The relationship between training load and injury risk in basketball is a critical factor in performance optimization and injury prevention. Evidence accumulated over the past 25 years indicates a complex, non-linear association: while excessive training may increase injury risk, appropriately managed workloads can provide protective benefits, whereas undertraining or sudden workload spikes may also elevate risk. This review synthesizes findings from studies examining professional and youth basketball players, incorporating both observational and retrospective cohort research. A systematic search of PubMed, Scopus, Web of Science, and Google Scholar up to September 2025 identified six studies that met the inclusion criteria. Observational studies using session rating of perceived exertion (s-RPE) demonstrated that most injuries occurred in the lower extremities and were frequently associated with periods of peak physical and psychological fatigue. These monitoring approaches represent practical and cost-effective tools for tailoring workloads and preventing overtraining. Retrospective cohort analyses of professional players indicated that athletes with lower in-game activity, such as fewer decelerations or reduced distance covered, exhibited higher injury incidence, suggesting that under-loaded players may be at greater risk. In youth basketball, wearable technologies and neuromuscular metrics such as weighted jump height revealed that overuse injuries often occur following periods of low chronic workload combined with high acute load highlighting the impact of sudden workload spikes. Collectively, these findings underscore the importance of individualized workload management, progressive training strategies, and continuous monitoring to reduce injury risk while optimizing performance. Integrating session rating of perceived exertion and biomechanical metrics into training planning offers an evidence-based approach for safeguarding athletes’ health and optimizing outcomes.
Artificial intelligence and computer vision have made significant progress in recent decades, profoundly impacting many scientific and professional disciplines, kinesiology included. The development of markerless motion capture technologies has enabled precise tracking of kinematic and dynamic parameters of the human body movements without the need for physical markers or complex equipment. These technologies use advanced computer vision and deep learning algorithms to analyze human movements in real time, allowing the quantification of biomechanical parameters such as joint angles, movement speed, stride length, gait asymmetries, and complex movements such as jumping or running. Markerless technologies reduce preparation and recording time and allow movement analysis in natural conditions, making them useful not only in laboratory but also in clinical, sports, rehabilitation, and everyday settings. The use of smartphone video recordings further facilitates the availability and implementation of these systems. However, the application of markerless technologies to complex three-dimensional movements, such as trunk rotations or upper limb activities, remains a challenge. The accuracy of these systems depends on various factors, including movement type, number of cameras, recording quality, and lighting conditions. Advances in deep learning and computer vision allow continuous improvement in reliability, making these systems more competitive with the traditional marker-based methods. Markerless technologies have significant potential in rehabilitation and sports performance optimization, but further development is needed regarding validation standardization and algorithmic robustness. This paper aims to show how markerless technologies enable new approaches in the analysis of human movement, exploring their advantages, challenges, and potential for further development in kinesiology.
Although evidence suggests that physical fitness level may play a contributing role in injury development in athletes, available literature yields conflicting results with positive, null or even negative associations between them. Therefore, the main purpose of the study was to examine cross-sectional associations between baseline physical fitness and injury occurrence. In this study, participants were 60 male 1st Division basketball players (mean age: 22.1 ± 1.4 years, height: 193.3 ± 6.2, body mass: 89.3 ± 12.1 kg). Physical fitness was assessed through musculoskeletal (squat jump, countermovement jump, and countermovement jump with the arm swing) and cardiorespiratory fitness (maximal oxygen uptake). Injury registration included a question regarding any musculoskeletal complaint or injuries during the previous seven days with ‘yes’ and ‘no’ answers. The least fit group of participants in squat jump (OR = 1.25, 95% CI 1.10 to 2.55, p<.001), countermovement jump (OR = 1.14, 95% CI 1.02 to 1.96, p=.036), and maximal oxygen uptake (OR = 1.32, 95% CI 1.10 to 2.10, p<.001) exhibited the highest likelihood of injury occurrence, compared with the high fit group. The medium fit group in squat jump (OR = 1.05, 95% CI 1.01 to 4.05, p=.045) was at the significant and increased risk for injury occurrence comparing with the high fit group. This study indicates that lower levels of musculoskeletal and cardiorespiratory physical fitness may lead to higher likelihood of injury occurrence in male basketball players. Thus, physical fitness may be considered as a protective factor against injuries incurred.
