Search Results (126)

Background: Reaction time and coordination are key performance components in team sports such as handball, particularly during the developmental years. Integrating visual and cognitive stimuli through smart technologies has been shown to facilitate motor skill development in young athletes. Methods: This study evaluated the effects of a BlazePod-based training protocol on reaction time, visuomotor coordination, movement quickness, and change-of-direction performance in junior male handball players aged 12–14 years. Thirty-two athletes (mean age = 13.37 ± 0.29 years) were randomly assigned to an experimental group (n = 16), in which the traditional neuromotor/coordination block of regular practice was replaced with BlazePod-based drills three times per week for eight weeks, or to a control group (n = 16), which trained the same capacities with traditional handball-specific exercises without technology. Training frequency (3 sessions/week), session duration (90 min), and the workload of the 30 min neuromotor block were matched between groups. Motor performance was assessed using four tests: Focus Reactions, Fast Feet, Clap Challenge, and the Agility T-Test. Paired- and independent-samples t-tests were applied to compare pre- and post-intervention scores. Results: The experimental group showed significant within-group improvements in Focus Reactions (p = 0.002) and AgilTT_ShuffleLeft (p = 0.014), whereas the control group showed no improvements and a small but significant worsening in Focus Reactions. Between-group comparisons at post-test revealed significant differences in favor of the experimental group for Fast Feet (p = 0.036), Clap Challenge (p = 0.008), AgilTT_Overall (p < 0.001), and AgilTT_SprintBack (p = 0.003). Conclusions: The integration of BlazePod technology into handball training produced measurable improvements in reaction speed and lateral agility among junior players. These findings suggest that technology-assisted neuromotor training represents a viable training modality that can replace a traditional neuromotor block within youth handball practice while maintaining overall training dose. Full article

This study examined the effect of competition stress on recovery time in female collegiate soccer players. Thirty NCAA Division I athletes were monitored over 35 consecutive days using Polar Team Pro wearable devices, which captured exercise duration, distance covered, energy expenditure, sprint count, speed, heart rate, training load, and recovery duration. Data were collected across 20 practices and 7 competitions, totaling 845 observations. Linear regression was used to assess whether formal competition independently influenced recovery duration, controlling for time of day and workload variables. Athletes averaged 20.1 ± 1.1 years of age. Across all sessions, the mean exercise duration was 59.5 ± 38.7 min, with an average distance of 2.6 ± 2.1 km, and energy expenditure of 387.2 ± 283.5 kcals. Recovery duration was significantly longer after competition (51.3 ± 59.6 h) compared to practice (13.0 ± 15.8 h, p < 0.001). The regression model indicated that formal competition predicted an additional 51 h of recovery time (β = 50.540; p < 0.001), independent of physical workload. Recovery following formal competition is significantly prolonged, holding multiple components of workload constant. These findings offer novel insights into female athlete recovery and highlight the importance of sex-specific approaches in sports science. Full article

Recent advancements in wearable technology have allowed researchers to collect high-resolution data on athletes’ workloads and performance, paving the way for more accurate mathematical models in sports science. In this paper, inspired by the modeling of heart rate during exercise, we introduce a novel linear, time-varying, two-state discrete-time dynamical model for predicting athletic performance in elite-level soccer players. Model parameters are estimated via the Differential Evolution optimization algorithm, and GPS-derived metrics such as metabolic power and equivalent distance index are incorporated. The model originally accounts for complex interactions between a performance-related state variable and a second lumped variable, whose dynamics are intertwined. This model was compared to the most effective deterministic (though uncertain) one in the literature, namely the (nonlinear) Busso model. Results, concerning two professional soccer players over a half-season period, show that the proposed model outperforms the traditional approach in estimation and predictive accuracy, with significantly higher correlation coefficients and lower estimation and prediction errors across all players. These findings suggest that integrating two-state dynamics and fine-grained GPS metrics provides a more biologically realistic framework for load monitoring in team sports. The proposed model thus represents a powerful tool for training optimization and athlete readiness assessment, with potential applications in real-time decision support systems for coaching staff. By predicting the effects of training load on future performance, it might also contribute to injury risk reduction and the prevention of maladaptive responses to excessive workload. Full article

