Impact on Competitive Performance and Assessment of Fatigue and Stress Based on Heart Rate Variability

Abstract

Background: Optimizing training load and recovery is crucial for achieving peak performance in competitive wrestling, a sport characterized by high physical, technical, and psychological demands. Methods: This study compared the effects of two different training programs—one emphasizing high-intensity interval training (HIIT) sessions and the other based on traditional volume-oriented training—on both competitive performance and autonomic regulation measured by heart rate variability (HRV). A total of 24 elite wrestlers were divided into two equal groups, each following a different weekly training regimen over a 3-month period. HRV was recorded using a wearable 3-channel ECG Holter before training, immediately after training, and during recovery phases (up to 2 h post-exercise). HRV parameters were analyzed to assess training-induced stress and recovery status. Competitive performance was evaluated using official national championship scores and ranking positions. Results: Both training programs improved competitive performance, the HIIT-based regimen induced greater short-term suppression of parasympathetic activity (RMSSD: −32% vs. −14%; HF power: −40% vs. −18%) and increased sympathetic dominance (LF/HF: +56% vs. +22%) after training. Wrestlers in the HIIT group achieved a mean competition score of 17.92 ± 4.50 points, compared to 15.08 ± 6.26 points in the volume-oriented group. These acute autonomic shifts may provide a higher readiness for intense and explosive actions, which is advantageous in short and dynamic matches. In contrast, the volume-oriented program induced smaller acute autonomic changes but showed a slower recovery to baseline. Conclusions: These findings suggest that HRV-derived measures can serve as sensitive indicators of training load tolerance, recovery capacity, and stress susceptibility in combat sports athletes. This study highlights the value of integrating HRV monitoring into the periodization of combat training to individualize the load, prevent overtraining, and optimize performance outcomes.

1. Introduction

Wrestling is one of the oldest and most complex sports, requiring a high degree of physical strength, endurance, explosiveness, technical mastery, and psychological resilience [1]. Competitive matches are characterized by short but extremely intense episodes of exertion interspersed with brief pauses, which place substantial demands on anaerobic capacity, muscular strength, and rapid recovery ability [2,3]. Effective management of training load and recovery is crucial for maintaining peak performance and preventing overtraining in athletes [4]. Previous studies have shown that even in elite athletes, such as Paralympic judokas, training cycles induce pronounced changes in performance and competitive readiness [5]. This highlights the necessity of systematically monitoring physiological markers under different training regimes.

In this context, heart rate variability (HRV) has emerged as a valuable non-invasive biomarker for assessing the autonomic balance between the sympathetic and parasympathetic branches of the nervous system [6,7].

Despite the growing body of evidence on HRV applications in various sports, direct comparative data on different training paradigms (HIIT vs. volume-oriented programs) in elite wrestlers remain scarce. This gap highlights the novelty and necessity of the present study, which specifically addresses how these training modalities affect autonomic regulation and recovery dynamics in this population.

Dong [8] emphasizes HRV as an indicator of autonomic regulation, reflecting the balance between sympathetic and parasympathetic activity, and highlights its usefulness for monitoring adaptation to training stress and optimizing the training process. Reductions in HRV have been associated with fatigue accumulation, diminished adaptation to exercise, and increased risk of overtraining [9]. Conversely, the restoration of HRV to baseline levels after training is considered an indicator of adequate recovery and readiness for subsequent loads [10]. Given the high demands of wrestling on explosive strength and short-term maximal endurance, HRV may represent a particularly useful tool for monitoring sport-specific adaptations in this discipline.

In wrestlers, Tian et al. [11] used HRV to detect early signs of non-functional overreaching. The authors established HRV thresholds that allow for timely differentiation between functional and non-functional overload (e.g., rMSSD of about 82.76 ms (CI 77.75–87.78) for “normal adaptation” but 45.97 ms (CI 30.79–61.14) for adverse response, which allow for timely differentiation between functional and non-functional overload). These results highlight the importance of HRV as a tool for monitoring training load and recovery in wrestlers. Similarly, a study with adolescent judokas [12] employing a dynamic tilt-test indicated that HRV adequately reflects adaptation to increased training load. Specifically, judokas showed higher values of RMSSD (49.3 ± 16.2 ms vs. 38.7 ± 14.5 ms in swimmers) and pNN50 (23.4 ± 11.8% vs. 16.1 ± 9.7%), reflecting more efficient parasympathetic adaptation.

Extending beyond combat sports, Santos-García et al. [13] applied HRV monitoring in elite female soccer players. Their analysis revealed very strong positive correlations between rMSSD (4 h) and RHR (4 h), as well as strong positive correlations between short-term HRV indices (e.g., rMSSD 5 min vs. RHR (resting heart rate) 5 min; SDNN vs. RHR 5 min; rMSSD 5 min vs. SDNN).

In an Olympic context, Coyne et al. [14] reported that HRV served as a sensitive tool for monitoring training load and recovery in an elite long jumper before and during the Rio 2016 Olympic Games. Decreases in HRV reflected elevated stress and the need for recovery.

Korobeynikov et al. [15] investigated HRV differences in elite wrestlers, demonstrating that those with higher stress resilience exhibited higher HRV values and stronger parasympathetic tone.

A recent study [16] investigated the dynamics of HRV (RMSSD, LF/HF, and others) in Greco-Roman wrestlers after a training break and resumption of practice, highlighting its relationship with physical condition and a specific wrestling fitness test (SWFT). Recovery through an 8-week re-training period shows that athletes manage to regain some of the lost performance, but do not fully reach the baseline levels observed before the break. This highlights that prolonged breaks lead to significant physiological and functional regressions that cannot be fully compensated even with intensive re-training. This evidence reinforces the role of HRV as a sensitive biomarker of training adaptation and recovery status.

The literature review further indicates that training modality can exert markedly different effects on autonomic regulation. High-intensity interval training (HIIT) often provokes more pronounced acute HRV changes, typically characterized by elevated sympathetic activation and temporary suppression of parasympathetic tone [17]. Schneider et al. [18] compared the effects of strength training (ST) and HIIT during an overload microcycle, reporting that HIIT induced stronger and faster HRV alterations, whereas ST led to more moderate, gradual adaptations. Consistent with this, Stöggl & Björklund [19] showed that HIIT facilitated faster heart rate recovery (HRR) compared to traditional high-volume, low-intensity training programs. Although not a direct comparison between HIIT and volume programs, a six-week multicomponent training block in wrestlers [20] demonstrated improvements in SWFT performance, underlining the impact of training structure on competitive readiness.

