Impact of Short and Long Daytime Nap Opportunities on Agility, Aerobic, and Anaerobic Performance in Collegiate Badminton Players

Summary

This study investigated the acute effects of two daytime nap opportunities (40 min and 90 min) on agility, anaerobic performance, and aerobic capacity in collegiate badminton players using a crossover repeated-measures design.

Abstract

This study investigated the effects of two daytime nap opportunities (40 min and 90 min) on agility, anaerobic performance, and aerobic capacity in collegiate badminton players. Twenty collegiate badminton players participated in a randomized crossover repeated-measures design, including 10 females (age: 20.9 years ± 1.5 years, height: 167.9 cm ± 4.3 cm, weight: 58.3 kg ± 6.1 kg) and 10 males (age: 21.4 years ± 1.4 years, height: 179.7 cm ± 2.8 cm, weight: 73.0 kg ± 3.4 kg). Three experimental conditions were included: no nap (N0), a 40 min nap opportunity (N40), and a 90 min nap opportunity (N90), with a 72 h washout period between sessions. Following each condition, participants completed tests of agility (Y-test), anaerobic capacity (300 yard Shuttle), and aerobic capacity (Yo-Yo Intermittent Recovery Test). Significant main effects of nap condition were observed for all performance outcomes (p < 0.001). Compared with N0, both N40 and N90 improved agility and anaerobic performance. While both nap durations significantly improved physical performance compared with the no-nap condition, the improvements observed in N90 compared to N40 were statistically significant but characterized by small effect sizes (d = 0.12–0.16). This suggests that while a 90 min nap may offer additional benefits, the incremental gain over a 40 min nap is modest for specific performance outcomes.

Introduction

Badminton, as a high-intensity and fast-paced competitive sport, requires athletes to possess agility, quick reaction capabilities, and cognitive decision-making skills¹. Meanwhile, badminton players also need to possess strong anaerobic and aerobic capacities². Therefore, after badminton players complete a high-intensity training session or match, adequate, high-quality sleep is regarded as a crucial factor in the recovery of physical function. Previous studies have reported that sleep deprivation or poor sleep quality may increase fatigue levels, impair reaction time, and reduce physical performance across a variety of sports. For example, previous research has reported impairments in reaction time among badminton players following mental exertion tasks designed to simulate the effects of insufficient sleep³. Additionally, when athletes experience sleep deprivation, their recovery capacity and athletic performance may both be compromised, leading to decreased anaerobic power, diminished endurance and strength, as well as impaired high-intensity interval training performance⁴.

Collegiate badminton players often follow a demanding schedule with morning and afternoon sessions. This second training bout frequently coincides with the 'post-lunch dip'—a transient period of reduced alertness and neuromuscular efficiency occurring between 13:00 and 16:00 due to circadian rhythms. This physiological trough can compromise technical execution and increase injury risk, making effective midday recovery strategies essential for this population⁵. However, the extent of this performance decline is related to sleep deprivation from the previous night and overall fatigue levels. Nonetheless, in the absence of morning matches, badminton competitions in the afternoon sessions usually start during the aforementioned time slots. While traditional recovery modalities such as active cool-downs, cryotherapy, and nutritional interventions (e.g., hydration and protein synthesis) are effective in accelerating metabolic clearance and muscular repair, they often overlook the restoration of the central nervous system (CNS). In contrast, napping offers unique neurobiological benefits by downregulating the sympathetic nervous system and facilitating neuroendocrine homeostasis, which are beyond the scope of purely physical recovery methods⁶. Therefore, taking a nap during the day can be an effective strategy for badminton players, as it can enhance recovery and reduce the negative effects of sleep deprivation⁷. However, research specifically examining the relationship between daytime napping and athletic performance in racket sports, such as badminton, remains sparse. Badminton demands a unique integration of reactive agility, repeated anaerobic power, and intermittent aerobic endurance. While previous studies have shown that a 30 min nap can improve sprint performance and both 20 min and 90 min naps can enhance repeated sprint ability^8,9, the dose-response relationship of napping on the multi-dimensional physical requirements of badminton players is not well understood. Furthermore, while durations of 25–45 min have been shown to reduce sleep pressure and fatigue^10,11, and naps exceeding 30 min are generally linked to improved endurance and explosive power, a clear physiological rationale for choosing specific durations in a high-performance context is often lacking.

