Discovery and Characterisation of Forward Line Formations at Centre Bounces in the Australian Football League.

The extent of player formation usage and the characteristics of player arrangements are not well understood in Australian football, unlike other team-based invasion sports. Using player location data from all centre bounces in the 2021 Australian Football League season; this study described the spatial characteristics and roles of players in the forward line. Summary metrics indicated that teams differed in how spread out their forward players were (deviation away from the goal-to-goal axis and convex hull area) but were similar with regard to the centroid of player locations. Cluster analysis, along with visual inspection of player densities, clearly showed the presence of different repeated structures or formations used by teams. Teams also differed in their choice of player role combinations in forward lines at centre bounces. New terminology was proposed to describe the characteristics of forward line formations used in professional Australian Football.

Association Between Position-Specific Impact and Movement Characteristics of Professional Rugby Union Players During Game Play.

ABSTRACT: Peek, RJ, Carey, DL, Middleton, KJ, Gastin, PB, and Clarke, AC. Association between position-specific impact and movement characteristics of professional rugby union players during game play. J Strength Cond Res 37(1): 161-166, 2023-The aim of this study was to understand the association between impact and movement characteristics during whole game and peak 1- to 10-minute rolling windows in professional rugby union. Maximal impact (impacts·min-1) and corresponding running (m·min-1) characteristics as well as maximal running (m·min-1) and corresponding impact (impacts·min-1) characteristics were obtained for 160 athletes from 4 teams across the 2018 and 2019 Super Rugby seasons. A linear mixed-effects model reported a positive association between whole-game running and impacts, where greater impact characteristics corresponded with greater running characteristics. The average 1-minute peak running characteristics (150-160 m·min-1) typically occurred when no impacts occurred. The average 1-minute peak impact characteristics (4-6 impacts·min-1) corresponded with an average relative distance of 90-100 m·min-1. Worst case scenario observed impact characteristics as large as 15 impacts·min-1 with a corresponding relative distance of 140 m·min-1. When training for peak period characteristics, running may be completed in isolation; however, peak impacts often occur in conjunction with moderate to high running movements. Given running and impact characteristics can appear concurrently within game play, this highlights the need to train them accordingly. As such, when prescribing training drills to replicate the peak characteristics in rugby union, consideration should be taken for both running and impact characteristics.

Elite Junior Australian Football Players With Impaired Wellness Are at Increased Injury Risk at High Loads.

BACKGROUND: Elite junior Australian football players experience high training loads across levels of competition and training. This, in conjunction with impaired wellness, can predispose athletes to injury. HYPOTHESIS: Elite junior Australian football players exposed to high loads with poor wellness are more likely to be at risk of injury than those with improved wellness. STUDY DESIGN: Longitudinal prospective cohort study. LEVEL OF EVIDENCE: Level 3. METHODS: Data were collected and analyzed from 280 players across the 2014 season. Internal load was measured via session rating of perceived exertion. Player wellness was reported according to ratings of sleep quality, fatigue, soreness, stress, and mood. Week- and month-based training load measures were calculated, representing a combination of absolute and relative load variables. Principal component analysis factor loadings, based on 17 load and wellness variables, were used to calculate summed variable covariates. Injury was defined as "any injury leading to a missed training session or competitive match." Associations between covariates and injury risk (yes/no) were determined via logistic generalized estimating equations. RESULTS: A significant interaction term between load and wellness on injury was found [odds ratio (OR) 0.76; 95% CI 0.62-0.92; P < 0.01), indicating that wellness acts as a "dimmer switch" of load on injury. Further, there was evidence of moderated mediation (OR 0.71; 95% CI 0.57-0.87; P < 0.01). When wellness was low, injury risk started to increase substantially at a 1-week load of 3250 au. CONCLUSIONS: Subjective measures of training load are associated with injury risk through a nonlinear relationship. This relationship is further influenced by player wellness, which can amplify the risk of injury. There is evidence that higher stress is linked with injury and that soreness and sleep mediate any stress-injury relationship. CLINICAL RELEVANCE: Coaching efforts to manage training load and player adaptive responses, including wellness, may reduce the risk of injury, with stress, soreness, and sleep particularly relevant at this level.

