Achieving Competitive Excellence in Taekwondo: The Relationship Between Unloaded Countermovement Jump Kinetic Variables and Sport-Specific Motor Tasks

Abstract

Background. In taekwondo (TKD), high-intensity actions—particularly kicks and rapid changes of direction—are key determinants of sport-specific performance. Kinetic vari-ables derived from unloaded countermovement jumps (CMJs) are employed as proxies of neuromuscular efficiency. However, most studies have examined the link between CMJ outputs and TKD using jump height alone in sport-specific tasks. Objective. To determine the associations between unloaded CMJ-derived kinetic variables and sport-specific performance, identifying key determinants of repeated high-intensity kicking capacity and change-of-direction ability. Methods. Fifteen national-team athletes (nine men, six women; 18–27 years) completed unloaded CMJ testing (Day 1) and, after 48 h, the Taekwondo-Specific Agility Test (TSAT) and the Multiple Frequency Speed of Kick Test (FSKTMULT) (Day 2). Results. For FSKTMULT, jump height (r = 0.545–0.746), take-off velocity (r = 0.548–0.799), and mean power (r = 0.602–0.799) were positively correlated with the number of kicks across all sets (p = 0.001–0.044). Stepwise regression identified mean power as the sole significant predictor, explaining 32–46% of the variance across sets. For TSAT, time correlated negatively with mean power (r = −0.678, p = 0.008), mean force (r = −0.536, p = 0.048), and RFD (0–30%) (r = −0.655, p = 0.011). Mean power and mid-propulsion impulse (30–60%) jointly explained 72.8% of the variance in TSAT time (R² = 0.728, p < 0.001). Conclusions. Unloaded CMJ mean power and mid-propulsion impulse (30–60%) emerge as proxies of neuromuscular efficiency linked to sport-specific perfor-mance, supporting their use for athlete monitoring and targeted training.

1. Introduction

Competitive taekwondo (TKD) has become increasingly dynamic and complex due to frequent rule changes and the introduction of technologies such as electronic body protectors [1]. The sport is characterized by rapid exchanges of front and roundhouse kicks, often executed with spinning and jumping components [2,3,4], together with acceleration–deceleration demands across multiple planes. These demands require high linear and angular velocities in the thigh and shank segments [5,6,7,8] and sufficient force to execute kicks reaching velocities of 5.2–18.3 m·s⁻¹, generating impacts of 122.6–9015 N [2,9]. Optimal performance depends on the integrated synergy of strength, speed, multidirectional movement skills, and muscle endurance—each essential for repeated kicking actions [10,11,12,13]. Accordingly, analyzing these physical attributes is essential.

Among field tests, the countermovement jump (CMJ) is the most widely used assessment of neuromuscular characteristics and lower-limb power, particularly with respect to the slow stretch–shortening cycle (SSC > 250 ms) [14]. The CMJ comprises a rapid eccentric descent followed by explosive concentric propulsion, capitalizing on stored elastic energy and post-activation potentiation [15]. Its kinematic similarity to the triple-extension pattern renders it a valid model for estimating lower-limb power and monitoring neuromuscular fatigue, although sensitivity may vary with technical execution [16,17].

Technological advances now permit detailed analysis of CMJ kinetics using force platforms with sampling frequencies ≥ 1000 Hz, yielding reliable mechanical variables including peak and mean power, peak force, take-off velocity, rate of force development (RFD), impulse, and the modified reactive strength index (RSImod). Collectively, these indices provide a more comprehensive characterization of neuromuscular function than jump height alone [17,18,19].

Considering TKD-specific performance, field tests with high ecological validity have been developed to evaluate combat-specific capacities [20]. The Taekwondo-Specific Agility Test (TSAT) has been validated as a reliable and sensitive measure of change-of-direction ability in elite athletes [20], whereas the Frequency Speed of Kick Test Multiple (FSKTMULT) assesses kicking-specific muscular endurance [10]. Both tests effectively discriminate competitive levels and are instrumental for talent identification and training monitoring [20].

