Background/Objectives: To compare the external load (EL) of elite youth soccer players during official international matches between age categories and playing positions. Methods: The sample consisted of 42 elite youth soccer players categorized by age categories, U-15, U-17 and U-20 and playing positions: central defender (CD); fullback (FB); midfielder (MF); wide attacker (WA) and striker (ST). The Vector X7 (Catapult Sports) device was used for collecting the following EL variables: total distance traveled (TD), player load (PL) and distance traveled per velocity band 0 to 7 km/h (D7); 7 to 13 km/h (D13); 13 to 19 km/h (D19); 19 to 23 km/h (D23) and >23 km/h (HSR). Linear mixed-effect models were applied to analyze the differences. Results: Large differences were found between positions (p < 0.01) in TD (η²p = 0.48), PL (η²p = 0.30), D19 (η²p = 0.44), D23 (η²p = 0.68) and HSR (η²p = 0.53). Large differences were found according to category between U-15 and U-17 in TD (p = 0.006 and η²p = 0.25) and D13 (p = 0.003 and η²p = 0.27). Large interaction effects were found in DT (p = 0.014 and η²p = 0.44) and D23 (p = 0.002 and η²p = 0.51). Conclusions: This study concludes that there are differences in EL in official matches in elite youth players between age categories and playing position. These differences can be applied in practice to design individualized training by playing position and to monitor EL during microcycles.

The running cycle is distinguished from the gait cycle by the presence of a flight phase and distinct biomechanical characteristics. Despite existing frameworks for the temporal segmentation of running, these models remain underutilized in comprehensive biomechanical analyses, particularly for delineating phases, subphases, and key events. This study aims to provide a review of historical and contemporary temporal models of the running cycle and to introduce a unified structure designed to enhance analytical precision. The proposed framework divides the running cycle into two primary phases: (a) contact (subdivided into braking and propulsion subphases) and (b) flight, together with three critical events: (1) initial contact, (2) transition of braking–propulsion, (3) toe-off. While leg swing is not considered a phase in this framework due to temporal overlap with other phases, its recognized importance in running mechanics warrants its integrated analysis under the proposed temporal phase delineation. Additionally, methodologies for identifying these events through dynamometry and motion capture are evaluated, emphasizing their role in contextualizing kinetic and kinematic data. By integrating this temporal structure, the study aims to standardize biomechanical assessments of running technique, fostering more consistent comparisons across studies. Such integration has the potential to not only refine interpretations of running mechanics but also to enable practical advancements in athletic training, injury mitigation, and performance optimization.

Assessing the reliability of measurement instruments and equipment is essential to ensure the accurate tracking of athletes over extended periods, minimizing the measurement errors caused by chance or other factors. However, a less common but equally important analysis is the verification of inter-measurement agreement, which complements the reliability results. Purpose: To evaluate the intra- and inter-test reliability of an isometric hip adduction strength and asymmetries test in professional soccer players. Methods: Twenty-three professional male soccer players were evaluated on two occasions, 1 week apart. The force signal was collected using force plates (Pasco PS-2141), and the data processing was performed using Matlab software (R2023a, MathWorks, Natick, MA, USA). The peak force, interval RFD, peak RFD, peak force asymmetry and RFD were analyzed. Intraclass correlation coefficients (ICCs) and coefficients of variation (CV) were calculated to corroborate the intra- and inter-test reliability. In addition, the degree of agreement of the asymmetries was corroborated through the kappa index. Results: The peak force demonstrated an acceptable absolute reliability (CV < 10%) for the intra-test and test–retest condition, an excellent relative intra-test reliability and a good to moderate reliability for the test–retest reliability. However, the peak force asymmetry showed a moderate test–retest reliability and agreement. For the intra-test condition, the RFD variables demonstrate a moderate to excellent relative reliability; however, all demonstrate unacceptable absolute reliability (CV > 10%) in at least one of the evaluation sessions. A moderate to poor test–retest reliability and unacceptable absolute reliability were observed for all the RFD variables. Conclusions: The peak force is the variable with the highest intra- and inter-test reliability, so its use is recommended to longitudinally assess the maximum strength of the adductors in professional soccer players, but not the asymmetry orientation of the peak force. The RFD variables should be interpreted with caution due to their inconsistent reliability, and it is necessary to improve the methods used to achieve adequate reliability.