Characterising Psycho-Physiological Responses and Relationships during a Military Field Training Exercise.

Over a 15-day period, that included an eight-day field trial, the aims of this study were to (1) quantify the physical workload, sleep and subjective well-being of soldiers in training; (2a) Explore relationships between workload and well-being, and (2b) sleep and well-being; (3) Explore relationships between workload, sleep, and well-being. METHODS: Sixty-two Combat Engineer trainees (59 male, 3 female; age: 25.2 ± 7.2 years) wore an ActiGraph GT9X to monitor daily energy expenditure, physical activity, and sleep. Rating of perceived exertion (RPE), sleep quality, and fatigue were measured daily, subjective well-being was reported days 1, 5, 9, 13 and 15. Multi-level models were used for the analysis. RESULTS: Well-being was affected by a combination of variables including workload, subjective sleep quality, sleep duration, and sleep efficiency. RPE and subjective sleep quality were consistently significant parameters within the models of best fit. CONCLUSIONS: Perceptions of well-being were lower during the field training when physical workload increased, and sleep decreased. Energy expenditure was comparatively low, while daily sleep duration was consistent with field training literature. Subjective assessments of workload and sleep quality were consistently effective in explaining variations in well-being and represent an efficient approach to monitor training status of personnel.

A Strategy to Inform Athlete Sleep Support From Questionnaire Data and Its Application in an Elite Athlete Cohort.

PURPOSE: Information from the Pittsburgh Sleep Quality Index (PSQI) and Athlete Sleep Behavior Questionnaire (ASBQ) provide the ability to identify the sleep disturbances experienced by athletes and their associated athlete-specific challenges that cause these disturbances. However, determining the appropriate support strategy to optimize the sleep habits and characteristics of large groups of athletes can be time-consuming and resource-intensive. The purpose of this study was to characterize the sleep profiles of elite athletes to optimize sleep-support strategies and present a novel R package, AthSlpBehaviouR, to aid practitioners with athlete sleep monitoring and support efforts. METHODS: PSQI and ASBQ data were collected from a cohort of 412 elite athletes across 27 sports through an electronic survey. A k-means cluster analysis was employed to characterize the unique sleep-characteristic typologies based on PSQI and ASBQ component scores. RESULTS: Three unique clusters were identified and qualitatively labeled based on the z scores of the PSQI components and ASBQ components: cluster 1, "high-priority; poor overall sleep characteristics + behavioral-focused support"; cluster 2, "medium-priority, sleep disturbances + routine/environment-focused support"; and cluster 3, "low-priority; acceptable sleep characteristics + general support." CONCLUSIONS: The findings of this study highlight the practical utility of an unsupervised learning approach to perform clustering on questionnaire data to inform athlete sleep-support recommendations. Practitioners can consider using the AthSlpBehaviouR package to adopt a similar approach in athlete sleep screening and support provision.

COVID-19 Lockdown: A Global Study Investigating the Effect of Athletes' Sport Classification and Sex on Training Practices.

