Athlete monitoring in professional Australian football: Measurement characteristics, parsimony and relationships with performance

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Australian football (AF) is a physically-demanding, high-intensity field-based sport with players competing in the presence of performance-related psychological stress. This requires detailed monitoring of players for training and competition to maximise their readiness for high-level performance. Historically, monitoring team sport athletes has been based on the theoretical β€˜fitness-fatigue’ model whereby performance can be deduced with knowledge of fitness (positive effects of training completed) and fatigue (residual impairments of function due to an acute training dose) over acute (~15 days) and chronic timeframes (~50 days). However, in practice, individual training load is prescribed to players over acute timeframes of ~7 days prior to competition matches, dictated by scheduling of matches every 6-8 days during the competition season. The prescription of acute training load is informed by a range of athlete monitoring data measuring training load completed, training response and neuromuscular performance. However, despite anecdotal evidence of the use of individual acute training load prescription in professional AF, it has not been presented empirically. This thesis contains five studies that aim to build a novel conceptual model of acute training load prescription using a refined collection of monitoring tests with suitable measurement characteristics that relate to competition performance in professional AF. 𝘚𝘡𝘢π˜₯𝘺 π˜–π˜―π˜¦ and 𝘚𝘡𝘢π˜₯𝘺 π˜›π˜Έπ˜° evaluated the measurement characteristics of reliability and sensitivity of common tests of training response, neuromuscular performance and aerobic fitness using test-retest and signal-to-noise ratio methods. The results showed that perceived wellness questionnaires, countermovement jump tests, eccentric hamstring force tests, isometric adductor force tests and heart rate recovery tests possess acceptable reliability and sensitivity, allowing confident identification of meaningful test results for practitioners. 𝘚𝘡𝘢π˜₯𝘺 π˜›π˜©π˜³π˜¦π˜¦ and 𝘚𝘡𝘢π˜₯𝘺 𝘍𝘰𝘢𝘳 addressed the issue of monitoring data overload for team sport practitioners by applying principal component analyses (PCA) to the monitoring tests established in 𝘚𝘡𝘢π˜₯𝘺 π˜–π˜―π˜¦ and 𝘚𝘡𝘢π˜₯𝘺 π˜›π˜Έπ˜° in addition to measures of training load and extended this analysis to propose two practical methods of using the results of PCA to enhance efficiency in team sport monitoring systems. 𝘚𝘡𝘢π˜₯𝘺 π˜›π˜©π˜³π˜¦π˜¦ demonstrated that external load, internal load and perceived wellness represent statistically separate constructs of the training process, across acute (7-day) and chronic (28-day) timeframes commonly used to categorise athlete monitoring data. 𝘚𝘡𝘢π˜₯𝘺 𝘍𝘰𝘢𝘳 identified components to represent isometric adductor force, eccentric hamstring force and countermovement jump power. These findings indicate that many individual measures commonly collected and analysed in professional team sport monitoring systems assess similar aspects of the training process, and hence some variables can be excluded from monitoring systems to enhance efficiency in the use of financial and human resources. 𝘚𝘡𝘢π˜₯𝘺 𝘍π˜ͺ𝘷𝘦 analysed the effect of a refined collection of measures of training load, training response and neuromuscular output from previous studies in the thesis and showed that z-score increases in individual acute training load associated with an 18-23% increase in performance z-score. This finding indicates that team competition schedule may have a confounding effect on acute load completed prior to a match as longer between-match periods provide for opportunity and flexibility for greater load completion. 𝘚𝘡𝘢π˜₯𝘺 𝘍π˜ͺ𝘷𝘦 also found no significant relationships between a range of other commonly collected monitoring variables and performance change. Collectively, the thesis populated a novel conceptual model of acute training load prescription with individual adjustments of acute load informed by a refined range of reliable and sensitive monitoring measures that relate to individual performance changes.
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