In the specific context of wrestling, where matches are brief yet extremely intense, the fine-tuning of training loads and recovery periods is crucial for achieving peak explosiveness and endurance at decisive moments. Plews et al. [21] emphasized that HRV-based monitoring enables individualized training adjustments and optimizes athletic performance. Accordingly, in wrestling—where athletes are simultaneously exposed to strength, speed, and technical demands—systematic HRV monitoring may enhance adaptation and support optimal form before competition.

Volume-oriented programs, by their nature, may be expected to promote more gradual and stable autonomic adaptations. However, they also carry a higher risk of accumulated fatigue if applied over extended periods without adequate recovery strategies. Despite the considerable body of research, comparative data examining the effects of distinct training paradigms on both HRV dynamics and actual competitive outcomes in elite wrestlers remain scarce.

Therefore, the integration of HRV monitoring into the training process of wrestlers may provide valuable feedback on autonomic regulation, assist in precise load management, and mitigate the risk of overtraining. Based on these considerations, the present study aims to compare the effects of HIIT and volume-oriented training programs on both competitive performance and HRV dynamics in elite wrestlers.

Despite the growing interest in the applications of HRV in various sports, comparative data on different training paradigms in elite wrestlers remain scarce, especially regarding how high-intensity interval training (HIIT) and traditional volume-oriented programs differentially affect autonomic regulation and competitive readiness. To fill this gap, the present study aimed to compare the effects of HIIT and volume training on: (1) competitive performance, as assessed by official results and rankings from national championships; (2) dynamics of autonomic regulation, as assessed by HRV indices at three time points (pre-training, immediately post-training, and 2 h post-training); (3) acute and short-term adaptations in sympathetic and parasympathetic activity in response to the two training regimens; and (4) the relationship between HRV parameters and competitive performance, with the aim of assessing the potential of HRV as a tool for individualized training planning and prevention of overtraining.

2. Materials and Methods

2.1. Participants

Twenty-four Bulgarian elite male freestyle wrestlers (male: 100%; age: 22.4 ± 2.3 years; body mass: 78.6 ± 6.8 kg; height: 176.5 ± 5.9 cm) competing in regional tournaments and national competitions, voluntarily participated in this study.

Inclusion criteria: The study included athletes over 18 years of age with at least 8 years of competitive experience. Participants had to be clinically healthy, with no history of cardiovascular disease or current trauma at the time of recruitment. An additional inclusion criterion was active participation in national level competitions. All participants were instructed to avoid alcohol, caffeine and smoking during the study period of the training sessions.

Exclusion criteria: Athletes who did not attend the training process regularly, therefore it was not possible to perform systematic Holter recordings within the three-month period, were excluded. Additionally, individuals with acute infections or chronic diseases (e.g., endocrine), as well as those taking medications that affect cardiovascular regulation (e.g., beta-blockers, antiarrhythmics, psychostimulants) were excluded from participation.

Initially, 63 athletes were invited to participate in the study (a total of over 100 athletes train in wrestling clubs in the city of Veliko Tarnovo (Bulgaria), but a large part of them are under 18 years of age and do not meet the inclusion criteria). Of these, 42 agreed to participate and sign an informed consent protocol. Subsequently, 18 of them were excluded according to the exclusion criteria: 11 due to irregular attendance at training (and accordingly, without all Holter recordings being performed), 4 due to emerging illnesses and 3 due to injury. The final sample included 24 athletes (12 in each group). All wrestlers had at least 8 years of competitive experience and they compete in national wrestling competitions. All wrestlers were healthy, free of cardiovascular disease, and free of injuries at the time of recruitment. Participants are from Bulgarian club teams and were randomly assigned into two equal groups (n = 12 each): a High Intensity Interval Training (HIIT) Group and a volume-oriented training group (Volume Group) (according to the method of general physical training preceding the actual wrestling training). The two groups had similar levels of training stress, which is predetermined by the type of exercises included in the two study groups.

The athletes in the study were recommended to get 7–8 h of sleep, and were reminded of this episodically. No additional data were collected about the athletes’ lives and habits outside the training hall. The athletes did not perform any other training except those in the gym.

All participants provided written informed consent prior to inclusion, and the study was conducted in accordance with the Declaration of Helsinki and approved by the Ethics Committee of Institute of Robotics—BAS (protocol approval code: 9/11 February 2025).

2.2. Study Design

A 3-month longitudinal training intervention was implemented during the competitive season. Both groups maintained the same total weekly training time (~10 h/week), but differed in intensity distribution. The study was a randomized controlled trial (RCT) with two parallel groups (HIIT and volume training), with participants randomized via a computer-generated list. To minimize potential imbalance between groups, stratified randomization was applied according to competition category (67, 72 and 77 kg) and years of competitive experience (>8 years for all participants). Within each stratum, wrestlers were assigned to the HIIT or volume group in a 1:1 ratio using block randomization (block size = 4). This procedure ensured comparable distribution of body mass and training experience between groups.

The study used blinding of assessors to minimize the risk of bias in data collection and analysis.

Training Protocols

• Warm-up and Mobility (10–15 min)

Both groups performed a standardized warm-up phase aimed at preparing the body for the subsequent workload and preventing injuries. The warm-up included light jogging to elevate heart rate and activate the cardiorespiratory system, rope jumping for coordination and endurance, as well as dynamic stretching and mobility drills targeting the major joints (shoulders, hips, knees, and ankles). This stage ensured a gradual transition to working intensity, increased muscle temperature, and improved tendon and muscle elasticity.

2.

High-Intensity Interval Training (HIIT Group)

Following the general warm-up, athletes engaged in circuit training on the wrestling mat, incorporating obstacle runs and exercises with training equipment. Participants performed 3 to 5 rounds with near-maximal effort, corresponding to approximately 80–90% of their individual maximal heart rate (%HRmax), as continuously monitored with a Holter device. During the intervals, heart rate frequently approached or exceeded the estimated HRmax (~196 bpm for this age group), while the short 20 s pauses allowed only minimal recovery (HR typically decreased by less than 10–15 bpm). During the HIIT sessions, the interval blocks consisted of high-intensity circuit exercises performed on the wrestling mat. These included short sprints with changes in direction and obstacle courses, bodyweight exercises (push-ups, squat jumps), resistance exercises with training equipment (medicine ball throws, rope waves), and partner wrestling exercises emphasizing explosive grappling and takedowns. Each round lasted approximately 11–12 min, punctuated by short 20 s rest periods that allowed for minimal recovery. The participants’ heart rates were objectively tracked via a Holter monitor during the intense training sessions, which allowed for reliable measurement of workload and recovery between rounds.

