Editorial: Load and Wellness Quantification in Sports and Physical Activity

Rafael Oliveira ^1,2* João Paulo Brito ^1,2 Francisco Tomás González-Fernández ³ Ryland Morgans ⁴

• ¹ School of Sport, Polytechnic Institute of Santarém, Santarém, Portugal
• ² Research Centre in Sports Sciences, Health Sciences and Human Development (CIDESD), University of Trás-os-Montes and Alto Douro, Vila Real, Portugal
• ³ Department of Physical Education and Sports, University of Granada, Granada, Spain
• ⁴ School of Sport and Health Sciences, Cardiff Metropolitan University, Cardiff, United Kingdom

Load and wellness (sometimes referred to as wellbeing) monitoring of training or competition are useful to improve performance (Gabbett et al., 2017). While load can be divided into two dimensions: internal (e.g., rating of perceived exertion (RPE) and heart rate) and external (e.g., running and accelerometry based measures) (Bourdon et al., 2017;Miguel et al., 2021), wellness can also include varying measures of fatigue, quality of sleep, muscle soreness, stress, and mood which are regularly collected through questionnaires (Hooper & Mackinnon, 1995;McLean et al., 2010).However, the existing literature is not consistent when demonstrating the relationship between load and wellness metrics. For example, a systematic review investigated the relationship between wellness and training load measures in teamsport athletes, revealing a spectrum of relationships ranging from no correlation to very large associations (Duignan et al., 2020). Moreover, a more recent systematic review suggested a low level of sleep quality and quantity may negatively affect soccer performance while also increasing injury risk (Clemente et al., 2021). Furthermore, Rico-González et al. (2021) examined team sports (rugby, handball, basketball, futsal, hockey, and Australian football) and observed that Immunoglobulin A (IgA) tend to decrease when a higher training load or congested period occurs. An association between low levels of IgA and higher upper respiratory tract infection was found, which consequently may decrease wellness (Rico-González et al., 2021).Therefore, the aim of this research topic was to provide information on load and wellness monitoring of different sports and analyzing the relationship between the different dimensions.The articles within this Research Topic addressed diverse aspects of sports such as: the prediction of soccer injuries using GPS-based metrics (e.g. acceleration and deceleration); the impact of sleep on emotional and physical wellbeing, using daily sleep diaries and questionnaires in professional cricketers; the stretch-shortening cycle fatigue response, using the countermovement jumps and 10-5 hop tests, to a highintensity stressful phase of training in collegiate men's basketball; internal load, using energy expenditure, oxygen consumption, heart rate and RPE, of seven different indoor cardiovascular machines; the training intensity distribution of the different training zones (i.e., zone 1, 2 and 2), using different internal load measures (heat rate, blood lactate, peak oxygen consumption (VO2peak) and RPE) and external load measures (% of race-pace, power, velocity) by elite-to-world-class endurance athletes; and analysis of the sports initiation (M.A.M.I.deporte®) practiced by between children and parents through a survey analysis.For instance, there are three articles in the sporting field, two articles examining recreational participants and one reviewsion. Regarding sports, Saberisani et al. found that no external load variables showed high predictive power (> 0.95), although a close value (0.91) for the number of decelerations was observed, highlighting the load management of this metric as a potential injury risk factor in soccer. The same authors also suggested using this metric for acute, chronic, and acute-to-chronic workload calculation which can be replicated for varying soccer contexts (e.g., different countries, leagues, ages and sexes) and other team sports (e.g., futsal, handball, basketball, rugby, etc.). Grewal et al. focused on wellness, specifically sleep but it also included muscle soreness, readiness, stress and fatigue monitoring. This research highlighted that better sleep quality positively influences the overall emotional and physical well-being of professional cricketers. These results emphasize the importance of targeted sleep interventions to improve sleep quality and subsequently optimize psychological and physiological wellness. Again, the findings of the present article can be replicated for differing contexts of both individual and team sports. Moreover, Philipp et al. explored the stretch-shortening-cycle fatigue response (through different type of jumps such as countermovement jumps and 10-5 hop) to a one-week highintensity fatiguing phase of training and found that basketball players experienced acute fatigue, as well as potentially longer lasting reductions in performance. Notably, these findings can be replicated and also highlight the practical ease of these tests to monitor fatigue in various contexts.Considering recreational participants, Prieto-González et al. compared energy expenditure, VO2peak, and heart rate recorded in middle-aged adults while exercising on seven different indoor cardiovascular machines at maximal and submaximal intensities. The main findings showed that the treadmill expended the greatest energy, followed by the stair climber and the elliptical trainer. It was also reported that participants displayed greater enjoyment which may lead to improved exercise adherence. Moreover, Cueto-Martín et al. highlighted the joint activity of parents and children (between 2 and 11 years) while completing vigorous physical activity and suggesting that this type of programs can promote better environments for the family by sharing healthy lifestyle habits. Additionally, a better understanding of parents' influence on children's physical activity is crucial to improve while also increasing positive effects on health and well-being.Finally, Sperlich et al. presented a review on the training intensity distribution (training at moderate (Zone 1), heavy (Z2) and severe (Z3)) of elite-to-world-class endurance athletes during different phases of the season and highlighted that the existing literature did not allow general conclusions to be drawn due to the greater variability of utilized methods. Furthermore, the lack of contextual information concerning the mode of exercise, environmental conditions, and biomechanical aspects of the exercise were evident. Such findings reinforce the inclusion of both the type of load quantification (external and internal) and wellness monitoring for better insights and load adjustments. Furthermore, the study context, participants and exercise protocols are essential for enhanced research methods and its replicability.The articles presented in this Research Topic contribute for a better knowledge about the interaction of some load and wellness metrics in several sports. Except for the review study, the other studies can be fully replicated in diverse sports settings or geographic contexts, potentially validating the findings discussed. This compilation addresses several sports, including young, professional, recreational, male, and female athletes. Importantly, it addresses some gaps in the literature such as the simultaneous practice of physical activity for parents and their children. Consequently, this Research Topic serves as a relevant tool for sport researchers, coaches, parents, and practitioners.Nonetheless, more research is needed to provide deeper insights on training methodologies as well as to provide more clarifications on when using different metrics and how to interpret them.