PURPOSE: To investigate differences in athletes' knowledge, beliefs, and training practices during COVID-19 lockdowns with reference to sport classification and sex. This work extends an initial descriptive evaluation focusing on athlete classification. METHODS: Athletes (12,526; 66% male; 142 countries) completed an online survey (May-July 2020) assessing knowledge, beliefs, and practices toward training. Sports were classified as team sports (45%), endurance (20%), power/technical (10%), combat (9%), aquatic (6%), recreational (4%), racquet (3%), precision (2%), parasports (1%), and others (1%). Further analysis by sex was performed. RESULTS: During lockdown, athletes practiced body-weight-based exercises routinely (67% females and 64% males), ranging from 50% (precision) to 78% (parasports). More sport-specific technical skills were performed in combat, parasports, and precision (∼50%) than other sports (∼35%). Most athletes (range: 50% [parasports] to 75% [endurance]) performed cardiorespiratory training (trivial sex differences). Compared to prelockdown, perceived training intensity was reduced by 29% to 41%, depending on sport (largest decline: ∼38% in team sports, unaffected by sex). Some athletes (range: 7%-49%) maintained their training intensity for strength, endurance, speed, plyometric, change-of-direction, and technical training. Athletes who previously trained ≥5 sessions per week reduced their volume (range: 18%-28%) during lockdown. The proportion of athletes (81%) training ≥60 min/session reduced by 31% to 43% during lockdown. Males and females had comparable moderate levels of training knowledge (56% vs 58%) and beliefs/attitudes (54% vs 56%). CONCLUSIONS: Changes in athletes' training practices were sport-specific, with few or no sex differences. Team-based sports were generally more susceptible to changes than individual sports. Policy makers should provide athletes with specific training arrangements and educational resources to facilitate remote and/or home-based training during lockdown-type events.

The temporal distribution and occurrence of impacts and movement relative to peak periods in men's rugby union.

OBJECTIVES: This study identifies the distribution (as a percentage of the positional peak) and occurrence (within a half) of 1-min movement characteristics (m·min-1) and contact-based events (impact·min-1) during professional rugby union game play. DESIGN: Within 95 rugby union games, players wore global positioning system (GPS) devices (n = 1422 player-game files, 160 athletes). One-minute rolling-window averages were calculated with the maximum and mean value being recorded for each dependent variable; relative distance (m·min-1) and impacts (impact·min-1), then standardised by the positional peak mean. METHODS: The distribution of these variables accumulated in 10% increments of the peak were determined as was their occurrence throughout a playing half for each positional group. RESULTS: The greatest distribution of game play (%) was observed at ~30-39% of the positional peak for movement and with no impacts. The greatest occurrence of maximum positional peak 1-min movement periods occurred at the beginning of each half and declined as the half went on. Peak impact characteristics, however, were found to be more sporadic across a half. CONCLUSIONS: These findings suggest that the distribution of positional peak 1-min movement (80-100%+) and peak impacts (4+) were <5% of overall game play, and observed <2% of total occurrences. This highlights that practitioners should alter training drills by time, volume, and intensity in order to replicate the peak intensities of game play.

Factors Predicting Training Delays and Attrition of Recruits during Basic Military Training.

Ensuring a balance between training demands and recovery during basic military training (BMT) is necessary for avoiding maladaptive training responses (e.g., illness or injury). These can lead to delays in training completion and to training attrition. Previously identified predictors of injury and attrition during BMT include demographic and performance data, which are typically collected at a single time point. The aim of this study was to determine individual risk factors for injury and training delays from a suite of measures collected across BMT. A total of 46 male and female recruits undertaking the 12-week Australian Army BMT course consented to this study. Injury, illness, attrition, and demographic data were collected across BMT. Objective measures included salivary cortisol and testosterone, step counts, cardiorespiratory fitness, and muscular endurance. Perceptions of well-being, recovery, workload, fatigue, and sleep were assessed with questionnaires. Baseline and mean scores across BMT were evaluated as predictors of injury and attrition using generalized linear regressions, while repeated-measures ANOVA was used for the group comparisons. From the 46 recruits, 36 recruits completed BMT on time; 10 were delayed in completion or discharged. Multiple risk factors for injury during BMT included higher subjective ratings of training load, fatigue, and stress, lower sleep quality, and higher cortisol concentrations. Higher ratings of depression, anxiety, and stress, and more injuries were associated with a higher risk of delayed completion. Higher concentrations of testosterone and higher levels of fitness upon entry to BMT were associated with reduced risk of injury and delayed completion of BMT. Ongoing monitoring with a suite of easily administered measures may have utility in forewarning risk of training maladaptation in recruits and may complement strategies to address previously identified demographic and performance-based risk factors to mitigate injury, training delays, and attrition.

Quantification of Recruit Training Demands and Subjective Wellbeing during Basic Military Training.