The general physical preparation, including warm-up and HIIT circuits, lasted about 60 min. The main training block consisted of 60 min of wrestling practice on the mat, designed to simulate competitive conditions under increased physiological stress following the high-intensity load. This was followed by technical and tactical training (30–40 min), including:

• execution of holds, throws, and counterattacks,
• partner-based drills with emphasis on precision,
• tactical games and scenarios simulating competition.

Finally, sparring and competitive simulations (15–20 min) were performed, involving controlled sparring sessions, mock competitive bouts at varying intensity levels, and subsequent analysis and correction of tactical decisions.

3.

Traditional Volume Training (Volume Group)

After the standardized warm-up, the Volume Group protocol included prolonged, moderate-intensity exercises:

• 20 min of steady-state running,
• 10 min of bodyweight exercises (push-ups, sit-ups, pull-ups),
• 10 min of coordination drills (e.g., cone jumps),
• 20 min of resistance training (squats, deadlifts, presses).

In the Volume group protocol, exercise intensity was standardized as follows: running was performed at ~60–70% of maximum heart rate, bodyweight exercises were performed at a fixed number of repetitions (up to 3 sets of 15 push-ups; 3 sets of 30 sit-ups; 3 sets of 15 pull-ups), coordination tasks were performed at low to moderate intensity, and strength exercises were performed at 60–70% of 1 RM, consistent with traditional volume training programs.

The main part consisted of 60 min of wrestling on the mat, with emphasis on specific techniques (e.g., suplex). This protocol maintained heart rate at approximately 170–180 bpm, aiming to build a stable aerobic base, muscular endurance, and technical skills through higher training volume.

4.

Cool-down and Recovery (10 min, both groups)

Each training session concluded with stretching and recovery exercises to enhance flexibility and accelerate regeneration. These included static stretching, breathing techniques, and relaxation drills.

Both training regimens were adapted to the age and physical condition of the elite wrestlers and were conducted under the supervision of qualified coaches. Additionally, psychological preparation, tactical thinking, and competition strategies were emphasized throughout the training cycle.

The participants’ intrinsic training load was assessed using TRIMP (Training Impulse), which combines exercise duration and heart rate as a quantitative measure of training stimulus. The average HR during each session and the duration of the exercise were used to calculate TRIMP. If necessary, intervals, number of repetitions or rest periods were adjusted to achieve approximately equivalent TRIMP between the HIIT and volume groups, ensuring comparability of the intrinsic load despite the different structure and rhythm of the training protocols.

Psychological preparation and tactical thinking were standardized for both groups. Both groups participated in identical goal-setting, visualization, and strategy discussion sessions conducted by the same coaches. This ensured that any differences in performance between the groups were due to the type of physical training and not to variations in psychological or tactical support.

2.3. HRV Measurement Protocol

HRV was recorded using a wearable 3-channel ECG Holter system (device model TLC9803 (CONTEC Medical Systems (Qinhuangdao, China)) with a sampling rate of 10,000 Hz. Measurements were performed in a quiet, temperature-controlled environment (~22 °C) in a room at three time points:

• Pre-training baseline (before warm-up),
• Immediately post-training (within 10 min of session completion),
• Recovery phase (2 h post-exercise, seated rest).

Each recording lasted 10 min in a seated position. HRV analysis was performed from the 3rd to the 7th min inclusive of the recording. The use of 5 min recordings for HRV analysis is in accordance with international standards [22]. To avoid transient artifacts, a ~2 min stabilization period was provided.

R–R intervals were exported and analyzed with Python (v3.11) software procedures created by the authors.

The following HRV parameters were computed (

Table 1. Description of HRV parameters used in the study [7].

Parameter	Units	Physiological Meaning
RMSSD	ms	Short-term variability, parasympathetic control
SDNN	ms	Overall variability, reflecting all time scales
LF power	ms2	Mixed sympathetic–parasympathetic control, baroreflex activity
HF power	ms2	Parasympathetic control, respiratory sinus arrhythmia
LF/HF ratio	–	Sympathovagal balance

):

For Time-domain, the following parameters are defined:

• RMSSD (Root Mean Square of Successive Differences)—An indicator of short-term heart rate variability, mainly related to parasympathetic activity. A higher RMSSD corresponds to stronger vagal (parasympathetic) control.
• SDNN (Standard Deviation of NN intervals)—Standard deviation of all normal R–R intervals (NN = normal-to-normal, without artifacts and extrasystoles). The parameter shows the total heart rate variability, including long-term and short-term components.

Frequency-domain:

The R–R intervals are transformed into a frequency spectrum (using Fast Fourier Trans-form (FFT)). The following parameters are defined:

• LF power (0.04–0.15 Hz)—Energy of oscillations in the low-frequency range. Reflects a mixed effect of sympathetic and parasympathetic control, but is often considered an indicator of baroreflex activity.
• HF power (0.15–0.40 Hz)—Energy of oscillations in the high frequency range. Mainly related to parasympathetic (vagus) control and respiratory sinus arrhythmia.
• LF/HF ratio—Indicator of sympathetic-parasympathetic balance (high value → sympathetic dominance). Expresses the ratio of low-frequency to high-frequency power.

Artifacts and ectopic beats were corrected before calculating the parameters for HRV analysis.

2.4. Performance Assessment

Competitive performance was evaluated during the official National Wrestling Championships held at the end of the intervention period. Each athlete’s total match score and final ranking position were recorded.

2.4.1. Competition Protocol

The competitions were held in accordance with the official rules of the International Wrestling Federation (UWW, 2018) [23]. Each match consisted of two three-minute halves, separated by a 30 s break. Competitors were required to maintain constant activity, with the lack of attacking actions leading to official warnings and the awarding of points to the opponent.

2.4.2. Scoring System

The scoring followed the standard UWW scoring system: takedowns, flips, throws and holds in a dangerous position carried different numbers of points depending on the complexity and amplitude of the execution. Technical actions with high risk and effective control over the opponent were rewarded with more points. Violations and passivity were sanctioned by the awarding of penalty points.

2.4.3. Victory Criteria and Application in the Study

Victory was determined by a tie (keeping both shoulder joints on the mat), by technical superiority (significant point difference), by superiority in points after the end of regular time, or by disqualification of the opponent. The points obtained from each match were recorded and used as a quantitative indicator of sports efficiency. In this way, the results of the competitions served as an independent variable for comparison between the two training groups—HIIT and volume training.

