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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.

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... Heart rate was continuously monitored throughout the entire session. Thirty minutes after each training session the participants provided their sRPE using the modified CR-10 scale [8,10]. All participants were familiar with the RPE scale as they had used it for several weeks prior to this study. ...
... Training load was calculated using the sRPE method, Edwards' TL and Banister TRIMP. Session RPE TL was calculated by multiplying RPE score with training session duration, expressed in minutes [8,10]. ...
... after situational kata training session performed in this study, suggesting higher metabolic stress [10]. Therefore, the larger and significant correlations between sRPE and both HR-based methods for TL assessment that were found in kumite studies are not surprising. ...
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This study was intended to investigate the associations between session Ratings of Perceived Exertion (sRPE) and Edwards’ training load (TL) and Banister training impulse (TRIMP) in order to determine the validity of the sRPE method for TL assessment in karate kata discipline. Eight elite karate kata athletes, members of the national karate team, took part in this study. A multistage 20 m shuttle run test was performed to determine maximal heart rate (HRmax). Subsequently, the subjects performed 3 different kata training sessions separated by minimally 48 hours. To calculate Edwards TL, Banister TRIMP and sRPE, heart rate (HR) was continuously monitored during the sessions and RPE of the entire session was collected 30 minutes after each training session. The Pearson correlation coefficient (r) was used for determining associations between TL variables. Edwards TL (p = 0.064) and Banister TRIMP (p = 0.102) were not, but sRPE was significantly different between each training session (p < 0.001). There were no significant correlations between sRPE and Edwards TL (r = 0.53, p = 0.18) or Banister TRIMP (r = 0.13, p = 0.77) when data from all training sessions were pooled. A significant correlation was obtained between sRPE and Edwards TL (r = 0.71, p = 0.04) in situational training session, whereas in technical training session sRPE was significantly correlated with Banister TRIMP (r = 0.82, p = 0.01). HR-based methods for TL assessment are not able to discriminate between kata training sessions and, therefore, sRPE may be more useful for coaches to monitor TL in karate kata athletes.
... 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. ...
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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.
... RPE is a common measure of training intensity that measures an athlete's perceived effort of physiological stress from training and competition (Foster et al., 2021;Halson, 2014a). The method has been found to be a valid and reliable marker of training when compared to heart rate (Foster et al., 2001) and blood lactate concentrations (Lovell et al., 2013). ...
... Further support for the use of sRPE method relates to its temporal robustness (Foster et al., 2021). It was originally recommended that the rating be obtained close to 30minutes post exercise completion to prevent particularly hard or easy sections of the training session from dominating the athlete's perception (Foster et al., 1995). ...
... However, recent studies have demonstrated that time between completion of exercise and the collection of RPE has minimal effect on its accuracy, even up to several days after completion (Foster et al., 2021;Christen et al., 2016). Figure 2.8 from Foster et al. (2021) illustrates that while small differences across time exist, they rarely exceed 1 RPE unit, even for time periods of up to 2 weeks. ...
Thesis
Introduction: Amateur Rugby Union has an inherent risk of injury that is associated with detrimental effects on player welfare and team performance. The monitoring of players’ preparedness for, and response to, training has become an integral tool for coaches in injury risk management as it may aid in the prescription and design of training. A training monitoring system (TMS) should be both attainable and scientifically grounded, however, there is a paucity of information in relation to monitoring training at the amateur level and the inherent challenges this presents. Aim: The aim of this doctoral research was to explore the associations between subjective measures of training load (TL) and wellness with injury occurrence in match-play and training sessions in amateur rugby in Ireland. Fundamentally, this programme of research aimed to offer practical methods of monitoring training that has the potential to mitigate injury risk and, in turn, benefit the health and wellbeing of players. Methods: Five studies were conducted in this programme of research which: (1) systematically reviewed and critically appraised the existing relevant literature regarding associations between the acute:chronic workload ratio (ACWR), and injury in team sports (Chapter Three), (2) established the current training monitoring practices of practitioners working with in amateur Rugby Union clubs (Chapter Four), (3) developed and evaluated an online TMS (Chapter Five), examined methods of addressing missing TL using missing value imputation (MVI) (Chapter Six), and (5) explored possible associations between subjective self-reported measures of wellness, various training load metrics, and injury in amateur Rugby Union. Results: The findings of the systematic review support the association between the ACWR and non-contact injuries and its use as a valuable tool for monitoring TL as part of a larger scale multifaceted monitoring system that includes other proven methods. 72.7% of practitioners working with amateur Rugby Union clubs monitored training with the most common method being the session rate of perceived exertion (sRPE), used in 83.3% of monitoring systems. The 3 most prominent challenges to motoring training were found to be lack of player compliance, data inconsistency and match-day challenges. Practitioners should strive to keep missing TL data at a minimum, however imputing missing data with the Daily Team Mean (DTMean) was the most accurate MVI method of the twelve MWI methods examined. Lastly, logistic regression found significant, strong associations (odds ratio (OR) = 6.172, 95% CI = 0.254 – 0.473, p < 0.001) between the occurrence of injury and the summative score of overall wellness (0-day lag). Significant weak associations were found between the occurrence of injury and the majority of ACWR calculations when 3-day and 7-day injury lag periods were applied. Conclusion: The findings of this programme of research support the positive association between injury and both subjective wellness and TL. Monitoring training of amateur athletes has its own unique challenges and confounders (e.g., limited time with players, occupation of players, resources available). Practitioners must accept that due to the complexity of injury, a risk will always be present and instead focus on prescribing training that they deem will promote positive adaptations in a safe manner. However, a TMS consisting of subjective measures may mitigate injury risk in amateur Rugby Union by supporting decisions around training prescription.
... When multiplied by the duration of an exercise bout, this duration-intensity product yields an sRPE-derived measure of training load (sRPE-TL) as a subjective measure of internal load. This approach has been shown to provide a low-cost and low-tech method of quantifying internal training load in a variety of sport settings [9,10]. ...
... Since its introduction, sRPE-TL has been used in a large number of studies and has been shown to correlate well with other measures of internal load [10][11][12][13][14]. However, most training programs continue to prescribe work in terms of external load. ...
... In order to minimize the effect of fatigue immediately following a session, sRPE data were collected at least 30 min following the end of each session using a smartphone app (TeamBuildr; TeamBuildr, LLC, Landover, MD, USA). The sRPE has been shown to be very robust for time post exercise, around a nominal average of 30 min [10,20]. At this point, athletes were visually presented with the scale previously introduced by Foster et al. [9] and reported their RPE for the session. ...
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Purpose: The purpose of this study was to determine whether session rating of perceived exertion-derived training load (sRPE-TL) correlates with GPS-derived measures of external load in National Collegiate Athletics Association (NCAA) Division I female soccer athletes. Methods: Twenty-one NCAA Division 1 collegiate women's soccer athletes (11 starters, 10 non-starters; 65.1 ± 7.2 kg, 168.4 ± 7.9 cm, 20.3 ± 1.5 yrs) volunteered to take part in this study. Data for this study were collected over the course of 16 weeks during the 2018 NCAA women's soccer season. External load and heart rate (HR) data were collected during each training session and match during the season. At least 30 min after the end of an activity (e.g., match or practice), athletes were prompted to complete a questionnaire reporting their perceived exertion for the session. sRPE-TL was calculated at the end of the season by multiplying perceived exertion by the respective session duration. Results: sRPE-TL was very strongly correlated with total distance, distance covered in velocity zones 1-3, the number of accelerations in zones 4 and 5, total PlayerLoad™, and PlayerLoad™. For internal load, sRPE-TL correlated very strongly (0.70 ≤ |r| < 0.90) with Edward's and Bannister's TRIMP and strongly (0.50 ≤ |r| < 0.70) with duration spent in in heart rate zones 5 and 6 (80-90% and 90-100% max HR, respectively) while correlations with maximum HR (bpm), mean HR (bpm), and mean HR (%) and sRPE-TL were moderate (0.30 ≤ |r| < 0.50). Conclusions: In NCAA Division I women soccer, sRPE-TL is strongly associated with external measures of workload. These relationships were stronger during match play, with acceleration load and total distance exhibiting the strongest relationship with sRPE-TL.
