On maximum (1RM) from local muscular endurance. Different athletic male populations were assessed: racket/ball games players (n = 31), power lifters (n = 22), swimmers (n = 28), and rowers (n = 29). After the 1RM assessment for the bench press, the maximum number of repetitions (MNR) relative to the 1RM (85%, 75%, 60%, 40%, and 20%) was tested. No significant differences in strength evolution from 20% to 100% of the 1RM was found between power lifters and racket/ball games players and between swimmers and rowers. However, differences in the strength evolution appeared between these 2 mixed groups (p < 0.01), with differences appearing from 75% of 1RM to lesser relative strength (p < 0.05). Nonlinear equations fitted best with the actual data for the capacity to repeat lifts. The evolution of strength from 100% to 20% of 1RM was better described when the groups' specific equations were used as demonstrated by r2, and residuals range between the predicted minus the measured 1RM. The strength endurance competences for high loads (100%-75%) were adequately modelled by the equation based on the total population. The accuracy of the 1RM prediction was better when a reduced number of lifts was performed. For untrained or novice subjects, the use of group-specific equations for the all evolutionary profile of strength allows a good estimate of 1RM and provides adequate numbers of lifts for all levels of strength, thus optimizing the training programs....

In order to understand the determinants and trends of human performance evolution, we analyzed ten outdoor events among the oldest and most popular in sports history. Best performances of the Oxford-Cambridge boat race (since 1836), the channel crossing in swimming (1875), the hour cycling record (1893), the Elfstedentocht speed skating race (1909), the cross country ski Vasaloppet (1922), the speed ski record (1930), the Streif down-hill in Kitzbühel (1947), the eastward and westward sailing transatlantic records (1960) and the triathlon Hawaii ironman (1978) all follow a similar evolutive pattern, best described through a piecewise exponential decaying model (r² = 0.95±0.07). The oldest events present highest progression curvature during their early phase. Performance asymptotic limits predicted from the model may be achieved in fourty years (2049±32 y). Prolonged progression may be anticipated in disciplines which further rely on technology such as sailing and cycling. Human progression in outdoor sports tends to asymptotic limits depending on physiological and environmental parameters and may temporarily benefit from further technological progresses.

Repetitions of pre-competition weight-loss diets done by athletes participating in weight class sports can be regarded as periods of weight cycling. The aim of the present study is to identify the long term post-career (22 years) evolutionary profile of athletes’ BMI after such weight cycling. One hundred and thirty-six retired French athletes who participated in major international competitions in weight class sports (rowers, wrestlers, boxers, and judokas) were included. Former and current body mass, height, dietary characteristics during the career (annual frequency, amount of weight lost), current physical activity, and answers on the eating-attitude test were collected by phone interview (consistency was tested by comparison with measured weight). We performed ANOVA tests for comparison between groups (sport, dieting), post-hoc tests (Bonferroni test) to identify differences within groups. BMI’s changes were treated using a mixed model. The recorded weight changes did not depend upon time since retirement. Between 18 y and 50 y, athletes’ BMI increased by 3.2 kg/m2 compared to the 4.2 kg/m2 increase in the general population. This increase was independent of the number of diets during the career. Retired athletes declared a mean weekly physical activity of 4.8 h ± 4.3. The eating-attitude test showed low scores for all sports without any correlation to diet characteristics. Weight cycling during an athletic career does not induce a massive weight gain after retirement, probably due to the high level of physical activity still practiced after retirement by these athletes.

