Mental fatigue can impair physical, technical, and tactical performance in sports. Since most previous research used general cognitive tasks to elicit mental fatigue, the aim of this study was to investigate whether a more sport-specific task could induce the effects of mental fatigue and impair the subsequent physical and technical performance in a soccer small-sided game. Ten soccer players performed two small-sided games on two different days in a crossover design. Before each small-sided game, they performed a video-based tactical task (30 min) and a control task (documentary watching, 30 min) in a randomized and counterbalanced order. Mental effort was measured through a visual analog scale after the tactical and control tasks. Subjective ratings of perceived exertion were assessed through the RPE questionnaire after the end of the SSG. Physical performance was assessed during the SSG through GPS technology. Results showed no differences (p > 0.05) in physical performance between the two conditions. None of the technical variables were negatively affected by the video-based tactical condition, with the number of total passes (p = 0.003; ES = 0.72 medium) and successful passes (p = 0.003; ES = 0.82 large) results even improved by the video-based tactical task. The mental effort required by the video-tactical task was significantly higher than the control task (p = 0.002; ES = 2.09 huge). However, overall RPE did not differ between conditions. The video-based tactical task did not elicit mental fatigue and did not impair subsequent physical and technical performance. The higher ecological validity of the task and the higher motivation of the participants might have contributed to the results.

Predicting and avoiding an injury is a challenging task. By exploiting data mining techniques, this paper aims to identify existing relationships between modifiable and non-modifiable risk factors, with the final goal of predicting non-contact injuries. Twenty-three young soccer players were monitored during an entire season, with a total of fifty-seven non-contact injuries identified. Anthropometric data were collected, and the maturity offset was calculated for each player. To quantify internal training/match load and recovery status of the players, we daily employed the session-RPE method and the total quality recovery (TQR) scale. Cumulative workloads and the acute: chronic workload ratio (ACWR) were calculated. To explore the relationship between the various risk factors and the onset of non-contact injuries, we performed a classification tree analysis. The classification tree model exhibited an acceptable discrimination (AUC=0.76), after receiver operating characteristic curve (ROC) analysis. A low state of recovery, a rapid increase in the training load, cumulative workload, and maturity offset were recognized by the data mining algorithm as the most important injury risk factors.

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The analysis of the epidemiological data and the risk factors underlying injuries is crucial to promote prevention strategies in young soccer players. The objective of the present study was to perform a systematic literature review on the epidemiological data, described in the first part, and injury risk factors, presented in the second part. After electronic database searching, articles in line with the inclusion criteria were selected for the systematic review. Epidemiological data were extracted and discussed in this first part of the review. Data were grouped as follows: injury incidence, injury severity, and re-injury, injury types, injury mechanisms, and anatomical location. The principal findings of this first part of the review are as follows: (1) injury incidence is higher in older players and during matches than during training; (2) sex and maturity status may increase risk of injury; (3) male soccer players are more prone to muscle strains and ligament sprains while female players suffer more ligament sprains; (4) most injuries are located in the ankle and thigh in young male soccer players, and in the ankle and knee in female players; (5) severe injuries are less frequent but the incidence increases in older players. Re-injuries represent only a small percentage. Although soccer is considered a safe sport, many injuries are recorded in young soccer players every year. Injury predisposition changes in relation to age, sex, and biological age. Coaches and physical trainers should be aware of individual differences in order to promote prevention strategies and personalised training.

This study aimed to analyze different predictive analytic techniques to forecast the risk of muscle strain injuries (MSI) in youth soccer based on training load data. Twenty-two young soccer players (age: 13.5 ± 0.3 years) were recruited, and an injury surveillance system was applied to record all MSI during the season. Anthropometric data, predicted age at peak height velocity, and skeletal age were collected. The session-RPE method was daily employed to quantify internal training/match load, and monotony, strain, and cumulative load over the weeks were calculated. A countermovement jump (CMJ) test was submitted before and after each training/match to quantify players’ neuromuscular fatigue. All these data were used to predict the risk of MSI through different data mining models: Logistic Regression (LR), Random Forest (RF), Support Vector Machine (SVM). Among them, SVM showed the best predictive ability (area under the curve = 0.84 ± 0.05). Then, Decision tree (DT) algorithm was employed to understand the interactions identified by the SVM model. The rules extracted by DT revealed how the risk of injury could change according to players’ maturity status, neuromuscular fatigue, anthropometric factors, higher workloads, and low recovery status. This approach allowed to identify MSI and the underlying risk factors.

The aim of this study was to characterize the turning phase during a modified 505 test. Forty collegiate basketball students, divided into faster and slower performers and high-playing-level and low-playing-level groups, were evaluated for the force-time characteristics (braking and/or propulsive phase) of the penultimate foot contact (PFC), final foot contact (FFC), and first accelerating foot contact (AFC), and for completion time and approach velocity. Based on the composition of the AFC, trials were classified as braking/propulsive or only propulsive. Regression analysis for the prediction of completion time was performed. The AFC contributed to reacceleration through shorter contact times and step length, and lower braking force production (p < 0.05). Faster performers and the high-playing-level group demonstrated (p < 0.05): lower completion times, higher approach velocities, longer steps length in the PFC and FFC, greater braking forces and impulses in the PFC; greater braking and propulsive forces, braking impulses, lower contact times in the FFC; greater braking and propulsive horizontal forces, horizontal impulses, lower contact times and vertical impulses in the AFC. Kinetic variables from only the FFC and AFC and approach velocity predicted 75% (braking/propulsive trials) and 76.2% (only-propulsive trials) of completion times. The characterization of the turning phase demonstrated the specific contribution of each foot contact and the possible implications for training prescription.

The validity and reliability of the Optojump system were investigated for jumping height and flight time in vertical jump tests. Conversely, the purpose of the present study was to investigate the validity and reliability of the Optojump system for measuring contact time and lateral displacement in change of direction and lateral jump tests. Thirty basketball collegiate athletes were tested on two 10 m sprints with a 60° (COD60) or 180° (COD180) change of direction, lateral controlled (CLRJ) and maximal (MLRJ) rebound jump, and lateral countermovement (LCMJ) and squat (LSJ) jump with the concomitant use of two force plates and the Optojump system for the measurement of contact time in COD60, COD180, CLRJ, MLRJ, and lateral jumping distance in all the lateral jump tests. Almost perfect coefficients (r ≥ 0.95) emerged for contact time in COD60, COD180, CLRJ, MLRJ, although a systematic bias was found for COD60 (−0.01 s). Good-to-excellent reliability was found for almost all the measurements of contact time and lateral jumping distance for change of direction and lateral jump tests. Therefore, the use of Optojump system for testing change of direction and lateral jumping abilities should be executed with caution, avoiding misinterpretation of data.

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