In this study, 40 min and 90 min nap opportunities were selected based on the architecture of human sleep cycles rather than arbitrary previous benchmarks. A 40 min opportunity was designed to ensure participants received a significant dose of Slow-Wave Sleep (SWS), which is essential for physical recovery and hormonal regulation, while accounting for initial sleep latency. In contrast, a 90 min opportunity was chosen to facilitate a complete sleep cycle, encompassing both SWS and Rapid Eye Movement (REM) sleep. Theoretically, Slow-Wave Sleep (SWS), or deep sleep, is critical for physical recovery in badminton players as it stimulates the secretion of growth hormones necessary for tissue repair and glycogen sparing, thereby sustaining endurance during prolonged matches. Conversely, Rapid Eye Movement (REM) sleep facilitates memory consolidation and neural plasticity, which are paramount for the high-level cognitive demands of badminton, including anticipatory agility, rapid decision-making, and tactical thinking^12,13. However, practical implementation of napping requires a strategic approach to balance recovery and performance. A short nap (40 min) is often prioritized for acute alertness and cognitive sharpening while minimizing 'sleep inertia', the grogginess experienced upon waking, making it ideal for tight tournament schedules. In contrast, a full sleep cycle (90 min) allows for a complete transition through SWS and REM stages, providing more profound physiological recovery, though it necessitates a longer buffer period before competition⁸. Understanding these constraints is vital for coaches to integrate napping into varying training loads and competition windows. Therefore, this study aims to compare the effects of no nap (N0), a 40 min nap (N40), and a 90 min nap (N90) on the agility, anaerobic capacity, and aerobic capacity of collegiate badminton players with normal sleep. It was hypothesized that both nap opportunities would enhance performance compared to N0. Furthermore, the hypothesis is that a 90 min nap would yield superior benefits by achieving a full sleep cycle and the subsequent cognitive-restorative effects of REM sleep.

Protocol

The study involving human participants was approved by the Ethics Committee of Wuhan Sports University (approval number: 2023070). Participants were recruited between August 2023 and January 2024. All participants provided written informed consent prior to participation, in accordance with institutional and national ethical standards.

1. Participants

Sample size was calculated using G*Power software (version 3.1). For a repeated‑measures ANOVA within a crossover design, the test family was set to F‑tests, and the statistical model to ANOVA: repeated measures, within factors. Input parameters were: α = 0.05, power (1‑β) = 0.80, number of groups = 1, number of measurements = 3, and an assumed correlation among repeated measures of 0.5 (representing a moderate within‑subject correlation). The effect size was based on Cohen’s d = 0.54, derived from previous research on napping and physical performance. The minimum sample size for this study was determined to be 12 participants to maintain minimal correlation between repeated measures⁷. Considering the potential loss of samples during the experiment, the final sample included 20 collegiate badminton players, involving 10 females (age: 20.9 years ± 1.5 years, height: 167.9 cm ± 4.3 cm, weight: 58.3 kg ± 6.1 kg) and 10 males (age: 21.4 years ± 1.4 years, height: 179.7 cm ± 2.8 cm, weight: 73.0 kg ± 3.4 kg). All participants had at least 5 years of systematic badminton training experience and were actively trained as members of university badminton teams. On average, participants trained approximately five to six sessions per week, with each session lasting about 2–3 h. All participants passed the preliminary screening, which was conducted using the Pittsburgh Sleep Quality Index questionnaire (PSQI), indicating good sleep quality for selection as subjects (PSQI < 5). Additionally, all subjects had no history of injury, sleep disorders, or smoking. After being informed of the testing procedures and potential risks, they voluntarily participated in the study and signed an informed consent form. Participants were recruited between August 2023 and January 2024.