This study examined the relationship between training load, mileage, and session rating of perceived exertion (s-RPE) as predictors of injury and illness in Division I women’s soccer players. Twenty-four athletes were monitored over a 13-week season including 69 athlete exposures (49 training sessions and 20 matches). Internal and external load were measured during each athlete exposure. Player injury and illness status were documented daily by medical staff and categorized as healthy, medical attention, or time-loss. Associations between athlete exposures and injury/illness status were analyzed using a mixed-effects ordinal logistic regression model with player ID as a random intercept. A total of 1560 athlete observations were included. Higher daily mileage was associated with increased odds of injury or illness (OR = 1.67, 95% CI: 1.19–2.34). Training load was associated with reduced odds of injury or illness, with each unit increase lowering the odds by 42% (OR = 0.58, 95% CI: 0.41–0.83). Session-RPE was not significantly associated with injury or illness (OR = 0.96, 95% CI: 0.65–1.42). These findings indicate that accumulated mileage elevates injury and illness risk, while structured increases in training load enhance athlete resilience, and reduce injury and illness risk. Monitoring both internal and external workload provides performance staff with a practical approach to optimize training stress, augment recovery, and prepare athletes for the demands of competition in women’s soccer. Full article

Background: Professional football requires more attention in planning work regimens that balance players’ sports performance optimization and reduce their injury probability. Machine learning applied to sports science has focused on predicting these events and identifying their risk factors. Our study aims to (i) analyze the differences between injury incidence during training and matches and (ii) build and classify different predictive models of risk based on players’ internal and external loads across four sports seasons. Methods: This investigation involved 96 male football players (26.2 ± 4.2 years; 181.1 ± 6.1 cm; 74.5 ± 7.1 kg) representing a single professional football club across four analyzed seasons. The research was designed according to three methodological sets of assessments: (i) average season performance, (ii) two weeks’ performance before the event, and (iii) four weeks’ performance before the event. We applied machine learning classification methods to build and classify different predictive injury risk models for each dataset. The dependent variable is categorical, representing the occurrence of a time-loss muscle injury (N = 97). The independent variables include players’ information and external (GPS-derived) and internal (RPE) workload variables. Results: The Kstar classifier with the four-week window dataset achieved the best predictive performance, presenting an Area Under the Precision–Recall Curve (AUC-PR) of 83% and a balanced accuracy of 72%. Conclusions: In practical terms, this methodology provides technical staff with more reliable data to inform modifications to playing and training regimens. Future research should focus on understanding the technical staff’s qualitative vision of predictive models’ in-field applicability. Full article

Background: Accurate assessment of aerobic capacity is essential for performance monitoring in masters athletes, particularly in high-intensity team sports. The objective of this study was to evaluate the validity and agreement of three indirect maximal oxygen uptake (VO₂max) protocols (Åstrand–Ryhming, YMCA, and Polar OwnIndex Fitness test) against the gold-standard cardiopulmonary exercise testing (CPET) in masters basketball players. Methods: A cross-sectional comparative study included 50 male masters basketball players (aged 51–81 years, M = 64.3 ± 7.9). Validity was determined by comparing results from the three indirect protocols to direct VO₂max measurement via CPET. Agreement was assessed using Pearson correlations (r), systematic error, mean absolute error (MAE), and Bland–Altman limits of agreement. Results: The Åstrand–Ryhming test and YMCA tests showed the closest agreement with CPET (systematic error < 4%, MAE ≈ 17–18%, r > 0.50). The Polar OwnIndex test substantially overestimated VO₂max (mean error ≈ 30%, MAE = 32%). The Åstrand–Ryhming test at low workload yielded the strongest correlation (r = 0.75). Conclusions: The Åstrand–Ryhming and YMCA submaximal tests demonstrated acceptable validity and low systematic bias for estimating VO₂max in masters basketball players, positioning them as practical alternatives to CPET. Conversely, the Polar OwnIndex test showed poor agreement and clinically significant overestimation. These findings support the use of submaximal cycling protocols for fitness monitoring and tailored training prescription in this specific older athlete population. Future longitudinal research is warranted to confirm their ability to track fitness changes over time in this population. Full article

