This study examines the changes in maximum strength, vertical jump performance, and the load-velocity and load-power relationship after a resistance training period using a heavy load and an individual load that maximizes mechanical power output with and without including body mass in power calculations. Forty-three moderately trained men (age: 22.7 ± 2.5 years) were separated into 4 groups, 2 groups of maximum power, 1 where body mass was not included in the calculations of the load that maximizes mechanical power (Pmax - bw, n = 11) and another where body mass was included in the calculations (Pmax + bw, n = 9), a high load group (HL-90%, n = 12), and a control group (C, n = 11). The subjects performed 4-6 sets of jump squat and the repeated-jump exercises for 6 weeks. For the jump squat, the HL-90% group performed 3 repetitions at each set with a load of 90% of 1 repetition maximum (1RM), the Pmax - bw group 5 repetitions with loads 48-58% of 1RM and the Pmax + bw 8 repetitions with loads 20-37% of 1RM. For the repeated jump, all the groups performed 6 repetitions at each set. All training groups improved (p < 0.05) maximum strength in the semisquat exercise (HL-90%: 15.2 ± 7.1, Pmax - bw: 6.6 ± 4.7, Pmax + bw: 6.9 ± 7.1, and C: 0 ± 4.3%) and the HL-90% group presented higher values (p < 0.05) than the other groups did. All training groups improved similarly (p < 0.05) squat (HL-90%: 11.7 ± 7.9, Pmax - bw: 14.5 ± 11.8, Pmax + bw: 11.3 ± 7.9, and C: -2.2 ± 5.5%) and countermovement jump height (HL-90%: 8.6 ± 7.9, Pmax - bw: 10.9 ± 9.4, Pmax + bw: 8.8 ± 4.3, and C: 0.4 ± 6%). The HL-90% and the Pmax - bw group increased (p < 0.05) power output at loads of 20, 35, 50, 65, and 80% of 1RM and the Pmax + bw group at loads of 20 and 35% of 1RM. The inclusion or not of body mass to determine the load that maximizes mechanical power output affects the long-term adaptations differently in the load-power relationship. Thus, training load selection will depend on the required adaptations. However, the use of heavy loads causes greater overall neuromuscular adaptations in moderately trained individuals.

Background: Maturation is a complex biological process affecting all tissues, organs, and systems, particularly during adolescence. The Peak Height Velocity (PHV) period, a hallmark of adolescent growth spurts, is associated with individual differentiations in the development of performance attributes amongst youth. Understanding the influence of sports participation on strength and power during the PHV period is essential for optimizing training outcomes and reducing injury risk. This scoping review synthesizes the literature on the strength and power development in athletes during the PHV period across various sports, highlighting the interaction between maturation, training, and performance outcomes. Methods: A systematic search of PubMed and Scopus, supplemented by manual searches, identified peer-reviewed studies from 2004 to 2025. The included longitudinal studies involved structured training and assessed strength-related performance during and around the PHV period. PRISMA-ScR guidelines were followed. Results: Twelve studies met the inclusion criteria. It is found that strength and power are significantly affected during the PHV period and participation in sports mitigates these effects. Training characteristics such as training frequency/volume and sport specificity were key factors. Early maturers often outperformed late maturers, though adolescent awkwardness temporarily reduced performance around PHV. Conclusions: Systematic participation in sports training can limit the phenomenon of adolescent awkwardness in the performance of strength and power. Hence, training programs should be tailored to maturity status, emphasizing skill development, strength training, and injury prevention. Future research should explore individualized training and the mechanisms underlying performance variability during the PHV period.

This study examined the effects of two different resistance loads during high-intensity Functional Training (HIFT) on body composition and maximal strength. Thirty-one healthy young individuals were randomly assigned into three groups: moderate load (ML: 70% 1-RM), low load-(LL: 30% 1-RM), and control (CON). Each experimental group performed HIFT three times per week for 12 weeks with a similar total volume load. Body fat decreased equally in both experimental groups after 6 weeks of training (p < 0.001), but at the end of training it further decreased only in LL compared to ML (−3.19 ± 1.59 vs. −1.64 ± 1.44 kg, p < 0.001), with no change in CON (0.29 ± 1.08 kg, p = 0.998). Lean body mass (LBM) increased after 6 weeks of training (p = 0.019) in ML only, while after 12 weeks a similar increase was observed in LL and ML (1.11 ± 0.65 vs. ML: 1.25 ± 1.59 kg, p = 0.034 and 0.013, respectively), with no change in CON (0.34 ± 0.67 kg, p = 0.991). Maximal strength increased similarly in four out of five exercises for both experimental groups by between 9.5% and 16.9% (p < 0.01) at the end of training, with no change in CON (−0.6 to 4.9%, p > 0.465). In conclusion, twelve weeks of HIFT training with either low or moderate resistance and equal volume load resulted in an equal increase in LBM and maximal strength, but different fat loss.

