The Response to Training and Risk of Injuries in Elite Australian Footballers

Training is the systematic application of stress and recovery. The process of striking a balance between stress and recovery is facilitated by monitoring the stress dose (training load) and the response to the applied stress. This thesis investigated several musculoskeletal adaptions in response to training as well as the individual and combined effects of several athlete-monitoring-derived factors on the risk of injury in elite Australian footballers.\ud The first study evaluated the influence of individual internal and external training load and leg dominance on changes in the Achilles and patellar tendon structure. The internal structure of the Achilles and patellar tendons of both lower limbs of 26 elite Australian footballers was assessed using ultrasound tissue characterization at the beginning and the end of an 18 week pre-season. Possibly to very likely small increases in the proportion of aligned and intact tendon bundles occurred in the dominant Achilles (initial value 81.1%; change, ±90% confidence limits 1.6%, ±1.0%), non-dominant Achilles (80.8%; 0.9%, ±1.0%), dominant patellar (75.8%; 1.5%, ±1.5%), and non-dominant patellar (76.8%; 2.7%, ±1.4%) tendons. Measures of training load had inconsistent effects on changes in tendon structure; for example, there were possibly to likely small positive effects on the structure of the non-dominant Achilles tendon, likely small negative effects on the dominant Achilles tendon, and predominantly no clear effects on the patellar tendons. The small and inconsistent effects of training load are indicative of the role of recovery between tendon overloading (training) sessions and the multivariate nature of the tendon response to load with leg dominance a possible influencing factor.\ud The aim of the second study was to determine the normal week-to-week variability of the sit and reach test (S&R), dorsiflexion lunge test (DLT), and adductor squeeze test (AST) scores, as well as the individual differences in variability and the effects of training load on the scores. Forty-four elite Australian rules footballers completed the weekly musculoskeletal screening tests on day two or three post-main training (pre-season) or post-match (in-season) over a 10 month season. Ratings of perceived exertion and session duration for all training sessions were used to derive various measures of training load via both simple summations and exponentially weighted moving averages. Data were analysed via linear and quadratic mixed modelling and interpreted using magnitude-based inference. Substantial small to moderate variability was found for the tests at both season phases; for example over the in-season, the normal variability ±90% confidence limits were as follows: S&R ±1.01 cm, ±0.12; DLT ±0.48 cm, ±0.06; AST ±7.4%, ±0.6%. Small individual differences in variability existed for the S&R and AST (factor standard deviations between 1.31 and 1.66). All measures of training load had trivial effects on the screening scores. A change in a test score larger than the normal variability is required to be considered a true change. Athlete monitoring and flagging systems need to account for the individual differences in variability. The S&R, DLT, and AST are not sensitive to internal training load when conducted two or three days post-training or post-match, and the scores should be interpreted cautiously when used as measures of recovery.\ud Study three evaluated the individual and combined effects of several athlete-monitoring-derived factors on the risk of soft-tissue non-contact injuries. A cohort of 55 elite Australian footballers was prospectively monitored over two consecutive seasons. Internal and external training load was quantified using the session rating of perceived exertion and GPS/accelerometer units, respectively. Cumulative loads and acute-to-chronic workload ratios were derived using rolling averages and exponentially weighted moving averages (smoothed loads). History of injuries in the current and previous seasons was also recorded along with professional experience, weekly musculoskeletal screening, and subjective wellness scores for individual athletes. Individual and combined effects of these variables on the risk of injury were evaluated with generalized linear mixed models. High cumulative loads and acute-to-chronic workload ratios were associated with increased risk of injuries. The effects for measures derived using exponentially weighted moving averages were greater than those for rolling averages. History of a recent injury, long-term experience at professional level, and substantial reductions in a selection of musculoskeletal screening and subjective wellness scores were also associated with increased risk. The effects of high cumulative load were underestimated by ~20% before adjusting for previous injuries, whereas the effects of high acute-to-chronic workload ratios were overestimated by 10-15%. Injury-prone players were at a more than five times higher risk of injuries compared to robust players (hazard ratio 5.4, 90% confidence limits 3.6–12). Combinations of multiple risk factors were associated with extremely large increases in risk; for example, a hazard ratio of 22 (9.7–52) was observed for the combination of high acute load, recent history of a leg injury, and a substantial reduction in the adductor squeeze test score. This study determined that the information from athlete monitoring practices should be interpreted collectively and used as a part of the injury prevention decision-making process along with consideration of individual differences in risk. The findings of this thesis highlight the multivariate nature of the response to training and injuries. This thesis has provided a framework for the monitoring of team sport athletes to ensure a better application of training stress and reduce the now much better understood risk of injury