Despite these advances, research on the relationships between CMJ-derived neuromuscular characteristics and TKD-specific performance still faces methodological and practical limitations. Most studies have assessed the CMJ using jump mats in national-level samples, constraining generalizability to elite populations and limiting the assessment of neuromuscular specificity. For example, Ojeda-Aravena et al. [12] reported inverse correlations between TSAT time execution and jump height in both squat jump and CMJ, as well as a positive association between squat-jump height and the total number of kicks in FSKTMULT. Similarly, Albuquerque et al. [21] observed a moderate correlation between mean CMJ height and total kicks. However, these studies prioritized jump height rather than kinetic variables, precluding the identification of parameters (e.g., RFD, impulse, RSImod) that may more accurately predict change-of-direction ability and repeated-kicking capacity in national-team TKD athletes.

Clarifying these relationships would enable strength and conditioning practitioners to design resistance and plyometric programs that optimize triple-extension mechanics and power production within temporally relevant windows. This approach would also facilitate monitoring of fatigue and training adaptations using sensitive kinetic variables and allow the establishment of individualized reference values to guide load periodization and injury prevention throughout the competitive season.

Accordingly, this study aimed to examine the associations between kinetic variables from unloaded CMJs and sport-specific performance tasks, identifying key determinants of kicking ability and change-of-direction performance. Based on prior evidence [12,13,21], we hypothesized that kinetic variables from the unloaded CMJ—particularly velocity-related parameters—would predict performance on TKD-specific tests in national-team athletes.

2. Materials and Procedures

2.1. Participants

Fifteen TKD athletes from the Chilean national team (nine men, six women; black belts, 1st–3rd Dan) participated in this cross-sectional study. Mean age was 20.1 ± 2.8 years (range: 18–27 years) and mean stature 172.2 ± 6.8 cm (155–186 cm). The athletes had 15.2 ± 4.2 years of TKD practice (9–20 years) and had competed in an average of 1.8 ± 1.1 national and 4.5 ± 2.9 international events. All trained six days·week⁻¹, ~4 h·session⁻¹, during the early preparatory phase for international competition. The inclusion criteria were as follows: (a) at least four years of competitive experience to ensure consolidated technical skills and consistent neuromuscular adaptations typical of high-performance athletes; (b) participation in a minimum of three training sessions per week to maintain standard preparation and reduce variability related to inconsistent training [22]; (c) current engagement in the preparatory phase for competitions approved by the National Taekwondo Sports Federation, recognized by World Taekwondo, in order to standardize training regimens and physiological states [12]; and (d) no recent rapid reduction in body mass, to control for acute metabolic and hormonal fluctuations resulting from caloric restriction [21]

The study complied with STROBE guidelines for observational research and the Declaration of Helsinki, and was approved by the local ethics committee (Code: 520-2022). All participants provided informed consent.

2.2. Procedures

Athletes attended the laboratory for two testing sessions separated by 48 h. All were in the initial phase of physical preparation according to their annual training macrocycles. During each performance test, athletes were randomly assigned, and the principal investigator remained blinded to identities via anonymized codes.

Visit 1 comprised the CMJ assessment in a temperature-controlled laboratory (21 °C). Visit 2 was conducted in TKD-specific facilities adhering to official competition standards. Athletes performed the TSAT, followed by the FSKTMULT, with active recovery between tests. Participants were instructed to exert maximum effort during each trial. The order of assessments and warm-up followed a standardized protocol [22]. For CMJs and TSAT, the best of three attempts was retained; due to the high muscular demand of the FSKTMULT, only one valid attempt was performed. A 10 min seated rest separated tests to minimize fatigue.

2.3. Physical Performance Assessments

2.3.1. Unloaded Countermovement Jump (CMJ)

After a standardized warm-up (10 min dynamic stretching and preparatory vertical jumps), athletes performed CMJs with verbal instruction to standardize depth (~90° knee flexion). Trials were repeated if landing did not occur with plantar flexion and knee extension [22]. Vertical ground-reaction force was recorded at 1000 Hz using a force platform (FP8; HUR Labs, Oulu, Finland). Proprietary software (Force Platform Software Suite; HUR Labs) displayed kinetic data in real time following Bishop et al. [22]. Center-of-mass (COM) velocity was obtained by dividing net force (force minus body weight) by body mass and integrating using the trapezoid rule [23]. Jump height was calculated from COM vertical velocity at take-off [24]. Net impulse was derived from the time integral of net vertical force [25]. Peak force was defined as the maximum force during the concentric phase. Power output was computed as the product of force and velocity [25]. RSImod was calculated as CMJ height divided by time to take-off [23]. To analyze impulse shape and RFD, the propulsion phase was divided into three equal-duration sub-phases (0–30%, 30–60%, 60–90%) [24].