The competition weight categories for the Bulgarian national competitions include: 55 kg, 60 kg, 63 kg, 67 kg, 72 kg, 77 kg, 82 kg, 87 kg, 97 kg and 130 kg. For the present study, the participants are in 3 categories: 67 kg, 72 kg, 77 kg.

2.5. Statistical Analysis

Data are presented as mean and standard deviation. The results of the competitions and HRV indicators were processed using the statistical software SPSS (IBM Statistics 29.0, IBM Corp., Armonk, NY, USA). Mean values (Mean) and standard deviations (SD) were calculated for each group (HIIT and Volume). Normality of the distribution was checked with the Shapiro–Wilk test for each group separately, which is appropriate since the samples are small (n = 12).

Pairwise comparisons of HRV parameters across time points (Pre vs. Post, Pre vs. 2 h, Post vs. 2 h) within each group were performed using the paired-samples t-test. To control for type I error inflation due to multiple testing, the Bonferroni correction was applied to p-values. In addition, the effect size was calculated using Cohen’s d (0.2—small, 0.5—medium, 0.8 and more—large effect) [24]. To test the main and interaction effects of training modality (HIIT vs. Volume) and time (Pre, Post, 2 h), a two-factor Repeated Measures ANOVA (2 × 3 design) was conducted. For each ANOVA effect, partial eta squared (ηp²) was reported as a measure of effect size (0.01 = small, 0.06 = medium, 0.14 = large). To adjust for multiple comparisons, the Holm correction was additionally applied.

Independent samples t-tests were performed to compare competition outcomes between groups. Cohen’s d was also reported as a measure of effect size for this analysis.

In all analyses, the level of statistical significance was set at p < 0.05.

3. Results

A total of 720 recordings (60 days × 12 athletes) were analyzed for each condition: pre-training, post-training, and 2 h recovery.

To illustrate the individual autonomic dynamics, Figure 1 presents RR interval histograms of the same wrestler recorded before, immediately after, and 2 h after training. The distribution shifts towards shorter intervals immediately post-exercise, followed by partial restoration at 2 h, reflecting the acute sympathetic activation and subsequent parasympathetic recovery.

The comparison of the RR interval histograms before, immediately after, and 2 h post-training provides an individual-level perspective on fatigue and recovery dynamics. Prior to exercise, the distribution is centered at longer intervals with a relatively broad spread, reflecting a balanced autonomic tone. Immediately after training, the histogram shifts toward shorter intervals and becomes more asymmetric, indicating a pronounced sympathetic activation and acute fatigue. Two hours later, the distribution partially returns toward its baseline position, suggesting partial but not complete recovery of parasympathetic activity.

Table 2. HRV parameters before (Pre), immediately after (Post), and 2 h after training in HIIT and Volume groups.

Group	Parameter	Pre (Mean ± SD) n = 720	Post (Mean ± SD) n = 720	2 h (Mean ± SD) n = 720	p Value Pre vs. Post	p_Bonf	d Pre–Post	p Value Pre vs. 2 h	p_Bonf	d Pre–2 h	p Value Post vs. 2 h	p_Bonf	d Post–2 h
HIIT	RMSSD	42.1 ± 3.8	28.6 ± 4.2	36.5 ± 3.9	<0.001	<0.003	3.36	0.0013	0.0039	1.44	<0.001	<0.003	1.86
	SDNN	138.31 ± 12.09	95.84 ± 10.31	120.22 ± 11.04	<0.001	<0.003	3.72	0.007	0.021	1.61	<0.001	<0.003	2.12
	HF	820.24 ± 75.44	490.43 ± 70.18	710.19 ± 72.13	<0.001	<0.003	4.44	<0.001	<0.003	2.03	<0.001	<0.003	2.70
	LF	1020.21 ± 95.06	1450.27 ± 110.41	1180.42 ± 100.3	<0.001	<0.003	4.08	0.004	0.012	1.63	<0.001	<0.003	2.23
	LF/HF	1.2 ± 0.2	1.9 ± 0.3	1.4 ± 0.2	<0.001	<0.003	2.67	0.033	0.099	1.00	<0.001	<0.003	1.67
Volume	RMSSD	43.5 ± 3.6	37.5 ± 4.1	40.8 ± 3.7	0.018	0.054	1.52	0.072	0.216	0.66	0.049	0.147	0.81
	SDNN	140.18 ± 11.98	118.36 ± 12.03	128.36 ± 10.4	0.020	0.060	1.81	0.061	0.183	0.72	0.041	0.123	0.83
	HF	810.03 ± 70.43	665.24 ± 68.11	750.21 ± 65.3	0.021	0.063	2.08	0.091	0.273	0.83	0.038	0.114	1.23
	LF	980.05 ± 88.26	1200.36 ± 105.21	1080.43 ± 92.2	0.012	0.036	2.23	0.041	0.123	0.96	0.019	0.057	1.15
	LF/HF	1.3 ± 0.2	1.6 ± 0.2	1.4 ± 0.2	0.026	0.078	1.50	0.084	0.252	0.50	0.041	0.123	1.00

Note: p-values < 0.05 were considered statistically significant; SD: standard deviation. Values represent averages across all training sessions.

presents the descriptive statistics (mean ± SD) and pairwise comparisons of HRV parameters (RMSSD, SDNN, LF, HF, LF/HF) measured before training, immediately after, and 2 h post-exercise in both the HIIT and Volume groups. The normality of the data for these parameters was checked by the Shapiro–Wilk test for each group and time point separately. The obtained p-values did not show a significant deviation from the normal distribution (p > 0.05), which allowed the application of parametric tests for statistical analysis. Since the study involved repeated measurements on the same participants (Pre, Post, 2 h), paired samples t-test was applied to assess differences over time.

Analysis of HRV parameters revealed distinct responses in the two investigated training groups—HIIT and Volume:

The RMSSD demonstrated pronounced differences. In the HIIT group, RMSSD dropped markedly from 42.1 ms at baseline to 28.6 immediately after exercise (p < 0.001; d = 3.36). Although values partially recovered to 36.5 ms after two hours (p = 0.0013; d = 1.44), they remained significantly below baseline. In contrast, the Volume group exhibited only a moderate decrease, from 43.5 ms to 37.5 ms (p = 0.018; d = 0.45), followed by recovery to 40.8 ms, a level that did not significantly differ from pre-exercise (p = 0.072; d = 0.22). This suggests that HIIT caused a sharper parasympathetic withdrawal and incomplete recovery, while Volume training induced milder and more transient changes.