... It is thus possible that adding perceptual information such as rating of perceived exertion [70] and talk test [71] collected during GTX, as well as during real-time training sessions, could help coaches and researchers to translate laboratory test responses and adjust workload more accurately throughout training sessions [68][69][70][71], thereby minimizing prescription mistakes. Studies have pointed out that athletes often perform their recovery sessions at a higher intensity than that intended by the coach, making it unable for them to achieve the preassigned intensity during high-intensity sessions [72,73]. In this sense, TID quantification through running speed could help athletes adopt an appropriate "easy" training intensity according to specific coaching prescriptions. ...
... e. warm-up, main session, and cooldown) [1]. In this line, Foster et al. [72] emphasized that accounting for s-RPE at the different parts of the interval training sessions and tempo runs may be a useful strategy. Moreover, it has been highlighted that s-RPE may play a fundamental role as a method to quantify internal training load, mainly because it is sensitive to external factors such as volume and duration [65,74], therefore providing additional information about the amount of accumulated fatigue not available from other markers of training load [75]. ...
... Thus, either a faster speed for a given distance with same HR or a decreased HR for a given speed and distance would represent a positive adaptation to training [50]. Moreover, due to the complex interaction among the psychophysiological variables that make up endurance training in middle-and long-distance runners, coaches should include the s-RPE daily to globally understand [72] how their athletes respond to the external load implemented during the training session. It may be that an approach aiming to evaluate the s-RPE of each of the main parts of the training session (i. ...
Article
Training-intensity distribution (TID) is considered the key factor to optimize performance in endurance sports. This systematic review aimed to: I) characterize the TID typically used by middle-and long-distance runners; II) compare the effect of different types of TID on endurance performance and its physiological determinants; III) determine the extent to which different TID quantification methods can calculate same TID outcomes from a given training program. The keywords and search strategy identified 20 articles in the research databases. These articles demonstrated differences in the quantification of the different training-intensity zones among quantification methods (i. e. session-rating of perceived exertion, heart rate, blood lactate, race pace, and running speed). The studies that used greater volumes of low-intensity training such as those characterized by pyramidal and polarized TID approaches, reported greater improvements in endurance performance than those which used a threshold TID. Thus, it seems that the combination of high-volume at low-intensity (≥ 70% of overall training volume) and low-volume at threshold and high-intensity interval training (≤ 30%) is necessary to optimize endurance training adaptations in middle-and long-distance runners. Moreover, monitoring training via multiple mechanisms that systematically encompasses objective and subjective TID quantification methods can help coaches/researches to make better decisions.
... However, a later study (10) showed that sRPE value is not influenced by the exercise intensity performed toward the end of training sessions. Therefore, subsequent studies (1,6,11,13,16,19,20) have investigated the effect of different postexercise rating times on sRPE. Most of these studies suggest that a 10-minute postexercise time is sufficient to obtain an accurate and reliable sRPE value (1,11,13,20). ...
... This scale represents a 10-cm line with rest and maximal effort indicated at the left and right borders, respectively. Subjects made a mark between the borders, which was measured manually and represented their sRPE (1,6). In addition, familiarization with the use of the VAS to quantify the exercise intensity was performed over the previous month before the start of the study. ...
... The main finding of this study was that training session demands can be quantified in an accurate manner from sRPE within a time frame of 5 minutes to 72 hours posttraining. These results are similar to those previously reported (1,6,11,13,20) and suggest that it is not necessary wait exactly 30 minutes after training sessions to obtain sRPE. Similar sRPE values have been found at 5 (1), 10 (1,13,20), 15 (1,11), and 20 minutes (1,13) after training sessions. ...
Article
The purpose of this study was to analyze the effect of post-exercise rating times (from 0-min to 4-wks) on sRPE. Twenty five athletes (12 females and 13 males) from different sports (sprinting, endurance running, cycling and volleyball) were involved in this study. At least 3 training sessions per subject were quantified based on sRPE using a visual analog scale. The scale was administered immediately after, at 5-, 10-, 20- and 30-min, 24-, 48- and 72-h, 1-, 2-, 3- and 4-wk post-exercise. In addition, the effect of rating time on sRPE was studied according to the training intensity. For this, the training sessions were classified (based on the 30-min rating) as easy (sRPE <3), moderate (sRPE 3-5) and hard (sRPE >5). A significant (P < 0.001) main effect of the post-exercise rating time on sRPE was found. There were significant (P < 0.05) differences between sRPE obtained at 30-min and those obtained immediately after hard training sessions, and at 1-, 2-, 3- and 4-wk post-exercise. There was no significant effect of rating time on sRPE in the easy and moderate training sessions. In conclusion, the present data suggest that athletes’ sRPE may be obtained in a valid and reliable manner within a time frame of 5-min to 72-h post-training. The effect of post-exercise rating time on sRPE seems to be conditioned by the training intensity, especially in those training sessions whose training intensity was high (sRPE >5).
... Session rating of perceived exertion (sRPE) (17) and sRPE training load (sRPE load) are easy, low-cost methods and have become popular methods for measuring internal load (16,20). Several studies have investigated training load using sRPE load in different team sports, including team handball (2,8,12,16,24). ...
... Session rating of perceived exertion (sRPE) (17) and sRPE training load (sRPE load) are easy, low-cost methods and have become popular methods for measuring internal load (16,20). Several studies have investigated training load using sRPE load in different team sports, including team handball (2,8,12,16,24). However, to serve as a tool for practitioners and coaches, the validity and reliability of sRPE load are imperative. ...
... Associations between objective and subjective measures of internal and external load can provide evidence for the validity and sensitivity of internal load measures, which is essential in the absence of any gold standard criterion measure (31). Several studies have investigated such relationships in team sports for several different variables (16,20,31). A meta-analysis found high correlations between sRPE load and total distance covered (r 5 0.79) and accelerometer derived load variables that include PlayerLoad (r 5 0.63) in team sports (31). ...
Article
Full-text available
Session rating of perceived exertion (sRPE) is a subjective self-reported measure of training load and is a popular method in several different team sports. This study aimed to investigate the validity of sRPE, by correlating sRPE load (sRPE × minutes of training) and heart rate (HR) expressed as Edwards Summated Heart Rate Zones (SHRZ) and PlayerLoad among Danish youth team handball players. Second, the study aimed to investigate sRPE load's ability to descriptively differentiate between a low and a high training load category. A comparative cross-sectional study was conducted in the in-season period. Fourteen training sessions were measured from 6 teams, in which PlayerLoad, Edwards SHRZ, and sRPE load were measured for the training session and collected from 47 subjects (23 males and 24 females). Pearson's product-moment correlation coefficients were calculated between sRPE load and Edwards SHRZ and PlayerLoad. Furthermore, a high and a low load category were made from PlayerLoad or Edwards SHRZ to investigate sRPE load's ability to discriminate between high and low objective load. Large correlations between sRPE load and Edwards SHRZ (0.52 [95% CI 0.27:0.70]) and between sRPE load and PlayerLoad (0.67 [95% CI 0.47:0.80]) were observed. Our findings further indicate that sRPE load can differentiate between a high and a low training load category in both Edwards SHRZ and PlayerLoad. Our results show that sRPE load reflects both internal and external load during team handball training sessions and seems to discriminate between high- and low-intensity training sessions. These results support the validity of sRPE load for measuring training load in young team handball players.
