sRPE Training Load Research Articles

Training loads and microcycle periodisation in Italian Serie A youth soccer players

ABSTRACT Microcycles are fundamental structures for training prescription and load management, helping to optimise training effects and performance. This study quantified external and internal loads of Italian Serie A youth soccer players across competitive weeks and their periodisation within microcycles. Data were collected from 90 players belonging to four age groups (under-19, -17, -16, -15) across a season. Methods of monitoring external [duration and global navigation satellite systems (GNSS)] and internal load [heart rate (HR) and rating of perceived exertion (RPE)] were employed. Linear mixed models determined differences in training loads across age groups, training days and player positions. Under-19 and under-17 players trained five times per week, while younger players trained four times. Late-stage academy players (under-19 and -17) demonstrated higher weekly accumulated external and sRPE training load compared to their younger counterparts (p < 0.05 between groups). Weekly accumulated HR internal loads were higher in under-15 players (p < 0.05 between groups). Marked fluctuations of daily load were observed across microcycles in under-19 and under-17 groups (p < 0.05 between days). These findings highlight progressive increases in training load throughout the development pathway, with late-stage academy players training with higher frequency, volume and marked periodisation compared to younger players.

Comparison of acute physiological responses between one long and two short sessions of moderate-intensity training in endurance athletes.

To compare acute physiological responses and perceived training stress between one long and two short time- and intensity-matched sessions of moderate-intensity training in endurance athletes. Fourteen male endurance athletes (VO2max: 69.2 ± 4.2mL·min-1·kg-1) performed one 6 × 10-min interval session (SINGLE) and two 3 × 10-min interval sessions interspersed with 6.5h recovery (DOUBLE) of moderate-intensity training on two separate days, while running in the laboratory, using a counterbalanced cross-over trial. The two training days were separated into a first part/session (interval stage 1-3) and second part/session (interval stage 4-6). Respiratory variables, heart rate (HR), blood lactate concentrations (BLa), and rating of perceived exertion (RPE) were collected during sessions, whereas supine heart rate (HR) was assessed in a 60-min recovery period following sessions. Measures of perceived training stress (1-10) were assessed in the morning of the subsequent day. HR, Bla, and RPE increased in the second compared to first part of SINGLE (168 ± 7 vs. 173 ± 7bpm, 2.60 ± 0.75 vs. 3.01 ± 0.81mmol·L-1, and 13.4 ± 1.0 vs. 14.8 ± 1.1-point, respectively, all p < 0.05). HR and Bla decreased in the second compared to first session of DOUBLE (171 ± 9 vs. 166 ± 9bpm and 2.72 ± 0.96 vs. 2.14 ± 0.65mmol·L-1, respectively, both p < 0.05). SINGLE revealed higher supine HR in the recovery period following sessions (65.4 ± 2.5 vs. 60.7 ± 2.5bpm p < 0.05), session RPE (sRPE, 7.0 ± 1.0 vs. 6.0 ± 1.3-point, p = .001) and sRPE training load (929 ± 112 vs. 743 ± 98, p < 0.001) compared to DOUBLE. In the subsequent morning, increased levels of perceived fatigue and muscle soreness were observed following SINGLE compared to DOUBLE (7.0 ± 2.5 vs. 8.0 ± 1.0-point, p = .049 and 6.0 ± 2.5 vs. 7.0 ± 2.5-point, p = .002, respectively). One long moderate-intensity training session was associated with a duration-dependent "drift" in physiological responses compared to two short time- and intensity-matched sessions, thereby suggesting a higher overall training stimulus. Simultaneously, the lower cost of the two shorter sessions indicates that such organization could allow more accumulated time at this intensity. Overall, these findings serve as a starting point to better understand the pros and cons of organizing moderate-intensity training as one long versus shorter sessions performed more frequently (e.g., as "double threshold training") in endurance athletes.

The Relationships Between External and Internal Training Loads in Mixed Martial Arts.

