This study examined the effects of induced mental and muscular fatigue on soccer players' physical activity profile and collective behavior during small-sided games (SSG). Ten youth soccer players performed a 5vs5 SSG under three conditions: a) control, playing without any previous activity; b) muscular fatigue, playing after performing a repeated change-of-direction task; c) mental fatigue, playing after completing a 30 min Stroop color-word task. Players' positional data was used to compute time-motion and tactical-related variables. The muscular fatigue condition resulted in lower distances covered in high speeds (∼27%, 0.3; ±0.5) than the control condition. From the tactical perspective, the muscular fatigue condition resulted in lower distance between dyads and players spent ∼7% more time synchronized in longitudinal displacements than the control condition (0.3; ±0.3). Additionally, players spent ∼14% more time synchronized with muscular fatigue than with mental fatigue (0.7; ±0.3). The mental fatigue condition resulted in a very likely more predictable pattern in the distance between dyads than in muscular fatigue condition (0.4; ±0.2). Also, the mental fatigue possibly decreased the teams' stretch index when compared with control (0.2; ±0.3) and likely increased compared with muscular fatigue (0.5; ±0.5). The better levels of longitudinal synchronization after muscular fatigue, might suggest the usage of tactical-related tasks after intense exercise bouts. The lower physical performance and time spent longitudinally synchronized after mental fatigue, should alert to consider this variable before matches or training activities that aim to improve collective behavior.

Understanding how youth football players base their game interactions may constitute a solid criterion for fine-tuning the training process and, ultimately, to achieve better individual and team performances during competition. The present study aims to explore how passing networks and positioning variables can be linked to the match outcome in youth elite association football. The participants included 44 male elite players from under-15 and under-17 age groups. A passing network approach within positioning-derived variables was computed to identify the contributions of individual players for the overall team behaviour outcome during a simulated match. Results suggested that lower team passing dependency for a given player (expressed by lower betweenness network centrality scores) and high intra-team well-connected passing relations (expressed by higher closeness network centrality scores) were related to better outcomes. The correlation between the dyads’ positioning regularity and the passing density showed a most likely higher correlation in under-15 (moderate effect), indicating a possible more dependence of the ball position rather than in the under-17 teams (small/unclear effects). Overall, this study emphasizes the potential of coupling notational analyses with spatial-temporal relations to produce a more functional and holistic understanding of teams’ sports performance. Also, the social network analysis allowed to reveal novel key determinants of collective performance.

This study examined the effects of mental fatigue and additional corridor and pitch sector lines on players’ physical and tactical performances during soccer small-sided games. Twelve youth players performed four Gk+6vs6+Gk small-sided games. Prior to the game, one team performed a motor coordination task to induce mental fatigue, while the other one performed a control task. A repeated measures design allowed to compare players’ performances across four conditions: (a) with mental fatigue against opponents without mental fatigue in a normal pitch (MEN), (b) with mental fatigue on a pitch with additional reference lines (#MEN); (c) without mental fatigue against mentally fatigued opponents on a normal pitch (CTR); and (d) without mental fatigue on a pitch with reference lines (#CTR). Player’s physical performance was assessed by the distance covered per minute and the number of accelerations and decelerations (0.5-3.0 m/s2; > -3.0 m/s2). Positional data was used to determine individual (spatial exploration index, time synchronized in longitudinal and lateral directions) and team-related variables (length, width, speed of dispersion and contraction). Unclear effects were found for the physical activity measures in most of the conditions. There was a small decrease in time spent laterally synchronized and a moderate decrease in the contraction speed when MEN compared to the CTR. Also, there was a small decrease in the time spent longitudinally synchronized during the #MEN condition compared to MEN. The results showed that mental fatigue affects the ability to use environmental information and players’ positioning, while the additional reference lines may have enhanced the use of less relevant information to guide their actions during the #MEN condition. Overall, coaches could manipulate the mental fatigue and reference lines to induce variability and adaptation in young soccer players’ behavior.

Purpose: The aim of this study was to identify the effects of a differential-learning program, embedded in small-sided games, on the creative and tactical behavior of youth soccer players. Forty players from under-13 (U13) and under-15 (U15) were allocated into control and experimental groups and were tested using a randomized pretest to posttest design using small-sided games situations. Method: The experimental group participated in a 5-month differential-learning program embodied in small-sided games situations, while the control group participated in a typical small-sided games training program. In-game creativity was assessed through notational analyses of the creative components, and the players’ positional data were used to compute tactical-derived variables. Results: The findings suggested that differential learning facilitated the development of creative components, mainly concerning attempts (U13, small; U15, small), versatility (U13, moderate; U15, small), and originality (U13, unclear; U15, small) of players’ actions. Likewise, the differential-learning approach provided a decrease in fails during the game in both experimental groups (moderate). Moreover, differential learning seemed to favor regularity in pitch-positioning behavior for the distance between players’ dyads (U13, small; U15, small), the distance to the team target (U13, moderate; U15, small), and the distance to the opponent target (U13, moderate; U15, small). Conclusions: The differential-learning program stressed creative and positional behavior in both age groups with a distinct magnitude of effects, with the U13 players demonstrating higher improvements over the U15 players. Overall, these findings confirmed that the technical variability promoted by differential learning nurtures regularity of positioning behavior.

Artificial Intelligence (AI) is transforming the field of sports science by providing unprecedented insights and tools that enhance training, performance, and health management. This work examines how AI is advancing the role of sports scientists, particularly in team sports environments, by improving training load management, sports performance, and player well-being. It explores key dimensions such as load optimization, injury prevention and return-to-play, sports performance, talent identification and scouting, off-training behavior, sleep quality, and menstrual cycle management. Practical examples illustrate how AI applications have significantly advanced each area and how they support and enhance the effectiveness of sports scientists. This manuscript also underscores the importance of ensuring that AI technologies are context-specific and communicated transparently. Additionally, it calls for academic institutions to update their curriculums with AI-focused education, preparing future sports professionals to fully harness its potential. Finally, the manuscript addresses future challenges, such as the unpredictable nature of team sports, emphasizing the need for interdisciplinary collaboration, including clear communication and mutual understanding between sports scientists and AI experts, and the critical balance between AI-driven insights and human expertise.