differently in head-to-head competition compared to time-trial exercises: Relational athlete-environment aspects seem to outweigh benefits of the individual optimal energy distribution. Also, the behaviour of the opponents has been shown to influence pacing strategies of competing athletes, again demonstrating the importance of relational athlete-environment aspects in addition to strictly internal factors. An ecological perspective is presented in which opponents are proposed to present social affordances, and decision-making is conceptualized as a resultant of affordance-competition. This approach will provide novel insights in tactical decision-making and pacing behaviour in head-to-head competitions. Future research should not only focus on the athlete’s internal state, but also try to understand opponents in the context of the social affordances they provide.
The primary aim of the study was to assess the level of agreement between the criterion session-rating of perceived exertion (sRPE30min) and a practical measure of a self-reported web-based training load questionnaire 24-hours post-training (sRPE24h) in adolescent athletes. The secondary aim was to assess the agreement between weekly summated sRPE24h values (ƩsRPE24h) and a weekly web-based training diary (sRPEweekly) for all field-based training accumulated on a subsequent training week. Thirty-six male adolescent rugby players (age 16.7 ± 0.5 years) were recruited from a regional academy. sRPE30min measures were recorded 30-minutes following a typical field-based training session. Participants then completed the sRPE24h via a web-based training load questionnaire 24-hours post-training, reporting both session duration and intensity. In addition, on a subsequent week, participants completed the sRPE24h daily and then completed the sRPEweekly at the end of the week, using the same web-based platform, to recall all field-based training session durations and intensities over those seven days. Biases were trivial between sRPE30min and sRPE24h for sRPE (0.3% [-0.9 to 1.5]), with nearly perfect correlations (0.99 [0.98 to 0.99), and small typical error of the estimate (TEE; 4.3% [3.6 to 5.4]). Biases were trivial between ƩsRPE24h and sRPEweekly for sRPE (5.9% [-2.1 to 14.2]), with very large correlations (0.87 [0.78 to 0.93]), and moderate TEE 28.5% [23.3 to 36.9]). The results of this study show that sRPE24h is a valid and robust method to quantify training loads in adolescent athletes. However, sRPEweekly was found to have a substantial TEE (29%), limiting practical application.
Session rating of perceived exertion (sRPE) is known to significantly relate to heart rate (HR) based methods of quantifying internal training load (TL) in a variety of sports. However, to date this has not been investigated in fencing and was therefore the aim of this study. TL was calculated by multiplying the session rating of perceived exertion (sRPE) with exercise duration, and through Heart rate (HR) -based methods calculated using Banister's and Edward's TRIMP. Seven male elite foil fencers (Mean ± SD: Age = 22.3 ± 1.6 years, height = 181.3 ± 6.5 cm, body mass = 77.7 ± 7.6 kg) were monitored over the period of one competitive season. The sRPE and HR of 67 training sessions and three competitions (87 poule bouts and 12 knockout rounds) were recorded and analysed. Correlation analysis was used to determine any relationships between sRPE and HR-based methods, accounting for individual variation, mode of training (footwork drills vs. sparring sessions) and stage of competition (poules vs. knockouts). Across two footwork sessions, sRPE, Banister's and Edward's TRIMP were found to be reliable, with coefficient of variation values of 6.0, 5.2 and 4.5% respectively. Significant correlations with sRPE for individual fencers (r = 0.84 - 0.98) and across mode of exercise (r = 0.73 - 0.85) and competition stages (r = 0.82 - 0.92) were found with HR-based measures. sRPE is a simple and valuable tool coaches can use to quantify TL in fencing.
Purpose:
The session RPE (sRPE) has gained popularity as a "user friendly" method for evaluating internal training load. sRPE has historically been obtained 30-min following exercise. This study evaluated the effect of post-exercise measurement time on sRPE following steady-state and interval cycle exercise.
Methods:
Well-trained subjects (N=15) (VO2max=51+4 & 36+4 ml.kg-1 (cycle ergometer) for men & women, respectively) completed counterbalanced 30-min steady-state and interval training bouts. The steady-state ride was at 90% of ventilatory threshold (VT). The work-to-rest ratio of the interval rides was 1:1 and the interval segment durations were 1-, 2- & 3-min. The high-intensity component of each interval bout was 75% peak power output (PPO), which was accepted as a surrogate of the respiratory compensation threshold, critical power or maximal lactate steady state. Heart rate (HR), blood lactate [BLa], and Rating of Perceived Exertion (RPE) were measured. The sRPE (Category Ratio Scale) was measured at 5-, 10-, 15-, 20-, 2-, 30-, 60-min and 24-hr following each ride, using a Visual Analog Scale (VAS) to prevent bias associated with specific RPE verbal anchors.