Background and Objectives: This study aimed to assess the week-by-week predictive value of Acute:Chronic Workload Ratios (ACWRs) for non-contact injury risk in professional soccer players. Materials and Methods: A cohort of 40 elite players was monitored using GPS over two competitive seasons. Binomial logistic regression and ROC curve analyses were performed on ACWR metrics—including total distance, moderate-to high-speed running, sprinting, acceleration, and deceleration—during the four weeks prior to injury (W4 to W1). p-values were further adjusted for multiple comparisons using the false discovery rate (FDR) correction (q < 0.05). Results: Significant predictive models emerged mainly for ACWR metrics related to moderate-speed running (15–20 km/h), sprinting (>25 km/h), and acceleration/deceleration. The ACWR for 15–20 km/h (DSR15–20) demonstrated the highest predictive accuracy, particularly in Week 3 (AUC = 0.811, p = 0.004). Sprinting (DSR>25) was also significantly associated with injury occurrence across Weeks 1–4 (AUC = 0.709–0.755, p = 0.011–0.024). Acceleration (ACC) and deceleration (DEC) metrics showed significant associations prior to correction—ACC in Weeks 3–4 (AUC = 0.737–0.755, p = 0.020–0.026) and DEC in Weeks 3–4 (AUC = 0.720–0.741, p = 0.029–0.043)—but these associations did not retain significance following FDR adjustment (q = 0.052–0.086). In contrast, total distance (ACWR TD) and high-speed running (20–25 km/h) were weaker predictors, reaching only marginal or nonsignificant levels (e.g., Week 3, AUC = 0.675, p = 0.054). After FDR correction, only DSR15–20 and DSR>25 remained statistically significant (q < 0.05), confirming them as robust predictors of non-contact injury risk. Multivariable models adjusted for age and playing position confirmed these findings, with DSR15–20 and DSR>25 retaining their predictive value independent of confounding factors. Injury risk thresholds were established through Estimated Marginal Means (EMMs), defining the “Sweet Spot” and “Danger Zone” for each metric, whereas the “Low Load” zone was treated as exploratory. Conclusions: This weekly ACWR monitoring approach enables practical injury risk profiling, helping training staff optimize load management and minimize non-contact injury risk in elite soccer. Full article

Basketball is a high-intensity, intermittent sport in which physical demands fluctuate depending on different contextual variables. Most studies addressed these demands in isolation without integrative approaches. Therefore, the present study aimed to identify key variables explaining players’ physical workload across game quarters and playing positions through principal component analysis (PCA). Ninety-four elite U18 male basketball players were registered during the EuroLeague Basketball ANGT Finals using WIMU PRO™ multi-sensor wearable devices that integrate local positioning systems (LPS) and microelectromechanical systems (MEMS). From over 250 recorded variables, 31 were selected and analyzed by PCA for dimensionality reduction, analyzing the effects of game quarter and playing position. Five to eight principal components explained 61–73% of the variance per game quarter, while between four and seven components explained 64–69% per playing position. High-intensity variables showed strong component loadings in early quarters, with explosive distance (loading = 0.898 in total game, 0.645 in Q1) progressively declining to complete absence in Q4. Position-based analysis revealed specific workload profiles: guards required seven components to explain 69.25% of the variance, with complex movement patterns, forwards showed the highest explosive distance loading (0.810) among all positions, and centers demonstrated concentrated power demands, with PC1 explaining 34.12% of the variance, dominated by acceleration distance (loading = 0.887). These findings support situational and individualized training approaches, allowing coaches to design individual training programs, adjust rotation strategies during games, and replicate demanding scenarios in training while minimizing injury risk. Full article

