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Physiological and psychological demands during training and competition generate fatigue and reduce an athlete’s sport-specific performance capacity. The magnitude of this decrement depends on several characteristics of the exercise stimulus (eg, type, duration, and intensity), as well as on individual characteristics (eg, fitness, profile, and fatigue resistance). As such, the time required to fully recover is proportional to the level of fatigue, and the consequences of exercise-induced fatigue are manifold. Whatever the purpose of the ensuing exercise session (ie, training or competition), it is crucial to understand the importance of optimizing the period between exercise bouts in order to speed up the regenerative processes and facilitate recovery or set the next stimulus at the optimal time point. This implies having a fairly precise understanding of the fatigue mechanisms that contribute to the performance decrement. Failing to respect an athlete’s recovery needs may lead to an excessive accumulation of fatigue and potentially “nonfunctional overreaching” or to maladaptive training. Although research in this area recently increased, considerations regarding the specific time frames for different physiological mechanisms in relation to exercise-induced fatigue are still missing. Furthermore, recommendations on the timing and dosing of recovery based on these time frames are limited. Therefore, the aim of this article is to describe time courses of recovery in relation to the exercise type and on different physiological levels. This summary supports coaches, athletes, and scientists in their decision-making process by considering the relationship of exercise type, physiology, and recovery.

While the effects of sleep loss on performance have previously been reviewed, the effects of disturbed sleep on recovery after exercise are less reported. Specifically, the interaction between sleep and physiological and psychological recovery in team-sport athletes is not well understood. Accordingly, the aim of the current review was to examine the current evidence on the potential role sleep may play in postexercise recovery, with a tailored focus on professional team-sport athletes. Recent studies show that team-sport athletes are at high risk of poor sleep during and after competition. Although limited published data are available, these athletes also appear particularly susceptible to reductions in both sleep quality and sleep duration after night competition and periods of heavy training. However, studies examining the relationship between sleep and recovery in such situations are lacking. Indeed, further observational sleep studies in team-sport athletes are required to confirm these concerns. Naps, sleep extension, and sleep-hygiene practices appear advantageous to performance; however, future proof-of-concept studies are now required to determine the efficacy of these interventions on postexercise recovery. Moreover, more research is required to understand how sleep interacts with numerous recovery responses in team-sport environments. This is pertinent given the regularity with which these teams encounter challenging scenarios during the course of a season. Therefore, this review examines the factors that compromise sleep during a season and after competition and discusses strategies that may help improve sleep in team-sport athletes.

The Lamberts and Lambert Submaximal Cycle Test (LSCT) is a novel test designed to monitor performance and fatigue/recovery in cyclists. Studies have shown the ability to predict performance; however, there is a lack of studies concerning monitoring of fatigue/recovery. In this study, 23 trained male cyclists (age 29 ± 8 y, VO_2max 59.4 ± 7.4 mL · min⁻¹ · kg⁻¹) completed a training camp. The LSCT was conducted on days 1, 8, and 11. After day 1, an intensive 6-day training period was performed. Between days 8 and 11, a recovery period was realized. The LSCT consists of 3 stages with fixed heart rates of 6 min at 60% and 80% and 3 min at 90% of maximum heart rate. During the stages, power output and rating of perceived exertion (RPE) were determined. Heart-rate recovery was measured after stage 3. Power output almost certainly (standardized mean difference: 1.0) and RPE very likely (1.7) increased from day 1 to day 8 at stage 2. Power output likely (0.4) and RPE almost certainly (2.6) increased at stage 3. From day 8 to day 11, power output possibly (–0.4) and RPE likely (–1.5) decreased at stage 2 and possibly (–0.1) and almost certainly (–1.9) at stage 3. Heart-rate recovery was likely (0.7) accelerated from day 1 to day 8. Changes from day 8 to day 11 were unclear (–0.1). The LSCT can be used for monitoring fatigue and recovery, since parameters were responsive to a fatiguing training and a following recovery period. However, consideration of multiple LSCT variables is required to interpret the results correctly.