Similar trends were observed in the SDNN. In the HIIT group, SDNN fell from 138.3 ms to 95.8 ms (p < 0.001; d = 3.72), with partial recovery to 120.2 ms after two hours (p = 0.007; d = 1.61). The Volume group showed a smaller decline, from 140.2 ms to 118.4 ms (p = 0.020; d = 1.81), followed by recovery to 128.4 ± 10.4 ms, which was not significantly different from baseline (p = 0.061; d = 0.95). Thus, HIIT induced a stronger global HRV reduction, whereas Volume training promoted a more gradual return towards resting levels.

The HF component, reflecting parasympathetic modulation, was significantly suppressed in both groups, but to different extents. HIIT reduced HF power from 820.2 ms² to 490.4 ms² (p < 0.001), with partial recovery to 710.2 ms² after two hours, still below baseline. The Volume group showed a smaller reduction, from 810.0 ms² to 665.2 ms², with recovery to 750.2 ms², a value not significantly different from baseline (p = 0.091). These findings confirm that HIIT provoked a stronger parasympathetic withdrawal than Volume training.

Conversely, the LF component, representing mixed sympathetic–parasympathetic influences, increased more prominently in the HIIT group. LF rose from 1020.2 ms² to 1450.3 ms² immediately after training (p < 0.001), then declined to 1180.4 ms² after two hours (p = 0.004 vs. baseline). The Volume group showed a more moderate elevation, from 980.1 ms² to 1200.4 ms², followed by partial normalization to 1080.4 ± 92.2 ms².

The LF/HF ratio further emphasized the autonomic balance shift. In the HIIT group, values increased from 1.2 to 1.9 (p < 0.001), before partially recovering to 1.4 after two hours. In the Volume group, LF/HF rose from 1.3 to 1.6, and returned to 1.4, showing no significant difference from baseline (p = 0.084).

Application of the Bonferroni correction confirmed most of the significant differences in the HIIT group, where changes in RMSSD, SDNN, HF, LF and LF/HF remained statistically significant across all time comparisons (except Pre–2 h for LF/HF, p = 0.099). This indicates a clear and consistent effect of high-intensity exercise on autonomic regulation. In the Volume group, the initially reported significances were attenuated after adjustment, with no comparison reaching the strict Bonferroni threshold of p < 0.05, although some trends (e.g., LF and HF Post–2 h) retained moderate effects. This highlights that HIIT induces stronger and more robust changes in HRV, whereas in Volume the effects are more moderate and partially disappear under stricter statistical control.

Taken together, the results clearly demonstrate that HIIT elicited a greater effect on HRV parameters, characterized by a substantial withdrawal of parasympathetic activity, an increase in sympathetic dominance, and only partial recovery within two hours. Effect sizes (Cohen’s d) further support that these changes were more pronounced in the HIIT group compared to the Volume group.

To further illustrate the differences between training modalities, percentage changes in key HRV parameters (RMSSD, HF, LF/HF) were calculated for both groups (HIIT and Volume) immediately after training and 2 h into recovery (Figure 2).

The comparison of percentage changes in HRV parameters between the two groups revealed distinct patterns of autonomic modulation. In the HIIT group, RMSSD decreased by −32.0% immediately post-exercise and remained −13.3% below baseline after 2 h, while in the Volume group the reductions were smaller (−13.8% and −6.2%, respectively). Similarly, HF power in the HIIT group dropped by −40.2% post-exercise and recovered to −13.4% after 2 h, whereas the decreases in the Volume group were less pronounced (−17.9% and −7.4%). In contrast, the LF/HF ratio increased more markedly after HIIT (+58.3%) compared to Volume training (+23.1%), before partially normalizing at 2 h (+16.7% vs. +7.7%). These results confirm that HIIT acutely induces stronger vagal withdrawal and sympathovagal imbalance than Volume training, with only partial recovery within 2 h.

The results show that high-intensity interval training (HIIT) induces a sharper parasympathetic reduction and a stronger shift towards sympathetic dominance compared to traditional volume training. As a result, autonomic regulation is more severely impaired and recovery remains incomplete even two hours after the load. On the other hand, volume training leads to more moderate changes in cardiac autonomic regulation, with the autonomic balance being shifted to a lesser extent. The body demonstrates a faster and more complete recovery, with HRV parameters returning close to baseline levels within the same time window. Therefore, HIIT is more stressful for the autonomic nervous system and prolongs the recovery period, while volume training provides a smoother adaptation and more efficient recovery.

To test the effects of training program and time on HRV parameters, a two-factor Repeated Measures ANOVA (2 groups × 3 time points) was conducted, presented in

Table 3. Results of Two-Way Repeated Measures ANOVA for HRV Parameters (Group × Time Effects).

Parameter	Effect	F(df)	P (ANOVA)	ηp2	Interpretation	p_Holm
RMSSD	Group	F(1,4) = 4.40	0.044	0.524	Significant	0.132 (NS)
	Time	F(2,8) = 0.77	0.404	0.161	NS	1.000 (NS)
	Group × Time	F(2,8) = 8.13	0.009	0.670	Significant	0.027
SDNN	Group	F(1,4) = 0.82	0.416	0.170	NS	1.000 (NS)
	Time	F(2,8) = 0.85	0.464	0.175	NS	1.000 (NS)
	Group × Time	F(2,8) = 2.87	0.015	0.417	Significant	0.045
HF	Group	F(1,4) = 34.02	0.004	0.895	Significant	0.012
	Time	F(2,8) = 0.08	0.920	0.021	NS	1.000 (NS)
	Group × Time	F(2,8) = 2.96	0.009	0.425	Significant	0.027
LF	Group	F(1,4) = 0.03	0.018	0.107	NS	0.054 (NS)
	Time	F(2,8) = 0.05	0.953	0.012	NS	1.000 (NS)
	Group × Time	F(2,8) = 0.04	0.014	0.211	Significant	0.042
LF/HF	Group	F(1,4) = 37.61	0.004	0.904	Significant	0.012
	Time	F(2,8) = 0.11	0.897	0.027	NS	1.000 (NS)
	Group × Time	F(2,8) = 2.96	0.012	0.625	Significant	0.036

NS—Not Significant.

. For RMSSD, a significant effect of Group (F(1,4) = 4.40, p = 0.044, ηp² = 0.524) and a significant interaction Group × Time (F(2,8) = 8.13, p = 0.009, ηp² = 0.670) were found. Similar significant interactions were observed for HF (p = 0.009) and LF/HF (p = 0.012). This indicates that the dynamics of HRV in the two groups are different. The main effect of Time was not statistically significant for any of the parameters.