As a multidisciplined combat sport, relationships between external and internal training loads and intensities of mixed martial arts (MMA) have not been described. The aim of this study was to determine the external loads and intensities of MMA training categories and their relationship to internal loads and intensities. Twenty MMA athletes (age = 23.3 [5.3] y, mass = 72.1 [7.2]kg, stature = 171.5 [8.4]cm) were observed for 2 consecutive weeks. Internal load and intensity (session rating of perceived exertion [sRPE]) were calculated using the Foster RPE for the session overall (sRPE-training load [TL]) and segmented RPE (segRPE-TL) for each training category: warm-up, striking drills, wrestling drills, Brazilian jiujitsu (BJJ) drills, striking sparring, wrestling sparring, BJJ sparring, and MMA sparring. External load and intensity were measured via Catapult OptimEye S5 for the full duration of each session using accumulated Playerload (PLdACC) and PLdACC per minute (PLdACC·min-1). Differences in loads between categories and days were assessed via Bayesian analysis of variance (BF10 ≥ 3). Predictive relationships between internal and external variables were calculated using Bayesian regression. Session overall sRPE-TL = 448.6 (191.1)arbitrary units (AU); PLdACC = 310.6 (112)AU. Category segRPE-TL range = 33.8 (22.6)AU (warm-up) to 122.8 (54.6)AU (BJJ drills). Category PLdACC range = 44 (36.3)AU (warm-up) to 125 (58.8)AU (MMA sparring). Neither sRPE-TL nor PLdACC changed between days. PLdACC was different between categories. Evidence for regressions was strong-decisive except for BJJ drills (BF10 = 7, moderate). R2 range = .50 to .77, except for warm-up (R2 = .17), BJJ drills (R2 = .27), BJJ sparring (R2 = .49), and session overall (R2 = .13). While MMA training categories may be differentiated in terms of external load, overall session external load does not change within or between weeks. Resultant regression equations may be used to appropriately plan MMA technical/tactical training loads.

Effects of Dryland Training During the COVID-19 Lockdown Period on Swimming Performance.

To examine the effect of dryland training during an 11-week lockdown period due to COVID-19 on swimming performance. Twelve competitive swimmers performed 50- and 300-m maximum-effort tests in their preferred stroke and 200-, 400-, and four 50-m front crawl sprints (4 × 50m) before and after the lockdown period. Critical speed as an index of aerobic endurance was calculated using (1)50-, 300-, and (2)200-, 400-m tests. Blood lactate concentration was measured after the 400- and 4 × 50-m tests. To evaluate strength-related abilities, the dryland tests included handgrip and shoulder isometric strength. Tethered swimming force was measured during a 10-second sprint. During the lockdown period, dryland training was applied, and the session rating of perceived exertion training (sRPE) load was recorded daily. sRPE training load during the lockdown was decreased by 78% (16%), and critical speed was reduced 4.7% to 4.9% compared to prelockdown period (P < .05). Performance time in 200, 300, and 400m deteriorated 2.6% to 3.9% (P < .05), while it remained unaltered in 4 × 50- and 50-m tests (P > .05). Tethered force increased 9% (10%) (P < .01), but handgrip and shoulder isometric force remained unaltered (P > .05). Blood lactate concentration decreased 19% (21%) after the 400-m test and was unchanged following the 4 × 50-m tests (P > .05). Performance deterioration in the 200, 300, and 400m indicates reduced aerobic fitness and impaired technical ability, while strength and repeated-sprint ability were maintained. When a long abstention from swimming training is forced, dryland training may facilitate preservation in short-distance but not middle-distance swimming performance.

Are Measurement Instruments Responsive to Assess Acute Responses to Load in High-Level Youth Soccer Players?

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.MethodsData 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).ConclusionResults 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.

Monitoring the Heart Rate Variability Responses to Training Loads in Competitive Swimmers Using a Smartphone Application and the Banister Impulse-Response Model.

