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Purpose: To explore complex system behavior and subsequent team performance in professional rugby union. Methods: Here, we present 2 studies. In the first, we used global positioning system technology to measure player clustering during stoppages in play in nearly 100 games of professional rugby union to explore team (complex system) behavior and performance. In the second, we measured stress hormones (cortisol and testosterone) prior to team meetings and analyzed these relative to amount of time and the frequency with which players looked at peer presenters, as well as subsequent training performance, to explain how stress may lead to behaviors observed in the first study and subsequent match performance. Results: No link between player clustering during stoppages of play and performance was observed. When players (complex system agents) demonstrated greater levels of stress (as indicated by greater cortisol-awakening response and a greater decline in testosterone-to-cortisol ratio across the morning), they tended to look at peer presenters more; however, training quality declined (P = .02). Correlational analysis also showed that training quality was related to testosterone-to-cortisol ratio (P = .04). Conclusions: Team behavior is complex and can be unpredictable. It is possible that under stress, complex system agents (ie, rugby union players) look at (and cluster toward) their teammates more; however, meaningful interaction may not necessarily occur. Furthermore, while complex system (team) analysis may be valuable strategically in rugby union in the context of describing behavior, without understanding “how” or “why” intrateam/interagent behaviors emerge it may have little meaning.

Given the importance of body composition in maintaining optimal physical and functional capacities, the use of appropriate, field-based assessment tools should be a priority to assist in maintaining the occupational safety of firefighters and the community. For ease, body mass index has often been used to assess these changes. However, it is limited in its accuracy. The purposes of this study were twofold: (a) to compare the validity of different measures of body composition against dual-energy X-ray absorptiometry (DXA) in urban firefighters and (b) to assess these measures in their ability to provide meaningful interpretation of criteria-driven categories of adiposity. A total of 64 male firefighters (age = 44.0 ± 9.5 years) underwent full anthropometric profiling (predictor equations used to determine body fat percentage [BF%]), bioelectrical impedance analysis (BIA), and DXA assessments. Participants’ body mass index was calculated, and BF% and lean mass were determined along with criteria-driven categorizations of adiposity. Anthropometric (skinfolds) predictor equations (e.g., mean bias = −4.4% for BF%) were typically closer to DXA measures, compared with BIA (9.4% for BF%). However, when determining categories of criteria-driven adiposity, BIA (42.9% overweight or obese) provided closer estimates to the DXA-determined distribution (44.6%) than anthropometric-based measures (up to 40%). Body mass index appears an inappropriate measure for accurately determining categories of adiposity with 64.1% classified as overweight or obese. Given the logistical constraints of anthropometric profiling, and the closeness of BIA to DXA in adiposity categories, BIA may be a suitable alternative to DXA for assessing body composition in professional urban firefighters.