Purpose: Assess and describe the physical demands and changes in subjective wellbeing of recruits completing the 12 week Australian Army Basic Military Training (BMT) course. Methods: Thirty-five recruits (24.8 ± 6.8 y; 177.4 ± 10.1 cm, 75.6 ± 14.7 kg) consented to daily activity monitoring and weekly measures of subjective wellbeing (Multi-component Training Distress Scale, MTDS). The physical demands of training were assessed via wrist worn activity monitors (Actigraph GT9X accelerometer). Physical fitness changes were assessed by push-ups, sit-ups and multi-stage shuttle run in weeks 2 and 8. Results: All objective and subjective measures significantly changed (p < 0.05) across the 12 week BMT course. In parallel, there was a significant improvement in measures of physical fitness from weeks 2 to 8 (p < 0.001). The greatest disturbance to subjective wellbeing occurred during week 10, which was a period of field training. Weeks 6 and 12 provided opportunities for recovery as reflected by improved wellbeing. Conclusions: The physical demands of training varied across the Australian Army 12 week BMT course and reflected the intended periodization of workload and recovery. Physical fitness improved from week 2 to 8, indicating a positive training response to BMT. Consistent with findings in sport, wellbeing measures were sensitive to fluctuations in training stress and appear to have utility for individual management of personnel in the military training environment.

Techniques to derive and clean acceleration and deceleration data of athlete tracking technologies in team sports: A scoping review.

The application of acceleration and deceleration data as a measure of an athlete's physical performance is common practice in team sports. Acceleration and deceleration are monitored with athlete tracking technologies during training and games to quantify training load, prevent injury and enhance performance. However, inconsistencies exist throughout the literature in the reported methodological procedures used to quantify acceleration and deceleration. The object of this review was to systematically map and provide a summary of the methodological procedures being used on acceleration and deceleration data obtained from athlete tracking technologies in team sports and describe the applications of the data. Systematic searches of multiple databases were undertaken. To be included, studies must have investigated full body acceleration and/or deceleration data of athlete tracking technologies. The search identified 276 eligible studies. Most studies (60%) did not provide information on how the data was derived and what sequence of steps were taken to clean the data. Acceleration and deceleration data were commonly applied to quantify and describe movement demands using effort metrics. This scoping review identified research gaps in the methodological procedures and deriving and cleaning techniques that warrant future research focussing on their effect on acceleration and deceleration data.

Sleep of recruits throughout basic military training and its relationships with stress, recovery, and fatigue.

OBJECTIVE: Studies in basic military training (BMT) examining sleep are largely cross-sectional, and do not investigate relationships between sleep, stress, recovery and fatigue. The aims of this study were to (1a) quantify changes in recruits' sleep quantity and quality over 12 weeks of BMT; (1b) quantify changes in recruits' perceptions of stress, fatigue and recovery over BMT; and (2) explore relationships between sleep, and perceptions of stress, fatigue and recovery. METHODS: 45 recruits (37 male; 8 female, age: 25.2 ± 7.2 years, height: 176.2 ± 10.0 cm, mass: 76.8 ± 15.0 kg) wore ActiGraph GT9X's for 12 weeks of BMT, collecting sleep duration, efficiency and awakenings. Subjective sleep quality, fatigue were measured daily, with stress and recovery measured weekly. Multi-level models assessed relationships between sleep, and stress, recovery, and fatigue. RESULTS: Objective daily means for sleep duration were 6.3 h (± 1.2 h) and 85.6% (± 5.5%) for sleep efficiency. Main effects were detected for all mean weekly values (p < 0.05). Sleep quality showed the strongest relationships with stress, recovery and fatigue. The best model to explain relationships between, stress, recovery and fatigue, included sleep quality, sleep duration, sleep efficiency and awakenings. CONCLUSIONS: The reported mean sleep duration of 6.3 h per night may negatively impact training outcomes across BMT. Combining both subjective and objective measures of sleep best explained relationships between sleep metrics stress, fatigue and recovery. Perceived sleep quality was most strongly related to change in stress, recovery, or post-sleep fatigue.