2.3.2. Taekwondo-Specific Agility Test (TSAT)

Athletes performed the TSAT according to Chaabene et al. [26]. From a guard stance with both feet behind the start/finish line, the sequence was as follows: (a) advance to the center point in guard stance; (b) turn toward partner 1, move laterally, and execute a left-leg roundhouse kick (dollyo chagi); (c) move toward partner 2 and perform a right-leg roundhouse kick; (d) return to the center; (e) advance toward partner 3 and execute a double front kick in a twist (narae chagi); and (f) retreat to the start/finish line. Partners held the target pad at torso level. Incorrect technique (e.g., foot position or insufficient impact) required a restarted attempt after 3 min recovery. An electronic stopwatch (Brower Timing Systems, Salt Lake City, UT, USA) recorded time.

2.3.3. Frequency Speed of Kick Test Multiple (FSKTMULT)

Athletes performed the FSKTMULT according to the standardized protocol of da Silva Santos and Franchini [27]. This test assesses an athlete’s ability to sustain high-intensity kicking performance over multiple bouts. Each of the five sets consisted of 10 s of consecutive kicks, followed by 10 s of passive recovery. The protocol required athletes to perform the test against a partner wearing a chest protector. An audible signal initiated each set, cueing the athlete to execute as many kicks as possible on alternating legs. A standard smartphone camera (iPhone 11; Apple Inc., Cupertino, CA, USA) recorded the trial for subsequent verification. The performance analysis recorded the total number of kicks per set (S1–S5), the total kicks, and the kick decrement index (KDI).

2.4. Statistical Analysis

Data were collected in Microsoft Excel and analyzed in JASP (version 0.16.4; JASP Team). Descriptive results are mean ± standard deviation (SD) with 95% confidence intervals (95% CI). Normality was assessed via the Shapiro–Wilk test. Independent-samples t-tests examined sex differences. Partial correlations (Pearson) were computed between CMJ kinetic variables and FSKTMULT/TSAT performance, controlling for sex, body mass, and age. Effect sizes (ESs) used Fisher’s z, classified as <0.10 (trivial), >0.10 (small), >0.30 (moderate), and >0.50 (large) [28].

Subsequently, a stepwise multiple regression analysis employed the forward selection method. The models incorporated kinetic variables from the unloaded CMJ that demonstrated significant correlations (p < 0.05) with the TKD-specific tests. Model assumptions included outlier detection via residual analysis. Potential collinearity between predictors was examined via the variance inflation factor (VIF) and tolerance, with thresholds of VIF < 10 and tolerance > 0.2. Independence of errors was verified using the Durbin–Watson test [12].

Absolute reliability between CMJ attempts and TSAT performance was assessed via the coefficient of variation (CV < 10%), while the intraclass correlation coefficient (ICC (3,1) > 0.90) determined relative reliability [29]. Statistical significance was set at p < 0.05.

3. Results

3.1. Normality and Descriptive Analysis

Normality was confirmed for all variables except height (Shapiro–Wilk). Reliability analysis demonstrated acceptable values for the countermovement jump (CMJ) (ICC = 0.89, 95% CI [0.78, 0.93], CV = 8.7%) and the Taekwondo-Specific Agility Test (TSAT) (ICC = 0.84, 95% CI [0.72, 0.87], CV = 9.3%).

Table 1. Descriptive specific taekwondo performance and CMJ unloaded kinetic variables.