First, to examine whether heart rate variability (HRV) responses can be modeled effectively via the Banister impulse-response model when the session rating of perceived exertion (sRPE) alone, and in combination with subjective well-being measures, are utilized. Second, to describe seasonal HRV responses and their associations with changes in critical speed (CS) in competitive swimmers. A total of 10 highly trained swimmers collected daily 1-minute HRV recordings, sRPE training load, and subjective well-being scores via a novel smartphone application for 15 weeks. The impulse-response model was used to describe chronic root mean square of the successive differences (rMSSD) responses to training, with sRPE and subjective well-being measures used as systems inputs. Changes in CS were obtained from a 3-minute all-out test completed in weeks 1 and 14. The level of agreement between predicted and actual HRV data was R2 = .66 (.25) when sRPE alone was used. Model fits improved in the range of 4% to 21% when different subjective well-being measures were combined with sRPE, representing trivial-to-moderate improvements. There were no significant differences in weekly group averages of log-transformed (Ln) rMSSD (P = .34) or HRV coefficient of variation of Ln rMSSD (P = .12); however, small-to-large changes (d = 0.21-1.46) were observed in these parameters throughout the season. Large correlations were observed between seasonal changes in HRV measures and CS (changes in averages of Ln rMSSD: r = .51, P = .13; changes in coefficient of variation of Ln rMSSD: r = -.68, P = .03). The impulse-response model and data collected via a novel smartphone application can be used to model HRV responses to swimming training and nontraining-related stressors. Large relationships between seasonal changes in measured HRV parameters and CS provide further evidence for incorporating a HRV-guided training approach.

The Relationships between Internal and External Load Measures for Division I College Football Practice.

The aim of this study is to explore the relationships between internal and external load measures in American football. Thirty football players wore a portable integrated monitor unit for 10 weeks during the fall football season. Relationships between internal and external load measurements were determined. Internal load consisted of heart rate zones and heart rate-derived measures and session Ratings of Perceived Exertion (sRPE). External load consisted of distance in different speed zones, total distance traveled, and accelerations. There were many significant positive relationships, but the meaningful relationships (r > 0.5) were between heart rate-derived measures of load (Training Impulse and heart rate reserve) and low-intensity movement and total distance. Only accelerations between 1 and 1.99 m·s−2 were moderately correlated to heart rate-derived internal load. RPE values alone did not correlate strong enough with any of the measure but sRPE training load (sRPE-TL) correlated to most external values. Overall, moderate correlations were present between heart rate-derived internal load to total distance and lower intensity movement. sRPE-TL values had high correlations but were highly dependent on duration, not perceived exertion. When addressing load in American football, duration of the session is a key component in determining internal load as HR data and sRPE alone do not correlate highly with external loads.

Characterising the application of the "progressive overload" principle of exercise training within cardiac rehabilitation: A United Kingdom-based community programme.

BackgroundRecent concerns have cast doubt over the effectiveness of cardiac rehabilitation [CR] programmes for improving cardiorespiratory fitness [CRF] in patients with a history of cardiac disease in the United Kingdom [UK]. We aimed to characterise the weekly progression of exercise training dose over an 8-week Phase III CR programme as we felt this may be partly responsible for the lack of improvement in CRF reported in previous studies.DesignObservational study.MethodsWe evaluated a community-based Phase III CR programme in the UK. During each training session, patients wore an Apple Watch and the weekly progression of exercise training dose/load was quantified. The analysis was based on 332 individual training sessions. Exercise intensity [% heart rate reserve] during the cardiovascular [CV] exercise training component [%HRR-CV], CV training duration; estimated changes in cardiorespiratory fitness [change in estimated metabolic equivalents (METs)]; session rating of perceived exertion [sRPE], sRPE training load [sRPE-TL], and exercise training impulse [TRIMP] were evaluated.ResultsThirty cardiac patients [83% male; age [SD] 67.0 [10.0] years; body mass index [SD] 28.3 [4.6] kg∙m-2] were recruited to an 8-week programme [16 sessions in total]. Bayesian repeated-measures ANOVA indicated anecdotal evidence for the alternative hypothesis for changes in %HRR-CV (BF10 = 0.61), sRPE (BF10 = 1.1), and change in estimated METs (BF10 = 1.2) during CR. Conversely, Bayesian repeated-measures ANOVA showed extreme evidence for changes in CV training duration (BF10 = 2.438e+26), TRIMP (BF10 = 71436), and sRPE-TL (BF10 = 779570).ConclusionThe key exercise training principle of progressive overload was only partially applied. Increases observed in exercise dose were due to increases in the duration of CV training, rather than combined with increases in exercise intensity [%HRR-CV and sRPE]. Accordingly, allied health professionals must ensure that exercise intensity is more consistently progressed to optimise the exercise stimulus and improvements in CRF and patient outcomes.