... However, a later study (10) showed that sRPE value is not influenced by the exercise intensity performed toward the end of training sessions. Therefore, subsequent studies (1,6,11,13,16,19,20) have investigated the effect of different postexercise rating times on sRPE. Most of these studies suggest that a 10-minute postexercise time is sufficient to obtain an accurate and reliable sRPE value (1,11,13,20). ...
... This scale represents a 10-cm line with rest and maximal effort indicated at the left and right borders, respectively. Subjects made a mark between the borders, which was measured manually and represented their sRPE (1,6). In addition, familiarization with the use of the VAS to quantify the exercise intensity was performed over the previous month before the start of the study. ...
... The main finding of this study was that training session demands can be quantified in an accurate manner from sRPE within a time frame of 5 minutes to 72 hours posttraining. These results are similar to those previously reported (1,6,11,13,20) and suggest that it is not necessary wait exactly 30 minutes after training sessions to obtain sRPE. Similar sRPE values have been found at 5 (1), 10 (1,13,20), 15 (1,11), and 20 minutes (1,13) after training sessions. ...
... Darüber hinaus kann der effektive Workload, d. h. das Produkt aus Anstrengungsgrad und Dauer einer Trainingseinheit als Session-RPE für ein systematisches Monitoring eingesetzt werden (Foster et al., 2021;Foster et al., 2001;Foster, Rodriguez-Marroyo, & de Koning, 2017;Gabbett, 2020;Gomes et al., 2020;Haddad, Padulo, & Chamari, 2014;Haddad et al., 2017;Robertson et al., 2000;Scott, Duthie, Thornton, & Dascombe, 2016). ...
... Bisher nicht geprüfte Aspekte, z. B. zur divergenten Validität, sowie die Relevanz der ASS im Sinne eines Monitorings für das Erkennen von Übertrainingsmerkmalen und Verletzungsrisiken sind in weiteren Studien zu prüfen (Foster et al., 2021;Gabbett, 2016). Ebenso erscheinen Studien angezeigt, in denen bspw. ...
... innerhalb von maximal 30 min nach dem Training oder des Wettkampfs, die Beanspruchung bspw. über eine App erfasst werden kann (Foster et al., 2021), stellt die Anstrengungsskala Sport (ASS) eine zuverlässige und sprachlich eindeutige Single-Item-Skala dar, die mehr Systematik in diesen wichtigen Bereich der Leistungssteuerung und des Monitorings bringen kann. Die Entwicklung aufgaben-bzw. ...
Article
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Zusammenfassung Aufgrund ihrer Einfachheit und Nutzerfreundlichkeit wird für die Erfassung der subjektiven Beanspruchungswahrnehmung in Training und Wettkampf bevorzugt die Category Ratio Scale (CR10-Skala) oder eine daran angelehnte Ein-Item-Skala eingesetzt. Die CR10-Skala stellt eine nicht-lineare, leicht positiv beschleunigte Funktion bezogen auf die Beanspruchung dar, die in der autorisierten deutschen Fassung mit „Anstrengungsempfinden“ übersetzt wird. Allerdings ist festzuhalten, dass die existierenden Skalen keine vollständigen Stufenbezeichnungen beinhalten und/oder die Stufenbezeichnungen Überschneidungen mit verwandten Konstrukten, z. B. Ermüdung zulassen. Die Anstrengungsskala Sport (ASS) zeichnet sich demgegenüber durch vollständige Stufenbezeichnungen und begriffliche Klarheit mit der komparativen Deklination des Adjektivs anstrengend aus. Auf der Grundlage einer rationalen Konstruktionsstrategie sowie einer systematischen Item-Analyse kann gezeigt werden, dass die Voraussetzungen für die Verwendung der ASS als Verhältnisskala gegeben sind, die eine zuverlässige und inhaltlich eindeutige Messung der Anstrengung gestattet.
... However, the evaluation of some markers, such as oxygen consumption and blood lactate concentration, requires specific equipment, usually of high cost, a specialized team and greater time demand, which makes it difficult to use in daily training and competitions (Barroso, Cardoso, do Carmo, & Tricoli, 2014). Because of this, the method proposed by Foster et al. (1995) which consists of multiplying the duration of the training session, in minutes, by the value of the training intensity, indicated by the Borg CR10 scale adapted by Foster et al. (1995) has been used in a wide variety of exercise activities ranging from aerobic to resistance to games (Foster et al., 2021). The session rating of perceived exertion (S-RPE) method was designed to estimate the internal load of an entire training session, and been shown to be useful in elite athletes (Foster et al., 2021). ...
... Because of this, the method proposed by Foster et al. (1995) which consists of multiplying the duration of the training session, in minutes, by the value of the training intensity, indicated by the Borg CR10 scale adapted by Foster et al. (1995) has been used in a wide variety of exercise activities ranging from aerobic to resistance to games (Foster et al., 2021). The session rating of perceived exertion (S-RPE) method was designed to estimate the internal load of an entire training session, and been shown to be useful in elite athletes (Foster et al., 2021). In addition, the method has also been used to verify the correspondence between the training planned by the coach and the executed/perceived by the athlete (Barnes, 2017;Redkva, da Silva S, Paes, & Dos-Santos, 2017;Brink, Frencken, Jordet, & Lemmink, 2014;Foster, Heimann, Esten, Brice, & Porcari, 2001b). ...
... The main limitation of the present study was not using methods based on physiological measurements. On the other hand, the S-RPE appears to have much to offer relative to effectively assessing the internal load (Foster et al., 2021). Besides, the quantification of the internal load by the S-RPE method is non-invasive and easy to apply. ...
Article
The aim was to compare the rating of perceived exertion (RPE), duration and session-RPE (S-RPE) prescribed by the coaches to those perceived by the cyclists in training sessions. The classification of RPE, duration and S-RPE of 14 male road cycling and mountain biking athletes were compared with the planned values of five coaches. The results revealed no differences for average RPE (P = 0.586), duration (P = 0.717) and S-RPE (P = 0.738) between coaches and cyclists. When comparing the three categories of effort, the results of the intensity of training sessions designed to be easy were perceived as significantly harder by cyclists compared to coaches (3.0 [2.0] vs. 2.0 [0.0] a.u.; P = 0.013). In addition, the correlations between coaches and cyclists on RPE (r = 0.73), duration (r = 0.95) and S-RPE (r = 0.87) were large, almost perfect and very large (P < 0.0001) respectively. In conclusion, our results indicate a mismatch between coaches (prescription) and cyclists (perception) of easy RPE training sessions, where the cyclists perceived the session harder. However, the S-RPE can be used to prescribe the internal training load of trained cyclists.
... Although there are widely accepted guidelines for exercising patients with known heart disease [19,20] and a rich literature on monitoring exercise training in athletes [21][22][23][24], there is virtually no evidence of how much exercise is actually accomplished by patients enrolled in rehabilitation programs. It can be argued that guidelines without evidence of how well they are complied with are of limited value. ...
... The rating of perceived exertion (RPE) is a method of estimating internal training load and has been shown to be an acceptable surrogate of objective markers of exercise intensity such as percentage of heart rate (%HR) reserve and blood lactate accumulation either during an acute bout of exercise [26][27][28] or during an entire exercise session (thus including exercise duration which causes an upward drift in the workload-RPE relationship), the session RPE (sRPE) [21,22,29,30]. sRPE is easy to use and is accessible to most populations. ...
... sRPE is easy to use and is accessible to most populations. Based on studies conducted by Foster et al. [22,29,30], Day et al. [31], and Herman et al. [32], sRPE has been shown to be valid in terms of evaluating entire training sessions at intensities ranging from light to vigorous, and in multiple modes of exercise [22]. Historically, sRPE was measured 30-min post exercise to get an accurate judgment of the overall intensity of the exercise training session. ...