Background: High-performance tennis exposes players to repetitive high-load strokes and abrupt directional changes, which substantially increase musculoskeletal injury risk. This systematic review synthesized evidence on epidemiology, risk factors, and physiotherapy-led preventive strategies in elite adolescent and adult players. Methods: Following a PROSPERO-registered protocol, MEDLINE, Web of Science, and Scopus were searched (2011–2024) for observational studies reporting epidemiological outcomes in high-performance tennis. Methodological quality was appraised with NIH tools, and certainty of evidence was graded with GRADE. Results: Thirty-seven studies met inclusion criteria: 16 in adolescents, 18 in adults, and 3 mixed. Incidence ranged from 2.1 to 3.5 injuries/1000 h in juniors and 1.25 to 56.6/1000 h in adults. Seasonal prevalence was 46–54% in juniors and 30–54% in professionals. Lower-limb trauma (48–56%) predominated, followed by lumbar (12–39%) and shoulder overuse syndromes. Across age groups, abrupt increases in the acute-to-chronic workload ratio (≥1.3 in juniors; ≥1.5 in adults) were the strongest extrinsic predictor of injury. Intrinsic contributors included reduced glenohumeral internal rotation, scapular dyskinesis, and poor core stability. Three prevention clusters emerged: (1) External load control, four-week “ramp-up” strategies reduced injury incidence by up to 21%; (2) Kinetic-chain conditioning, core stability plus eccentric rotator-cuff training decreased overuse by 26% and preserved shoulder mobility; and (3) Technique/equipment adjustments, grip-size personalization halved lateral epicondylalgia, while serve-timing modifications reduced shoulder torque. Conclusions: Injury risk in high-performance tennis is quantifiable and preventable. Progressive load management targeted kinetic-chain conditioning, and tailored technique/equipment modifications represent the most effective evidence-based safeguards for adolescent and adult elite players. Full article

Background: Understanding the relationship between physical demands and game performance is essential to optimize player development and management in basketball. This study aimed to examine the association between game performance and physical demands in youth male basketball players. Methods: Fifteen players (16.3 ± 0.7 years) from a Spanish 4th division team were monitored over seven official games. Game performance variables were extracted from official statistics, including traditional and advanced metrics. Physical demands were monitored using an Electronic Performance Tracking System device, combining a positioning system and inertial sensors. Partial correlations, controlling for minutes played, were calculated to explore associations between physical demands and performance variables, both for the entire team and by playing position. Results: Significant correlations between physical demands and game performance were observed. Points scored correlated strongly with total distance and high-intensity accelerations, while assists correlated with high-intensity decelerations. Inertial metrics, such as player load and the number of jumps, showed large correlations with points, two-point attempts, and the efficiency rating. Positional analysis revealed stronger and more numerous correlations for centers compared to guards and forwards. Inertial sensor-derived metrics exhibited a greater number and strength of correlations than positioning metrics. Conclusions: Game performance and physical demands are intrinsically related, with specific patterns varying by playing position. Inertial sensors provide valuable complementary information to positioning systems for assessing physical demands in basketball. These findings can assist practitioners in tailoring monitoring and training strategies to optimize performance and manage player workload effectively. Full article