Soccer is an aerobic sport with intermittent characteristics, requiring load management strategies. The physical efficiency index (PEI) is commonly used for this purpose, calculated as the ratio between external and internal load (distance per minute / %HRmax). Recently, a new PEI was proposed, incorporating the number of accelerations [(number of accelerations x distance per minute) / %HRmax] due to their impact on match performance. Therefore, the aim of this study was to compare the traditional PEI with the new PEI in professional soccer matches. This study compared both indices in 14 matches played by a professional team in Brazil’s Série B, with 11 athletes (25.4 ± 3.24 years; 74.17 ± 4.60 kg; 179.10 ± 7.94 cm; VO₂ max: 54.76 ± 12.24 ml/kg/min). Variables analyzed included total distance covered, sprints, accelerations, and decelerations. The average total distance was 9712.00 ± 490.90 m, with 496.80 ± 88.28 m in high-speed running and 173.98 ± 40.20 m in sprints. The mean number of accelerations was 103.4 ± 8.91, and decelerations 99.72 ± 9.06. The new PEI showed higher values than the traditional PEI (1.35 vs. 1.18; p<.001). Results suggest that the new PEI, incorporating accelerations, is a more suitable tool for load monitoring, as it better reflects the biomechanical and physiological demands of the game. This can help optimize training strategies, minimize athletes’ fatigue, and improve their post-match recovery.
The aim of this study was to compare the performance of the Abalakov jump (AJ) test and the countermovement jump (CMJ) test in youth football players, and to examine the effects of these tests on jump-related outputs. Thirty-two male football players, aged between 10 and 14 years with an average of three years of football experience, participated in the study. Jump tests were performed using the ForceDecks system (VALD, Brisbane, Australia). Force-time derived performance variables obtained during CMJ and AJ were analyzed and compared. The findings revealed that the AJ test produced significantly higher values in jump height, peak force, peak power, and take-off velocity compared to the CMJ (p<.05). While the AJ test provides an advantage in sport-specific and dynamic performance measurements, the CMJ can be used as a more standardized and controlled assessment tool. Therefore, it is recommended that both tests be used complementarily in training monitoring and performance evaluation processes in football players within this age group.
The purpose of this study was to investigate the prevalence, risk factors, and rehabilitation strategies for low back pain among high-level competitive figure skaters across singles, pair, and ice dance disciplines. A total of 194 skaters completed a detailed questionnaire assessing training routines, on- and off-ice activities, and history of lumbar spine problems. Results indicated that 33.7% of singles skaters, 41.1% of pair skaters, and 25.9% of ice dancers reported low back pain interfering with training regime or competition. Statistical analysis showed that inclusion of trunk stability, balance, and strengthening exercises in off-ice training was associated with a significantly lower prevalence of low back pain (p<.05), with core stability exercises demonstrating the greatest effect: 94.6% of skaters without low back pain regularly performed these exercises compared with 24.6% of those with low back problems. Statistically significant associations (p<.05) were observed between low back pain and the execution of technically demanding lifts and complex spins, whereas no such association was found for less demanding skating elements. All participants reporting low back pain received individualized physiotherapy programs targeting core stability, strength, coordination, and proprioception, which were associated with effective recovery and return to sport-specific activities. These findings highlight the mechanical demands on the lumbar spine in high-level figure skaters and underscore the importance of structured on- and off-ice training programs, together with targeted physiotherapy, for the prevention and rehabilitation of low back pain
This study evaluated the Critical Speed (CS) model as a tool to predict performance during major swimming competitions. This is a retrospective observational study that used data publicly available. Data were collected from 40 elite swimmers (21 men, 19 women) across 60 data sets, and their performances in the finals of the 400 m, 800 m, and 1500 m freestyle events were analyzed. The CS model (including CS and D′) was calculated from the first two events and used to predict performance in the third. For men, the model used 400 m and 800 m data to predict 1500 m; for women, it used 400 m and 1500 m to predict 800 m. The model yielded reasonably accurate predictions, with a mean error of 6.3 ± 8.2 seconds (0.7 ± 1.0%) for men and -2.0 ± 3.0 seconds (-0.4 ± 0.6%) for women. Accuracy was higher for women, likely due to the use of interpolation rather than extrapolation. The CS model shows potential for real-time use in multi-event competitions, offering coaches and athletes a practical, low-cost tool for pacing strategies, opponent analysis, and performance forecasting using only in-competition data. Despite some limitations, such as selection bias and uncontrolled variables, the CS model is a promising method for elite-level performance management, but its generalization to a broader population of athletes has not yet been attested.