Article
Full-text available
Exercise training is an important component of clinical exercise programs. Although there are recognized guidelines for the amount of exercise to be accomplished (≥70,000 steps per week or ≥150 min per week at moderate intensity), there is virtually no documentation of how much exercise is actually accomplished in contemporary exercise programs. Having guidelines without evidence of whether they are being met is of limited value. We analyzed both the weekly step count and the session rating of perceived exertion (sRPE) of patients (n = 26) enrolled in a community clinical exercise (e.g., Phase III) program over a 3-week reference period. Step counts averaged 39,818 ± 18,612 per week, with 18% of the steps accomplished in the program and 82% of steps accomplished outside the program. Using the sRPE method, inside the program, the patients averaged 162.4 ± 93.1 min per week, at a sRPE of 12.5 ± 1.9 and a frequency of 1.8 ± 0.7 times per week, for a calculated exercise load of 2042.5 ± 1244.9 AU. Outside the program, the patients averaged 144.9 ± 126.4 min, at a sRPE of 11.8 ± 5.8 and a frequency of 2.4 ± 1.5 times per week, for a calculated exercise load of 1723.9 ± 1526.2 AU. The total exercise load using sRPE was 266.4 ± 170.8 min per week, at a sRPE of 12.6 ± 3.8, and frequency of 4.2 ± 1.1 times per week, for a calculated exercise load of 3359.8 ± 2145.9 AU. There was a non-linear relationship between steps per week and the sRPE derived training load, apparently attributable to the amount of non-walking exercise accomplished in the program. The results suggest that patients in a community clinical exercise program are achieving American College of Sports Medicine guidelines, based on the sRPE method, but are accomplishing less steps than recommended by guidelines.
... 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. ...
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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.
... Coaches can change the outcome/stimuli of intensity measure into an internal training load measure by multiplying the RPE score with the duration of the training session. This is called the session RPE (sRPE) which is used widely amongst sport disciplines [8,9]. Training load can be measured as either external or internal. ...
... Due to the nature of this study, it was impossible to control this aspect. Notwithstanding, RPE is remarkably robust relative to the timing between the training session and the collection of the RPE [24,9]. isRPE was quantified by multiplying the intended duration with the iRPE of the training session, while sRPE was quantified as the experienced RPE by the cyclists multiplied by the actual duration of the training session [7]. ...
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This study aimed to investigate whether (semi-)professional cyclists’ execution of a training program differs from the coach’s designed training program. Also, the study sought to ascertain, in instances where the training sessions were indeed executed as designed by the coach, whether the perception of the cyclists differed from the intention of the coach. This study highlights the differences between the coach and the individual cyclist. In total 747 training sessions were collected from 11 (semi-)professional cyclists. Rating of Perceived Exertion (RPE) and session Rating of Perceived Exertion (sRPE) were compared with intended RPE (iRPE) and intended sRPE (isRPE), planned by the coach. Pearson’s correlation, regression coefficients and Typical Error of Estimate (TEE) were used to identify differences between the executed and planned training sessions. Moderate to large TEEs were noted between executed and intended sRPE, which indicates that cyclists do not always execute the training program planned by the coach. Furthermore, when the training was executed as planned by the coach, very large correlations but moderate to very large TEEs were noted between cyclists’ (s)RPE and the coach’s i(s)RPE, with unique individual regression coefficients. This indicates that the relationship between RPE and iRPE is unique to each cyclist. Both the different execution and perception of the training program by the individual cyclists could cause an impaired training adaptation. Therefore, the coach must pay attention to the perception of training sessions by the individual cyclist. Improved individual management of training load could result in the optimization of the proposed training program.
... The Elite female OW swimmers from this case study were asked to swim in the specified training zone without any other information or feedback, 7 that is, according to their own perceived exertion (intensity). 16 Thus, any change in v at the same intensity was mainly due to their perceived exertion. 16 Also, graphical data presented in our work (Figures 1-3) allowed us to observe and compare suits at both relative and absolute v. Besides, although the IIST was made up of fixed distances, [La − ] andVO 2 response were monitored to determine each swimming training zone (intensity) used (Z1, Z2, Z3, and Z4) during IIST. ...
... 16 Thus, any change in v at the same intensity was mainly due to their perceived exertion. 16 Also, graphical data presented in our work (Figures 1-3) allowed us to observe and compare suits at both relative and absolute v. Besides, although the IIST was made up of fixed distances, [La − ] andVO 2 response were monitored to determine each swimming training zone (intensity) used (Z1, Z2, Z3, and Z4) during IIST. Another relevant and interesting justification for our approach is that OW swimming coaches typically apply these swimming training zones (intensities) on their training programs, which are also the main swimming intensities used by OW swimmers during the 10-km Olympic event. ...
Article
Aim: We investigated how Arena Powerskin R-EVO Closed Back (swimsuit) and Arena Carbon Triwetsuit (full-sleeve, wetsuit), both approved by the Fédération Internationale de Natation (FINA) regulations, affect biomechanics and energetics of 3 Elite female open water (OW) swimmers at maximal and 4 submaximal swimming intensities. Methods: Three Elite female OW swimmers (OW1 = 24 y, 1.64 m, 60 kg; OW2 = 23 y, 1.69 m, 65 kg; OW3 = 27 y, 1.63 m, 64.5 kg) were tested 1 week prior to a FINA/CNSG Marathon Swim World Series event and 40 days before the 18th FINA World Championships 2019. Each OW swimmer completed 2 identical testing sessions, one with a swimsuit and other with a wetsuit, involving shoulder flexion power output (SFPO) assessed from medicine ball throw (MBT), maximal performance and drag coefficient assessment, and an incremental intermittent swim test (IIST) at 4 different relative intensities. Results: Estimated peak oxygen uptake was 4.4 L·min−1 for OW1, 5.6 L·min−1 for OW2, and 5.0 L·min−1 for OW3. Despite a distinct behavior observed on index of coordination for OW3, a null index of synchronization, increased stroke rate (mean difference = 2%–8%), reduced drag factor (minimum = −14%; maximum = −30%), lower energy cost (mean difference = −2% to −6%), and faster performance (mean difference = 2% to 3%) were observed with the wetsuit compared with swimsuit for all Elite OW swimmers. Conclusion: The wetsuit enhances submaximal swimming performance and this increase is dependent on the OW swimmer’s characteristics. The higher stroke rate and lower stroke length detected with wetsuit could be related to movement constraints imposed by the suit.
... The pursuit of a session measure was originated by Foster's adaptation of the Borg rating of perceived exertion (RPE) scale (Foster et al., 2001). Through his adaptation of Borg's 10-point RPE scale (Borg, 1982), Foster et al. (2001) created a subjective method for quantifying training load, one proven as a valuable tool for guiding exercise prescription (Foster et al., 2021). The quantification of a total training load value was achieved by multiplying the perceived difficulty of the session on the 10point scale by the duration of the session in minutes to calculate session Rating of Perceived Exertion (sRPE). ...
... This is highlighted by Foster's own statement that their work "has taken advantage of liberal modifications of Borg's original methods (Foster et al., 2021, p. 612)." These adaptations have included changes to the language, use of color coding, or providing pictured cartoons (Utter et al., 2004;Foster et al., 2021). The objective of the current research is to extend this process of iteration by specifically considering the athlete's internal response to a training session as a whole. ...
