Subjective and objective assessments applied to monitor an athlete’s recovery status can assist coaches in effective training prescription, thus reducing the risk of non-functional overreaching (NFOR) alongside optimising the stimulus to promote training adaptation [1
]. Accordingly, methods applied to monitor aspects of athlete recovery must be sensitive to changes in recovery status induced by different training loads. Self-reported well-being questionnaires have been proposed as valid measures to assess athlete responses to daily training and competition [2
]. Previous studies have identified that daily self-report well-being questionnaires are sensitive to manipulations in training and competition load in high intensity intermittent team sport players [3
]. The use of objective assessments to identify the maladaptive response associated with non-functional overreaching (NFOR) has received considerable attention [1
]. Popular objective methods include countermovement jumps (CMJ) [1
], resting HR (HRrest
) and heart rate variability (HRV) [6
]. However, the sensitivity of these measures to assess athlete recovery remains equivocal with some studies reporting a sensitivity or lack of sensitivity to changes in training load [2
Although sport teams often train together, as individuals the time-course of recovery from a physical training stimulus is dependent on numerous factors including initial level of fitness, genetics, prior recovery and training exposure [8
]. Therefore it is important that training and recovery metrics are considered on an individual basis rather than just in relation to the training group. Hence, establishing an individual baseline, the error within the measure and what constitutes a meaningful change [9
] is important to effective monitoring enabling practitioners to identify red flags and modify training for each individual [10
]. Furthermore, the utility of subjective and objective assessments in a team sport setting is dependent on the assessment’s ability to provide cost efficient, simple and accessible information on the athlete’s time-course of recovery [11
To date, no study has communicated how subjective and objective assessments respond on a group and individual basis to known high and low external training loads. Therefore, the aim of this study is to compare the sensitivity of selected subjective and objective monitoring assessments in detecting changes in group and individual responses to a low load and high load bout of high intensity intermittent exercise.
The main finding of the present study were that group responses showed selected items of the WQ (motivation, recovery, sleep quality and muscle soreness), HRrest and indices of HRV were sensitive to changes in training load. However, in the current study the CMJ was not sensitive to acute fluctuations in training load. Individual WQ responses revealed 7/9, 7/9, 6/9, 6/9, 5/9, 3/9 and 1/9 participants reported deteriorations in perceptions of recovery, sleep quality, motivation, muscle soreness, fatigue, stress and appetite, respectively following high load compared to low load. Also, 4/6, 2/6 and 1/6 individuals for HRrest, ln SDNN and ln rMSSD, respectively, reported a substantial chance of a negative response after high load compared to low load.
This study indicates that selected WQ items could provide important information on the recovery status of a player given their sensitivity to changes in high load and low load. Moderate to large deteriorations in perceptions of motivation, recovery, sleep quality and muscle soreness were evident following the high load compared to low load. Previously the WQ identified poorer perceptions of well-being in elite youth soccer players in the later seasonal training blocks, potentially due to an accumulation of training load [3
]. In addition, other self-report questionnaires have shown sensitivity to changes in training load across in-season training weeks assessed using three questionnaire items (fatigue, sleep quality and muscles soreness) in elite soccer players [19
]. Furthermore, Gastin, et al. [5
] reported items of wellness (fatigue, muscle strain, hamstring strain, pain/stiffness, power, sleep quality, stress and well-being) improved on a daily basis throughout the week following a high competitive match load and subsequent lower loads throughout the week in Australian rules football players.
These previous studies provide an insight into the ecological validity of the use of self-report questionnaires in team sports. However, other stresses accumulated during these periods in addition to the training load reported such as additional training and non-sport specific stress may have contributed to the proposed dose-response relationship between perceptions of well-being and training load. In the present study, the high load and low load trials were carried out in a controlled low load training week. Therefore, the present study highlights the sensitivity of daily subjective self-report questionnaires to changes in recovery status induced by training load manipulations.
The WQ items fatigue, stress and appetite were not sensitive to the differing high load and low load trials. In contrast, a previous study reported fatigue and stress were sensitive to within training week variation in high load and low load [5
]. One factor influencing these differences could be the magnitude of stress in the present study may have been lower given match simulations may not elicit physiological responses as high as for a competitive fixture [20
]. Conversely, given the relative isolation of high load and low load in the present study, fatigue, stress and appetite may be sensitive to accumulated loads but not high acute loads.
The individual differences presented in this study highlight individual responses to a fixed bout of high intensity intermittent exercise. Participant I had the lowest RPE load and one of the highest estimated
max values. Therefore, the relatively lower internal load could in part explain the lack of any changes in perceptions of well-being in the WQ for participant I. Conversely participants A and F reported poorer perceptions of well-being despite similar
max values. This highlights confounding factors in addition to training load such as relationships and lifestyle [21
] which could influence perceptions of well-being during recovery. Hence, it is important each athlete is assessed on an individual basis.
Subjective measures have been reported to show greater sensitivity to increased acute and chronic training loads in comparison with objective measures [2
]. The present study reported group CMJ performance was not sensitive to changes in training load. However, HRRest
and HRV were sensitive to changes in acute training loads.
CMJ is a simple assessment which could be used as an objective measure of neuromuscular performance prior to training (Twist and Highton 2013). However, the present study suggests that the CMJ measure using a contact mat is not sensitive to high training loads. In contrast, previous studies show decrements in CMJ performance 24 h and 48 h following a competitive fixture (Ascensao et al. 2011; Fatouros et al. 2010; Magalhaes et al. 2010) and a 90 min match simulation (LIST; Bailey et al. 2007; Magalhaes et al. 2010). These differences could reflect difference in the magnitude of the acute load (De Hoyo et al. 2016; Magalhaes et al. 2010). Furthermore, more expensive equipment such as force plates may be required to detect neuromuscular fatigue in a CMJ (Gathercole et al. 2015).
Group analysis of HR indices in the present study suggests HRRest
and HRV measures were sensitive to changes in training load. These measures of the autonomic nervous system have previously been proposed as a marker of NFOR and are reported to be sensitive to acute changes in training load [6
]. Often team sport players are required to perform competitively twice a week [23
]. Therefore, the sensitivity of HR indices to high acute training loads might be a useful tool for coaches and practitioners.
In an applied setting, monitoring must be carried out on an individual level due to the aforementioned individual differences. On an individual level it has been proposed that HR indices are too variable to assess athletes based upon a single measure (Buchheit 2014; Plews et al. 2013). Individual increases in 4/6 participants were evident for HRrest, but only 2/6 and 1/6 participants reported a reduction in ln SDNN and ln rMSSD, respectively. Given the magnitude of the ‘noise’ and the SWC in measures of HR, single infrequent assessments of HR indices may only be sensitive to very large fluctuations in training load. Therefore, frequent daily assessment of HR indices using a rolling average would be required to reduce the ‘noise’ of the measurement which is often not practical in team sport players (Buchheit 2014; Plews et al. 2013).
A limitation to the present study was the small sample size. The study population was a convenience sample recruited from a group of rugby players competing at a select level. A follow-up study with more participants is needed to confirm the findings of the present study.