Factors that Influence Session-Rating of Perceived Exertion in Elite Gaelic Football.

Malone, S, Hughes, B, Roe, M, Mangan, S, and Collins, K. Factors that influence session-rating of perceived exertion in elite Gaelic football. J Strength Cond Res 34(4): 1176-1183, 2020-The current investigation examined the relationships between external training load (TL) measures and the session rating of perceived exertion (s-RPE) within Gaelic football players. Furthermore, we examined the effect that player experience, playing position, and 1-km time trial (TT) performance had on perception of TL. Physical performance (total distance, high-speed distance, very high-speed distance, max velocity, total accelerations, and maximal velocity exposures) and perceived TL (s-RPE) data were collected from 45 elite intercounty Gaelic football players (mean ± SD age of 24.2 ± 2.9 years; height: 180 ± 7 cm; mass: 81 ± 7 kg) over a 1-year period this resulted in 4,095 individual training session data being collected. There were moderate to very large associations between s-RPE and distance measures. Post hoc analysis revealed that the 0-1-year group had a higher s-RPE TL than the 2-3-year (d = 0.84 ± 0.33, small), 4-6-year (d = 0.91 ± 0.30, small), and 7+ year (d = 0.81 ± 0.30, small) groups. Midfielders reported higher s-RPE when compared with all positions (d = 1.21 ± 0.21, moderate). Half-backs (d = 0.81 ± 0.30, small), and half-forwards (d = 0.84 ± 0.31, small) had a higher s-RPE TL than the full-backs and full-forwards when external TL was accounted for (d = 1.21 ± 0.58, moderate). When aerobic fitness was considered, a 1.2% AU increase in s-RPE TL per 1 second increase in TT time (90% confidence limits: 1.07-2.64) when external TL was held constant was observed. The current investigation has shown moderate to very large associations between s-RPE and distance measures. When experience and fitness were considered as potential moderators of TL, it was observed that a given external TL may result in different internal responses between athletes. This potentially leaves individuals at risk of overtraining or failing to elicit positive adaptation. It is therefore vital that coaches and trainers give consideration to these mediators of s-RPE TL.

Validity of Session-Rate of Perceived Exertion to Quantify Training Loads in Paralympic Swimmers.

Sinnott-O'Connor, C, Comyns, TM, and Warrington, GD. Validity of session-RPE to quantify training loads in Paralympic swimmers. J Strength Cond Res 35(9): 2611-2615, 2021-Multiple measures may be used by coaches to quantify training load (TL). The application of heart rate (HR) has limitations in swimming and in Paralympic swimmers, and it may not always be a suitable measure. Therefore, the aim of this study was to determine the validity and reliability of the session-rate of perceived exertion (sRPE) method for quantifying internal TL in Paralympic swimmers. A further aim was to examine the relationship between athlete and coach perceptions of sRPE TL. Four international Paralympic swimmers selected to compete in Rio 2016 Paralympic Games participated in this study. Heart rate, RPE, and session duration were recorded for 30 training sessions of varied intensities across a 6-week home training period to quantify TL. Significant high to very high positive correlations were observed between sRPE and 3 HR-based measures-Banister's, Edwards, and Lucia's TRIMP (r = 0.68, 0.66, 0.74, p < 0.01, respectively). Moderate correlations were observed between sRPE and distance measures (r = 0.53, p < 0.05) but were lower than those observed with HR-based measures. A 2-way analysis of variance identified significant differences in the sRPE ratings between coaches and athletes (F(2, 108) = 170.4, p < 0.01, η2 = 0.75). The results of this study suggest that the sRPE method may be an appropriate monitoring tool for quantifying TL during water-based training using a single measure in Paralympic swimmers.