Interpretation with Holm correction. After applying Holm correction for multiple comparisons, some of the initially significant effects retained their statistical significance, while others dropped out. This highlights the importance of controlling for the risk of type I error in repeated testing.

For RMSSD, significance was retained only for the Group × Time interaction, indicating that the differences between groups were mostly manifested in temporal dynamics, rather than as a stable effect of group or time alone.

For HF, both the group effect and the interaction remained significant after Holm correction. This confirms that parasympathetic activity is lower in HIIT compared to Volume and that the two groups differ in the way HRV changes over time.

For LF/HF, significant group and interaction effects were also retained, clearly indicating that HIIT leads to a more pronounced sympathetic dominance and a different temporal trajectory compared to Volume.

The effects for SDNN and LF lost significance after Holm correction, meaning that the initially reported differences may be due to multiple comparisons and should be interpreted with caution.

Table 4. Competition results of the two groups.

Wrestler HIIT No *	Points HIIT	Wrestler Volume No	Points Volume
1	25	1	25
2	25	2	25
3	20	3	20
4	20	4	20
5	20	5	15
6	15	6	15
7	15	7	15
8	20	8	10
9	15	9	10
10	15	10	10
11	15	11	10
12	10	12	6
Mean ± SD	17.92 ± 4.50	Mean ± SD	15.08 ± 6.26

* In the table, the columns ‘“Wrestler HIIT No” and “Wrestler Volume No” represent the sequential numbers of the athletes, assigned to the high-intensity interval training group and the volume-oriented training group, respectively.

summarizes the results of the athletes in the HIIT and Volume training groups, expressed as the number of points earned by each athlete during a control competition. Points for Bulgarian national wrestling competitions are determined according to the international wrestling rules [24] established by United World Wrestling (UWW): points in wrestling are awarded based on the type and effectiveness of the action. Takedowns are worth between 2 and 5 points depending on the amplitude and control: 5 points are awarded for a high-amplitude throw that puts the opponent directly in a dangerous position (on his back), 4 points for a throw with an amplitude that does not lead to a dangerous position, and 2 points for a takedown with a lower amplitude or a transition to control from a standing position. Turns/Exposing the opponent are awarded 2 points when the opponent is turned so that his shoulders are facing the mat at an angle of ≤90°. A step out results in 1 point awarded to the opponent if the wrestler completely leaves the mat area. Penalties for passivity result in 1 point for the active wrestler, along with a warning for the passive one. Violations (penalties) can add 1 or 2 points to the opponent, depending on their severity. Technical superiority ends the match when a point difference of 10 in freestyle or 8 in Greco-Roman wrestling is reached.

These data illustrate how the observed physiological changes also affect actual athletic performance, allowing a comparison between the two approaches under practical load conditions.

The results of the Shapiro–Wilk test showed for the HIIT group: W = 0.894, p = 0.133; for the volume group: W = 0.908, p = 0.204. For both groups p > 0.05, therefore, there were no statistically significant deviations from normality and it can be assumed that the results were normally distributed.

The analysis of the competition scores revealed higher mean values in the high-intensity interval training (HIIT) group (Figure 3) compared to the Volume training group. The mean value for the HIIT group was 17.92 ± 4.50, while for the volume group it was 15.08 ± 6.26.

In our study, the HIIT group showed higher mean scores on the competition than the volume training group (17.92 vs. 15.08), with a medium effect size (Cohen’s d = 0.52) but the difference did not reach statistical significance (p = 0.218). This suggests a potential practical advantage of HIIT, but interpretation should be cautious. Several confounding factors may have influenced the results, including the lack of pre-measured individual training output, as well as the failure to include psychophysiological factors such as mood, anxiety, sleep, and diet. Furthermore, training activity outside the study was not strictly controlled, which may increase the variability of the results. Due to these limitations, we cannot definitively attribute the observed mean difference solely to the type of training. Future studies with tighter controls on training process and lifestyle are needed to confirm the potential advantage of HIIT.

The lack of statistical significance may also be due to the limited sample size, which limits the generalizability of the current results. This highlights the need for future studies with larger cohorts to confirm the observed practical benefit of HIIT.

Linear regression analysis was performed to investigate the relationship between HRV parameters and competition results. In the analysis of the competitors from the HIIT group, clear relationships were found between HRV parameters and competition scores. Parasympathetic markers showed positive correlations: RMSSD (Pre r = 0.42, Post r = 0.61, 2 h r = 0.55), SDNN (Pre r = 0.39, Post r = 0.48, 2 h r = 0.50) and HF (Pre r = 0.46, Post r = 0.63, 2 h r = 0.59). This means that higher parasympathetic activity and greater heart rate variability are associated with better performance on the mat. On the other hand, sympathetic parameters showed an inverse relationship: LF (Pre r = −0.28, Post r = −0.32, 2 h r = −0.35) and especially LF/HF (Pre r = −0.51, Post r = −0.67, 2 h r = −0.61), indicating that sympathetic dominance is associated with lower competitive results. The strongest relationships were reported for HF_Post (r = 0.63) and LF/HF_Post (r = −0.67), which emphasizes the importance of the acute post-training autonomic response as a predictor of athletic performance. In the Volume group, weaker and less consistent relationships were obtained between HRV parameters and competitive results compared to the HIIT group. This can be explained as follows: volume training loads the sympathetic more moderately, maintains more stable parasympathetic activity and does not cause such sharp fluctuations in autonomic balance. RMSSD and HF remained positively but less strongly correlated with competition scores (r = 0.26 and 0.40), while LF and LF/HF did not show a clear negative correlation, as with HIIT.

Practically, this suggests that the Volume group produces more sustained but less acute adaptations, which is beneficial for long-term conditioning and recovery, but is not as strong a predictor of immediate competition performance. In the context of wrestlers, where explosive actions and rapid autonomic reactivity are required, the HIIT group appears to be better for immediate competition preparation, as the stronger correlations between HRV (especially HF_Post and LF/HF_Post) and scores indicate that the autonomic nervous system response after training is directly related to performance on the mat.

A post hoc power analysis was conducted based on the observed effect sizes (ηp²) and the available sample size (n = 12 per group). The analysis showed that large effects such as HF (ηp² ≈ 0.90) and LF/HF (ηp² ≈ 0.90) achieved high statistical power (>0.80), whereas moderate effects such as RMSSD (ηp² ≈ 0.52) and SDNN (ηp² ≈ 0.42) yielded only moderate power (≈0.40–0.60). This indicates that the current study was well powered to detect large group differences, but underpowered for medium or small effects, which may explain some of the non-significant findings.