2. Experimental design

The study used a crossover repeated-measures design consisting of three test sessions, as illustrated in Figure 1. Participants were assigned to one of the six possible condition sequences (N0-N40-N90, N40-N90-N0), a computer-generated random sequence to minimize potential order effects. A 72 h interval between trials was used as a washout period to prevent carryover effects. This washout duration was chosen based on previous nap intervention studies that have used 72 h intervals to minimize carryover effects between conditions⁷. Due to the nature of the nap intervention, participants were aware of their assigned condition (no nap, 40 min, or 90 min nap opportunity). A sham or equivalent control was not possible, making the study inherently unblinded. Prior to the tests, participants were required to familiarize themselves with the experimental procedures, which included the laboratory environment, questionnaire completion, and methods for assessing exercise performance. Under the N40 condition, participants entered a comfortable, warm, completely dark, and quiet sleep room at 12:50. After 10 min of bed preparation, the nap commenced at 13:00 and lasted for 40 min¹⁰. To ensure the reproducibility of the nap conditions, the sleep environment was strictly controlled: ambient temperature was maintained at 22 °C via a central climate control system, and light levels were kept below 5 lux (measured by a digital illuminance meter, model HS1010), achieving near-total darkness. Researchers monitored the participants via a low-light infrared camera system from an adjacent room to maintain a "non-intrusive" supervision protocol. Checkpoints for successful nap onset included: (1) no limb movement for > 5 consecutive minutes on actigraphy; (2) observed muscle relaxation (e.g., jaw release); and (3) the transition to rhythmic, slowed diaphragmatic breathing. If a participant failed to show these signs within the first 20 min of the opportunity, the session was flagged, though they were still required to remain in bed to maintain the "opportunity" protocol¹⁴. Although polysomnography was not used, sleep behavior was monitored by research staff, and participants were required to remain in bed throughout the nap opportunity. Upon awakening, participants underwent a recovery period from sleep inertia, maintaining at least 1 h of recovery time. During this period, participants could choose activities such as reading or watching videos to remain awake until the tests began at 15:30. The N90 condition followed an identical experimental procedure to that of N40, with the wake-up time set at 14:30. Subjects were also given a 1 h recovery period from sleep inertia, resulting in the testing time being scheduled for 15:30, which is to overcome any sleep inertia that may occur after a nap¹¹. The final test was conducted under the no-nap condition, during which subjects were required to engage in activities such as reading, watching videos, or playing games until they entered the testing site at 15:30. Although sleep was not objectively measured during the nap, upon waking, participants were asked to rate their subjective sleep quality on a study‑specific 0–10 scale, where 0 indicated “no sleep,” 5 indicated “some sleep but interrupted,” and 10 indicated “deep and uninterrupted sleep throughout (Table 1)⁸. However, these ratings served as a procedural check to ensure all participants reached a restorative state prior to testing. Subsequently, all participants performed a standardized 10 min warm-up exercise before commencing the exercise tests¹⁵.

On the day of the experiment, participants were instructed to maintain their normal dietary and sleep habits the night before testing and to avoid consuming caffeinated beverages or other stimulants. Because this was an acute experiment, all exercise tests were conducted at the same time (3:30 pm) to minimize disruption to the circadian rhythm¹³. After a 15 min standardized warm-up, the subjects first underwent an agility test (Y-test), and then, 10 min later, they underwent an anaerobic capacity test (300 yard Shuttle), and after a 20 min recovery period, they completed an aerobic capacity test (Yo-Yo Intermittent Recovery Test). Each session commenced with a 15 min standardized warm-up adhering to the RAMP protocol (Raise, Activate, Mobilize, Potentiate) to ensure physiological readiness and inter-trial consistency¹⁶. The protocol was structured as follows: Raise (5 min): Participants performed low-intensity jogging at a self-selected pace, targeting a Heart Rate (HR) of 50%–60% of their age-predicted maximum to increase core temperature. Activate and Mobilize (5 min): A dynamic stretching circuit was executed, comprising 10 repetitions of each exercise: controlled leg swings (anterior-posterior and lateral), walking lunges with thoracic rotation, dynamic calf stretches, and arm circles, targeting the major muscle groups involved in badminton movements. Potentiate (5 min): Participants engaged in badminton-specific agility drills, including shadow footwork at increasing intensities (70%, 85%, and 100% of perceived maximal effort) and three sub-maximal 10 m sprints. To minimize inter-subject variability, all warm-up phases were led by a certified strength and conditioning coach and conducted under the same environmental conditions (24 °C). This rigorous standardization was implemented to control the "warm-up effect" which could otherwise confound the influence of sleep on physical performance. Meanwhile the tests were conducted strictly according to the standard testing procedures of the National Strength and Conditioning Association of the United States: (1) non-fatigue test (2), agility test, (3) maximum explosive power and strength test, (4) sprint test, (5) muscle endurance test, (6) anaerobic capacity test, (7) aerobic capacity test. This order reflects a progression from non‑fatiguing to more fatiguing assessments, but it also means that the aerobic test was always performed under the highest accumulated fatigue. This potential influence should be considered when interpreting improvements in aerobic capacity associated with naps. At the same time, the interval time between tests was required to be 5 min to ensure phosphagen recovery. Therefore, in this experiment, to ensure the athletes fully recovered, 10 min and 20 min recovery periods were adopted (Figure 2).

