This study aimed to analyze the correlations among weekly (w) acute workload (wAW), chronic workload (wCW), acute/chronic workload ratio (wACWR), training monotony (wTM), training strain (wTS), sleep quality (wSleep), delayed onset muscle soreness (wDOMS), fatigue (wFatigue), stress (wStress), and Hooper index (wHI) in pre-, early, mid-, and end-of-season. Twenty-one elite soccer players (age: 16.1 ± 0.2 years) were monitored weekly on training load and well-being for 36 weeks. Higher variability in wAW (39.2%), wFatigue (84.4%), wStress (174.3%), and wHI (76.3%) at the end-of-season were reported. At mid-season, higher variations in wSleep (59.8%), TM (57.6%), and TS (111.1%) were observed. Moderate to very large correlations wAW with wDOMS (r = 0.617, p = 0.007), wFatigue, wStress, and wHI were presented. Similarly, wCW reported a meaningful large association with wDOMS (r = 0.526, p < 0.001); moderate to very large associations with wFatigue (r = 0.649, p = 0.005), wStress, and wHI. Moreover, wTM presented a large correlation with wSleep (r = 0.515, p < 0.001); and a negatively small association with wStress (r = −0.426, p = 0.003). wTS showed a small to large correlation with wSleep (r = 0.400, p = 0.005) and wHI; also, a large correlation with wDOMS (r = 0.556, p = 0.028) and a moderate correlation with wFatigue (r = 0.343, p = 0.017). Wellness status may be considered a useful tool to provide determinant elite players’ information to coaches and to identify important variations in training responses.

This study sought to analyze the relationship between in-season training workload with changes in aerobic power (VO2max), maximum and resting heart rate (HRmax and HRrest), linear sprint medium (LSM), and short test (LSS), in soccer players younger than 16 years (under-16 soccer players). We additionally aimed to explain changes in fitness levels during the in-season through regression models, considering accumulated load, baseline levels, and peak height velocity (PHV) as predictors. Twenty-three male sub-elite soccer players aged 15.5 ± 0.2 years (PHV: 13.6 ± 0.4 years; body height: 172.7 ± 4.2 cm; body mass: 61.3 ± 5.6 kg; body fat: 13.7% ± 3.9%; VO2max: 48.4 ± 2.6 mL⋅kg–1⋅min–1), were tested three times across the season (i.e., early-season (EaS), mid-season (MiS), and end-season (EnS) for VO2max, HRmax, LSM, and LSS. Aerobic and speed variables gradually improved over the season and had a strong association with PHV. Moreover, the HRmax demonstrated improvements from EaS to EnS; however, this was more evident in the intermediate period (from EaS to MiS) and had a strong association with VO2max. Regression analysis showed significant predictions for VO2max [F(2,20) = 8.18, p ≤ 0.001] with an R2 of 0.45. In conclusion, the meaningful variation of youth players’ fitness levels can be observed across the season, and such changes can be partially explained by the load imposed.

Concurrent resistance and aerobic training (CT) has been applied to optimize both strength and aerobic performance. However, it should be carefully prescribed, as there are some factors, as the training intensity, which have strong influence on training adaptations. Thus, we conducted a systematic review to analyze the scientific evidence regarding aerobic and resistance exercise intensities during CT and their effect on performance outcomes. The effects of exercise intensity on a subsequent detraining period were also assessed. Nine studies met the inclusion criteria, the risk of bias was assessed, and the percentage of changes and effect sizes were quantified. CT improved running times (10 m, 30 m and 10 km) and strength performance (one-repetition maximum, countermovement jump) regardless of exercise intensity used (4–47%, ES=0.4–2.8). Nevertheless, higher aerobic training intensities (≥ lactate threshold intensity) resulted in higher aerobic gains (5–10%, ES=0.3–0.6), and greater neuromuscular adaptations were found when higher resistance loads (≥ 70% of maximal strength) were used (10–14%, ES=0.4–1.3). Most training-induced gains were reversed after 2–4 weeks of detraining. Although further research is needed, it seems that higher intensities of aerobic or resistance training induce greater aerobic or neuromuscular gains, respectively. Nevertheless, it seems that higher resistance training loads should be combined with lower aerobic training intensities for increased strength gains and minimal losses after detraining.

