Internal and External Load Control in Team Sports through a Multivariable Model.

Data related to 141 sessions of 10 semi-professional basketball players were analyzed during the competitive period of the 2018-2019 season using a multivariable model to determine possible associations between internal and external load variables and fatigue. Age, height, weight, sessional rate of perceived exertion (sRPE), summated-heart-rate-zones, heart rate variability, total accelerations and decelerations were the covariates, and post-session countermovement jump loss (10% or higher) the response variable. Based on the results observed, a rise in sRPE and accelerations and decelerations could be associated with increased lower-body neuromuscular fatigue. Observing neuromuscular fatigue was 1,008 times higher with each additional sRPE arbitrary unit (AU). Each additional high-intensity effort also increased the probability of significant levels of neuromuscular fatigue by 1,005 times. Fatigue arising from demanding sporting activities is acknowledged as a relevant inciting event leading to injuries. Thus, the methodology used in this study can be used then to monitor neuromuscular fatigue onset, also enhancing proper individual adaptations to training.

Low External Workloads Are Related to Higher Injury Risk in Professional Male Basketball Games.

The primary purpose of this study was to identify potential risk factors for sports injuries in professional basketball. An observational retrospective cohort study involving a male professional basketball team, using game tracking data was conducted during three consecutive seasons. Thirty-three professional basketball players took part in this study. A total of 29 time-loss injuries were recorded during regular season games, accounting for 244 total missed games with a mean of 16.26 ± 15.21 per player and season. The tracking data included the following variables: minutes played, physiological load, physiological intensity, mechanical load, mechanical intensity, distance covered, walking maximal speed, maximal speed, sprinting maximal speed, maximal speed, average offensive speed, average defensive speed, level one acceleration, level two acceleration, level three acceleration, level four acceleration, level one deceleration, level two deceleration, level three deceleration, level four deceleration, player efficiency rating and usage percentage. The influence of demographic characteristics, tracking data and performance factors on the risk of injury was investigated using multivariate analysis with their incidence rate ratios (IRRs). Athletes with less or equal than 3 decelerations per game (IRR, 4.36; 95% CI, 1.78-10.6) and those running less or equal than 1.3 miles per game (lower workload) (IRR, 6.42 ; 95% CI, 2.52-16.3) had a higher risk of injury during games (p < 0.01 in both cases). Therefore, unloaded players have a higher risk of injury. Adequate management of training loads might be a relevant factor to reduce the likelihood of injury according to individual profiles.

The Relationship of Practice Exposure and Injury Rate on Game Performance and Season Success in Professional Male Basketball.

The objectives of this study were to determine the relationship among game performance, injury rate, and practice exposure in a professional male basketball team. A retroospective analysis of prospective collected data was conducted over seven consecutive seasons (2007/2008 to 2013/2014). Data collection included sports performance during competition (statistical evaluation), injury rate, and total exposure (games and practices). Over the surveillance period, 162 injuries (91 practice; 71 matches) occurred over 32,668 hours of exposure (556 games and 2005 practices). There was a strong positive correlation between: 1) exposure (total number of practices and hours of exposure) and the total number of injuries (r = 0.77; p = 0.04); 2) exposure (total hours of exposure and total hours of practice exposure) and performance (total team ranking) (r = 0.77 and p = 0.04, and r = 0.8 and p = 0.03, respectively); and 3) total number of injuries and performance (total team ranking) (r = 0.84; p = 0.02). While increasing practice and competition time is related to greater team performance, it also increases the number of injuries. However, higher injury rates were not associated with worse overall team performance. Efforts to reduce high-risk activity during practice, optimally replaced with injury prevention training, might help to reduce injury risk.

Training Model for Extended Career Athletes: A Narrative Review.

CONTEXT: Today's elite and professional sports tend to feature older, more seasoned athletes, who have longer sporting careers. As advancing age can potentially limit peak performance, balancing training load is necessary to maintain an optimal state of performance and extend their sports career. OBJECTIVE: To describe an appropriate training model for extended career athletes. DATA SOURCES: Medline (PubMed), SPORTDiscus, ScienceDirect, Web of Science, and Google Scholar. STUDY SELECTION: A search of the literature between January 1, 2015 and November 22, 2023 was performed in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. STUDY DESIGN: Narrative review. LEVEL OF EVIDENCE: Level 4. DATA EXTRACTION: Data were extracted from studies related to the management of training and performance of athletes with extended and long careers. RESULTS: A total of 21 articles related to extended careers were found. Key themes from these papers included: expertise, biological maturation, and specificity; epidemiology and health; athlete monitoring; strength training; load management and detraining; success management. CONCLUSION: A training model for extended career athletes should balance the deleterious effects of age with the athletes' knowledge of, and expertise within, the sport. Designing specific training that accommodates previous injuries, training load intolerances, and caters for quality of life after retirement should be key considerations. Load management strategies for athletes with extended careers should include strength training adaptations to minimize pain, load-response monitoring, a broad range of movement, recovery and intensity activities, and the avoidance of large training load peaks and periods of inactivity.

