The purpose of the study was to describe pacing patterns of the finishers of the World Marathon Majors series and the effect of sex and age on the pacing pattern. The finishers of the World Marathon Majors series, a total of 69 814 male runners and 46 856 female runners with finishing time ≤ 6 hours were included in the analysis. Difference in pacing (dev%) was calculated as a difference between the first and second half of the marathon and expressed as a percentage of time. Analysis of variance (ANOVA) was used to evaluate the differences within and between the marathon time groups. The differences between the first and second half of the marathon by sex and age group were analysed using linear regression. The average difference between the first and second half of the marathon was 3.44±2.67% for male and 2.81±2.10% for female runners. Male runners with finishing times of 3:00 (h:min) and females with 4:00 (h:min) or slower had the significantly faster first half of the marathon compared to the evenly paced marathon (p=.038 and p=.001, respectively). Regression analysis revealed that female runners had 0.26% smaller difference between the first and second half of the race compared to male runners (R2=0.256; p<.001) when controlled for age and time group. Also, veterans (40 years and older) paced more evenly compared to non-veterans (R2=0.256; p<.001). In conclusion, irrespective of sex and age, faster finishers maintain a more constant velocity than the slower ones. In addition, women and veterans present more even pacing strategy compared to men and non-veterans, respectively.

The aim of the study was to compare the effects of different types and periodization of strength training on body composition and maximal aerobic performance in 10-week training period in adolescent XC skiers. Twenty-eight adolescent competitive cross-country skiers, including 10 females (age 17.9 ± 1.8 years; body mass 69.6 ± 9.7 kg; height 1.77 ± 0.1 m; training experience 8.6 ± 3.2 years) took part in this study. Pre- and post-intervention performance was measured with the incremental exercise test (Pmax) on a double poling ski ergometer. Changes in body composition were measured with DXA. In addition to regular endurance training, experimental group one (EXP1) performed maximal and explosive strength training two times per week, experimental group two (EXP2) performed maximal and explosive strength training 1–3 times per week, and the traditional (TRAD) group performed low intensity–high volume strength training 2 times per week. Increases in arm, trunk, and overall lean mass were found in TRAD (p < 0.05). Increases in arm lean-mass was found in EXP1 (p < 0.05), while no changes in body composition occurred in EXP2 (p ≥ 0.05). Pmax improved significantly in all groups (p < 0.05). Changes in body mass, overall and arm lean mass was related to changes in absolute performance (W; p < 0.05), while no relationships were found between changes in body composition parameters and relative performance (W/kg; p ≥ 0.05). In conclusion, different periodization of strength training led to similar improvements in double poling ergometer performance, but resulted in different changes in body composition (lean mass) in adolescent cross-country skiers.

Pind, R, Mäestu, E, Purge, P, Jürgenson, J, Arend, M, and Mäestu, J. Internal load from hard training sessions is related to changes in performance after a 10-week training period in adolescent swimmers. J Strength Cond Res 35(10): 2846–2852, 2021—The purpose of this study was to investigate the association between session rating of perceived exertion (sRPE) and its categorization with the changes in swimming performance in adolescent swimmers. National level swimmers (age 16.4 ± 2.1 years, V̇o 2max 50.0 ± 4.0 ml·min−1·kg−1) participated in a 10-week period preceding the National Winter Championships. Pre-training and post-training physiological parameters and swimming performance were measured. All training bouts with sRPE data were recorded. In addition, trainings were categorized as light, moderate, or hard. For calculating the corresponding internal training load (ITL), 2 fixed categorizations were applied based on earlier published sources and an individualized categorization based on ventilatory thresholds. During the 10-week training period, large to very large increases were found in aerobic (effect size [ES] = 1.58) and anaerobic threshold power output W·kg−1 (ES = 2.46), respectively, and smaller, but significant, improvement in 100-m swimming performance (ES = 0.36). Total ITL during the 10-week period was significantly related to changes in anaerobic threshold (r = 0.81). Fixed and individualized sRPE methods from hard sessions were associated with changes in V̇o 2max (r = 0.77) and performance of only 100-m leg kicks (r = 0.76), respectively. Internal training load was related to changes in performance variables during the 10-week study period. Using individualized sRPE values, the accumulation of the ITL from hard training sessions was associated with changes in V̇o 2max and swimming performance. The aforementioned categorization could help coaches in appropriate application of ITL for assessing the total training load in adolescent swimmers.

Regular physical activity and participation in organized sports is important contributor to performance and for overall health and fitness in humans of various age range. In performance related areas, every detail in the training sessions is important for the athlete to be in the best shape the chosen competition day. Sport scientists have been making hard effort to find out how the training has the influence on performance. Thus, training monitoring is important tool to evaluate an athlete's response to training. Banister developed the 'training impulse' (TRIMP) as a method to quantify training load. The TRIMP consists of the exercise intensity calculated by the heart rate (HR) reserve method and the duration of exercise. Foster et al. [23] developed a modification of the rating of the perceived exertion method, which uses Rated Perceived Exertion (RPE) as a marker of training intensity within the TRIMP concept. For quantifying and calculating training load, the athlete's RPE (1-10pt scale) is multiplied by the duration of the session. Ideally, the perceptions of training load should match between athlete and coach to have optimal adaptation. Thus, this brief review article is evaluating training monitoring opportunities without the need of expensive equipment.

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