This study investigated the association between body composition parameters and half-marathon running performance in a sample of 193 runners classified in tiers 1-3. Participants were measured for body fat percentage, muscle mass, visceral fat, body mass index, total body water, and bone mass using a bioimpedance analyser one day before the official race. The running time in minutes was recorded after the race. Descriptive statistics revealed a wide range of body composition and performance values, reflecting the heterogeneity of the examined runners. Multiple linear regression analysis was conducted to assess the predictive value of the body composition variables on running time. The model, which included six body composition parameters, explained almost 83% of the variance in half-marathon running time (R²=0.834), with body fat percentage emerging as the only significant predictor (β=0.193, p=.002). Higher body fat percentage was associated with longer running times, while other parameters did not reach statistical significance. The reduction in the Root Mean Square Error relative to the baseline model confirmed the improved prediction accuracy when other body composition measures were included. These findings highlight the importance of body composition, especially body fat percentage, in endurance performance. The results can help coaches and sports professionals optimize training and monitor body composition to enhance athletic performance in runners.
This study aimed to evaluate the intra-individual between-day variability in the number of repetitions performed before exceeding 10%, 20%, and 30% velocity loss thresholds (VLTs) during the back squat exercise. Thirty resistance-trained male wrestlers performed sets of repetitions to failure at 70% and 80% of their 1-repetition maximum (1RM) on two separate days. Velocity loss was calculated using as the reference either the first repetition of the set or the fastest repetition. The set termination criterion specified stopping the set after one or two consecutive repetitions exceeded the prescribed VLT. Variability in repetitions was expressed as the coefficient of variation (CV), calculated as the absolute difference between sessions divided by the average repetitions across sessions. All factors, including load (70%1RM vs. 80%1RM), reference repetition (first repetition vs. fastest repetition), and set termination criterion (one vs. two repetitions exceeding the VLT), significantly affected the number of repetitions performed for the 10%, 20%, and a 30% VLT conditions (p<.01). Regardless of these factors, intra-individual variability in the number of repetitions performed between sessions was consistently high (CV > 10%). These findings highlight two key challenges when using VLTs in training prescription. First, specifying a VLT alone is insufficient, as the actual number of repetitions performed—which ultimately dictates adaptations—is influenced by multiple methodological factors. Second, even when methodological factors are standardized, the inherent variability in the number of repetitions performed across sessions remains high, which could impact acute fatigue responses and long-term training adaptations.
Soccer is an aerobic sport with intermittent characteristics, requiring load management strategies. The physical efficiency index (PEI) is commonly used for this purpose, calculated as the ratio between external and internal load (distance per minute / %HRmax). Recently, a new PEI was proposed, incorporating the number of accelerations [(number of accelerations x distance per minute) / %HRmax] due to their impact on match performance. Therefore, the aim of this study was to compare the traditional PEI with the new PEI in professional soccer matches. This study compared both indices in 14 matches played by a professional team in Brazil's S & eacute;rie B, with 11 athletes (25.4 +/- 3.24 years; 74.17 +/- 4.60 kg; 179.10 +/- 7.94 cm; VO2 max: 54.76 +/- 12.24 ml/kg/min). Variables analyzed included total distance covered, sprints, accelerations, and decelerations. The average total distance was 9712.00 +/- 490.90 m, with 496.80 +/- 88.28 m in high-speed running and 173.98 +/- 40.20 m in sprints. The mean number of accelerations was 103.4 +/- 8.91, and decelerations 99.72 +/- 9.06. The new PEI showed higher values than the traditional PEI (1.35 vs. 1.18; p<.001). Results suggest that the new PEI, incorporating accelerations, is a more suitable tool for load monitoring, as it better reflects the biomechanical and physiological demands of the game. This can help optimize training strategies, minimize athletes' fatigue, and improve their post-match recovery.
