Training loads and player wellness in youth sport: Implications for illness

Despite the athlete monitoring cycle becoming increasingly popular within sport, very little evidence exists with regards to the relationships present between its measures or its relationship with illness incidence in youth athletes. The aim of this thesis was to evaluate the true predictive ability of an integrated athlete monitoring cycle model, incorporating measures of the training dose (training load), training recovery (sleep) and training response (wellness questionnaires (DWB and PRS), countermovement jumps and salivary IgA (s-IgA)), with regards to illness incidence in youth athletes. Study 1 outlined the reliability and usefulness of DWB (poor/marginal), PRS (poor/marginal) and CMJ (good/useful). Despite study 1’s findings, study 2 showed that CMJ was not suitable for use as a training response measure in youth athletes. Studies 3 and 4 supported the use of the sleep quality subscale as a training recovery measure rather than within the DWB training response measure (which was reduced to the four item DWBno-sleep). The overall DWBno-sleep score, fatigue, stress and mood were statistically related to the training recovery, whereas only muscle soreness was related to the training dose. Statistically, PRS was related to both the training dose and recovery. Despite the presence of these statistical relationships, only the effect of training load, including match exposure, on PRS was practically interpretable. Unfortunately, technical issues prevented the true predictive ability of an integrated athlete monitoring cycle model with regards to illness incidence being tested. However, study 5 showed that s-IgA measures could not accurately predict illness in youth athletes. Furthermore, analysis of the longitudinal trends of s-IgA, DWBno-sleep and PRS showed that the subjective fatigue/wellness measures were more responsive to qualitative events than objective measures of immune function. Overall, the results of this thesis provide support for the use of the integrated athlete monitoring cycle in youth athletes, particularly when subjective training response measures are included. However, future research needs to consider the true predictive ability of the proposed integrated athlete monitoring cycle model with regards to illness incidence.