Effects of adding dual-task or sport-specific task constrains to jump-landing tests on biomechanical parameters related to injury risk factors in team sports: a systematic review.

Background: Jumping and landing tests are frequently used as a tool to assess muscle function. However, they are performed in a controlled and predictable environment. The physical tests commonly used as part of the criteria for return to sport after injury are often performed with little or no cognitive load and low coordinative demand compared to game-specific actions. The aim of this systematic review was to examine the influence of performing a dual task (DT) or sport-specific task constrains during jump-landing tests on biomechanical variables related to lower limb injury risk in team sports. Methods: This systematic review followed the specific methodological guidelines of the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA). The search was conducted in the databases Medline (PubMed), Web of Science, Cochrane Plus, and SportDiscus for studies published from 2013 until June 30, 2023. To be eligible, studies had to include: (1) kinematic and/or kinetic assessment of injury risk factors in the lower extremity; (2) a comparison between a simple jump or landing test and a DT jump or landing test which included cognitive information. The risk of bias in the selected articles was analyzed using the recommendations of the Cochrane Collaboration. Results: Of the 656 records identified, 13 met the established criteria. Additionally, two more articles were manually included after screening references from the included articles and previous related systematic reviews. Regarding the Risk of bias assessment, 12 studies did not surpass a score of 3 points (out of a total of 7). Only three studies exceeded a score of 3 points, with one article achieving a total score of 6. From the included studies, comparative conditions included actions influenced by the inclusion of a sports ball (n = 6), performing tasks in virtual environments or with virtual feedback (n = 2), participation in cognitive tasks (n = 6), and tasks involving dual processes (n = 7). The execution of decision-making (DM) during the jump-landing action resulted in biomechanical changes such as lower peak angles of hip flexion and knee flexion, along with increased vertical ground reaction force, knee abduction, and tibial internal rotation. Regarding limitations, discrepancies arise in defining what constitutes DT. As a result, it is possible that not all studies included in this review fit all conceptual definitions of DT. The inclusion of DT or constraints in jump-landing tests significantly alters biomechanical variables related to lower extremity injury risk in team sports. In future research, it would be beneficial to incorporate tasks into jumping tests that simulate the specific cognitive demands of team sports. This systematic review was registered in PROSPERO (registration number: CRD42023462102) and this research received no external funding.

Analysis of professional soccer players in competitive match play based on submaximum intensity periods.

The main objective of this study is to analyse sub-maximum intensity periods (SubMIP's) manifested by professional soccer players during official matches (number of events and time spent in each event), according to the player position, match halve and match, and also to group the players according to their SubMip values during the competition. Methods: We collected a total of 247 individual records of 14 players using Global Positioning System (GPS) during 15 official league matches (Azerbaijan Premier League 2019-2020). We calculated both the number of SubMIPs events and the time each player spent in the SubMIPs zone (threshold of 85% MIP). We analysed the possible independence of the variables with the Kruskal-Wallis test and the possible specific relationships between the groups using a post-hoc analysis with Dunn's test. In order to explore the possible distribution of physical demands in homogeneous groups, a cluster analysis was performed. Results: The statistical analysis showed significant differences between the individual variables in the number of events and in the time spent by the player above the threshold in distance covered at speed >19.8 km/h (HSR), distance covered at speed >25.2 km/h (Sprint), acceleration density (AccDens), mean metabolic power (MetPow), metres per minute (Mmin) and high metabolic load distance >25.5 W/kg (HMLD). Differences were also found according to the playing position in MetPow, Mmin and between halves in AccDens, MetPow, Mmin. In the clustering based on the time spent by the player in SubMIPs, three main groups were described: (1) the centroid was located in lower values in each of the variables; (2) there were an accentuation of the AccDens variable; (3) all the variables, except AccDens, were accentuated. Conclusions: The main differences with regard to SubMIPs were related to the player's individual physical performance and not to position. However, the player's position could act as an attractor and show significant differences during matches.

Evaluation of cognitive load in team sports: literature review.

In team sports, load management has become one of the most common areas of investigation, given that effective control over load is the key to being able to optimize performance and avoid injuries. Despite the constant evolution and innovation in the latest theories, we can see a clear tendency in load management that focuses on physiological and mechanical aspects and neglects its cognitive character, which generates the variability inherent in the performance of athletes in a changing environment. Indicators of response that inform methods of control over cognitive load can include cognitive, physiological and behavioral indicators. However, limited investigations exist to support the reliability of each indicator regarding cognitive load. For this reason, the objective of this literature review is to present strategies used to manage cognitive load in team sports, as well as the indicators utilized for such a proposition and their relationships in specific contexts.

Influence of Strength Programs on the Injury Rate and Team Performance of a Professional Basketball Team: A Six-Season Follow-Up Study.