Purpose: Despite indications of positive effects of sauna (SAU) interventions, effects on performance recovery are unknown. The aim of the current study was to investigate acute effects of SAU bathing after an intensive training session on recovery of swim performance. Methods: In total, 20 competitive swimmers and triathletes (3 female and 17 male) with a minimum of 2 y of competition experience (national level or higher) participated in the study. Athletes completed an intensive training session followed by either a SAU bathing intervention or a placebo (PLAC) condition in a randomized order. SAU consisted of 3 × 8 min of SAU bathing at 80–85°C, whereas during PLAC, athletes applied a deidentified, pH-balanced massage oil while passively resting in a seated position. Prior to training, swimmers conducted a 4 × 50-m all-out swim test that was repeated on the following morning. Furthermore, subjective ratings of fatigue and recovery were measured. Results: Swimmers performed significantly worse after SAU (4 × 50-m pre–post difference: +1.69 s) than after PLAC (−0.66 s; P = .02), with the most pronounced decrease in the first 50 m (P = .04; +2.7%). Overall performance of 15 athletes deteriorated (+2.6 s). The subjective feeling of stress was significantly higher after SAU than after PLAC (P = .03). Conclusion: Based on published findings, the smallest substantial change in swimming performance is an increase in time of more than 1.2 s; thus, the observed reductions appear relevant for competitive swimmers. According to the current results, coaches and athletes should be careful with postexercise SAU if high-intensity training and/or competitions are scheduled on the following day.

The purpose of this study was to compare the pacing profiles between distance- and duration-based trials of short and long duration. Thirteen trained cyclists completed 2 time-based (6 and 30 min) and 2 distance-based (4 and 20 km) self-paced cycling time trials. Participants were instructed to complete each trial with the highest average power output. Ratings of perceived exertion (RPEs) were measured throughout the trials. Average power output was not different between the 4-km and 6-min trials (324 ± 46 vs 325 ± 45 W; P = .96) or between the 20-km and 30-min trials (271 ± 44 vs 267 ± 38 W; P = .24). Power output was greater on commencement of the distance-based trials when short and long trials were analyzed together. Furthermore, the rate of decline in power output over the 1st 40% of the trial was greater in the 20-km trial than in the 30-min trial (P = .01) but not different between the 4-km and the 6-min trials (P = .13). RPE was greater in the 4-km trial than in the 6-min trial but not different between the 20-km and 30-min trials. These findings indicate that athletes commenced distance-based time trials at relatively higher power outputs than a similar time-based trial. Such findings may result from discrete differences in our ability to judge or predict an exercise endpoint when performing time- and distance-based trials.

Purpose: This study aimed to examine the responsiveness of commonly used measurement instruments to a short training camp by examining the time course of psychophysiological responses in high-level youth soccer players. Methods: Monitoring was carried out in 14 U15 male soccer players of 1 professional youth academy. Players provided data 3 days prior to (D − 3), during (D2−D4), and 1 (D + 1) and 4 days (D + 4) after the camp: 4 items for the Short Recovery and Stress Scale (SRSS), a countermovement jump (CMJ), and a submaximal run to assess exercise heart rate and heart-rate recovery. Training load during the camp followed an alternating low–high pattern, with lower training loads on D1 and D3 and higher training loads on D2 and D4. Results: Changes in SRSS physical performance capability, emotional balance, overall recovery, muscular stress, and overall stress were small to moderate on D3 and moderate to large on D + 1, while changes were trivial on D + 4. Some CMJ parameters related to the eccentric phase were slightly improved on D3, and these parameters were slightly impaired on D4. Changes in CMJ parameters were trivial on D + 1 and D + 4. After a moderate decrease in exercise heart rate on D3, there was a small decrease on D + 4 and a moderate increase in heart-rate recovery. Conclusion: Measurement instruments such as the SRSS and submaximal runs can be used to monitor acute psychophysiological responses to load, while the CMJ may provide little insight during periods of intensified training load.