Abstract
The aim of this study is to identify the relationship between different internal and external load measures and next day subjective wellbeing. With institutional ethics approval, ten academy rugby union players (Five forwards, and five backs) with a local National League One club agreed to participate in the study (aged; 18.4 ± 1.0 years, height; 181.3 ± 5.9 cm, body mass 85.9 ± 13.0 kg, VO2max 56.2 ± 6.8 mL·kg−1·min−1). Before the 6-week in-season data collection period, participants completed an incremental treadmill test to determine lactate thresholds at 2 mmol·L−1 (LT) and 4 mmol·L−1 and the heart rate blood lactate (HR-BLa) profile for individualized training impulse (iTRIMP) calculations. Internal training load was quantified using Banister’s TRIMP, Edward’s TRIMP, Lucia’s TRIMP, individualised TRIMP and session-RPE. External training load was reported using total distance, PlayerLoadTM, high-speed distances (HSD) > 18 km∙h−1 and >15 km∙h−1, and individualized high-speed distance (iHSD) based on each player’s velocity at OBLA. On arrival and prior to all training sessions players completed a well-being questionnaire (WB). Bayesian linear mixed model analysis identified that a range of internal and external load measures explained between 30% and 37% of next-day total wellbeing and between 65% and 67% of next-day perceived stress. All other internal and external load measures demonstrated very weak to moderate relationships (R2 = 0.08 to 0.39) with all other wellbeing components. Internal sRPE, iTRIMP and bTRIMP loads alongside external HSD loads provide coaches with the most practical measures to influence players’ perceived wellbeing.
Highlights
The general aim of athletic training is to induce a physiological stress which stimulates adaptation [1]
During the six-week in-season study period internal and external load measures and subjective wellbeing questionnaires were obtained from a total of 164 training observations for the ten participants
To identify the feasibility of relationship between each training load (TL) measure and wellbeing variable and provide guidance for coaches to better manage players’ well-being, the parameter estimate was multiplied for each load measure to elicit a change of 1 on the well-being questionnaire
Summary
The general aim of athletic training is to induce a physiological stress which stimulates adaptation [1]. One of the purposes of athlete monitoring is to better understand the relationship between what is done and how players may respond [2]. This has commonly been termed the dose-response (D-R). To better understand the performance potential of a player, coaches need to be able to quantify aspects of each training session with measures that are related to changes in measures of player’s fitness and fatigue [2]. The aim being for coaches to determine an appropriate dose-response relationship enabling them to take a proactive rather than reactive role
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