The development of Global Positioning System (GPS) technology has contributed in various ways to improving the physical condition of modern football players by enabling the quantification of physical load. Previous studies have reported that the running demands of matches vary depending on playing position and formation. Over the past decade, despite the widespread use of GPS technology, studies that have investigated the running performance of young football players within the 1-4-3-3 formation are particularly limited. Therefore, the aim of the present study was to create the match running profile of playing positions in the 1-4-3-3 formation among high-level youth football players. An additional objective of the study was to compare the running performance of players between the two halves of a match. This study involved 25 football players (Under-19, U19) from the academy of a professional football club. Data were collected from 18 league matches in which the team used the 1-4-3-3 formation. Positions were categorized as Central Defenders (CDs), Side Defenders (SDs), Central Midfielders (CMs), Side Midfielders (SMs), and Forwards (Fs). The players’ movement patterns were monitored using GPS devices and categorized into six speed zones: Zone 1 (0.1–6 km/h), Zone 2 (6.1–12 km/h), Zone 3 (12.1–18 km/h), Zone 4 (18.1–21 km/h), Zone 5 (21.1–24 km/h), and Zone 6 (above 24.1 km/h). The results showed that midfielders covered the greatest total distance (p = 0.001), while SDs covered the most meters at high and maximal speeds (Zones 5 and 6) (p = 0.001). In contrast, CDs covered the least distance at high speeds (p = 0.001), which is attributed to the specific tactical role of their position. A comparison of the two halves revealed a progressive decrease in the distance covered by the players at high speed: distance in Zone 3 decreased from 1139 m to 944 m (p = 0.001), Zone 4 from 251 m to 193 m (p = 0.001), Zone 5 from 144 m to 110 m (p = 0.001), and maximal sprinting (Zone 6) dropped from 104 m to 78 m (p = 0.01). Despite this reduction, the total distance remained relatively stable (first half: 5237 m; second half: 5046 m, p = 0.16), indicating a consistent overall workload but a reduced number of high-speed efforts in the latter stages. The results clearly show that the tactical role of each playing position in the 1-4-3-3 formation, as well as the area of the pitch in which each position operates, significantly affects the running performance profile. This information should be utilized by fitness coaches to tailor physical loads based on playing position. More specifically, players who cover greater distances at high speeds during matches should be prepared for this scenario within the microcycle by performing similar distances during training. It can also be used for better preparing younger players (U17) before transitioning to the U19 level. Knowing the running profile of the next age category, the fitness coach can prepare the players so that by the end of the season, they are approaching the running performance levels of the next group, with the goal of ensuring a smoother transition. Finally, regarding the two halves of the game, it is evident that fitness coaches should train players during the microcycle to maintain high movement intensities even under fatigue. Full article

This study aimed to compare the external peak physical demands (PDs) of under-19-year-old (U19) and professional male football players according to playing position. Positional data derived from Global Positioning System (GPS) tracking during 15 matches in the 2023/24 season for both groups were analyzed. The following variables were measured: total distance, high-intensity running distance, sprint distance, acceleration count, and high-intensity actions. A linear mixed-effects model was employed, with category and playing position included as fixed effects to compare these metrics at the player level. The results revealed only a few significant differences in physical demands between the U19 and professional players. Notably, central defenders and central midfielders exhibited lower performance in HSR distance compared to other positions, with the professional players registering higher values than their U19 counterparts. However, no significant differences were observed for total and relative sprint distances, the number of accelerations, high intensity and relative sprint running efforts. These findings highlight the overall similarity in physical demands between U19 players and professional players, suggesting that elite youth athletes may be adequately prepared to meet the physical challenges of professional competition, with the exception of HSR distance. These conclusions have practical implications for coaches and performance staff, supporting the development of position-specific training programs, optimizing workload management through GPS monitoring, improving microcycle planning, and enhancing injury prevention strategies. Full article

Objectives: The purpose of the present study was to investigate the relationship between acute and chronic loads, and the fatigue response within male elite professional football players. Design: 40-week longitudinal study across the 2021–2022 season in the English Championship. Methods: Twenty-three outfield football players had workload measured using global positioning system (Distance, High-Intensity Distance and Sprint Distance) and perceived exertion. Load-response was measured via a perceived wellbeing questionnaire, counter-movement jump (CMJ) and salivary immunoglobulin A. Results: General estimating equation models identified 18 significant interactions between workload and load-response markers. Thirteen significant interactions were found between acute and chronic workloads and CMJ variables, jump height, eccentric duration and flight contraction time. A poor CMJ was observed when acute sprint workload was >+1 standard deviation and chronic distance increased. However, when chronic perceived exertion increased, and acute sprint workload was >+1 standard deviation an advantageous response was detected on counter movement jump variables. The S-IgA response to acute and chronic workload was more variable; when chronic loads were >+1 standard deviation above mean values and acute workload increased, salivary immunoglobulin A was both suppressed and elevated depending on the interacting acute variable. Higher chronic workload was associated with better perceived wellbeing, even when acute workload was >+1 standard deviation above the mean. Conclusion: In general, low chronic workloads and acute spikes in workload were associated with poorer neuromuscular and immune function. Furthermore, CMJ performance and perceived wellbeing improved when chronic workloads were higher, despite the occurrence of acute spikes in workload. Full article