The main purpose of the present study was to examine the associations between anaerobic power output and agility-related tests in basketball. Fifty-eight female basketball players (age: 24.3 +/- 2.8 years, height: 185.1 +/- 6.3 cm, weight: 83.4 +/- 10.1 kg) of the Chinese 1st basketball division were recruited. Anaerobic power output was assessed by the Running-Based Anaerobic Sprint Test (RAST) and agility by the T-test and the T-505 test with and without the ball. Pearson's product moment correlation and regression analysis were used to examine the associations and predictive ability. Absolute power output (W) was inversely and strongly correlated with the T-test without the ball (r = -0.67) and with the ball (r = -0.64) and with the T-505 without the ball (r = -0.84) and with the ball (r = -0.73). Relative power output (W/kg/s) was inversely and strongly correlated with the T-test without the ball (r = -0.62) and with the ball (r = -0.50) and with the T-505 without the ball (r = -0.76) and with the ball (r = -0.70). Absolute power output was well-predicted by all agility tests, accounting for a minimum of 40% of the variance shared for the T-test with the ball. Similar observations were shown for the relative power output, where the T-test with the ball yielded the lowest amount of the variance shared (25%), while the T-505 test without the ball seemed to be the strongest factor for predicting the absolute (71%) and relative (57%) power outputs. The findings should serve as an avenue for planning training protocols to enhance agility-related outcomes to effectively increase anaerobic performance.
We examined whether lifting velocity can serve as an objective indicator for predicting clean and jerk one-repetition maximum (1RM). Fourteen competitive adolescent male weightlifters completed two sessions, each involving an incremental loading test at 50%, 70%, 80%, and 90% of 1RM, followed by load increases until reaching actual 1RM. Peak velocity (PV) was recorded for all lifts using a GymAware device. In second session, 1RM was predicted using the individual load-PV relationship derived from three exercise phases (clean, jerk, and entire movement) combined with either the actual or optimal minimal velocity threshold (MVT) from first session. Absolute errors from the test-retest of the actual 1RM (5.0 kg) were not significantly different to those from all velocity-based methods (range = 6.3-10.2 kg; p=.158-0.730), except for the larger errors obtained for the clean phase combined with the actual MVT (10.1 kg p=.008). Random errors for the actual 1RM (15.7 kg) fell within the range of velocity-based methods (13.2-23.1 kg). These results suggest that, although a direct assessment of the actual 1RM remains the most accurate method, measuring PV during warm-up sets may serve as a supplementary tool for guiding the selection of initial attempts in weightlifting competitions.
This study aims to assess the effects of resistance training using flywheel devices—hereafter referred to as flywheel eccentric overload training (FEOT)—compared to conventional resistance training (including external-load resistance training and bodyweight training) on athletic performance, providing theoretical guidance and practical foundations for the scientific development of diverse training regimens. Randomized controlled trials on FEOT interventions (up to January 2024) from five Chinese/English databases were analyzed using Review Manager 5.3 and Stata-SE 15 for meta-analysis, subgroup analysis, and bias assessment. A total of 21 articles were included in this study (14 high-quality, seven moderate-quality based on the methodological assessment). The results of the meta-analysis revealed that, compared to the conventional resistance training, FEOT significantly outperformed in countermovement jump (CMJ; SMD=0.60, 95% CI: 0.26 to 0.95, p<.05), change-of-direction performance (COD; SMD=-1.23, 95% CI: -1.89 to -0.57, p<.05), and short-distance sprint performance (SMD=-0.56, 95% CI: -0.89 to -0.23, p<.05). Subgroup analysis revealed: 1) Compared to the external-load resistance training, FEOT improved CMJ (SMD=0.56, 95% CI: 0.13 to 0.99, p<.05), short-distance sprinting (SMD=-0.61, 95% CI: -0.95 to -0.27, p<.05), and COD (SMD=-1.34, 95% CI: -2.38 to -0.30, p<.05), but not 1RM strength (SMD=0.30, 95% CI: -0.50 to 1.10, p>.05). 2) Versus the bodyweight training, FEOT improved CMJ (SMD=0.77, 95% CI: 0.25 to 1.29, p<.05) and COD (SMD=-1.16, 95% CI: -2.02 to -0.30, p<.05), but not short-distance sprinting (SMD=-0.31, 95% CI: -1.47 to 0.86, p>.05). Our conclusions are: 1) compared with the conventional resistance training, FEOT yields greater improvements in CMJ, COD, and short-sprint performance and 2) FEOT outperforms external-load resistance training across CMJ, COD, and short-sprint outcomes, and shows clear advantages over bodyweight training in CMJ and COD, supporting its value as an effective strategy for enhancing explosive lower-limb performance.