3. The Actigraph analysis

The night before each experimental test, subjects wore a GT3X activity monitor on their non‑dominant arm to record sleep patterns and ensure adherence to a consistent sleep‑wake schedule. Subjects were instructed to fall asleep between 22:30 and 23:00 and wake up the following morning between 7:30 and 8:15¹⁵. Sleep and wake behaviors were analyzed using ActiLife 6 software. The device was set to a sampling frequency of 30 Hz, and activity counts were integrated over 60 s epochs¹³. Settings included a sampling rate of 30 Hz with the "Low Frequency Extension" disabled to avoid noise from non-ambulatory movements. Prior to each use, devices were fully charged and time-synced with the laboratory’s master atomic clock. To confirm data validity, a post-collection checkpoint was applied: a trial was deemed valid only if the wear-time exceeded 90% of the prescribed sleep window, cross-referenced with the event markers manually pressed by the participants upon "lights out" and "final awakening"¹⁷. The Sadeh algorithm was applied to estimate sleep parameters due to its validated accuracy against polysomnography¹⁸. Differences between time in bed, time asleep, and time awake were cross‑validated using a sleep diary¹⁴. Derived sleep parameters included bedtime, wake time, sleep latency, sleep efficiency, total sleep time, and total time in bed.

4. Agility test

1. Y-test
   The Y-test is a reactive agility assessment, as illustrated in Figure 3. Subjects begin 0.5 m behind the Swift timing gate, which serves as the starting position. Upon hearing the "go" command, the subject passes through the timing gate, sequentially triggering the device. Upon reaching the marked cone, infrared devices on both sides randomly illuminate and emit sound from one side. The subject must react swiftly and sprint to the end of the indicated side to complete a Y-test. This test involves a 5 m sprint, a 45-degree change of direction (either left or right), followed by another 5 m sprint at maximum speed. The direction change is determined randomly by a trigger at the 2.5 m mark, which activates a timing gate. When the subject passes this trigger, one of the timing gates on the left or right will randomly illuminate. The subject must then react quickly and sprint through the illuminated gate as fast as possible.
   1. Equipment setup
      Three Swift Performance dual-beam infrared timing gates were used. The start gate and the two finish gates were positioned at 0.8 m above the ground to ensure the trunk, rather than an arm or leg, triggered the sensor ¹⁹.
   2. Calibration
      Before each testing session, gates were aligned using a laser leveling tool and tested with three "dummy" sprints to ensure triggering consistency within ±0.01 s. Trigger Mechanism: The central "decision" gate (at 2.5 m) was programmed with a random-logic algorithm. As the participant’s torso broke the beam, a 200 ms delay was followed by the activation of either the left or right LED beacon.
   3. Validity checkpoint
      A trial was discarded and repeated if the participant: (1) anticipated the direction by leaning before the light triggered; (2) touched a boundary cone; or (3) failed to pass through the center of the timing gates. A 3 min rest was provided after any invalidated trial to prevent fatigue accumulation. Each subject is required to perform three tests, with a 30 s interval between each attempt. During this interval, the subject returns to the starting position by either running or walking slowly, then proceeds to the next round of testing. The optimal sprint time for each test is selected as the basis for analysis.