The purpose of this study was to quantify intermittent training sessions using different types of exercise. Strength, sprint, and endurance sessions were performed until exhaustion. These sessions were quantified by the product of duration and heart rate (HR) (i.e., training impulse (TRIMP) and HR-zone methods), by the product of duration and rate of perceived exertion (RPE-based method), and a new method (work endurance recovery (WER)). The WER method aims to determine the level of exercise-induced physiological stress using the ratio of cumulated work – endurance limit, which is associated with the naparian logarithm of the ratio of work–recovery. Each session's effects were assessed using blood lactate, delayed onset muscle soreness (DOMS), RPE, and HR. Because sessions were performed until exhaustion, it was assumed that each session would have a similar training load (TL) and there would be low interindividual variability. Each method was used to compare each of the TL quantifications. The endurance session induced the higher HR response (p < 0.001), the sprint session the higher blood lactate increase (p < 0.001), and the strength session the higher DOMS when compared with sprint (p = 0.007). TLs were similar after WER calculations, whereas the HR- and RPE-based methods showed differences between endurance and sprint (p < 0.001), and between endurance and strength TL (p < 0.001 and p < 0.01, respectively). The TLs from WER were correlated to those of the HR-based methods of endurance exercise, for which HR was known to accurately reflect the exercise-induced physiological stress (r = 0.63 and r = 0.64, p < 0.05). In addition, the TL from WER presented low interindividual variability, yet a marked variability was observed in the TLs of HR- and RPE-based methods. As opposed to the latter two methods, WER can quantify varied intermittent exercises and makes it possible to compare the athletes’ TL. Furthermore, WER can also assist in comparing athlete responses to training programs.

On (RPE) during resistance exercises was influenced by the exercise volume and athletes' training state. Eighty physical education students (well trained, less well trained, and novices) rated their perceived exertion of multilift sets using the category-ratio scale. These sets were performed with moderate (60–80% of 1-repetition maximum [1RM]) and heavy loads (80–100% of 1RM) involving low volume of exercise (5.5 ± 1.1 reps for moderate and 1.3 ± 0.4 reps for the heavy load) and high volume of exercise (moderate load: 17.5 ± 2.1 reps; high load: 2.9 ± 0.6 reps). The exercise volume of the sets was expressed relatively to individual maximal capacities using the maximum number of repetition (MNR) for the load lifted. General linear model describes that RPE was related to MNR % with a training state effect (p < 0.01) observed only for sets involving a low MNR % and without effect of absolute volume and exercise intensity (high MNR sets: adjusted R2 = 0.65 and 0.78 and low MNR sets adjusted R2 = 0.37 and 0.34 in low MNR tests). High standard errors of estimated relative volume appeared when using the RPE from low exercise volume sets (12.8 and 14.4% of actual relative volume). Coaches should consider the RPE resulting from high exercise-induced physical strain to estimate the actual relative volume and to estimate the individual MNR at a given load....

The purpose of this study was to quantify training loads (TL) of high intensity sessions through original methods (TRIMP; session-RPE; Work-Endurance-Recovery) and their updated alternatives (TRIMP_cumulative; RPE_alone; New-WER). Ten endurance athletes were requested to perform five sessions until exhaustion. Session 1 composed by a 800m maximal performance and four intermittent sessions performed at the 800m velocity, three sessions with 400m of interval length and work:recovery ratios of 2:1, 1:1 and 1:2 and one with 200m intervals and 1:1. Total TL were quantified from the sessions’ beginning to the cool-down period and an intermediate TL (TL₈₀₀) was calculated when 800m running was accumulated within the sessions. At the end of the sessions high and similar RPE were reported (effect size, η² = 0.12), while, at the intermediate 800m distance, the higher interval distances and work:recovery ratios the higher the RPE (η² = 0.88). Our results show marked differences in sessions’ total TL between original (e.g., lowest TL for the 800m and highest for the 200m-1:1 sessions) and alternative methods (RPE_alone and New-WER; similar TL for each session). Differences appear in TL₈₀₀ notably between TRIMP and other methods which are negatively correlated. All TL report light to moderate correlations between original methods and their alternatives, original methods are strongly correlated together, as observed for alternative methods. Differences in TL quantification between original and alternative methods underline that they are not interchangeable. Because of high exercise volume influence, original methods markedly enhance TL of sessions with higher exercise volumes although these presented the easiest interval distances and work-recovery ratios. Alternative methods based on exhaustion level (New-WER) and exertion (RPE_alone) provided a new and promising point of view of TL quantification where exhaustion determines the highest TL whatever the exercise. This remains to be tested with more extended populations submitted to wider ranges of exercises.