Variable	M	SD	95% CI [Lower, Upper]
Taekwondo-Specific Agility Test (TSAT)
TSAT (s)	6.887	0.893	[6.435, 7.338]
Frequency Speed of Kick Test Multiple (FSKTMULT)
S1 (kicks)	18.933	2.282	[17.778, 20.088]
S2 (kicks)	18.533	2.416	[17.311, 19.756]
S3 (kicks)	18.133	2.200	[17.020, 19.246]
S4 (kicks)	17.600	2.063	[16.556, 18.644]
S5 (kicks)	17.133	1.995	[16.124, 18.143]
Total kicks (kicks)	90.400	10.642	[85.014, 95.786]
Kick decrement index (%)	5.360	3.201	[3.740, 6.980]
CMJ kinetics variables
Force/body weight (N·kg−1)	43.450	35.121	[25.677, 61.223]
Jump height (cm)	27.817	7.315	[24.115, 31.519]
Take-off velocity (m·s−1)	2.319	0.296	[2.169, 2.468]
Peak power output (W)	2959.685	980.891	[2463.294, 3456.075]
Mean jump power (W)	911.716	281.017	[769.505, 1053.927]
Relative power (W·kg−1)	42.629	7.762	[38.700, 46.557]
Mean force (N)	870.262	170.043	[784.210, 956.314]
Peak impulse (N·s)	170.595	48.143	[146.231, 194.958]
Peak force (N)	1605.469	407.710	[1399.143, 1811.795]
CMJ Impulse phases
0–30% impulse (N·s)	200.400	37.219	[181.565, 219.235]
30–60% impulse (N·s)	219.960	65.869	[186.626, 253.294]
60–90% impulse (N·s)	90.800	50.805	[65.089, 116.511]
CMJ RFD phases
Initial RFD (0–30%) (N·s−1)	2449.667	398.533	[2247.985, 2651.349]
Sustained RFD (30–60%) (N·s−1)	263.067	88.104	[218.481, 307.653]
Peak RFD (60–90%) (N·s−1)	7248.933	3213.237	[5622.841, 8875.026]
Modified reactive strength index (RSImod)	0.358	0.093	[0.311, 0.406]

TSAT = Taekwondo-Specific Agility Test; FSKTMULT = Frequency Speed of Kick Test Multiple; CMJ = countermovement jump; RFD = rate of force development; W = watt; W·kg⁻¹ = watt per kilogram; N = newton; N·kg⁻¹ = newton per kilogram; N·s = newton-second; N·s⁻¹ = newton per second; kg·m s⁻¹ = kilogram-meter per second; m s⁻¹ = meter per second; cm = centimeters; % = percentage; kicks = count (number of kicks).

presents descriptive data for the 15 TKD athletes. No significant sex differences were observed for the analyzed variables (p > 0.05). The multiple linear regression model met all assumptions. The Durbin–Watson statistic (range: 1.561–2.027, p > 0.245) indicated no autocorrelation. Tolerance values (1.000) and variance inflation factor (VIF) (1.000) confirmed the absence of collinearity. Standardized residuals (range: −1.825 to 1.778) showed a symmetric distribution with no extreme values. All coefficients were significant (p < 0.05), with 95% confidence intervals excluding zero.

3.2. Relationship Between Unloaded CMJ Kinetic Variables and Sport-Specific Performance in Taekwondo

3.2.1. Taekwondo-Specific Agility Test (TSAT)

Significant negative correlations emerged between TSAT execution time and CMJ metrics. The analysis identified large effect sizes for mean power output and initial rate of force development (RFD 0–30%), with moderate correlations for peak impulse, mean force, and velocity at 30–60% (Figure 1).

In Model 1, mean jump power output significantly accounted for 60.2% of the variance in TSAT execution time (F = 19.694, p < 0.001, 95% CI [0.002, 0.004]). Model 2, which added impulse during 30–60% of the CMJ propulsion, increased the explained variance to 72.8% (F = 16.025, p < 0.001, 95% CI [0.001, 0.007]), representing a 12.5% improvement over Model 1 (F = 5.516, p = 0.037, 95% CI [0.001, 0.004]). For details, see the Supplementary Table S1.

3.2.2. Frequency Speed of Kick Test Multiple (FSKTMULT)

Significant positive correlations were observed between CMJ variables and FSKTMULT performance, with mean jump power output representing the most consistent predictor. Across sets (S1–S5) and for total kicks, moderate-to-large correlations were found for jump height, take-off velocity, peak/mean power, mean force, and peak impulse (Figure 1). No significant associations were detected with the kick decrement index (KDI). For total kicks, mean jump power output and mean force demonstrated large correlations, whereas jump height and take-off velocity exhibited moderate correlations (Figure 1).

The multiple linear regression confirmed mean jump power output as the sole significant predictor across all models. For S2, it explained 32% of the variance (F = 6.071, p = 0.028, 95% CI [0.001, 0.009]); for S3, 46% (F = 13.066, p = 0.003, 95% CI [0.002, 0.009]); for S4, 39% (F = 9.922, p = 0.008, 95% CI [0.002, 0.008]); for S5, 44% (F = 11.993, p = 0.004, 95% CI [0.002, 0.008]); and for total kicks, 34% (F = 8.477, p = 0.012, 95% CI [0.006, 0.041]). For details, see the Supplementary Table S1.

