Athlete sleep can be disrupted by sport- and non-sport-related factors. However, the interactions of these sleep-related factors are not well understood. Systems science approaches, such as causal loop diagramming (CLD), provide an opportunity to map these interactions. This project aimed to (1) develop a CLD of the athlete sleep system describing the interacting variables, (2) identify feedback loops and potential leverage points to optimise athlete sleep, and (3) demonstrate the applicability of a CLD to guide the development of a sleep monitoring framework. A systems-based model of athlete sleep was developed using CLD, informed by existing literature and refined through a consensus process involving ten subject matter experts (nine from Australia, one from the USA). The model was then interrogated using network analysis to identify key variables based on their position and connectivity within the system. These findings informed the development of a generic sleep monitoring framework. The CLD comprised 48 variables and 120 relationships across four domains: travel demands, behavioural and lifestyle factors, athlete condition and readiness, and resourcing and scheduling constraints. Overall, 12 key variables were identified, with hours of travel, number of time zones crossed, dose of caffeine, and amount of resources or expenditure available being the most connected upstream variables. Level of pre-sleep arousal, sleep opportunity, travel fatigue, and level of performance received the greatest number of incoming relationships, representing points at which multiple pathways converge. Physical condition, level of performance, quality of diet, and importance of competition most frequently linked different quadrants of the system. These variables informed a three-tier monitoring framework capturing upstream determinants and downstream consequences of sleep. According to the CLD, sleep health in athletes extends beyond an individual behaviour issue and is influenced by the structure and functioning of sport systems. Interactions among travel demands, physical readiness, behavioural and lifestyle factors, and organisational constraints sustain athlete sleep health over time. Consequently, meaningful improvements in sleep health are likely to arise from both system-level interventions and individual behaviour change strategies.
Basketball is a physically demanding intermittent team sport which requires a multifaceted approach to optimise player preparation, performance, health, and recovery. Quantifying the training and match demands of professional basketball players can help practitioners develop effective strategies for managing fatigue, monitoring training loads, and guiding physical preparation. Sleep and travel disruptions present additional challenges to practitioners and can have deleterious effects on recovery and readiness to compete. Nutrition is also an essential component supporting performance and recovery and should be individualised to the needs of each player. The inherent complexity of basketball requires practitioners to develop a holistic view that considers the interaction between tactical, technical, psychological, and physical basketball-related factors along with external factors from the greater basketball system (e.g., players, coaches, support staff, organisations, schedules, referees, and governing bodies) that can influence performance. Advances in technology continue to shape performance monitoring, injury-risk forecasting, and training methodologies, yet practitioners must be aware of potential risks such as player privacy concerns and the misuse of data. A comprehensive understanding of these factors provides valuable insights for practitioners to develop effective evidence-based strategies and frameworks for working with professional male basketball players.
Sleep is essential for optimal performance and recovery in athletes. Post-exercise cold exposure, including cold water immersion and cryotherapy, is typically used to enhance recovery, but its effects on sleep remain unclear. Emerging evidence also suggests that post-exercise heat exposure, including sauna and hot water immersion before sleep may improve both objective and subjective sleep outcomes. However, the effectiveness of post-exercise thermal interventions for improving nocturnal sleep in athletes specifically has not yet been comprehensively evaluated. This narrative review synthesizes the current evidence and discusses the potential physiological mechanisms by which post-exercise thermal interventions may influence nocturnal sleep in athletes. Despite methodological heterogeneity, existing research indicates that post-exercise thermal interventions may influence the subsequent nocturnal sleep of athletes through multiple and varying interacting mechanisms. For example, cold exposure close to bedtime (< 2 h) may disrupt sleep by reducing the distal-to-proximal skin temperature gradient (DPG), thereby increasing sleep onset latency and shortening sleep duration. In contrast, when applied more than 2 h before bedtime, cold exposure may improve sleep by augmenting parasympathetic tone and/or reducing muscle soreness and associated nocturnal movement. Although it remains unclear whether post-exercise heat exposure improves sleep via autonomic modulation or reduced muscle soreness, existing evidence indicates that sleep may be facilitated by an increased DPG. Moderating factors such as sex, time of day, environmental temperature, bedding microclimate, acclimatization status, and training load may influence the effects of post-exercise thermal interventions on sleep and should be investigated in future studies.
Lean body mass (LBM) strongly associates with the capacity to deliver and consume oxygen in pilot studies performed in adults with low LBM. We aimed to test whether LBM generally accounts for the phenotype of the circulatory system and hence its sex dimorphism in humans. Healthy women and men (n = 294, 50