Article
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Monitoring session training load to optimize the training stress that drives athlete adaptation and subsequent performance, is fundamental to periodization and programming. Analyzing the internal load experienced by the individual in response to the external load prescribed by coaching staff is crucial to avoid overtraining and optimize training adaptation. Subjective measures provide more information regarding individual training load, as heart rate measures alone do not account for collisions, eccentric muscle actions, muscle soreness, weather conditions, or accumulated training loads, which are paramount to the athlete experience. However, the current subjective metric for interpreting session training load (sRPE) is poorly shaped to the athlete's global response to the whole session, often showing poorer correlations to heart rate (HR) measures during intermittent or high-intensity activity. This study introduces a new metric, the Global Session Metric Score (GSMs), which creates a symmetrical relation between the verbal descriptor and numeric values, as well as more applicable session-specific verbal descriptors for the highest level of exertion. Twenty-four D1 male college soccer field players (age: 20.5 +/– 1.42) wore HR monitors and reported GSMs for all practices and games within an entire season. Linear regression with 10-fold cross validation was used to test the relation between GSMs with B-TRIMP and E-TRIMP, respectively. These models demonstrate good performance with consistency and reliability in the estimation of GSMs to predict both B-TRIMP (R2 = 0.75–0.77) and E-TRIMP (R2 = 0.76–0.78). The findings show promise for the GSMs index as a reliable means for measuring load in both training and matches during a high-intensity intermittent team sport. Future studies should directly compare GSMs to the existing sRPE scale within a controlled laboratory setting and across various other sports. GSMs provides coaches and clinicians a simple and cost-effective alternative to heart rate monitors, as well as a proficient measure of internal training load experienced by the individual.
... 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]. ...
Article
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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.
... One of the most common measures related to internal load is the rate of perceived exertion (RPE) [1,27]. RPE has previously been defined as a valid instrument to quantify the intensity levels or internal load achieved in a task [28,29]. Furthermore, RPE has commonly been used optimally to control the load that is generated in the players during SSG [30]. ...
... The CR-10 Borg scale [29] was obtained immediately after each set of SSGs. All the players were familiar with this tool, using it daily both in training and in competition. ...
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The aim of the present study was to analyze the behavior of players in a standard small-sided game (SSG) according to the role played (offensive (OF), defensive (DF), and wildcard (W)) and its relationship with physical demands (PHYD), technical performance (TP), and internal load (RPE). A total of 24 young highly trained male soccer players (under 16: n = 12; under 19: n = 12) participated. During the SSG, the players alternated the three roles (OF, DF, and W). The duration of each repetition was 4 min with a passive rest of 3 min between them. Furthermore, it emphasized the high demand in all defensive parameters. In addition, DF roles showed higher values in PHYD and RPE, followed by the OF roles, and finally by the W roles. A complementary, positive moderate correlation was found between PHYD and RPE in the U16 dataset (r = 0.45, p < 0.006). Very large positive correlations were also found between PHYD and RPE in the U19 and merged dataset (r = 0.78, p < 0.001 and r = 0.46, p < 0.63, respectively). This information could be useful for coaches in order to structure the roles in SSGs and control training load.
... From this research, the most common internal TL measure was session ratings of perceived exertion (sRPE) which are also recommended as a primary TL intensity measure in team sports and used widely in endurance sports (Drew and Finch, 2016;McLaren et al., 2018;Mujika, 2017). There appears to be a relationship between sRPE-TL (the product of sRPE and session duration) (Foster et al., 2021) and performance in the sprints (Suzuki et al., 2006) where sRPE-TL using Bannister's model predicted performance in an elite Japanese 400-m sprinter. In regards to monitoring tools that can be used with sRPE-TL, the acute-to-chronic workload ratio (Hulin et al., 2014) has been the most popular in many coaching circles, although there seems to be significant statistical concerns with its use (Impellizzeri et al., 2020). ...
... Training load data as the product of sRPE (in this paper defined as the rating of perceived exertion for the complete training session by the athlete (Foster et al., 2021)) and session duration (Foster et al., 2001) were collected from both technical (i.e., sprint/jump) and non-technical (i.e., strength/power, corrective or recovery/regeneration) sessions and included competition loads. Alongside the total weekly TL and week-to-week change in TL, the following variables were calculated daily: i) acute TL (7-day average), ii) chronic TL (21-day average); iii) TSB (Allen and Coggan, 2010) and, iv) differential load (Lazarus et al., 2017) 2017). ...
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The primary objective of this investigation was to investigate the relationships between training load (TL), heart rate variability (HRV) and direct current potential (DC) with elite long jump performance prior to and during the 2016 Olympics Games. Sessional ratings of perceived exertion (sRPE), training duration, HRV and DC were collected from four elite athletes (26.4 ± 1.4 years, height 1.83 ± 0.05 m, weight 68.9 ± 5.0 kg) for a 16-week period in qualification for and competition at the 2016 Olympic Games. Acute and chronic TL, training stress balance and differential load were calculated with three different smoothing methods. These TL measures along with HRV and DC were examined for their relationship to intra-athlete performance using repeated measure correlations and linear mixed models. Successful compared to unsuccessful intra-athlete performances were characterised by a higher chronic TL (p < 0.01, f2 = 0.31) but only when TL was exponentially smoothed. There were also negative correlations between HRV and performance (r = -0.55, p < 0.01) and HRV was significantly lower for more successful performances (p < 0.01, f2 = 0.19). Exponentially smoothed chronic TL was significantly higher and HRV was significantly lower for successful intra-athlete performances prior and during the 2016 Olympics Games in an elite group of long jump athletes. Monitoring sRPE and HRV measures and manipulating TL prior to competition seems worthwhile for elite long jump athletes.
... Furthermore, training monotony is thought to measure the amount of variation in the TL and, if the monotony is high, this could be an indication that there is little variation in the TL. It is advocated that a monotony score of >2 is associated with potential negative training outcomes [102,116]. Alternatively, training strain is the cumulation of training monotony and the weekly load. ...
... These simple metrics may enable practitioners to determine the individual athlete's risk of over-reaching and/or overtraining. In conclusion, the likelihood of overtraining is increased with weekly TLs over 4400 AU, monotony over 2.2 AU and strain over 6000 AU, respectively [102,116,120]. ...
Article
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Athlete monitoring enables sports science practitioners to collect information to determine how athletes respond to training loads (TL) and the demands of competition. To date, recommendations for females are often adapted from their male counterparts. There is currently limited information available on TL monitoring in female Gaelic team sports in Ireland. The collection and analysis of female athlete monitoring data can provide valuable information to support the development of female team sports. Athletic monitoring can also support practitioners to help minimize risk of excessive TL and optimize potential athletic performance. The aims of this narrative review are to provide: (i) an overview of TL athlete monitoring in female team sports, (ii) a discussion of the potential metrics and tools used to monitor external TL and internal TL, (iii) the advantages and disadvantages of TL modalities for use in Gaelic team sports, and (iv) practical considerations on how to monitor TL to aid in the determination of meaningful change with female Gaelic team sports athletes.
... Session-RPE (sRPE) [duration x RPE] was calculated as a load variable for all trampoline and nontrampoline training. Session-RPE is a reliable and valid method of collecting training load (Foster et al., 2021;Haddad et al., 2017). Any missing duration data from competition or programme camps were added to the dataset, as these durations were known. ...
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There is currently limited research exploring the relationship between growth, training load and injury in gymnasts. Twenty-one national level, trampoline gymnasts recorded training load and injury for 8-weeks. Percentage of predicted adult height (%PAH) was calculated using the Khamis-Roche method and used to define growth spurt status. Training load was calculated using the session rate of perceived exertion and analysed as differential loads and as a 7-day exponentially weighted moving average (EWMA7day). There was a significant non-linear association between %PAH and the probability of injury when adjusting for either training load metric (differential load, P = 0.015; EWMA7day; P = 0.008), with the highest injury risk estimated at ~90% PAH (circa growth spurt). The probability of injury significantly increased with increases in EWMA7day training load (RR: 1.88 95% CI: 1.21-2.91, P = 0.005) but not with differential load. No significant interaction between %PAH, training load and the probability of injury were observed. Data suggest that competitive trampoline gymnasts are at an increased risk of injury during the adolescent growth spurt or with higher weekly training loads. Coaches should be educated and encouraged to identify periods of rapid growth and monitor training load, to reduce the risk of injury.