4. Discussion

This study aimed to examine the associations between kinetic variables from unloaded CMJs and sport-specific performance tasks, identifying key determinants of kicking ability and change-of-direction performance. The results confirmed the hypothesis, demonstrating significant relationships between CMJ-derived kinetic variables and performance in TKD-specific tests. These findings underscore the relevance of neuromuscular characteristics for sport-specific performance in elite TKD athletes.

The primary findings identified mean jump power as the main determinant of performance in the FSKTMULT, while impulse during 30–60% of propulsion significantly predicted TSAT execution time. Additionally, jump height, take-off velocity, mean jump power, peak impulse, and the modified reactive strength index (RSImod) showed significant correlations with the number of kicks per series (S1–S5), total kicks, and TSAT execution time. Mean jump power demonstrated a progressive influence across FSKTMULT sets, indicating its increasing contribution to sustaining consecutive kick volumes. In contrast, the KDI showed no significant correlations with neuromuscular performance.

These findings align with previous research. Albuquerque et al. [21] reported a moderate association between total kicks and CMJ jump height (r = 0.44, p = 0.004), while Ojeda-Aravena et al. [9] observed direct correlations between total kicks and squat-jump height (r = 0.66, p = 0.001), alongside a nonsignificant moderate correlation for CMJ height (r = 0.42, p = 0.07). Those authors also indicated that the eccentric utilization ratio (EUR) and RSI accounted for up to 76% of kicking performance variability (F = 29.66, p < 0.001), suggesting the particular relevance of neuromuscular efficiency in TKD performance.

Regarding TSAT execution time, the present study found mean jump power and RFD at 0–30% of CMJ as predictors, complementing previous results by Ojeda-Aravena et al. [9], who documented significant negative correlations between SJ height (r = −0.63, p < 0.05) and CMJ height (r = −0.53, p < 0.05) with agility performance.

The results suggest that lower-limb mechanical power is a key quality in TKD. Mean power derived from unloaded CMJ appears related to the execution of repeated efforts during FSKTMULT sets in elite athletes. Interestingly, these findings contrast with Sant’ana et al. [10], who observed no significant correlations between average power (W·kg⁻¹) derived from externally loaded SJ at 40% body mass and FSKTMULT performance (n = 16). This suggests that average mechanical power from the unloaded CMJ may serve as a practical indicator for monitoring slow SSC capacity and assessing training-program effectiveness. The CMJ’s biomechanical advantages—featuring triple lower-limb extension and integrating force–velocity values typically studied separately [9]—reinforce its relevance.

Significant correlations for RFD, peak impulse, at 30–60% of CMJ with both TSAT execution time and total kicks suggest that rapid force production and precise force application at strategic moments are important for TKD-specific direction changes and for sustaining high-intensity efforts. These findings align with prior research highlighting RFD as a critical factor in explosive movements [30,31]. High-level TKD athletes exhibiting higher RFD values may therefore execute kicks advantageously by anticipating opponents’ defenses, evading attacks, and efficiently adjusting movement patterns [32].

The moderate-to-strong correlations between impulse and velocity with both kicking performance and TSAT execution time represent another relevant finding. Impulse, reflecting the capacity to generate force over time [32], translates to greater acceleration during kicks and more effective direction changes. The moderate negative correlation between peak impulse and TSAT execution time (r = −0.577) suggests that athletes with higher impulse generation may complete change-of-direction tasks faster. Furthermore, the progressive influence of impulse across kicking series, peaking at S3 (r = 0.759), indicates its relevance for sustaining performance under fatigue due to its relationship with time-dependent force application [33].

The strong correlation with RFD at 0–30% and the moderate correlation with velocity at 30–60% of CMJ imply that elevated RFD promotes efficient eccentric–concentric transition, which is pertinent for acceleration and deceleration in direction changes [31,32]. These findings reinforce that force production over short intervals and power output in brief movements may be critical for key TKD actions, enabling athletes to evade, counterattack, or adjust positioning more effectively. Take-off velocity directly influences body-mass displacement and kick execution, while achieving high vertical velocity could benefit the execution of elevated kicks such as dollyo chagi and naeryo chagi that require striking high targets [12,21,22].