Smilios, I, Myrkos, A, Zafeiridis, A, Toubekis, A, Spassis, A, and Tokmakidis, SP. The effects of recovery duration during high-intensity interval exercise on time spent at high rates of oxygen consumption, oxygen kinetics, and blood lactate. J Strength Cond Res 32(8): 2183–2189, 2018—The recovery duration and the work-to-recovery ratio are important aspects to consider when designing a high-intensity aerobic interval exercise (HIIE). This study examined the effects of recovery duration on total exercise time performed above 80, 90, and 95% of maximum oxygen consumption (V̇o ₂max) and heart rate (HRmax) during a single-bout HIIE. We also evaluated the effects on V̇o ₂ and HR kinetics, blood lactate concentration, and rating of perceived exertion (RPE). Eleven moderately trained men (22.1 ± 1 year) executed, on 3 separate sessions, 4 × 4-minute runs at 90% of maximal aerobic velocity (MAV) with 2, 3, and 4 minutes of active recovery. Recovery duration did not affect the percentage of V̇o ₂max attained and the total exercise time above 80, 90, and 95% of V̇o ₂max. Exercise time above 80 and 90% of HRmax was longer with 2 and 3 minutes (p ≤ 0.05) as compared with the 4-minute recovery. Oxygen uptake and HR amplitude were lower, mean response time slower (p ≤ 0.05), and blood lactate and RPE higher with 2 minutes compared with 4-minute recovery (p ≤ 0.05). In conclusion, aerobic metabolism attains its upper functional limits with either 2, or 3 or 4 minutes of recovery during the 4 × 4-minute HIIE; thus, all rest durations could be used for the enhancement of aerobic capacity in sports, fitness, and clinical settings. The short (2 minutes) compared with longer (4 minutes) recovery, however, evokes greater cardiovascular and metabolic stress and activates to a greater extent anaerobic glycolysis and hence, could be used by athletes to induce greater overall physiological challenge.

The present study examined the short-term effects of loaded half squats (HSs) and loaded jump squats (JSs) with low and moderate loads on the squat jump (SJ) and the countermovement jump (CMJ) performance using a contrast training approach. Ten men (mean +/- SD age, 23 +/- 1.8 years) performed the HS and JS exercises twice with loads of 30% of 1 repetition maximum (1RM) (HS30% and JS30%, respectively) and 60% of 1RM (HS60% and JS60%, respectively). On each occasion, 3 sets of 5 repetitions with 3 minutes of rest were performed as fast as possible. Vertical jump performance was measured before exercise, 1 minute after each set, and at the fifth and 10th minutes of recovery. The CMJ increased significantly after the first and second set (3.9%; p < 0.05) compared with preexercise values following the JS30% protocol and 3.3% after the second and third sets of the JS60% protocol. Following the HS60% protocol, CMJ increased after the first and the second sets (3.6%; p < 0.05) compared with preexercise values, whereas SQ increased only after the first set (4.9%; p < 0.05) in this condition. These data show that contrast loading with the use of low and moderate loads can cause a short-term increase in CMJ performance. The applied loads do not seem to present different short-term effects after loaded JSs. When the classic form of dynamic HS exercise is performed, however, at least a moderate load (60% of 1RM) needs to be applied.

Maturation is a key factor in sports participation and often determines the young athletes’ characterization as a talent. However, there is no evidence of practical models for understanding the factors that discriminate children according to maturity. Hence, this study aims to deepen the understanding of the factors that affect maturity in 11-year-old Team Sports Athletes by utilizing explainable artificial intelligence (XAI) models. We utilized three established machine learning (ML) classifiers and applied the Sequential Forward Feature Selection (SFFS) algorithm to each. In this binary classification task, the logistic regression (LR) classifier achieved a top accuracy of 96.67% using the seven most informative factors (Sitting Height, Father’s Height, Body Fat, Weight, Height, Left and Right-Hand Grip Strength). The SHapley Additive exPlanations (SHAP) model was instrumental in identifying the contribution of each factor, offering key insights into variable importance. Independent sample t-tests on these selected factors confirmed their significance in distinguishing between the two classes. By providing detailed and personalized insights into child development, this integration has the potential to enhance the effectiveness of maturation prediction significantly. These advancements could lead to a transformative approach in young athletes’ pediatric growth analysis, fostering better sports performance and developmental outcomes for children.