... 14 In addition, IL can be evaluated subjectively through the use of scales with the session rating of perceived exertion (sRPE) among the most used in team sports. 11,15 The advantages of using sRPE relies on the fact that it is easy to use and interpret and can provide information on the physiological and psychological responses to the prescribed load. 16 Overall, to ensure a correct balance between the perception of the athletes and the objective load responses, a combination of objective and subjective measurements is recommended. ...
Article
Purpose: Assessing the relationship between external load (EL) and internal load (IL) in youth male beach handball players. Methods: A total of 11 field players from the Lithuanian U17 beach handball team were monitored across 14 training sessions and 7 matches. The following EL variables were assessed by means of inertial movement units: PlayerLoad™, accelerations, decelerations, changes of direction, and jumps and total of inertial movements. IL was assessed objectively and subjectively using the summated heart rate zones and training load calculated via session rating of perceived exertion, respectively. Spearman correlations (ρ) were used to assess the relationship between EL and IL. The interindividual variability was investigated using linear mixed models with random intercepts with IL as dependent variable, PlayerLoad™ as the independent variable, and players as random effect. Results: The lowest significant (P < .05) relationship was for high jumps with objective (ρ = .56) and subjective (ρ = .49) IL. The strongest relationship was for PlayerLoad™ with objective (ρ = .9) and subjective (ρ = .84) IL. From the linear mixed model, the estimated SD of the random intercepts was 19.78 arbitrary units (95% confidence interval, 11.75-33.31); SE = 5.26, and R2 = .47 for the objective IL and 6.03 arbitrary units (95% confidence interval, 0.00-7330.6); SE = 21.87; and R2 = .71 for the subjective IL. Conclusions: Objective and subjective IL measures can be used as a monitoring tool when EL monitoring is not possible. Coaches can predict IL based on a given EL by using the equations proposed in this study.
... Further studies should manipulate these factors when looking for different perceptual responses, including the evaluation of other different psychological constructs (e.g., enjoyment). In addition, the low sRPE values for the current protocols reinforces the low loading experienced by subjects despite completing 8 "all out" efforts in both sessions, also allowing comparisons with other exercise modalities with a well-accepted method for training monitoring [40]. ...
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Background: To the authors' knowledge, there have been no studies comparing the acute responses to "all out" efforts in concentric (isoinertial) vs. eccentric (isovelocity) cycling. Methods: After two familiarization sessions, 12 physically active men underwent the experimental protocols consisting of a 2-min warm-up and 8 maximal efforts of 5 s, separated by 55 s of active recovery at 80 rpm, in concentric vs. eccentric cycling. Comparisons between protocols were conducted during, immediately after, and 24-h post-sessions. Results: Mechanical (Work: 82,824 ± 6350 vs. 60,602 ± 8904 J) and cardiometabolic responses (mean HR: 68.8 ± 6.6 vs. 51.3 ± 5.7% HRmax, lactate: 4.9 ± 2.1 vs. 1.8 ± 0.6 mmol/L) were larger in concentric cycling (p < 0.001). The perceptual responses to both protocols were similarly low. Immediately after concentric cycling, vertical jump was potentiated (p = 0.028). Muscle soreness (VAS; p = 0.016) and thigh circumference (p = 0.045) were slightly increased only 24-h after eccentric cycling. Serum concentrations of CK, BAG3, and MMP-13 did not change significantly post-exercise. Conclusions: These results suggest the appropriateness of the eccentric cycling protocol used as a time-efficient (i.e., ~60 kJ in 10 min) and safe (i.e., without exercise-induced muscle damage) alternative to be used with different populations in future longitudinal interventions.
... The Rating of Perceived Exertion (RPE) is another commonly used method for assessing the internal training load [30][31][32][33]. Studies have showed moderate to large correlations between the heart rate and blood lactate concentrations [34,35]. ...
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Knowledge in the scientific domain of individual medley (IM) swimming training over a competitive season is limited. The purpose of this study was to propose a detailed coaching framework incorporating the key elements of a periodized training regimen for a 400 m IM swimmer. This framework was based on the available coaching and scientific literature and the practical experience and expertise of the collaborating authors. The season has been divided in two or three macrocycles, further divided in three mesocycles each (six or nine mesocycles in total), in alignment with the two or three main competitions in each macrocycle. The principal training contents to develop during the season expressed in blood lactate zones are: aerobic training (~2 mmol·L−1), lactate threshold pace (~4 mmol·L−1) and VO2max (maximum oxygen uptake) (~6 mmol·L−1). Strength training should focus on maximum strength, power and speed endurance during the season. Altitude training camps can be placed strategically within the training season to promote physiological adaptation and improvements in performance. A well-constructed technical framework will permit development of training strategies for the 400 m IM swimmer to improve both training and competitive performance.
... The question was "How intense was your session?." The players responded to this question 30 min after the end of training or match session (Foster et al., 2021). Durations of training sessions were measured. ...
Article
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The objectives of this study were to quantify the matches and training workload in micro-cycles of an elite young soccer team considering field position and to explain meso-cycles based on change of weekly acute (wAWL), chronic load (wCWL), acute-to-chronic workload ratio, training monotony (wTM), and training strain (wTS) between early-, mid-, and end-season periods considering playing position and whole team. Twenty-six under-16 elite young soccer players participated in this study, including six wide defenders and wide midfielders (WM), five central defenders (CD) and central midfielders, and four strikers (ST). Daily monitoring was performed by players for 20 weeks with the rating of perceived exertion using the Borg CR-10 scale. In comparison with early-season, results showed that there was a significant increase, in all playing positions, in wAWL and wCWL (except ST) and in wTM (except CD and ST) compared with end-season. On the other hand, there were significant reductions in wTS in CD, WM, and ST at the end-season. According to the results, coaches should consider the field position in different situations. Differences between training workload and matches can be a good guide for coaches, who have a special understanding of what causes the most load in training programs. Excessive training workload can potentially cause injury to adolescent athletes and controlling wTM can prevent this.
... RPE was obtained using the CR10 Borg RPE scale [15,16]. The scale was explained before the exercise and was recorded 2 min after the end of each test. ...
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CrossFit ® training is one of the fastest-growing fitness activities in the world due to its varied functional movement and competition experience. The performance is present in almost every workout of the day (WOD); however, there is a lack of knowledge in the science that did not allow us to fully understand the performance determinants of CrossFit WOD's like we do for other individual or team sports. The purpose of this study was to analyze the physical and physiological variables of recreational trained CrossFit athletes during one of the most famous WOD, FRAN, and to identify which variables best determine performance. Methods: Fifteen CrossFit practitioners performed, alone on separate days, 1RM and a maximum of repetitions of pull-ups test, 1RM and a maximum of repetitions of thrusters with 95 lb/43.2 kg, FRAN CrossFit WOD, and 2K Row test. Results: Blood lactate concentrate, HRmáx, HRav, and RPE achieved higher values for 2K Row and maximum repetitions of thrusters. Maximum repetition of thrusters and pull-ups, 1RM of thrusters, and 2K Row resulted in moderate to strong correlation with FRAN performance (r = −0.78; r = −0.58; r = −0.67; r = 0.63, respectively). Conclusions and practical applications: FRAN performance was strongly related to maximal and endurance strength training of thrusters, which should be prioritized .
... For example, the session rating of perceived exertion (s-RPE), which is the product of exercise duration (s) and RPE, is probably the most widely used metric in sport and exercise science. 69 Additionally, the product of exercise duration (s) and HR (bpm) is also commonly used. 49,50,67 Undoubtably, these metric holds great practical application for sport and exercise scientists. ...