Peak movement and impact characteristics of different training methods in professional rugby union.

The purpose of this study was to compare the peak periods (1- to 6-minute epochs) for three different training methods (game-based training - GBT; small-sided games - SSG; and conditioning training - CT) in elite male rugby union (RU) players. The peak movement (m·min-1) and impact (impact·min-1) characteristics of 42 players during in-season training were assessed. When comparing between training methods, SSG drills produced the greatest peak movement characteristics for all time epochs (1-minute average peak periods - SSG 195 m·min-1, GBT 160 m·min-1, and CT 144 m·min-1). The peak impact characteristics performed during training were 1-2 impact·min-1 for a 1-minute period and then decreased as the time period increased for all training methods. The greatest distribution of training time occurred at 30-39% (SSG and CT) and 40-49% (GBT) of peak movement intensity, with less than 5% of training performed at or above 80% peak intensity across all drill types. Findings from the current study show that the peak movement periods (m·min-1) in RU training from all three training methods match or exceed those which are previously reported in peak gameplay, yet their ability to replicate peak impact characteristics is questionable.

Predicting Youth Athlete Sleep Quality and the Development of a Translational Tool to Inform Practitioner Decision Making.

BACKGROUND: Identifying key variables that predict sleep quality in youth athletes allows practitioners to monitor the most parsimonious set of variables that can improve athlete buy-in and compliance for athlete self-report measurement. Translating these findings into a decision-making tool could facilitate practitioner willingness to monitor sleep in athletes. HYPOTHESIS: Key predictor variables, identified by feature reduction techniques, will lead to higher predictive accuracy in determining youth athletes with poor sleep quality. STUDY DESIGN: Cross-sectional study. LEVEL OF EVIDENCE: Level 3. METHODS: A group (N = 115) of elite youth athletes completed questionnaires consisting of the Pittsburgh Sleep Quality Index and questions on sport participation, training, sleep environment, and sleep hygiene habits. A least absolute shrinkage and selection operator regression model was used for feature reduction and to select factors to train a feature-reduced sleep quality classification model. These were compared with a classification model utilizing the full feature set. RESULTS: Sport type, training before 8 am, training hours per week, presleep computer usage, presleep texting or calling, prebedtime reading, and during-sleep time checks on digital devices were identified as variables of greatest influence on sleep quality and used for the reduced feature set modeling. The reduced feature set model performed better (area under the curve, 0.80; sensitivity, 0.57; specificity, 0.80) than the full feature set models in classifying youth athlete sleep quality. CONCLUSION: The findings of our study highlight that sleep quality of elite youth athletes is best predicted by specific sport participation, training, and sleep hygiene habits. CLINICAL RELEVANCE: Education and interventions around the training and sleep hygiene factors that were identified to most influence the sleep quality of youth athletes could be prioritized to optimize their sleep characteristics. The developed sleep quality nomogram may be useful as a decision-making tool to improve sleep monitoring practice among practitioners.

Training During the COVID-19 Lockdown: Knowledge, Beliefs, and Practices of 12,526 Athletes from 142 Countries and Six Continents.