Alves, AR, Marta, CC, Neiva, HP, Izquierdo, M, and Marques, MC. Concurrent training in prepubescent children: the effects of 8 weeks of strength and aerobic training on explosive strength and V[Combining Dot Above]O2max. J Strength Cond Res 30(7): 2019-2032, 2016-The purpose of this study was to compare the effects of 8-week training periods of strength training alone (GS), combined strength and aerobic training in the same session (GCOM1), or in 2 different sessions (GCOM2) on explosive strength and maximal oxygen uptake (V[Combining Dot Above]O2max) in prepubescent children. Of note, 168 healthy children, aged 10-11 years (10.9 ± 0.5), were randomly selected and assigned to 3 training groups to train twice a week for 8 weeks: GS (n = 41), GCOM1 (n = 45), GCOM2 (n = 38) groups, and a control group (GC) (n = 44; no training program). The GC maintained the baseline level, and trained-induced differences were found in the experimental groups. Differences were observed in the 1 and 3-kg medicine ball throws (GS: +5.8 and +8.1%, respectively; GCOM1: +5.7 and +8.7%, respectively; GCOM2: +6.2 and +8%, respectively, p < 0.001) and in the countermovement jump height and in the standing long jump length (GS: +5.1 and +5.2%, respectively; GCOM1: +4.2 and +7%, respectively; GCOM2: +10.2 and +6.4%, respectively, p < 0.001). In addition, the training period induced gains in the 20-m time (GS: +2.1%; GCOM1: +2.1%; GCOM2: +2.3%, p < 0.001). It was shown that the experimental groups (GCOM1, GCOM2, and GS) increased V[Combining Dot Above]O2max, muscular strength, and explosive strength from pretraining to posttraining. The higher gains were observed for concurrent training when it was performed in different sessions. These results suggest that concurrent training in 2 different sessions seems to be an effective and useful method for training-induced explosive strength and V[Combining Dot Above]O2max in prepubescent children. This could be considered as an alternative way to optimize explosive strength training and cardiorespiratory fitness in school-based programs.

The aims of this study were 1) to analyze the influence of chronological age, relative age, and biological maturation on accumulated training load and perceived exertion in young sub-elite football players and 2) to understand the interaction effects amongst age grouping, maturation status, and birth quartiles on accumulated training load and perceived exertion in this target population. A 6-week period (18 training sessions and 324 observation cases) concerning 60 young male sub-elite football players grouped into relative age (Q1 to Q4), age group (U15, U17, and U19), and maturation status (Pre-peak height velocity (PHV), Mid-PHV, and Post-PHV) was established. External training load data were collected using 18 Hz global positioning system technology (GPS), heart-rate measures by a 1 Hz short-range telemetry system, and perceived exertion with total quality recovery (TQR) and rating of perceived exertion (RPE). U17 players and U15 players were 2.35 (95% CI: 1.25–4.51) and 1.60 (95% CI: 0.19–4.33) times more likely to pertain to Q1 and Q3, respectively. A negative magnitude for odds ratio was found in all four quartile comparisons within maturation status (95% CI: 6.72–0.64), except for Mid-PHV on Q2 (95% CI: 0.19–4.33). Between- and within-subject analysis reported significant differences in all variables on age group comparison measures (F = 0.439 to 26.636, p = 0.000 to 0.019, η2 = 0.003–0.037), except for dynamic stress load (DSL). Between-subject analysis on maturity status comparison demonstrated significant differences for all training load measures (F = 6.593 to 14.424, p = 0.000 to 0.037, η2 = 0.020–0.092). Interaction effects were found for age group x maturity band x relative age (Λ Pillai’s = 0.391, Λ Wilk’s = 0.609, F = 11.385, p = 0.000, η2 = 0.391) and maturity band x relative age (Λ Pillai’s = 0.252, Λ Wilk’s = 0.769, F = 0.955, p = 0.004, η2 = 0.112). Current research has confirmed the effects of chronological age, relative age, and biological maturation on accumulated training load. Perceived exertion does not seem to show any differences concerning age group or maturity status. Evidence should be helpful for professionals to optimize the training process and young football players’ performance.