# The Relationship between Training Load Measures and Next-Day Well-Being in Rugby Union Players
## 4 Discussion
[14] has suggested that the relationship between self-report measures and training loads remains unclear and further assessment is required to establish their suitability to detect fatigue. Therefore, it is entirely possible that the relationships are not only confounded by the TL variables but also the suitability of the outcome measures. A limitation of this study was the small sample size. The study population was a convenience sample limited to the fifteen players who were regular first team players, as such would consistently play in all matches during the study period. To address the small sample size, a strength of using Bayesian analysis in this study is that the analysis is based around data points compared to sample size found in typical frequentist methods. Precision rather than power is the usual goal of Bayesian analysis and its priori sample size calculations. Follow up studies with more participants and using Bayesian analysis would help confirm the findings of this study. Both physiological and psychological factors have been shown to influence the accuracy of wellbeing questionnaires [7,8]. Additional stresses such as academic and social can have greater impact on perceptions of fatigue in academy age groups than elite senior players [27]. Additionally, the length of the rating scales used in typical well-being questionnaires may not allow athletes to fully describe their subjective fatigue. The small variance explained by the changes in WB makes their use to inform the dose-response relationship between TL and perceived fatigue is questionable. In a previous study [30] it was highlighted that individual responses to bouts of high TL, where players with the highest VO2 max typically reporting lower RPE for each exercise bout. In contrast, two players with similar VO2 max values reported different perceptions of fatigue. As such, subjective psychological responses are more complex and influenced by more than the physiological responses to training and match-play alone [12, 30, 31]. Ultimately, well-being questionnaires may require more sensitive scales to quantify the complex multifactorial nature of subjective fatigue more fully, of which the TL completed is only one factor. The data from this investigation would suggest no more than 33% to 36% of changes in total WB can be explained by external load measures (TD, PL, iHSD and HSD). This investigation viewed in the wider scope of the purpose of athlete monitoring would suggest caution is required if sports scientist is planning to use manipulation of TL to influence outcomes for subjective fatigue in rugby players. It could be that the unique nature of rugby and other team sports that involve contact and collisions during training and match-play provides an additional component that influences players perception of well-being that is not present in other teams' sports such as soccer. As such, further research is required into the relationship between TL measures and subjective fatigue measures to better understand to what extent a feasible relationship between measures of TL and subjective measures is possible and able to influence the training process. There is the possibility that typically collected training load measures do not explain larger proportions of perceptions in fatigue. Consequently, the hope of a dose-response relationship where we can confidently manipulate TL to impact levels of fatigue may not be possible at present. In this instance reacting to the response may be the only possible course of action [2].