Results:
sRPE, at 30-min post exercise, followed a similar trend: steady state=3.7, 1-min=3.9, 2-min=4.7, 3-min=6.2. No significant differences (p > 0.05) in sRPE were found based on post-exercise sampling times, from 5-min to 24-hr post-exercise.
Conclusion:
Post-exercise time does not appear to have a significant effect on sRPE after either steady-state or interval exercise. Thus, sRPE appears to be temporally robust and is not necessarily limited to the 30-min post exercise window historically used with this technique, although the presence/absence of a cool-down period after the exercise bout may be of importance.
Background:
The session rating of perceived exertion (session-RPE) proved to be a valuable method to quantify the internal training load (ITL) in taekwondo. However, no study validated this method in youth taekwondo athletes performing different training sessions. Thus this study aimed at evaluating the reliability of the session-RPE to monitor the ITL of prepubescent taekwondo athletes during pre-competitive (PC) and competitive (C) training sessions.
Methods:
Five female (age: 12.0 ± 0.7 y; height: 1.54 ± 0.08 m; body mass: 48.8 ± 7.3 kg) and four male (age: 12.0 ± 0.8 yrs; height: 1.55 ± 0.07 m; body mass: 47.3 ± 5.3 kg) taekwondo athletes were monitored during 100 individual sessions (PC: n = 33; C: n = 67). The Edwards' HR method was used as reference measure of ITL; the CR-10 RPE scale was administered at 1- and 30-minutes from the end of each session.
Results:
No difference for gender emerged. The ITLs of C (Edwards: 228 ± 40 arbitrary units, AU) resulted higher than that of PC (192 ± 26 AU; P = .04). Although all training typologies and data collections achieved significant correlations between Edwards' and session-RPE methods, a large relationship (r = .71, P < .001) emerged only for PC sessions evaluated at 30 minutes of the recovery phases.
Conclusion:
Findings support coaches of prepubescent taekwondo athletes to successfully use session-RPE to monitor the ITL of different training typologies. However, PC training evaluated at 30 minutes of the recovery phase represents the best condition for a highly reliable ITL perception.
Objective. The Session Rating of Perceived Extertion (RPE) is a method of measuring exercise intensity that may be useful for the quantitative assessment of exercise training programmes. However, there are inadequate data regarding the validity and reliability of the Session RPE method. This study was designed to evaluate both the validity and reliability of the Session RPE method in comparison to objective measures (%HRpeak, %HRreserve and %VO2peak) of exercise intensity. Methods. Fourteen healthy volunteers (7 male, 7 female) performed 6 randomly ordered 30-minute constant-load exercise bouts at 3 different intensities, with each intensity being repeated. Oxygen consumption (VO2) and heart rate (HR) were measured throughout each exercise bout and normalised to maximal values obtained during a preliminary maximal exercise test. Thirty minutes following the conclusion of each exercise bout, the subject rated the global intensity of the bout using a modification of the Category Ratio (CR) (0 - 10) RPE scale. This rating was compared to the mean value of objectively measured exercise intensity across the duration of the bout. Results. There were significant non-linear relationships between Session RPE and %VO2peak (R2 = 0.76), %HRpeak (R2 = 0.74) and %HRreserve (R2 = 0.71). There were no significant differences between test and retest values of %VO2peak, %HRpeak, %HRreserve and Session RPE during the easy (47 v. 47%, 65 v. 66%, 47 v. 48% and 2.0 v. 1.9), moderate (69 v. 70%, 83 v. 84%, 74 v. 75%, and 4.2 v. 4.3) and hard (81 v. 81%, 94 v. 94%, 91 v. 91% and 7.3 v. 7.4) exercise bouts. Correlations between repeated bouts for %VO2peak (r = 0.98), %HRpeak (r = 0.98), %HRreserve (r = 0.98) and Session RPE (r = 0.88) were significant and strong. Conclusions. The results support the validity and reliability of the Session RPE method of monitoring exercise intensity, although as might be predicted for a subjective method the Session RPE was less precise than the objective measures of exercise training intensity. South African Journal of Sports Medicine Vol. 18 (1) 2006: pp. 14-17