Transitioning from club to national teams: Training and match load profiles of international footballers

ObjectivesTo quantify and profile the training and match loads of international footballers as they transition from club-to-camp-to-tournament contexts during multiple international tournaments. DesignRetrospective single-cohort observational study. MethodsExternal (session duration and count) and internal (session Rating of Perceived Exertion [s-RPE]) load data of all outfield players from the same national team were compared between club, pre-tournament camp and initial tournament phases of 3 recent international competitions. Further, load profiles were compared between each phase based on the acute:chronic (A/C) ratio using a 7 to 21-day ratio. ResultsModerate-to-large effect sizes existed for increased number of sessions (ES=1.92; 90% CI: 1.56, 2.27) and s-RPE training load (ES=1.16; 0.84, 1.48) from club to camp. Conversely, transitioning from camp-to-tournament showed very large effects for decreased number of training sessions (ES=−3.17; −3.47, −2.86) and s-RPE training load (ES=−2.05; −2.35, −1.75), alongside increased number of matches (ES=1.87; 1.55, 2.18) and s-RPE match load (ES=1.57; 1.25, 1.89). Consequently, a moderate effect was evident for increased A/C ratio during the club-to-camp transition (ES=1.02; 0.70, 1.33), while a moderate decrease in the A/C ratio occurred during the tournament (ES=−0.76; −1.06, −0.46). ConclusionsInternational footballers showed expected increased training load when entering into pre-tournament camps, predominately via increased number of training sessions. Subsequent reductions in training volume coincide with increased match volume, though total load decreases. Such profiles provide insight into load accumulation transitioning from club to national teams in international footballers.

The Relationships Between Internal and External Measures of Training Load and Intensity in Team Sports: A Meta-Analysis.

The associations between internal and external measures of training load and intensity are important in understanding the training process and the validity of specific internal measures. We aimed to provide meta-analytic estimates of the relationships, as determined by a correlation coefficient, between internal and external measures of load and intensity during team-sport training and competition. A further aim was to examine the moderating effects of training mode on these relationships. We searched six electronic databases (Scopus, Web of Science, PubMed, MEDLINE, SPORTDiscus, CINAHL) for original research articles published up to September 2017. A Boolean search phrase was created to include search terms relevant to team-sport athletes (population; 37 keywords), internal load (dependent variable; 35 keywords), and external load (independent variable; 81 keywords). Articles were considered for meta-analysis when a correlation coefficient describing the association between at least one internal and one external measure of session load or intensity, measured in the time or frequency domain, was obtained from team-sport athletes during normal training or match-play (i.e., unstructured observational study). The final data sample included 122 estimates from 13 independent studies describing 15 unique relationships between three internal and nine external measures of load and intensity. This sample included 295 athletes and 10,418 individual session observations. Internal measures were session ratings of perceived exertion (sRPE), sRPE training load (sRPE-TL), and heart-rate-derived training impulse (TRIMP). External measures were total distance (TD), the distance covered at high and very high speeds (HSRD≥13.1-15.0kmh-1 and VHSRD≥16.9-19.8kmh-1, respectively), accelerometer load (AL), and the number of sustained impacts (Impacts>2-5G). Distinct training modes were identified as either mixed (reference condition), skills, metabolic, or neuromuscular. Separate random effects meta-analyses were conducted for each dataset (n=15) to determine the pooled relationships between internal and external measures of load and intensity. The moderating effects of training mode were examined using random-effects meta-regression for datasets with at least ten estimates (n=4). Magnitude-based inferences were used to interpret analyses outcomes. During all training modes combined, the external load relationships for sRPE-TL were possibly very large with TD [r=0.79; 90% confidence interval (CI) 0.74to 0.83], possibly large with AL (r=0.63; 90% CI 0.54to 0.70) and Impacts (r=0.57; 90% CI 0.47to 0.64), and likely moderate with HSRD (r=0.47; 90% CI 0.32to 0.59). The relationship between TRIMP and AL was possibly large (r=0.54; 90% CI 0.40to 0.66). All other relationships were unclear or not possible to infer (r range 0.17-0.74, n=10 datasets). Between-estimate heterogeneity [standard deviations (SDs) representing unexplained variation; τ] in the pooled internal-external relationships were trivial to extremely large for sRPE (τrange =0.00-0.47), small to large for sRPE-TL (τrange =0.07-0.31), and trivial to moderate for TRIMP (τrange=0.00-0.17). The internal-external load relationships during mixed training were possibly very large for sRPE-TL with TD (r=0.82; 90% CI 0.75to 0.87) and AL (r=0.81; 90% CI 0.74to 0.86), and TRIMP with AL (r=0.72; 90% CI 0.55to 0.84), and possibly large for sRPE-TL with HSRD (r=0.65; 90% CI 0.44to 0.80). A reduction in these correlation magnitudes was evident for all other training modes (range of the change in r when compared with mixed training -0.08 to -0.58), with these differences being unclear to possibly large. Training mode explained 24-100% of the between-estimate variance in the internal-external load relationships. Measures of internal load derived from perceived exertion and heart rate show consistently positive associations with running- and accelerometer-derived external loads and intensity during team-sport training and competition, but the magnitude and uncertainty of these relationships are measure and training mode dependent.

