Use of Numerically Blinded Ratings of Perceived Exertion in Soccer: Assessing Concurrent and Construct Validity

The Dose-Response in Elite Soccer: Preliminary Insights From Menstrual-Cycle Tracking During the FIFA Women's World Cup 2019

PURPOSE

This preliminary study examined the influence of estimated menstrual-cycle (MC) phase on responses to soccer matches and training sessions in preparation for and during the FIFA (Fédération internationale de football association) Women's World Cup 2019.

METHODS

Twenty outfield players representing a national team were tracked over a 45-day period. External (10-Hz global positioning system; total and distance covered at high-metabolic power [≥20 W·kg-1]) and internal load measures (minutes ≥80% heart-rate maximum, sessional ratings of perceived exertion) were collected during all training and matches, with single-item wellness measures (fatigue, soreness, sleep quality, and sleep duration) collected each morning prior to activity. MC phase was estimated individually via an algorithm, informed from pretournament survey responses and ongoing symptom reporting (FitrWoman). Model comparison statistics were used to determine the impact of estimated MC phase in nonhormonal contraceptive users (n = 16).

RESULTS

Sessional rating of perceived exertion responses to total distances ≥5 km were higher during the luteal phase (+0.6-1.0 au; P ≤ .0178) versus menstruation (phase 1), but no other observable dose-response trends were observed. Sleep, fatigue, and soreness ratings were not typically associated with MC phase, with the exception of exacerbated fatigue ratings in luteal versus follicular phase 48 hours postmatch (-0.73 au, P = .0275).

CONCLUSIONS

Preliminary findings suggest that estimated MC phase may contribute to the understanding of the dose-response to soccer training and matches.

A meta-analysis of the criterion-related validity of Session-RPE scales in adolescent athletes

BACKGROUND

The objective of this study was to establish the criterion-related validity of the session-rating of perceived exertion (s-RPE) method in adolescent athletes.

METHODS

According to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA 2020) guidelines, a meta-analysis (PROSPERO ID: CRD42022373126) was performed using Stata 15.1 software. Eight databases using the following terms: ('s-RPE' OR 'Rating Perceived Exertion session' OR 'RPE session' OR 'RPE' OR 'Rate of Perceived Exertion' OR 'Rated of Perceived Exertion') AND ('Adolescen*' OR 'Youth*' OR 'Teen*') AND ('validity' OR 'correlation' OR 'concurrent validity') were searched up to 2022. Articles meeting the inclusion criteria were screened and adopted the "Methodological Index for Non-Randomized Studies (MINORS)" to evaluate the risk of bias.

RESULTS

An initial 1798 studies using the s-RPE method were identified and finally, a total of 16 studies were included for further analysis. The relationship between assessment instruments CR-10 or CR-100 modified methods of s-RPE and the heart rate measures of these selected studies were calculated using correlation coefficient (r values) and Fisher's z-score. A strong to very strong correlation between s-RPE and HR was observed (overall: r = 0.74; CR-10: r = 0.69; CR-100: r = 0.80). CR-100 scale (Fisher's z = 1.09) was shown to have a higher criterion validity than that of the CR-10 scale (Fisher's z = 0.85).

CONCLUSION

Preliminary findings showed that s-RPE using either CR-10 or CR-100 scales can be used "stand-alone" for monitoring internal training load for children and adolescent athletes. Future studies should focus on whether CR-100 could better perform than CR-10 for junior and children athletes in different age groups and sports as well as the causes leading to potential scoring biases.

The Current State of Subjective Training Load Monitoring: Follow-Up and Future Directions

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.

The reliability, validity and sensitivity of an individualised sub-maximal fitness test in elite rugby league athletes

We aimed to examine the reliability, validity and sensitivity of an individualised sub-maximal fitness test (SMFTIFT60). Nineteen elite rugby league players performed a one-week test-retest of SMFTIFT60. Typical Errors and ICCs were: small (<3.5%) and extremely high (>0.90) for accelerometer-derived variables; moderate (<2.5% points) and moderate to very high (0.71-0.89) for exercise and recovery heart rate (HRex and HRR, respectively). Convergent validity correlations with the 10-week pre-season change in 30-15 Intermittent Fitness Test performance were large for changes in SMFTIFT60 HRex (r = -0.57) and HRR (0.60), and very large for changes in accelerometer measures (range: -0.71 to -0.79). For sensitivity, within-player dose-response relationships between SMFTIFT60 HRex and prior 3-day training loads were negative and ranged from moderate (session ratings of perceived exertion [sRPE-TL], r = -0.34), to large (high-speed running distance, -0.51; acceleration load, -0.73) and very large (heart rate Training Impulse [TRIMP], -0.83). All other relationships were unclear or trivial to small. Physiological and accelerometer-derived measures from the SMFTIFT60 are reliable and valid for the assessment of fitness in rugby league players. Only HRex appears sensitive to acute changes in training load. The SMFTIFT60 could be a useful monitoring tool in team sports.

Submaximal Fitness Tests in Team Sports: A Theoretical Framework for Evaluating Physiological State

Team-sports staff often administer non-exhaustive exercise assessments with a view to evaluating physiological state, to inform decision making on athlete management (e.g., future training or recovery). Submaximal fitness tests have become prominent in team-sports settings for observing responses to a standardized physical stimulus, likely because of their time-efficient nature, relative ease of administration, and physiological rationale. It is evident, however, that many variations of submaximal fitness test characteristics, response measures, and monitoring purposes exist. The aim of this scoping review is to provide a theoretical framework of submaximal fitness tests and a detailed summary of their use as proxy indicators of training effects in team sports. Using a review of the literature stemming from a systematic search strategy, we identified five distinct submaximal fitness test protocols characterized in their combinations of exercise regimen (continuous or intermittent) and the progression of exercise intensity (fixed, incremental, or variable). Heart rate-derived indices were the most studied outcome measures in submaximal fitness tests and included exercise (exercise heart rate) and recovery (heart rate recovery and vagal-related heart rate variability) responses. Despite the disparity between studies, these measures appear more relevant to detect positive chronic endurance-oriented training effects, whereas their role in detecting negative transient effects associated with variations in autonomic nervous system function is not yet clear. Subjective outcome measures such as ratings of perceived exertion were less common in team sports, but their potential utility when collected alongside objective measures (e.g., exercise heart rate) has been advocated. Mechanical outcome measures either included global positioning system-derived locomotor outputs such as distance covered, primarily during standardized training drills (e.g., small-sided games) to monitor exercise performance, or responses derived from inertial measurement units to make inferences about lower limb neuromuscular function. Whilst there is an emerging interest regarding the utility of these mechanical measures, their measurement properties and underpinning mechanisms are yet to be fully established. Here, we provide a deeper synthesis of the available literature, culminating with evidence-based practical recommendations and directions for future research.