This study aims to determine possible associations between strength parameters, injury rates, and performance outcomes over six seasons in professional basketball settings. Thirty-six male professional basketball players [mean ± standard deviation (SD): age, 30.5 ± 4.7 years; height, 199.5 ± 9.5 cm; body mass, 97.9 ± 12.9 kg; BMI 24.6 ± 2.5 kg/m2] participated in this retrospective observational study, conducted from the 2008-09 to the 2013-14 season. According to their epidemiological records, each player followed an individual plan designed within different strength training programs: Functional (n = 16), Eccentric (n = 8), or Resistance (n = 12). Seven hundred and fourteen valid records were obtained from 170 individual strength tests during 31 sessions. Tests performed were leg press, squat, and jerk. Parameters recorded were force, power, velocity, peak velocity, and time to peak velocity for strength; time loss injury and muscle injury for injury rate; and games won, games lost, and championships for performance outcomes. All the strength variables and injuries are independent of the strength programs (p < 0.01). The correlation analysis showed very significant relationships between muscular injuries and time to peak velocity (r = 0.94; p < 0.01), significant relationships between force and games lost (r = 0.85; p < 0.05), and muscular injuries with games lost (r = -0.81; p < 0.05) per season. Mean values per season described a possible association of force, time to peak velocity, and muscular injuries with performance outcomes (R 2 = 0.96; p < 0.05). In this specific context, strength variables and injury rate data show no association with a single type of strength training program in this cohort of high-performance basketball players.

Evidence-based post-exercise recovery strategies in rugby: a narrative review.

In the sport of rugby, athletes need a multitude of sport-specific skills along with endurance, power, and speed to optimize performance. Further, it is not unusual for athletes to play several competitive matches with insufficient recovery time. Rugby requires repeated bouts of high-intensity actions intermixed with brief periods of low-to-moderate active recovery or passive rest. Specifically, a match is characterized by repeated explosive activities, such as jumps, shuffles, and rapid changes of direction. To facilitate adequate recovery, it is necessary to understand the type of fatigue induced and, if possible, its underlying mechanisms. Common approaches to recovery may include nutritional strategies as well as active (active recovery) and passive recovery (water immersions, stretching, and massage) methods. However, limited research exists to support the effectiveness of each strategy as it related to recovery from the sport of rugby. Therefore, the main aim of the current brief review is to present the relevant literature that pertains to recovery strategies in rugby.

Ankle Sprain Versus Muscle Strain Injury in Professional Men's Basketball: A 9-Year Prospective Follow-up Study.

BACKGROUND: Ankle sprain is the most common injury in basketball players. However, in our routine clinical evaluation, we observe a high frequency of muscle injury. Currently, no reliable information is available regarding the magnitude of these types of injury. PURPOSE: To describe the type and rate of muscle injuries in male basketball players and discuss clinical management and prevention strategies. STUDY DESIGN: Descriptive epidemiology study. METHODS: A total of 59 professional male basketball players were evaluated over 9 seasons (2007-2015). All injuries during the study period were registered through use of a validated electronic medical record system. RESULTS: We analyzed 463 injuries, of which 207 resulted in time loss and 256 required medical attention, for a total exposure time of 42,678 hours for the 59 players involved in the study. Muscle strains and ankle sprains accounted for 21.2% (n = 98) and 11.9% (n = 55) of all injuries, respectively. The global incidence rate was 10.8 injuries per 1000 player-hours (95% CI, 9.9-11.9). The global injury burden was 53.9 days lost due to injuries per 1000 hours for a total exposure time. The incidence rate of muscle strains (2.3; 95% CI, 1.9-2.8) was higher than that of ankle sprains (1.3; 95% CI, 1-1.7). The incidence rate for muscle injuries for the entire study period was 1.8 times higher (95% CI, 1.28-2.49) than that for ankle sprains. CONCLUSION: In this study, muscle injuries were more commonly observed compared with ankle sprains. Prevention strategies for muscle injuries may be worth discussing.

Effects of a trail mountain race on neuromuscular performance and hydration status in trained runners.

BACKGROUND: The aims of this study were to examine the effects of a trail mountain race (TMR) on hydration status and neuromuscular performance of recreational trail runners, and to determine the relationship among these parameters, subject's characteristics and competitive performance. METHODS: Thirty-five male recreational trail runners (age 38.1±9.5 years; height 177.3±5.8 cm; body mass 73.8±8.4 kg) were assessed before and after a 21.1-km TMR. Hydration status (urine color [Ucol] and body mass [BM]) and neuromuscular performance (countermovement jump [CMJ] and rebound jumps [RJ]) were assessed. RESULTS: Significant changes following the TMR included RJ mean contact time (RJMCT) (12%, ES=-0.35, P<0.05) and dehydration status increases (BM reductions -2.7%, ES=0.24, P<0.001; Ucol: 147% increase, ES=-1.8, P<0.001). Low to moderate positive correlations were found between pre- and post-TMR BM (r=0.5-0.54; P<0.01), post-race Ucol (r=0.37; P<0.05), age (r=0.57; P<0.01) and TMR performance. Participants' age combined with Ucol and the RJMJH post-TMR, explained 65% of the variance in the final running time (r=0.81; P=0.000). CONCLUSIONS: Participation in a 21.1-km TMR in recreational runners results in small reductions of the neuromuscular function and increases in dehydration levels. The hydration status (Ucol) and the RJMJH post-TMR combined with the runners' chronological age seemed to be good predictors of the final running performance.