The objective was to systematically compare the effects of speed, agility, and quickness (SAQ) training, high-intensity interval training (HIIT), and small-sided games (SSG) training on sprint and change of direction (COD) performance in soccer players through pairwise and network meta-analyses. A comprehensive search of five electronic databases (PubMed, Web of Science, Embase, Cochrane, and EBSCO) was conducted during June 2025 to identify controlled trials involving SAQ, HIIT, or SSG training interventions. Studies meeting predefined eligibility criteria underwent pairwise meta‑analysis (PMA) to calculate standardized mean differences (SMDs) against control conditions, and network meta‑analysis (NMA) to estimate comparative efficacy across all three modalities. Surface under the cumulative ranking (SUCRA) values were computed to establish an intervention hierarchy. Twenty-three studies involving 914 participants were included. Pairwise meta-analysis (PMA) results showed that, compared with the control groups, only SAQ training significantly improved sprint (SMD = –1.23, 95% CI: –1.85 to –0.60, p<.001) and COD performance (SMD = –1.09, 95% CI: –1.69 to –0.48, p<.001). In network meta-analysis (NMA), SAQ ranked highest for sprint performance (SUCRA = 98.2%), followed by Conventional Training (CT) (57.0%), HIIT (36.7%), and SSG (8.1%). For COD performance, HIIT (SUCRA = 67.3%) ranked highest, followed by SSG (65.9%), SAQ (63.1%) and CT (3.7%). SAQ training demonstrated the most robust enhancement of sprint speed among the examined modalities. Although direct comparisons indicated benefits of SAQ for COD performance, its superiority was not confirmed in the network analysis, likely due to limited head-to-head data and study heterogeneity. A training strategy centered on SAQ, with supplemental HIIT and SSG components, is therefore recommended to optimize both sprint and COD adaptations in soccer players. PROSPERO: CRD42024583586
Taekwondo is an Olympic martial art that emphasizes complex kicking techniques requiring meticulous biomechanical execution. Understanding the mechanical determinants of these kicks is essential for performance enhancement and injury prevention. This systematic review aims at combining the available literature on the kinematic and kinetic features of taekwondo kicks to understand the biomechanics of the technique and training implications. A comprehensive search was done in the PubMed, Scopus, and Web of Science databases following PRISMA 2020 guidelines. The studies included used experimental methods, were published in scientific peer-reviewed journals and focused on the biomechanics of taekwondo kicks from the post-1996 period. A total of 294 articles were identified, and 86 studies met the inclusion criteria. The analysis revealed four main themes: dollyo chagi (n=49), ap chagi (n=9), yeop chagi (n=4), multiple kicks (n=12) and other kicks (n=12). The most consistent determinants of performance were hip joint torque and ground reaction forces (kinetics), and distal segment velocity (kinematics). Dollyo chagi had the highest rotational dynamics, necessitating power and speed, while yeop chagi showed how mass can be efficiently utilized to produce force. Ap chagi used a proximal-to-distal energy transfer mechanism to achieve the most efficient energy transfer. This review confirms the importance of biomechanics in the execution of taekwondo kicking techniques. It determines energy transfer, joint coordination, and muscle activation as crucial factors that describe the performance. Coaches should focus on hip mobility drills and proximal-to-distal sequencing exercises to enhance power output while minimizing joint loading to reduce injury risks.
This study investigates the correlation between lower extremity anthropometric parameters and the quadriceps angle in relation to horizontal jump performance in healthy young adults. Ninety-six healthy young adults (aged 18-30 years), participating in no regular sports activity, were included. Measurements of lower extremity length, thigh length, leg length, foot length, hip circumference, and waist circumference were taken in centimeters using a non-elastic tape measure in an upright position. The quadriceps angle was measured with a goniometer, and horizontal jump performance was assessed via the standing broad jump test. Data were analyzed using SPSS version 29.00. A significant negative correlation was found between the quadriceps angle (both legs) and hip circumference, waist circumference, foot length, and horizontal jump distance. The quadriceps angle of the right leg also negatively correlated with lower extremity, thigh, and leg lengths. Horizontal jump distance positively correlated with lower extremity, thigh, leg, and foot lengths. Longer lower extremity, thigh, leg, and foot lengths enhance horizontal jump performance, while an increased quadriceps angle reduces it. These results highlight the quadriceps angle as a critical factor in horizontal jump performance, warranting further research.