5. Anaerobic capacity test

1. 300 yard Shuttle
   The 300 yard Shuttle assesses both maximal and sub-maximal anaerobic running, as illustrated in Figure 4. Two athletes commence the test simultaneously; upon hearing the audible signal, each athlete sprints to the opposite side of the field, ensuring their feet touch the 25-yard line before immediately sprinting back to touch the starting line. This process is repeated a total of six times, executed as quickly as possible without any pauses in between. Upon completion of the test, two recorders document the subject's time to the nearest 0.1 s²⁰.

6. Aerobic capacity test

1. Yo-Yo intermittent recovery test
   All subjects performed the Yo-Yo Intermittent Recovery Test to assess endurance capacity through badminton-specific tasks, as illustrated in Figure 5. This test consisted of a 2 m x 20 m round-trip run interspersed with 10 s of recovery time. The Yo-Yo Intermittent Recovery Test commenced at 10 km/h and was regulated by 2–3 audio signals from a 20 min CD player operating at an incremental speed. Upon hearing the first audio signal, the athlete began running towards the folding line. When the second audio signal was heard, the athlete was required to reach the folding line and then immediately run back to the starting line, ensuring arrival before the next audio signal. After reaching the starting line, the athlete jogged to the 5 m mark and then returned to the starting line, pausing to await the next sound signal. A warning was issued for the first failure to reach either the turn-back or starting line within the allotted time. If the subject failed to reach the finish line in time a second time, the test was terminated, and the final level, along with the number of 2 m x 20 m intervals completed at that level, were recorded²¹.

7. Statistical analysis

All statistical analyses were performed using SPSS 27.0 software. The normality of the data was assessed using the Shapiro-Wilk test, and all data are presented as mean ± standard deviation. For the primary analysis, a one-way repeated-measures ANOVA was used to examine the effects of nap duration. Prior to running the ANOVA, Mauchly’s test of sphericity was conducted to verify the assumption of sphericity; in cases where this assumption was violated, the Greenhouse‑Geisser correction was applied, and the corrected degrees of freedom are reported along with F-values and exact P-values. When a significant main effect was observed, Bonferroni post-hoc tests were performed for pairwise comparisons. To accurately represent the magnitude of these differences in crossover design, effect sizes for pairwise comparisons were calculated as Cohen’s d (the difference between the means divided by the average standard deviation of the two conditions). This approach accounts for the correlation between repeated measures and provides a more robust estimate of effect size¹⁸. The resultant d values were interpreted as: < 0.2 (trivial), 0.2–0.5 (small), 0.5–0.8 (moderate), and ≥ 0.8 (large). All statistical analyses were conducted using two-sided hypothesis tests with α = 0.05.

Results

Sleep parameters
Sleep parameters (bedtime, wake time, sleep latency, sleep efficiency, total bedtime, and total sleep time) were similar to those of the night before each study condition. The results from a one-way ANOVA indicated no significant differences in the sleep variables and no evidence of sleep deprivation, as demonstrated in the findings (Table 1).

In this study, we evaluate the effects of different nap durations (N0, N40, N90) on athletes' per...

Discussion

This study evaluated the effects of different nap durations (N0, N40, and N90) on the agility, anaerobic capacity, and aerobic capacity of badminton players. All participants exhibited no significant differences in sleep variables (including total sleep time, sleep latency, sleep efficiency, and total time in bed) prior to the tests, and none experienced sleep deprivation before any test. The results indicated that, compared to no nap (N0), both a 40 min nap (N40) and a 90 min nap (N90) significantly enhanced test perfor...

Materials

List of materials used in this article

Name	Company	Catalog Number	Comments
ActiGraph GT3X+ Triaxial Accelerometer	ActiGraph LLC	GT3X+	Used for objective monitoring of sleep-wake patterns and physical activity. Location: Pensacola, FL, USA
ActiLife Software	ActiGraph LLC	N/A	Version 6.13.3 (or higher); used for data initialization, downloading, and scoring (Sadeh algorithm). Location: Pensacola, FL, USA
G*Power Software	Heinrich Heine University Düsseldorf	Version 3.1.9.7	Open-source software used for a priori power analysis and sample size estimation. Location: Düsseldorf, Germany
Wrist Band for ActiGraph	ActiGraph LLC	500-0013	Standard black nylon strap used for non-dominant wrist attachment. Location: Pensacola, FL, USA