No Additional Benefits of Block- Over Evenly-Distributed High-Intensity Interval Training within a Polarized Microcycle.

Introduction: The current study aimed to investigate the responses to block- versus evenly-distributed high-intensity interval training (HIT) within a polarized microcycle.Methods: Twenty well-trained junior cross-country skiers (10 males, age 17.6 ± 1.5 and 10 females, age 17.3 ± 1.5) completed two, 3-week periods of training (EVEN and BLOCK) in a randomized, crossover-design study. In EVEN, 3 HIT sessions (5 × 4-min of diagonal-stride roller-skiing) were completed at a maximal sustainable intensity each week while low-intensity training (LIT) was distributed evenly around the HIT. In BLOCK, the same 9 HIT sessions were completed in the second week while only LIT was completed in the first and third weeks. Heart rate (HR), session ratings of perceived exertion (sRPE), and perceived recovery (pREC) were recorded for all HIT and LIT sessions, while distance covered was recorded for each HIT interval. The recovery-stress questionnaire for athletes (RESTQ-Sport) was completed weekly. Before and after EVEN and BLOCK, resting saliva and muscle samples were collected and an incremental test and 600-m time-trial (TT) were completed.Results: Pre- to post-testing revealed no significant differences between EVEN and BLOCK for changes in resting salivary cortisol, testosterone, or IgA, or for changes in muscle capillary density, fiber area, fiber composition, enzyme activity (CS, HAD, and PFK) or the protein content of VEGF or PGC-1α. Neither were any differences observed in the changes in skiing economy, or 600-m time-trial performance between interventions. These findings were coupled with no significant differences between EVEN and BLOCK for distance covered during HIT, summated HR zone scores, total sRPE training load, overall pREC or overall recovery-stress state. However, 600-m TT performance improved from pre- to post-training, irrespective of intervention (P = 0.003), and a number of hormonal and muscle biopsy markers were also significantly altered post-training (P < 0.05).Discussion: The current study shows that well-trained junior cross-country skiers are able to complete 9 HIT sessions within 1 week without compromising total work done and without experiencing greater stress or reduced recovery over a 3-week polarized microcycle. However, the findings do not support block-distributed HIT as a superior method to a more even distribution of HIT in terms of enhancing physiological or performance adaptions.

Relationship Between Pretraining Subjective Wellness Measures, Player Load, and Rating-of-Perceived-Exertion Training Load in American College Football.