This study examined the relationship between alexithymia, sport injury anxiety, and injury recovery outcomes in athletes. A sample of 57 high-performance athletes (30 female) completed the Toronto Alexithymia Scale, Sport Injury Anxiety Scale, and Return to Sport after Serious Injury Questionnaire. Multiple regression analysis showed that difficulties in identifying feelings (a component of alexithymia), and sport injury anxiety significantly predicted negative recovery outcomes (return concerns), together explaining 27.7% of variance. However, neither alexithymia nor injury anxiety predicted positive recovery outcomes (renewed perspective), and both were unrelated to injury risk. The prevalence of alexithymia in this sample was approximately 20%, which is notably higher than general population estimates (~10%). This study provides preliminary evidence that emotion-related traits like alexithymia and contextual anxiety measures may play important roles in sport injury recovery processes, highlighting potential targets for psychological intervention during rehabilitation.
Humor, often viewed as a light-hearted communicative tool, also carries important relational significance in elite sport. Affiliative humor has the potential to build trust and cohesion, whereas aggressive humor may threaten relational safety and undermine athlete engagement. While humor has been widely studied in organizational psychology, its implications in sport coaching remain underexplored. This study examined how athletes’ perceptions of coaches’ humor styles influence motivational commitment through the mediating mechanisms of relationship quality—closeness, commitment, and complementarity—guided by Humor Styles Theory, the 3+1 Cs Model, and the Sport Commitment Model. Participants were 341 athletes (aged 18–35) from five team sports in Türkiye. Measures assessed perceptions of coaches’ affiliative and aggressive humor, coach–athlete relationship quality, and two forms of sport commitment: enthusiastic and constraint commitment. Regression-based mediation analyses tested indirect effects of humor styles on commitment through relational dimensions. Results indicated that affiliative humor was positively associated with enthusiastic commitment, fully mediated by athletes’ perceptions of commitment and complementarity, but not by closeness. In contrast, aggressive humor predicted lower levels of enthusiastic commitment, both directly and indirectly through weakened perceptions of commitment and complementarity. Neither humor style showed significant associations with constraint commitment. These findings suggest that affiliative humor may strengthens athletes’ motivation by reinforcing task-relevant relational dynamics, whereas aggressive humor can undermines them. In performance-driven contexts, functional alignment may be more influential than emotional closeness. Coach education programs should therefore encourage the intentional use of affiliative humor as a relational strategy to sustain athlete engagement and long-term commitment.
Small-sided games (SSGs) have gained prominence in rugby union training due to their potential to simultaneously develop players’ physical, technical, and tactical capacities. However, a comprehensive understanding of how SSGs are structured and applied remains limited. This narrative review aimed to identify and analyze studies that implemented SSGs in rugby union training, focusing on game formats, participant characteristics, and training outcomes. A literature search was conducted in PubMed, Scopus, Web of Science, SPORTDiscus, and SciELO databases up to March 2025. Sixteen studies published between 2012 and 2024 met the inclusion criteria. Data extraction was performed independently by two reviewers using a structured coding framework, and findings were synthesized narratively due to the heterogeneity of studies’ designs and outcomes. Results revealed considerable variation in SSG designs regarding the number of players (1v1 to 12v12), pitch dimensions (15×12 m to 100×70 m), and contact rules (touch, tackle, or non-contact). SSGs with fewer players and larger fields were associated with greater physical and perceptual demands. Technical and tactical benefits were also observed, particularly when SSGs were pedagogically adapted to the athletes’ experience and developmental level. Nonetheless, most studies involved adult male or elite players, highlighting a gap in research with female and youth categories. Furthermore, few studies examined how contact rules influenced training outcomes. Future investigations should include more diverse populations and explore how constraint manipulations affect game representativeness and skill acquisition in rugby union.
The aims of this study were to compare physical performance and injury profiles across different age categories and playing positions of soccer players, and to establish relationships between physical performance tests and positions. Soccer players of different age categories, senior (n=34), under-19 years (U19; n=53) and under-16 years (U16; n=54), performed countermovement jump (CMJ), change of direction (COD, 10+10-m with 90° turn), and linear sprint over 30-m tests. Change-of-direction loss was calculated. Injuries (i.e., incidence and burden) during the first phase of the season were recorded. Senior players showed the best performance in COD (effect size [ES] = 1.23-1.42), the U19 players were the best in sprint over 30-m (ES = 0.64-1.44) and the worst in COD loss (ES = 1.18-1.68). The U16 players showed the lowest values in countermovement jump (ES = 0.90-1.00) and linear sprint tests (ES = 0.64-1.46). No differences in physical performance were reported for the playing positions analysis. Senior players showed the highest total injury incidence and the greatest burden values, while wide midfield players presented the highest burden values. These results indicate that individualized training programs must be applied based on age and playing positions.
