Exercise-induced muscle damage is a well documented phenomenon particularly resulting from eccentric exercise. When eccentric exercise is unaccustomed or is performed with an increased intensity or duration, the symptoms associated with muscle damage are a common outcome and are particularly associated with participation in athletic activity. Muscle damage results in an immediate and prolonged reduction in muscle function, most notably a reduction in force-generating capacity, which has been quantified in human studies through isometric and dynamic isokinetic testing modalities. Investigations of the torque-angular velocity relationship have failed to reveal a consistent pattern of change, with inconsistent reports of functional change being dependent on the muscle action and/or angular velocity of movement. The consequences of damage on dynamic, multi-joint, sport-specific movements would appear more pertinent with regard to athletic performance, but this aspect of muscle function has been studied less often. Reductions in the ability to generate power output during single-joint movements as well as during cycling and vertical jump movements have been documented. In addition, muscle damage has been observed to increase the physiological demand of endurance exercise and to increase thermal strain during exercise in the heat. The aims of this review are to summarise the functional decrements associated with exercise-induced muscle damage, relate these decrements to theoretical views regarding underlying mechanisms (i.e. sarcomere disruption, impaired excitation-contraction coupling, preferential fibre type damage, and impaired muscle metabolism), and finally to discuss the potential impact of muscle damage on athletic performance.

Exercise-induced muscle damage (EIMD) is characterized by symptoms that present both immediately and for up to 14 days after the initial exercise bout. The main consequence of EIMD for the athlete is the loss of skeletal muscle function and soreness. As such, numerous nutrients and functional foods have been examined for their potential to ameliorate the effects of EIMD and accelerate recovery, which is the purpose of many nutritional strategies for the athlete. However, the trade-off between recovery and adaptation is rarely considered. For example, many nutritional interventions described in this review target oxidative stress and inflammation, both thought to contribute to EIMD but are also crucial for the recovery and adaptation process. This calls into question whether long term administration of supplements and functional foods used to target EIMD is indeed best practice. This rapidly growing area of sports nutrition will benefit from careful consideration of the potential hormetic effect of long term use of nutritional aids that ameliorate muscle damage. This review provides a concise overview of what EIMD is, its causes and consequences and critically evaluates potential nutritional strategies to ameliorate EIMD. We present a pragmatic practical summary that can be adopted by practitioners and direct future research, with the purpose of pushing the field to better consider the fine balance between recovery and adaptation and the potential that nutritional interventions have in modulating this balance.

In this study, we investigated changes in creatine kinase, perceptual and neuromuscular fatigue of professional rugby league players after match-play. Twenty-three male rugby league players (10 backs, 13 forwards) had their creatine kinase, perceptual ratings of fatigue, attitude to training, muscle soreness, and flight time in a countermovement jump measured before and 1 and 2 days after (day 1 and day 2 respectively) league matches. Total playing time, offensive and defensive contacts were also recorded for each player. Creatine kinase was higher both 1 and 2 days after than before matches (P < 0.05) in forwards and backs. Similarly, perceived fatigue and muscle soreness were higher than pre-match on both days 1 and 2 (P < 0.05), but did not differ between groups (P > 0.05). Jump performance was lower on day 1 but not day 2 for both groups (P < 0.05). While total playing time was longer in backs (P < 0.05), relative frequencies for all contacts were greater in forwards (P < 0.05). Contacts for forwards were correlated with all markers of fatigue (P < 0.05), but only flight time was correlated with offensive contacts in backs (P < 0.05). Despite the mechanisms of fatigue being different between forwards and backs, our results highlight the multidimensional nature of fatigue after a rugby league match and that these markers do not differ between positions.

Rugby league is a contact team sport performed at an average intensity similar to that of other team sports (~70–80% VO2max), made up of unsystematic movements of varying type, duration, and frequency. The high number of collisions, repeated eccentric muscle contractions associated with accelerating and decelerating, and prolonged aerobic nature of rugby league matches result in the development of fatigue in the days after exercise. Monitoring the presence and magnitude of this fatigue to maximize performance and training adaptation is an important consideration for applied sports scientists. Several methods have been proposed to measure the magnitude of fatigue in athletes. Perceptual measures (eg, questionnaires) are easy to employ and are sensitive to changes in performance. However, the subjective nature of such measures should be considered. Blood biochemical markers of fatigue may provide a more objective measure of homeostatic disturbances associated with fatigue; however, the cost, level of expertise required, and high degree of variability of many of these measures often preclude them from being used in the applied setting. Accordingly, simple measure of muscle function (eg, jump height) and simulated performance offer the most practical and appropriate method of determining the extent of fatigue experienced by rugby league players. A meaningful change in each measure of fatigue for the monitoring of players can be easily determined, provided that the reliability of the measure is known. Multiplying the coefficient of variation by 0.3, 0.9, and 1.6 can be used to determine a small, moderate, and large change, respectively.