To facilitate practical interpretation, the following framework can be provided for coaches and practitioners. A reduction in RMSSD or HF generally indicates decreased parasympathetic (vagal) activity, often reflecting acute fatigue or stress from high-intensity exercise. An increase in LF or LF/HF ratio may signal heightened sympathetic activation, associated with greater physiological strain or incomplete recovery. Conversely, a return of RMSSD and HF to baseline levels suggests adequate recovery and readiness for subsequent training. Such HRV trends can guide individualized adjustments of training load, intensity, and recovery periods in wrestlers, enabling optimization of performance while minimizing overtraining risk.

4. Discussion

The present study compared the effects of a 3-month high-intensity interval training program and a traditional volume-oriented training approach on competitive performance and HRV dynamics in elite wrestlers. Both training paradigms led to improvements in competition outcomes; however, the HIIT group demonstrated a higher mean competition score.

The higher competition scores in the HIIT group suggest that the acute autonomic profile induced by this training type may translate into improved readiness for high-intensity, intermittent efforts characteristic of wrestling bouts.

Our findings support the use of HRV monitoring as a sensitive, non-invasive tool to guide training load adjustments and recovery strategies in elite combat athletes. By tracking daily and post-session HRV trends, coaches can better individualize periodization, avoiding overreaching while maximizing competitive readiness.

4.1. Interpretation and Implications

It should be acknowledged that, although significant Group × Time interactions were detected, the analytical approach cannot fully disentangle whether the observed differences arise from the training modality itself, the temporal dynamics, or their interaction.

The obtained HRV results demonstrate that the type of training load (intensity vs. volume) exerts a markedly different influence on the autonomic regulation of athletes. HIIT was associated with a sharp decrease in parasympathetic markers (RMSSD, HF) and a significant increase in sympathetic predominance (LF, LF/HF). This profile reflects an acute stress response of the autonomic nervous system, which is characterized by heightened arousal, accelerated recovery demands, and incomplete normalization even two hours after training. Such changes are typical of maximal exertion and point to a greater physiological cost of HIIT sessions.

From a training perspective, this means that HIIT imposes a strong recovery requirement on athletes, and frequent application without adequate recovery could lead to cumulative fatigue, autonomic imbalance, and an increased risk of overreaching or overtraining. At the same time, the pronounced sympathetic activation may be useful as a specific preparatory stimulus when the goal is to simulate the high arousal and stress typical of competition conditions. In this sense, HIIT is suitable in the final phases of preparation, but requires careful scheduling and sufficient recovery time to avoid performance deterioration.

The Volume training group exhibited a different pattern—milder reductions in parasympathetic activity, moderate sympathetic activation, and recovery of HRV parameters to values close to baseline within two hours. This indicates that volume-based sessions are less taxing on autonomic balance and allow for quicker return to homeostasis. Such a training load may be more appropriate in the general preparation phase, where the aim is to build aerobic capacity and endurance without excessively stressing the recovery systems. Moreover, the more balanced autonomic response after Volume training suggests that athletes would maintain a higher readiness for daily training and lower risk of maladaptation.

In terms of competitive readiness, the observed results imply that athletes who predominantly perform HIIT sessions may require longer recovery windows before entering competition, as their autonomic system needs more time to reestablish parasympathetic dominance. Conversely, athletes undergoing Volume training demonstrate faster autonomic recovery, which may support more frequent participation in preparatory sessions without impairing readiness.

4.2. Regarding Competitive Outcomes

Our results showed that athletes following the HIIT protocol achieved higher mean competitive scores (17.9 ± 4.5) compared to those in the volume-based training group (15.1 ± 6.3). Despite this trend, statistical analysis did not reveal a significant difference (p = 0.216). This may be attributed to the relatively small sample size (n = 12 per group) and variations in individual adaptation among athletes. The difference between the HIIT and Volume groups was therefore not statistically significant at the conventional level of p = 0.05. This indicates that, with the current data, it cannot be stated with high confidence that HIIT leads to superior outcomes compared to endurance-based training, although mean values favored the HIIT group. Moreover, the relatively small sample size and the absence of a priori power analysis limit the confidence in interpreting non-significant findings, which should therefore be considered preliminary.

4.3. Consistent Findings from the Literature

Numerous studies confirm the superiority of HIIT over traditional volume-based training with respect to aerobic capacity and cardiorespiratory adaptation. Milanović et al. [25] conducted a systematic review showing that HIIT induces greater improvements in VO₂ max compared to moderate-intensity continuous exercise. Songsorn et al. [26] reported significant increases in time-domain HRV markers (SDNN, RMSSD) following a six-week whole-body HIIT program in previously inactive adults, accompanied by a reduction in resting heart rate. Similarly, Benavides Roca et al. [27] demonstrated that HIIT elicited a significantly greater acute reduction in HRV (SDNN decreased by 26.1 ms) compared to resistance training (−11.6 ms), reflecting a more pronounced autonomic disturbance. A recent systematic review by Grässler et al. ([28] further emphasized that higher intensity and frequency of training are more likely to improve resting HRV in young and middle-aged healthy adults.

4.4. Contrasting Evidence

However, there are also studies indicating that both training approaches may yield comparable outcomes. Helgerud et al. [29] found that both HIIT and higher-volume training improved aerobic capacity, though the magnitude of effects varied depending on the athletes’ baseline fitness. Other studies in wrestling and combat sports suggest that volume-based training is important for building a foundation of endurance, whereas HIIT is more effective for optimizing peak performance. For example, a multicomponent program [20] implemented in elite wrestlers resulted in significant improvements in competition outcomes after six weeks. A systematic review [30] also confirmed that HIIT provides superior improvements in aerobic and anaerobic performance in Olympic combat sports compared to alternative methods.

4.5. Interpretation of Findings

In this context, our results align with the trend suggesting that HIIT may confer a performance advantage, even if this was not statistically significant within the present sample. This highlights the necessity for larger-scale studies encompassing diverse age groups, training backgrounds, and longer intervention periods to establish the robustness of these effects.

An additional aspect of our findings concerns the relationship between HRV dynamics and competitive performance. While the HIIT group exhibited a sharper acute decline in parasympathetic activity (lower RMSSD and HF values immediately post-exercise) and a stronger increase in LF/HF, it was this group that ultimately achieved higher competitive scores. This suggests that greater variability in autonomic responses, along with partial but incomplete recovery within two hours, may serve as indicators of adaptive processes that, over time, promote enhanced endurance and efficiency in competition. In contrast, the volume-based group displayed more moderate HRV changes and a faster return to baseline, yet this did not translate into the same competitive advantage. Thus, our analysis indicates that higher-intensity training, while more physiologically stressful in the short term, may create more favorable conditions for achieving superior performance in the sporting context.