Background: Muscle injuries are among the main problems in professional soccer, affecting player availability and team performance. Countermovement jump (CMJ) variables have been proposed as indicators of injury risk and for detecting strength imbalances, although their use is less explored than isokinetic assessments. Unlike previous studies based solely on linear statistics, this research integrates biomechanical data with machine learning approaches, providing a novel perspective for injury prediction in elite soccer. Objective: To examine the association between CMJ variables and muscle injury risk during a competitive season, considering injury incidence and effective playing minutes. It was hypothesized that specific CMJ asymmetries would be associated with a higher injury risk, and that machine learning algorithms could accurately classify players according to their injury status. Methods: Forty-one professional soccer players (18 women, 23 men) from national league teams (Chile) were assessed during preseason using force platforms. Non-contact muscle injuries and playing minutes were recorded over 10 months after the CMJ evaluations. Analyses included two-way ANOVA (sex × injury status) and machine learning algorithms (Logistic Regression, Decision Tree, K-Nearest Neighbors [KNN], Random Forest, Gradient Boosting [GB]). Results: Significant sex differences were observed in most variables (p < 0.05 and η_p² > 0.11), except peak force and peak power asymmetry. For injury status, only peak force asymmetry differed, while sex × injury interactions were found in peak power and left peak power. KNN (Accuracy = 87% and CI 95% = 71% to 96%) and GB (Accuracy = 84% and CI 95% = 68% to 94%) achieved the best classification performance between injured and non-injured players. Conclusions: CMJ did not show consistent statistical differences between injured and non-injured groups. However, machine learning models, particularly KNN and GB, demonstrated high predictive accuracy, suggesting that injuries are a complex phenomenon characterized by non-linear patterns. These findings highlight the potential of combining CMJ with machine learning approaches for functional monitoring and early detection of injury risk, though validation in larger cohorts is required before establishing clinical thresholds and preventive applications.

Objective: To evaluate and compare the external and internal load of international matches between age categories and playing positions in a women's national team. Methods: 40 players from 3 age categories of the Chilean national teams. 14 players belonged to the U-17, 14 to the U-20 and 12 to the Senior National Team. The players were categorized according to the following playing positions: full-back (FB), central defender (CD), midfielders (MF), wide attacker (WA) and Striker (ST). The following variables were recorded: total distance (TD); distance in high-speed running >18 km/h (HSR); number of sprints at >18 km/h (NS); maximum velocity (MV), player load (PL) and rate of perceived effort (RPE). All variables were normalized by time except MV. An ANOVA two way was performed to make the comparison. Results: Medium differences were found in NS (p<0.01 and η²p=0.10) and large differences in MV (p<0.01 and η²p=0.17) and in RPE (p<0.01 and η²p=0.19). There were large interaction effects (p0.15) in TD, HSR, PL, and MV. There were large differences in all variables of external load according to playing position (p0.15). Conclusion: There are differences in external load based on age categories, playing positions and the interaction between both factors. The results can help coaching staff to program and monitor training microcycles according to the factors analyzed.

Background: The high demands of professional soccer predispose players to musculoskeletal injuries. The primary challenge for identifying potential risk factors lies in determining the appropriate assessment methods and indicators to consider. Kinetic variables have been identified as potential indicators of injury risk. Objectives: To conduct a systematic review of the literature analyzing the relationship between kinetic variables and the risk of indirect musculoskeletal injuries of the lower limb in professional soccer players. Methods: A search was conducted on Web of Science, PubMed, and Scopus following the PRISMA guidelines. The search included articles that link kinetic variables assessed through dynamometry to indirect lower limb injuries. Sample characteristics, assessments, injury follow-ups, and statistical results were extracted for qualitative synthesis. Results: A total of 1096 studies were initially identified, of which 380 duplicates were removed. After screening 716 articles by title and abstract, 631 were excluded. Subsequently, 85 full-text articles were examined, resulting in 11 studies being included. Of the included articles, 10 used isokinetic dynamometry and the Nordic hamstring curl test to assess lower limb strength. Conclusions: The results of this review indicate that kinetic variables, particularly isokinetic strength measures at different angular velocities, are consistently associated with indirect musculoskeletal injury risk in professional soccer players. The most relevant indicators include eccentric hamstring force and concentric quadriceps torque, which help identify strength deficits and muscular disequilibrium. Monitoring these variables through validated assessments enables the development of targeted prevention strategies. Additionally, injury risk assessment should integrate kinetic data with contextual indicators such as well-being, fatigue, and training load.