Article
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Despite the International System of Units (SI), as well as several publications guiding researchers on correct use of terminology, there continues to be widespread misuse of mechanical terms such as ‘work’ in sport and exercise science. A growing concern is the misuse of the term ‘load’. Terms such as ‘training load’ and ‘PlayerLoad’ are popular in sport and exercise science vernacular. However, a ‘load’ is a mechanical variable which, when used appropriately, describes a force and therefore should be accompanied with the SI-derived unit of the newton (N). It is tempting to accept popular terms and nomenclature as scientific. However, scientists are obliged to abide by the SI and must pay close attention to scientific constructs. This communication presents a critical reflection on the use of the term ‘load’ in sport and exercise science. We present ways in which the use of this term breaches principles of science and provide practical solutions for ongoing use in research and practice.
... Although training intensity and duration were originally based on the relative percent concept of Karvonen, more contemporary approaches have emphasized threshold-based prescription [4], and on simple psychophysiological approaches like rating of perceived exertion [5] and the Talk Test [6]. These latter approaches are somewhat evaluation independent in terms of prescribing the training load, but evaluation is still important in terms of assessing the outcomes of training. ...
Article
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Ever since the farm boy, Milo of Crotone, lifted a growing bullock every day, to become the strongest man in the world, and six-time champion of the ancient Olympic Games, we have known about the principle of progression of exercise training [...]
... This fact is in line with the recent historical perspective reflected by Foster et al. [26], which confirmed that the training impulse concept and internal workload assessed by the RPE are able to account for both positive and negative training outcomes and could be tools to understand the training process as a way to optimize outcomes. Consequently, the competitive calendar in team sports requires an optimization of the training plan and organization, mainly due to the short preparation time and the need to maintain athletes' high levels of performance in competitions [27,28]. ...
Article
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The purpose of this study was to compare the external load, internal load, and technical efficacy between the first and the second matches (M1 and M2) occurring in congested fixtures (two matches in two days) using the number of sets as a moderating factor. An observational analytic research design was adopted. Data from official volleyball matches were collected during the first competitive period of the championship, comprising 14 competitive games within 10 weeks. Ten male elite volleyball athletes (age: 21.7 ± 4.19 years of age; experience: 6.2 ± 3.8 years; body mass: 85.7 ± 8.69 kg; height: 192.4 ± 6.25 cm; BMI: 23.1 ± 1.40 kg/m2) participated in this study. Players were monitored for external load (number of jumps and height of jumps) and internal load (using the rate of perceived exertion-RPE). Additionally, notational analysis collected information about attack efficacy and receptions made during matches. The mixed ANOVA revealed no significant interaction between time (M1 vs. M2) and number of sets for number of jumps per minute (p = 0.235; η 2 p = 0.114), mean jump height (p = 0.076; η 2 p = 0.193), RPE (p = 0.261; η 2 p = 0.106), attack efficacy (p = 0.346; η 2 p = 0.085), Positive reception (p = 0.980; η 2 p = 0.002) and Perfect reception (p = 0.762; η 2 p = 0.022). In conclusion, congested fixtures do not seem to affect the performance of volleyball players negatively.
... In this regard, the approach of the current case report agrees with the recent suggestions on the need for combining both internal and external training load indices for optimized training load monitoring in runners [13]. Therefore, the concurrent use of sRPE and HRV would expand the validity of monotony scores for training monitoring [14], which should be confirmed in further studies. ...
Article
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Background: The association between heart rate variability (HRV), training load (TL), and performance is poorly understood. Methods: A middle-aged recreational female runner was monitored during a competitive 20-wk macrocycle divided into first (M1) and second mesocycle (M2) in which best performances over 10 km and 21 km were recorded. Volume (km), session rating of perceived exertion (sRPE), TL, and monotony (mean TL/SD TL) were the workload parameters recorded. The root mean square of the successive differences in R-R intervals (RMSSD), its coefficient of variation (RMSSDcv), and the RMSSD:RR ratio were the HRV parameters monitored. Results: During M2, RMSSD (p = 0.006) and RMSSD:RR (p = 0.002) were significantly increased, while RR was significantly reduced (p = 0.017). Significant correlations were identified between monotony and volume (r = 0.552; p = 0.012), RR (r = 0.447; p = 0.048), and RMSSD:RR (r = -0.458; p = 0.042). A sudden reduction in RMSSD (from 40.31 to 24.34 ms) was observed the day before the first symptoms of an influenza. Conclusions: The current results confirm the practicality of concurrent HRV and sRPE monitoring in recreational runners, with the RMSSD:RR ratio indicative of specific adaptations. Excessive training volume may be associated to both elevated monotony and reduced RMSSD:RR. Identification of mesocycle patterns is recommended for better individualization of the periodization used.
... It can be said that the traditional inventory management model has been unable to adapt to the requirements of inventory management in the information age due to the lack of a supply chain concept [3]. With the help of the enterprise management information system (ERP), the information of inventory management and control is an effective way to solve the traditional inventory management problems. ...
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Nowadays, more and more companies are applying total inventory management as well as human resource management as one of the core concepts of the enterprise management platform. ERP is a resource allocation platform based on information technology applications to have the advantage of advanced and comprehensive management ideas to provide planning and operation software for enterprise managers and employees. This paper describes in detail the ERP system, as well as its planning and control ideas, its ideas, and the idea of internal control of enterprises in line with the rapid development of the information economy and knowledge economy in today’s situation; ERP systems also have some inefficiencies and other situations; in response to this situation, this paper also analyzes the ERP system by analyzing the application of ERP systems in enterprises, from the market function information system and ERP system in the application to inventory management as well as to human resource management for decision-making, exploring its deficiencies in the inventory management system and human resource system and then proposing corresponding improvement methods and corresponding development measures. Enterprises can use the improved advanced information technology to enhance the unity and sharing of data and fine management and improve operational efficiency, and enterprises can achieve standardized and process-oriented management of daily operations by using the improved ERP to control various business processes such as production, procurement, and sales and realize the collaborative processing of financial and business processes.
... 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. ...
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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.
... 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). ...
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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. ...
Article
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). ...
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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. ...
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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]. ...
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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]. ...
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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. ...
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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.
... 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. ...
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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.
... Depending on the technology available and specific demands of the sport, various metrics may be evaluated to quantify workloads of athletes. Internal workload is often quantified using objective measures of physiological responses (i.e., heart rate, hormonal fluctuations, training impulses, etc.) [1] or subjective measures such as session ratings of perceived exertion (sRPE), perceived recovery status, perceived soreness, etc. [3]. External workload can be quantified using various measures of movement kinematics, derived from accelerometry, global positioning systems (GPS) [4], or local positioning systems (LPS) [1,5]. ...
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Research quantifying the unique workload demands of starters and reserves in training and match settings throughout a season in collegiate soccer is limited. Purpose: The purpose of the current study is to compare accumulated workloads between starters and reserves in collegiate soccer. Methods: Twenty-two NCAA Division III female soccer athletes (height: 1.67 ± 0.05 m; body mass: 65.42 ± 6.33 kg; fat-free mass: 48.99 ± 3.81 kg; body fat %: 25.22 ± 4.78%) were equipped with wearable global positioning systems with on-board inertial sensors, which assessed a proprietary training load metric and distance covered for each practice and 22 matches throughout an entire season. Nine players were classified as starters (S), defined as those playing >50% of playing time throughout the entire season. The remaining 17 were reserves (R). Goalkeepers were excluded. A one-way ANOVA was used to determine the extent of differences in accumulated training load throughout the season by player status. Results: Accumulated training load and total distance covered for starters were greater than reserves ((S: 9431 ± 1471 vs. R: 6310 ± 2263 AU; p < 0.001) and (S: 401.7 ± 31.9 vs. R: 272.9 ± 51.4 km; p < 0.001), respectively) throughout the season. Conclusions: Starters covered a much greater distance throughout the season, resulting in almost double the training load compared to reserves. It is unknown if the high workloads experienced by starters or the low workloads of the reserves is more problematic. Managing player workloads in soccer may require attention to address potential imbalances that emerge between starters and reserves throughout a season.