The relationship between pretraining subjective wellness and external and internal training load in American college football is unclear. To examine the relationship of pretraining subjective wellness (sleep quality, muscle soreness, energy, wellness Z score) with player load and session rating of perceived exertion (s-RPE-TL) in American college football players. Subjective wellness (measured using 5-point, Likert-scale questionnaires), external load (derived from GPS and accelerometry), and s-RPE-TL were collected during 3 typical training sessions per week for the second half of an American college football season (8wk). The relationship of pretraining subjective wellness with player load and s-RPE training load was analyzed using linear mixed models with a random intercept for athlete and a random slope for training session. Standardized mean differences (SMDs) denote the effect magnitude. A 1-unit increase in wellness Z score and energy was associated with trivial 2.3% (90% confidence interval [CI] 0.5, 4.2; SMD 0.12) and 2.6% (90% CI 0.1, 5.2; SMD 0.13) increases in player load, respectively. A 1-unit increase in muscle soreness (players felt less sore) corresponded to a trivial 4.4% (90% CI -8.4, -0.3; SMD -0.05) decrease in s-RPE training load. Measuring pretraining subjective wellness may provide information about players' capacity to perform in a training session and could be a key determinant of their response to the imposed training demands American college football. Hence, monitoring subjective wellness may aid in the individualization of training prescription in American college football players.

Monitoring What Matters: A Systematic Process for Selecting Training-Load Measures.

Numerous derivative measures can be calculated from the simple session rating of perceived exertion (sRPE), a tool for monitoring training loads (eg, acute:chronic workload and cumulative loads). The challenge from a practitioner's perspective is to decide which measures to calculate and monitor in athletes for injury-prevention purposes. The aim of the current study was to outline a systematic process of data reduction and variable selection for such training-load measures. Training loads were collected from 173 professional rugby union players during the 2013-14 English Premiership season, using the sRPE method, with injuries reported via an established surveillance system. Ten derivative measures of sRPE training load were identified from existing literature and subjected to principal-component analysis. A representative measure from each component was selected by identifying the variable that explained the largest amount of variance in injury risk from univariate generalized linear mixed-effects models. Three principal components were extracted, explaining 57%, 24%, and 9% of the variance. The training-load measures that were highly loaded on component 1 represented measures of the cumulative load placed on players, component 2 was associated with measures of changes in load, and component 3 represented a measure of acute load. Four-week cumulative load, acute:chronic workload, and daily training load were selected as the representative measures for each component. The process outlined in the current study enables practitioners to monitor the most parsimonious set of variables while still retaining the variation and distinct aspects of "load" in the data.

Cumulative Training Dose's Effects on Interrelationships Between Common Training-Load Models During Basketball Activity.

The influence of various factors on training-load (TL) responses in basketball has received limited attention. This study aimed to examine the temporal changes and influence of cumulative training dose on TL responses and interrelationships during basketball activity. Ten state-level Australian male junior basketball players completed 4 × 10-min standardized bouts of simulated basketball activity using a circuit-based protocol. Internal TL was quantified using the session rating of perceived exertion (sRPE), summated heart-rate zones (SHRZ), Banister training impulse (TRIMP), and Lucia TRIMP models. External TL was assessed via measurement of mean sprint and circuit speeds. Temporal TL comparisons were performed between 10-min bouts, while Pearson correlation analyses were conducted across cumulative training doses (0-10, 0-20, 0-30, and 0-40 min). sRPE TL increased (P < .05) after the first 10-min bout of basketball activity. sRPE TL was only significantly related to Lucia TRIMP (r = .66-.69; P < .05) across 0-10 and 0-20 min. Similarly, mean sprint and circuit speed were significantly correlated across 0-20 min (r = .67; P < .05). In contrast, SHRZ and Banister TRIMP were significantly related across all training doses (r = .84-.89; P < .05). Limited convergence exists between common TL approaches across basketball training doses lasting beyond 20 min. Thus, the interchangeability of commonly used internal and external TL approaches appears dose-dependent during basketball activity, with various psychophysiological mediators likely underpinning temporal changes.

A detailed quantification of differential ratings of perceived exertion during team-sport training.