Introduction: Basketball performance requires not only intermittent high-intensity movements—such as sprinting, jumping, and rapid directional changes—but also rapid decision-making under cognitive and psychological stress. Transcranial direct current stimulation (tDCS) has emerged as a potential modality to enhance both physical and mental performance due to its capacity to modulate cortical excitability and promote synaptic plasticity. Although the broader literature suggests that tDCS can benefit motor performance and endurance across various sports, its specific impact on basketball remains underexplored. Methods: This scoping review aimed to summarize current evidence on the effects of tDCS in basketball. A comprehensive literature search was conducted across databases including PubMed/Medline, Google Scholar, and Cochrane, identifying studies published between January 2008 and February 2025. Only clinical trials investigating tDCS interventions in basketball players were included. Eleven articles met the inclusion criteria and were synthesized narratively, with a focus on stimulation parameters (site, duration, intensity) and performance outcomes (shooting accuracy, dribbling, sprinting, decision-making, fatigue). Results: The reviewed studies indicated that tDCS—particularly when applied over the motor cortex—was associated with moderate improvements in shooting accuracy, dribbling time, repeated-sprint performance, and decision-making under fatigue. Some studies reported delayed rather than immediate benefits, suggesting that tDCS may prime neural networks for enhanced learning and retention. However, not all findings were consistent; certain interventions produced minimal or no significant effects, especially regarding subjective mental fatigue and cognitive workload. The variability in electrode placements and stimulation protocols highlights the need for methodological standardization. Conclusions: Current evidence partially supports the potential of tDCS to improve specific performance domains in basketball, particularly in skill acquisition, neuromuscular efficiency, and decision-making. Nevertheless, the findings are limited by small sample sizes, heterogeneous protocols, and a lack of long-term follow-up. Future research should prioritize larger, multisite studies with standardized tDCS parameters and ecologically valid outcome measures to confirm the efficacy and practical relevance of tDCS in competitive basketball settings. Full article

The aim of this study was to record and interpret external load parameters in professional soccer players in competitive microcycles with one or two matches per week, while investigating the interaction between training load and non-contact musculoskeletal injuries during training and matches. Musculoskeletal injuries in athletes are closely associated with workload fluctuations, particularly the acute:chronic workload ratio (ACWR) over preceding weeks. This study analyzed the physical workload of 40 high-level soccer players competing in the Greek championship across two seasons, encompassing 50 competitive microcycles, 60 official matches, and 300 training sessions. GPS-based assessments recorded total distance (TD), running speeds (15–20 km/h, 20–25 km/h, 25–30 km/h), accelerations (>2.5 m/s²), and decelerations (>2.5 m/s²). An independent sample t-test was conducted to compare injured and uninjured athletes, with statistical significance set at p < 0.05. Results showed that 20 injured athletes frequently exceeded the ACWR threshold (>1.3) compared to uninjured players. Analysis of the four weeks preceding the injury revealed that increased workload in high-intensity categories significantly contributed to non-contact injuries. Specifically, high running speeds of 15–20 km/h (p = 0.015), 20–25 km/h (p = 0.045) and >25 km/h (p = 0.008), as well as accelerations (p = 0.010), were linked to a higher risk of injury. The three-week ACWR model indicated statistically significant differences in the ACWR index for total distance (p = 0.033), runs at 15–20 km/h (p = 0.007), >25 km/h (p = 0.004), accelerations (p = 0.009), and decelerations (p = 0.013). In the two-week model, significant differences were found in runs at 15–20 km/h (p = 0.008) and >25 km/h (p = 0.012). In the final week, significant differences were observed in runs at 15–20 km/h (p = 0.015), >25 km/h (p = 0.016), and accelerations (p = 0.049). Additionally, running speeds of 25–30 km/h (p values between 0.004 and 0.016) played a key role in injury risk when limits were exceeded across all weekly blocks. These findings highlight the importance of monitoring ACWR to prevent injuries, particularly by managing high-intensity workload fluctuations in elite athletes. Full article