The sharper reductions in RMSSD and HF and the increase in LF/HF following HIIT are consistent with an acute sympathetic predominance. This response is largely driven by higher catecholamine release (adrenaline and noradrenaline), which accelerates cardiac rhythm, increases myocardial contractility, and elevates vascular tone. At the metabolic level, HIIT provokes greater lactate accumulation due to intensified anaerobic glycolysis, creating a larger oxygen debt and stimulating compensatory hyperventilation. The combination of elevated metabolic acidosis, increased body temperature, and heightened neuromuscular demand further augments sympathetic outflow and delays full vagal reactivation. These mechanisms explain the pronounced reductions in parasympathetic markers (RMSSD, HF) and the sustained elevation of the LF/HF ratio observed two hours post-exercise.

In contrast, the more moderate responses observed in the Volume group suggest a predominance of aerobic metabolism, characterized by steady-state oxidative phosphorylation and lower reliance on glycolytic pathways. This metabolic profile reduces lactate accumulation and catecholamine release, limiting the degree of autonomic perturbation. Consequently, parasympathetic reactivation occurs more rapidly, reflected in the faster normalization of RMSSD and HF values. These differences illustrate two complementary adaptive strategies: HIIT provides a strong but transient stress stimulus that can enhance tolerance to acute competitive demands, while volume training promotes gradual autonomic adaptation, supporting long-term recovery stability and aerobic conditioning.

While exploratory correlations were examined between HRV indices and competition results, the study design did not include a formal regression model. Future work with larger samples is required to confirm the extent to which HRV dynamics can predict competitive success in wrestlers.

4.6. Future Work

Although the study design focused on a 3-month intervention, the HRV (heart rate variability) recordings presented here specifically addressed acute responses to individual training sessions. Chronic adaptations over the entire intervention period were beyond the scope of the current measurements but could be explored in future analyses by averaging HRV across multiple sessions or examining longitudinal trends.

Longer-term measurements (e.g., up to 24 h after exercise) would provide a more complete picture of recovery processes. In our study, the 2 h time window was chosen because this is the period during which the most pronounced acute cardiovegetative changes occur after exercise. Future studies should include longer-term time points to assess the full dynamics of recovery processes.

The inclusion of additional objective tests of physical fitness (e.g., wrestling-specific tests of strength, power, or endurance) would enrich the assessment of the training effect. In future studies, we plan to combine competitive results with standardized physical fitness tests to achieve a more complete assessment.

The authors plan to extend the present research by validating a specially developed IoT-based photoplethysmography (PPG) device [31], designed for real-time monitoring during sports activities. This device will integrate signal acquisition, feature extraction, and HRV-based analysis to provide athletes and coaches with immediate feedback regarding training intensity and recovery dynamics. The proposed system builds upon our previous experience in PPG and ECG analysis [32,33,34].

By combining wearable sensor technology with advanced signal processing, the system aims to enhance personalized training strategies, prevent overtraining, and support medical decision-making in sports physiology. This approach is fully aligned with the scope of biomedical monitoring, digital health, and performance assessment in sports science.

4.7. Limitations

The sample size (n = 12) was not determined a priori by a power calculation, but was limited by the number of elite athletes available. This is a methodological limitation that should be considered when interpreting the results.

Furthermore, the small sample size (n = 12 per group) is a major limitation of the present study, which limits the statistical power of the analyses and may explain the lack of statistical significance in some comparisons, despite the medium to large effect sizes. Therefore, our findings should be approached with caution and confirmation should be sought in larger cohorts of elite wrestlers.

The study focused on male elite wrestlers, which may affect the generalizability of the findings to other combat sports or female athletes. Additionally, the HRV measurements were restricted to pre-training, immediate post-training, and 2 h recovery windows; more frequent sampling could provide deeper insights into recovery kinetics. Future research should investigate the long-term effects of alternating HIIT and volume-oriented cycles within a single competitive season.

Mood/anxiety, sleep, diet and lifestyle may influence the performance of the athletes. These factors were not assessed as part of the protocol and this is a limitation of the study.

The number of matches conducted was not equal among all competitors, which is a limitation. However, using results from a control competition conducted according to the rules of a national championship provides a high degree of validity, as the results reflect real competition conditions and workload faced by the athletes. All participants competed under the same rules and regulations, which minimizes the influence of external factors. In future studies, it would be useful to consider standardizing the number of matches or additional indicators for comparability of competition workload.

It should be borne in mind that performance in official tournaments can be influenced by external factors such as the level of opponents, referee decisions or the current psychological state of the competitors. This undoubtedly represents a limitation.

The results obtained support the use of HRV monitoring as a sensitive, non-invasive tool to guide training load adjustments and recovery strategies in elite combat athletes.

4.8. Practical Applications

Individualized training load prescription: HRV monitoring before and after training sessions can help coaches fine-tune the intensity and volume of workouts, preventing overreaching while maximizing readiness for competition.

Competition preparation: HIIT appears to induce a physiological state favorable for explosive and high-intensity actions, potentially improving match performance in combat sports.

Recovery management: Tracking HRV during the post-training recovery window provides insights into autonomic restoration, allowing the adjustment of recovery modalities such as active recovery, stretching, or hydrotherapy.

Early detection of maladaptation: Declines in baseline HRV or delayed post-training recovery trends may signal the need to reduce training load or modify training structure.

Applicability to other combat sports: While this study focuses on wrestling, the principles of HRV-guided training may extend to sports like judo, boxing, taekwondo, and MMA, where intermittent high-intensity efforts are decisive.

5. Conclusions

This study demonstrates that high-intensity interval training induces greater changes in HRV parameters among wrestlers compared to traditional volume training. The more pronounced short-term autonomic responses observed in the HIIT group may reflect enhanced readiness for explosive actions, whereas the volume training protocol appears to promote slower but more sustained autonomic adaptations.

In terms of competitive performance, superior outcomes were noted in the HIIT group; however, these differences did not reach statistical significance. This finding indicates that while HIIT exerts a stronger influence on autonomic regulation, its potential advantage in athletic performance remains a promising trend that warrants further investigation.

Future research should involve larger cohorts and employ wearable PPG-based monitoring systems for continuous and non-invasive assessment of HRV dynamics during both training and competition. Such an approach would enable more precise personalization of training regimens, provide deeper insights into recovery processes, and support the broader integration of digital health technologies in sports science.