To investigate the application of differential ratings of perceived exertion (dRPE) to team-sport training. Single cohort, observational study. Twenty-nine professional rugby union players were monitored over a six-week intensified training period. Training sessions were classified as: high-intensity intervals, repeated high-intensity efforts, speed, skill-based conditioning, skills, whole-body resistance, or upper-body resistance. After each session, players recorded a session rating of perceived exertion (sRPE; CR100®), along with differential session ratings for breathlessness (sRPE-B), leg muscle exertion (sRPE-L), upper-body muscle exertion (sRPE-U), and cognitive/technical demands (sRPE-T). Each score was multiplied by the session duration to calculate session training loads. Data were analysed using mixed linear modelling and multiple linear regression, with magnitude-based inferences subsequently applied. Between-session differences in dRPE scores ranged from very likely trivial to most likely extremely large and within-session differences amongst dRPE scores ranged from unclear to most likely very large. Differential RPE training loads combined to explain 66-91% of the variance in sRPE training loads, and the strongest associations with sRPE training load were with sRPE-L for high-intensity intervals (r=0.67; 90% confidence limits ±0.22), sRPE-B for repeated high-intensity efforts (0.89; ±0.08) and skill-based conditioning (0.67; ±0.19), sRPE-T for Speed (0.63; ±0.17) and Skills (0.51; ±0.28), and sRPE-U for resistance training (whole-body: 0.61; ±0.21, upper-body: 0.92; ±0.07). Differential RPE can provide a detailed quantification of internal load during training activities commonplace in team sports. Knowledge of the relationships between dRPE and sRPE can isolate the specific perceptual demands of different training modes.

Validity of the session rating of perceived exertion for monitoring exercise demands in youth soccer players.

The purpose of this study was to examine the concurrent and construct validity of the Borg (0-10) and children's OMNI scales for quantifying the exercise intensity and training load (TL) in youth soccer players. Twelve children (mean ± SD age 11.4 ± 0.5 y, height 154.3 ± 6.5 cm, body mass 39.5 ± 5.4 kg) took part in this study. Exercise intensity and TL were calculated on the basis of the session rating of perceived exertion (sRPE) and heart rate (HR; Edwards method) during 20 technical-tactical training sessions. Players' sRPEs were obtained from the Borg and OMNI scales. Low correlations between HR-based TL and sRPE TL based on the Borg (r = .17, P = .335) and OMNI (r = .34, P = .007) scales were obtained. Significant (P < .001) relationships in sRPE (r = .76) and TL (r = .79) between RPE scales were found. The current data do not support the relationship between the sRPE and HR methods for quantifying TL in youth soccer players. However, the sRPE method could be considered a better indicator of global internal TL, since sRPE is a measure of both physical and psychological stress. In addition, the authors demonstrated the construct validity for the OMNI scale to control exercise demands.

Characteristics impacting on session rating of perceived exertion training load in Australian footballers

The relationship between external training load and session rating of perceived exertion (s-RPE) training load and the impact that playing experience, playing position and 2-km time-trial performance had on s-RPE training load were explored. From 39 Australian Football players, 6.9 ± 4.6 training sessions were analysed, resulting in 270 samples. Microtechnology devices provided external training load (distance, average speed, high-speed running distance, player load (PL) and player loadslow (PLslow)). The external training load measures had moderate to very large associations (r, 95% CI) with s-RPE training load, average speed (0.45, 0.35–0.54), high-speed running distance (0.51, 0.42–0.59), PLslow (0.80, 0.75–0.84), PL (0.86, 0.83–0.89) and distance (0.88, 0.85–0.90). Differences were described using effect sizes (d ±95% CL). When controlling for external training load, the 4- to 5-year players had higher s-RPE training load than the 0- to 1- (0.44 ± 0.33) and 2- to 3-year players (0.51 ± 0.30), ruckmen had moderately higher s-RPE training load than midfielders (0.82 ± 0.58), and there was a 0.2% increase in s-RPE training load per 1 s increase in time-trial (95% CI: 0.07–0.34). Experience, position and time-trial performance impacted the relationship between external training load and s-RPE training load. This suggests that a given external training load may result in different internal responses between athletes, potentially leaving individuals at risk of overtraining or failing to elicit positive adaptation. It is therefore vital that coaches and trainers give consideration to these mediators of s-RPE training load.