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Purpose: To investigate the association between player wellness and injury in elite junior Australian football players over 1 competitive season. Methods: Prospective cohort study. Elite junior Australian football players (N = 196, average age = 17.7 y, range = 16–18 y) were recruited in the under-18 state league competition in Victoria, Australia. They recorded their wellness (sleep, fatigue, soreness, stress, and mood) according to a 5-point Likert scale 3 times weekly, with injuries (missed match/training session) entered into an online sport-injury surveillance system. A logistic generalized estimating equation was used to examine the association (expressed as odds ratio [OR]) between wellness and injury (yes/no). Results: Soreness was associated with injury at each time point across the week, with the strongest association evident for soreness reported 6 d postmatch (OR = 1.30; 95% confidence interval [CI], 1.17–1.44; P <.001). Stress and injury were associated with injury for average stress values across the week, as well as specifically on day 1 postmatch (OR = 1.10; 95% CI, 1.01–1.21; P =.038). Mood reported in the middle of the week (3 d postmatch) was associated with injury (OR = 0.87; 95% CI, 0.78–0.97; P =.014), as was fatigue (OR = 1.10; 95% CI, 1.00–1.22; P =.044). Conclusions: This study demonstrates key associations between wellness and injury in elite junior Australian football, specifically soreness, stress, fatigue, and mood. Monitoring strategies help identify injury-risk profiles, which can help decision makers (coaches or medical staff) intervene when relevant to reduce injury risk. [ABSTRACT FROM AUTHOR]

Purpose: To investigate the association between training and match loads and injury in elite junior Australian football players over 1 competitive season. Methods: Elite junior Australian football players (n = 290, age 17.7 [0.3] y, range 16–18 y) were recruited from the under-18 state league competition in Victoria to report load and injury information. One-week load (session rating of perceived exertion multiplied by duration) and all time-loss injuries were reported using an online sport-injury surveillance system. Absolute load measures (weekly sums) enabled the calculation of relative measures such as the acute:chronic workload ratio. Load measures were modeled against injury outcome (yes/no) using a generalized estimating equation approach, with a 1-wk lag for injury. Results: Low (<300 arbitrary units [au]) and high (>4650 au) 1-wk loads were associated with significantly higher risk of injury. Furthermore, low (<100 au) and high (>850 au) session loads were associated with a higher risk of injury. High strain values (>13,000) were associated with up to a 5-fold increase in the odds of injury. There was a relatively flat-line association between the acute:chronic workload ratio and injury. Conclusions: This study is the first investigation of elite junior athletes demonstrating linear and nonlinear relationships between absolute and relative load measures and injury. Coaches should focus player loads on, or at least close to, the point at which injury risk starts to increase again (2214 au for 1-wk load and 458 au for session load) and use evidence-based strategies across the week and month to help reduce the risk of injury. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]