OBJECTIVE: Our objective was to explore the training-related knowledge, beliefs, and practices of athletes and the influence of lockdowns in response to the coronavirus disease 2019 (COVID-19) pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). METHODS: Athletes (n = 12,526, comprising 13% world class, 21% international, 36% national, 24% state, and 6% recreational) completed an online survey that was available from 17 May to 5 July 2020 and explored their training behaviors (training knowledge, beliefs/attitudes, and practices), including specific questions on their training intensity, frequency, and session duration before and during lockdown (March-June 2020). RESULTS: Overall, 85% of athletes wanted to "maintain training," and 79% disagreed with the statement that it is "okay to not train during lockdown," with a greater prevalence for both in higher-level athletes. In total, 60% of athletes considered "coaching by correspondence (remote coaching)" to be sufficient (highest amongst world-class athletes). During lockdown, < 40% were able to maintain sport-specific training (e.g., long endurance [39%], interval training [35%], weightlifting [33%], plyometric exercise [30%]) at pre-lockdown levels (higher among world-class, international, and national athletes), with most (83%) training for "general fitness and health maintenance" during lockdown. Athletes trained alone (80%) and focused on bodyweight (65%) and cardiovascular (59%) exercise/training during lockdown. Compared with before lockdown, most athletes reported reduced training frequency (from between five and seven sessions per week to four or fewer), shorter training sessions (from ≥ 60 to < 60 min), and lower sport-specific intensity (~ 38% reduction), irrespective of athlete classification. CONCLUSIONS: COVID-19-related lockdowns saw marked reductions in athletic training specificity, intensity, frequency, and duration, with notable within-sample differences (by athlete classification). Higher classification athletes had the strongest desire to "maintain" training and the greatest opposition to "not training" during lockdowns. These higher classification athletes retained training specificity to a greater degree than others, probably because of preferential access to limited training resources. More higher classification athletes considered "coaching by correspondence" as sufficient than did lower classification athletes. These lockdown-mediated changes in training were not conducive to maintenance or progression of athletes' physical capacities and were also likely detrimental to athletes' mental health. These data can be used by policy makers, athletes, and their multidisciplinary teams to modulate their practice, with a degree of individualization, in the current and continued pandemic-related scenario. Furthermore, the data may drive training-related educational resources for athletes and their multidisciplinary teams. Such upskilling would provide athletes with evidence to inform their training modifications in response to germane situations (e.g., COVID related, injury, and illness).

Hydration Status and Fluid Replacement Strategies of High-Performance Adolescent Athletes: An Application of Machine Learning to Distinguish Hydration Characteristics.

There are limited data on the fluid balance characteristics and fluid replenishment behaviors of high-performance adolescent athletes. The heterogeneity of hydration status and practices of adolescent athletes warrant efficient approaches to individualizing hydration strategies. This study aimed to evaluate and characterize the hydration status and fluid balance characteristics of high-performance adolescent athletes and examine the differences in fluid consumption behaviors during training. In total, 105 high-performance adolescent athletes (male: 66, female: 39; age 14.1 ± 1.0 y) across 11 sports had their hydration status assessed on three separate occasions-upon rising and before a low and a high-intensity training session (pre-training). The results showed that 20-44% of athletes were identified as hypohydrated, with 21-44% and 15-34% of athletes commencing low- and high-intensity training in a hypohydrated state, respectively. Linear mixed model (LMM) analyses revealed that athletes who were hypohydrated consumed more fluid (F (1.183.85)) = 5.91, (p = 0.016). Additional K-means cluster analyses performed highlighted three clusters: "Heavy sweaters with sufficient compensatory hydration habits," "Heavy sweaters with insufficient compensatory hydration habits" and "Light sweaters with sufficient compensatory hydration habits". Our results highlight that high-performance adolescent athletes with ad libitum drinking have compensatory mechanisms to replenish fluids lost from training. The approach to distinguish athletes by hydration characteristics could assist practitioners in prioritizing future hydration intervention protocols.

Motives for Dropout Among Former Junior Elite Caribbean Track and Field Athletes: A Qualitative Investigation.

Anecdotal reports within the Caribbean track and field fraternity have revealed that there is a high level of athlete dropout from competitive sport at the junior-elite level, and a poor transition to senior-elite status. Consequently, this qualitative investigation explored the key motives that may have contributed toward the unsuccessful transitions and ensuing dropout of Caribbean track and field athletes during the junior to senior transition period. Eleven former junior-elite track and field athletes (four males, seven females; Mage = 29, SD ± 4.2 years) from four English-speaking Caribbean islands participated in semi-structured interviews. Following an inductive and deductive thematic analysis, four higher order themes were identified: (1) "there's not enough support"; (2) "felt pressure to make sure I committed"; (3) "it's always competitive here"; and (4) "battle with the injuries." For these former junior-elite Caribbean athletes, the decision on whether to continue within the sport was influenced by a combination of factors, although inadequate financial and organizational support had the most bearing on athletes' decision to drop out during the crucial transition years. Implications for consideration by key stakeholders and policymakers within the region are discussed.