... Players performed HIIT sessions, which consisted of 15 s of intermittent running at 90-100% of players' velocity at IFT (VIFT), followed by 15 s of resting (Table 1). The rating of perceived exertion (RPE) was obtained using the category ratio scale (6)(7)(8)(9)(10)(11)(12)(13)(14)(15)(16)(17)(18)(19)(20) to calculate the internal training load (ITL) immediately after the completion of each session [30]. The scale was introduced at the beginning in order to familiarise the players. ...
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This study aimed to compare the order effects of combined small-sided games (SSGs) and high-intensity interval training (HIIT) on the psychophysiological responses and physical and technical performances of young soccer players. Twenty-four soccer players (aged 14.63 ± 0.71 years) were randomly divided into SSGs + HIIT (n = 12) and HIIT + SSGs (n = 12) for 6 weeks. The SSGs consisted of two 4–16 min rounds of 2, 3, and four-a-side games with 2 min of passive resting, whereas the HIIT consisted of 6–10 min of high-intensity runs at varying intensities (from 90 to 100%). Pre-test and post-test elements included a 5–30 m sprint test, countermovement jump test, zigzag agility test with the ball and without the ball, repeated sprint ability test, speed dribbling ability test, three-corner run test, and Yo-Yo Intermittent Recovery Test level 1. Both combined training interventions produced similar improvements in physical performance and technical responses (p ≥ 0.05, d values ranging from 0.40 to 1.10). However, the combined HIIT + SSGs training produced meaningfully lower perceived exertion (p = 0.00, d = 2.98) and greater physical enjoyment (p = 0.00, d = 4.28) compared with the SSGs + HIIT intervention. Furthermore, the SSGs + HIIT group showed a higher training load than those from the HIIT + SSGs group for all weeks (p ≤ 0.05, d values ranging from 1.36 to 2.05). The present study’s results might be used by coaches and practitioners to design training programmes for youth soccer players.
... (2) Given that intensity appears to be the variable with the most significant influence on the responses, it would be recommendable to monitor exercise intensity during the race. The use of heart rate monitors that allow the %HR max or %HR reserve (Karvonen, 1957) to be recorded would be desirable, but otherwise, it could be assessed with a rating-of-perceived-exertion scale (Foster et al., 2021). (3) Considering the importance of dehydration on physiological responses, aspects that can influence it, such as temperature and humidity, should be reported. ...
Article
This study systematically reviewed and quantified the effects of running a long-distance race (LDR) on heart rate variability (HRV) and arterial stiffness (AS). All types of races of a distance equal to or greater than a marathon (≥42.2 km) were included. A total of 2,220 articles were identified, 52 were included in the qualitative analysis, and 48 were meta-analysed. The standardised mean difference pre- and post-race of various time-domain and frequency-domain indices of HRV, mean arterial blood pressure (MAP), systolic blood pressure (SBP), diastolic blood pressure (DBP) and carotid-femoral pulse wave velocity (cfPWV) was calculated. Regarding HRV, there was a significant decrease in most of the variables considered as markers of parasympathetic activity, indicating a shift of autonomic balance towards a reduced vagal tone. Regarding vascular variables, there was a significant drop in blood pressure and reduced AS. In conclusion, running an LDR seems to have a considerable acute effect on the autonomic nervous system, haemodynamics, and vascular properties. The observed effects could be categorised within the expected acute responses to long-lasting, strenuous exercise.
... 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. ...
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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.
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Introduction: Amid the historic coronavirus (SARS-CoV-2) global pandemic (i.e., COVID-19), public health authorities have recommended the use of facial coverings in order to mitigate the spread of this highly contagious pathogen. While coaches, self-training athletes, and the general public seek to continue their exercise programs in a safe and modified format, there is currently limited research available on the perceptual and physiological effects of facemask usage. This study was conducted to understand the physiological and perceptual effects produced during self-paced running while wearing a face mask. Methods: Eleven healthy college students performed three randomly sequenced 3200-meter self-paced running trials, each with a different masked condition (no-mask, surgical mask, and an N95 mask). Heart rate, Rating of Perceived Exertion (RPE), Rating of Perceived Dyspnea (RPD), pace, and completion time were measured for each trial. Prior to testing, subjects completed a PAR-Q+, a COVID-19 screening questionnaire, and a subjective running history questionnaire that was used to document prior running experience. Collectively, the participants reported an average weekly running frequency of 2.9 ± 1.2 days/week and an average running distance of 3.3 ± 1.8 miles/workout. Alpha was set at p < .05 to achieve statistical significance. Results: No significant difference was found between masked conditions. Wearing a mask did not have a significant effect on pace, completion time, or heart rate. Session RPE was significantly higher in the N95 condition (14.6 ± 2.21) compared to the control (12.8 ± 1.99) condition. Both the surgical (2.4 ± 1.12) and N95 conditions (3.2 ± 1.29) had significantly higher perceived dyspnea scores compared to the control (1.4 ± 1.07) group. Conclusions: During self-paced running, healthy young college students tend to maintain their normal running pace and total completion time while compensating with higher RPE and dyspnea scores.
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O futebol é compreendido como um sistema complexo e dinâmico. As equipes, portanto, são entendidas como um microssistema social, de modo que as ações no jogo emergem da sinergia entre diversas facetas do desempenho esportivo (Balague, Torrents, Hristovski, Davids, & Araújo, 2013; J. Garganta, 1995). Essencialmente, essas facetas podem ser avaliadas com o objetivo de fornecer feedbacks contínuos e precisos para os treinadores e jogadores sobre o desenvolvimento dos componentes do jogo e da vida (Carling, Reilly, & Williams, 2008). Pela natureza complexa e dinâmica do jogo, essas facetas sofrem influências mútuas umas sobre as outras, o que exige dos treinadores um entendimento sistêmico deste processo (Balagué, Torrents, Hristovski, & Kelso, 2017). Finalmente, como o tempo é precioso, é necessária uma integração ágil dos dados obtidos no dia-a-dia dos clubes. A avaliação deve, portanto, começar com objetivos específicos e propósitos precisos. Os instrumentos de avaliação devem modelar-se ao contexto e as características dos jogadores, com foco no desenvolvimento de ações no e para o jogo. Quando realizadas de maneira sistemáticas, contribuirão para o acompanhamento da evolução dos jogadores e fornecerão bases para ajustes e melhorias diretas nas intervenções a curto prazo. Os protocolos de avaliação devem ser consistentes com a noção de aquisição e manutenção do desempenho em um processo não linear. Nesse caso, a adaptabilidade as demandas do jogo são mais relevantes do que a simples aquisição ótima das facetas do desempenho, especialmente no caso de jovens jogadores. Neste capítulo, conceptualizamos o aspecto sinérgico das facetas do desempenho no futebol e mostramos possíveis avaliações para cada uma delas. Destacamos também o aspecto integrativo e multidisciplinar do desempenho, assim como elementos transversais ao processo de formação, tais como a idade, sexo, história e cultura esportiva dos jogadores. Por fim, oferecemos bases teóricas sólidas e soluções práticas para o leitor entender o processo de avaliação e treinamento respeitando sua natureza complexa e dinâmica.
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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.
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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.
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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.
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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.
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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).
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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.
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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.
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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.
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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.
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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.
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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.
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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.
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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.
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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.
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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.