This study aimed to examine the associations between lower-body explosive strength (squat jump—SJ, and countermovement jump—CMJ), speed (10- and 35-m linear sprints), and agility (t-test) capacities, after controlling for crucial predictors such as chronological age (CA) and body composition. The sample was composed of 164 adolescent male football players from under 19, under 17, and under 15 age groups. Body fat percentage (BF%) was significantly and positively related to body mass, speed, and agility. In contrast, BF% was a significant negative predictor of lower-body explosive strength. Sprint and t-test times were significantly and negatively correlated with lower-body explosive strength. After controlling for CA and body composition, SJ was the most significant predictor, accounting for 36 to 37% of the variance observed in the 35 m linear sprint and the t-test performance. Our main results suggest that lower-body explosive strength, particularly in the SJ, is a significant predictor of male adolescent male football players’ speed and agility capacities. Conversely, detrimental relationships between BF% and these outcomes were observed. Sports agents should consider lower-body explosive strength development as part of the youth football training process, particularly to improve maximal sprint and change of direction times, which are crucial to game performance.

Injuries are one of the most significant issues for elite football players. Consequently, elite football clubs have been consistently interested in having practical, interpretable, and usable models as decision-making support for technical staff. This study aimed to analyze predictive modeling of injury risk based on body composition variables and selected physical fitness tests for elite football players through a sports season. The sample comprised 36 male elite football players who competed in the First Portuguese Soccer League in the 2020/2021 season. The models were calculated based on 22 independent variables that included players’ information, body composition, physical fitness, and one dependent variable, the number of injuries per season. In the net elastic analysis, the variables that best predicted injury risk were sectorial positions (defensive and forward), body height, sit-and-reach performance, 1 min number of push-ups, handgrip strength, and 35 m linear speed. This study considered multiple-input single-output regression-type models. The analysis showed that the most accurate model presented in this work generates an error of RMSE = 0.591. Our approach opens a novel perspective for injury prevention and training monitorization. Nevertheless, more studies are needed to identify risk factors associated with injury prediction in elite soccer players, as this is a rising topic that requires several analyses performed in different contexts.

Studying fatigue is challenging because it is influenced by physiological, psychological, and sociological states. Fatigue can be assessed objectively or subjectively, but the literature has difficulty understanding how an analytical test relates to a response via a questionnaire. Thus, the purpose of this study was to evaluate the relationships between objective fatigue variables (Squat Jump (SJ) and Countermovement Jump (CMJ)) measured on day-2 to the game and subjective fatigue (Rating Perceived Exertion (RPE) measured on day-3 to the game and Hooper Index (HI) measured on day-2). The sample comprised 32 professional football players from the First Portuguese League aged 25.86 ± 3.15 years. The Spearman correlations and regression analyses were used to study the relationships between the variables. The results showed statistically significant (p < 0.05) but small correlations (0.113–0.172) between several objective metrics and the subjective metrics evaluated. In addition, we found two weak models with statistical significance (p < 0.05) between the dependent objective variables (contact time, height, and elasticity index) and the HI ($R^2$ = 3.7%) and RPE ($R^2$ = 1.6%). Also, nine statistically significant (p < 0.05) but weak models were observed between the subjective dependent variables (HI and RPE) and contact time ($R^2$ = 1.8–2.7%), flight time ($R^2$ = 1.1–1.9%), height ($R^2$ = 1.2–2.3%), power ($R^2$ = 1.4%), pace ($R^2$ = 1.2–2.1%), and elasticity index ($R^2$ = 1.6%). In conclusion, objective and subjective fatigue-monitoring tests in professional soccer do not measure identical but rather complementary aspects of fatigue, and therefore, both need to be considered to gain a holistic perspective.

Muscular strength is strongly related to speed and agility tasks, which have been described as the most decisive actions preceding goals in the soccer game. This study aimed to characterize the players’ strength indicators and to analyze the variation associated with age, competition level, and positional role. Eighty-three male soccer players from A team (n = 22), B team (n = 17), U-23 (n = 19), and U-19 (n = 25) participated in this study. Handgrip strength was assessed using a hand dynamometer (Jamar Plus+), countermovement jump (CMJ) and the squat jump (SJ) were evaluated using Optojump Next, and a Biodex System 4 Pro Dynamometer was used to assess the isokinetic strength of knee extension/flexion. Team A players showed increased lower-body strength compared to their peers, mainly through their increased vertical jumping capacity (i.e., CMJ and SJ; ps < 0.019), and superior performance in isokinetic assessments (i.e., peak torque, total work, and average power). Overall, older players outperformed their younger peers regarding vertical jumping, static strength, and average power in isokinetic strength (ps < 0.005). This study emphasizes the superior strength levels of professional soccer players compared with their lower-division peers, even after controlling by age. This information is of great value to sports agents and coaches, underlining the need to design and include strength-specific content during soccer training.

Speed and agility have been described as crucial abilities for soccer players. The purpose of this study was to analyze, in detail, the variance in speed and agility tasks explained by lower-body power after controlling for age and body composition. The participants were 96 male soccer players aged 16.1 ± 1.6 years. Body composition (stature, body fat percentage—BF%, body mass, and fat-free mass—FFM), lower-body power (countermovement jump—CMJ, and squat jump—SJ), speed (5-, 10-, and 35 m sprints), and agility (t-test) were assessed. Among body composition parameters, BF% presented the highest number of significant relationships with speed and agility, with the strength of correlations ranging from small (5 m sprint, r = 0.25) to large (35 m sprint, r = 0.52). The strongest correlation coefficient emerged between FFM and the 35 m sprint (r = −0.65). Significant correlations were found between vertical jump performance and the 35 m sprint (CMJ: r = −0.68; SJ: r = −0.69), followed by the t-test (CMJ: r = −0.35; SJ: r = −0.47). The hierarchical multiple regression model could explain 22% to 67% of the variance observed in agility scores and speed. BF% remained the most statistically significant negative predictor of all regression models. The CMJ remained a statistically significant positive predictor of the 35 m sprint (β = −0.581, p ≤ 0.01) after controlling for age and body composition. Integrating programs targeting lower-body power might be important to enhance speed and agility performance in youth soccer. On the other hand, future research based on multidisciplinary approaches to investigate the effects of nutritional strategies in reducing or preventing gains in BF% is still needed, which remained a significant predictor of sprint and agility performance in the final models.

In soccer, physical development is crucial for developing optimal performance. This study aimed to assess and compare the physical development of elite and non-elite professional soccer players. Seventy-eight male professional football players divided into four competitive levels participated in this study: the elite group (EG), the non-elite group A (NEG-A), the non-elite group B (NEG-B), and the under 23 group (U23). Body composition, static strength, lower-body explosive strength, flexibility, and balance were assessed. No significant statistical differences between elite and non-elite players were seen in body composition parameters. However, the EG performed better in static strength, lower-body explosive strength, flexibility, and balance, even after adjusting for the effects of chronological age. The analysis showed that the competitive level (group) explained 25% to 29% of the variance observed in the lower-body explosive strength tasks. Sports staff and coaches in different age categories or competitive levels should include specific lower-body explosive strength content during soccer training to promote players’ long-term development towards the elite level.