Questionnaire-Derived Sleep Habits and Academic Achievement in First Year University Students.

This study aimed to determine the effect of sleep quantity and quality via the Pittsburgh Sleep Quality Index (PSQI) on students' academic achievement in their first year of university study. In this cross-sectional study, 193 students (102 female, 91 male, mean ± SD; age = 19.3 ± 2.9 y) from an undergraduate Health degree in New Zealand completed the PSQI four weeks prior to the end of the semester in their first year of university study. Results from three core subjects in the first semester were averaged and correlations between the PSQI and academic success were evaluated using Spearman's rho (ρ). The group were also trichotomized using a PSQI global score of ≤5 as the threshold for "good" sleepers (n = 62, 32%), a score of 5-8 for "moderate" sleepers (n = 63, 33%) and a score ≥8 to characterize "poor" sleepers (n = 68, 35%). Overall, students averaged 7 h 37 min of self-reported sleep duration with an average bedtime of 22:55 p.m. and wake time of 8:01 a.m. There was a significant, small inverse relationship between academic performance and bedtime (p = 0.03, ρ = -0.14), with those going to bed earlier having superior academic success. The trichotomized data demonstrated no significant differences in academic performance between students with poor, moderate and good sleep quality (p = 0.92). Later bedtimes were associated with lower academic performance in a group of first year university students. However, there were no other relationships observed between academic success and self-reported sleep quality or quantity as determined by the PSQI. Enhancing awareness of the impact of sleep timing on academic success should be prioritized and strategies to improve sleep hygiene should be promoted to university students.

Impact of the talent development environment on the wellbeing and burnout of Caribbean youth track and field athletes.

This study examined the perceived talent development environment (TDE) of youth track and field athletes within the Caribbean region and explores the relationship with their subjective wellbeing and burnout levels. A sample of 400 Caribbean youth track and field athletes (male = 198, and female = 202; age 13-20 years) participated in this cross-sectional study. Athletes responded to a survey which included the Talent Development Environment Questionnaire (TDEQ-5), the World Health Organization Wellbeing Index (WHO-5) and the Athlete Burnout Questionnaire (ABQ). Structural equation modelling showed that a positive and supportive TDE was associated with better athlete wellbeing and lower athlete burnout. Moreover, gender and hours of training moderated relationships of athletes' perceptions of their development environment with wellbeing and burnout levels respectively. Furthermore, there was a positive association between the support network and athlete wellbeing, while holistic quality preparation was negatively associated with athlete burnout. Development environments perceived as supportive and geared towards a holistic athlete-centred approach were associated with better athlete wellbeing and lower burnout.

Technical determinants of success in professional women's soccer: A wider range of variables reveals new insights.

Knowledge of optimal technical performance is used to determine match strategy and the design of training programs. Previous studies in men's soccer have identified certain technical characteristics that are related to success. These studies however, have relative limited sample sizes or limited ranges of performance indicators, which may have limited the analytical approaches that were used. Research in women's soccer and our understanding of optimal technical performance, is even more limited (n = 3). Therefore, the aim of this study was to identify technical determinants of match outcome in the women's game and to compare analytical approaches using a large sample size (n = 1390 team performances) and range of variables (n = 450). Three different analytical approaches (i.e. combinations of technical performance variables) were used, a data-driven approach, a rational approach and an approach based on the literature in men's soccer. Match outcome was modelled using variables from each analytical approach, using generalised linear modelling and decision trees. It was found that the rational and data-driven approaches outperformed the literature-driven approach in predicting match outcome. The strongest determinants of match outcome were; scoring first, intentional assists relative to the opponent, the percentage of shots on goal saved by the goalkeeper relative to the opponent, shots on goal relative to the opponent and the percentage of duels that are successful. Moreover the rational and data-driven approach achieved higher prediction accuracies than comparable studies about men's soccer.