RSImod’s role in both FSKTMULT and TSAT performance suggests that eccentric loading plays a crucial role in rapid kick sequences and agility movements, consistent with its derivation from jump height and time to take-off [34]. Conversely, the lack of significant correlations for KDI aligns with Ojeda-Aravena et al. [12], indicating that this index may be less relevant for assessing neuromuscular performance in these specific tests.

4.1. Limitations and Future Research Directions

Several methodological considerations qualify the interpretation of these findings. The high physical demands of the FSKTMULT prevented the collection of test–retest data; therefore, intra-session reliability could not be assessed. Future research should address this aspect to further establish the FSKTMULT as a reliable measure of repeated kicking performance.

The sample comprised male and female athletes with relatively homogeneous performance levels and competitive experience. This homogeneity supports internal consistency but limits the generalizability of results to more diverse populations. Additionally, the small sample size (n = 15), drawn exclusively from a single Chilean national team, restricts extrapolation of findings to other countries, competitive levels, or training phases. Regarding the statistical approach, the use of stepwise multiple regression with a small sample increases the risk of overfitting; thus, the identified associations should be considered primarily exploratory. The absence of inter-session reliability data for the sport-specific tests, along with the omission of potentially influential variables such as training load, injury history, and psychological factors, also represents areas for methodological improvement in future studies.

Overall, these limitations highlight clear opportunities for future research employing larger and more diverse samples, multicenter designs, and robust statistical methods. Further investigation should also explore sex-based differences in CMJ kinetic metrics and their impact on TKD-specific performance.

4.2. Practical Highlights for Coaches and Athletes

The identified correlations underscore the complexity of applying CMJ kinetic variables to TKD-specific performance. Multiple neuromuscular parameters interact synergistically in explosive actions such as kicks, counterattacks, and rapid changes in direction. This interaction reflects the multifactorial nature of performance in TKD, where strength, power, and speed should be viewed as complementary components in the production of high-intensity technical actions. The athlete’s ability to coordinate these variables efficiently determines the effectiveness of critical actions during competition. Consequently, correlation analyses require cautious interpretation within an integrated performance framework. It is important to note that correlations do not imply causation. Although certain kinetic variables may be associated with improvements in specific task performance, they do not constitute evidence of causality. This distinction highlights the need to conduct longitudinal studies and controlled experimental trials to determine causal relations. Only rigorous experimental designs can clarify the extent to which indicators such as RFD, RSImod, or impulse causally determine improvements in change-of-direction ability and kicking capacity in TKD.

To the best of our knowledge, this study represents the first comprehensive analysis of neuromuscular performance measures derived from the CMJ in relation to sport-specific variables in TKD. This approach addresses a significant gap, as the prior literature has focused predominantly on jump height rather than systematic analysis of CMJ kinetics in sport-specific tasks. By establishing links between explosive strength parameters and sport-specific tests, new avenues of research open for athlete evaluation and the design of competition-oriented conditioning programs. The ability to generate force rapidly (RFD) and optimize the timing of force application (impulse and velocity) is fundamental to the effective execution of high-speed techniques. In TKD—where decisive actions occur within fractions of a second—the capacity to attain high force levels rapidly may determine success in scoring. Moreover, movement efficiency depends not only on the magnitude of force but also on its timely transmission along the kinetic chain, making intermuscular coordination a critical competitive factor.

This complexity demands examination of multiple CMJ kinetic indicators—including mean jump power, RSImod, peak impulse, and RFD—because each provides complementary performance perspectives that require specific training strategies. Within TKD, where explosive techniques are executed under strict spatiotemporal constraints, a differentiated understanding of these variables enables the design of more precise conditioning programs with greater transfer to competition. Mean jump power reflects the neuromuscular system’s ability to produce mechanical work efficiently during concentric phases, indicating the athlete’s capacity to sustain power output during repeated efforts—essential for frequent kicking and explosive displacement. Strength programs derived from Olympic lifting variations and loaded jumps effectively enhance this capacity in this sport [34].

RSImod, for its part, relates to efficiency in reactive actions during fast stretch–shortening cycles, where higher values reflect reduced ground contact times and greater force production. Plyometric training tends to improve this parameter through better utilization of elastic energy—directly transferable to combat-sport settings [35,36].

Peak impulse denotes the generation of high forces over brief periods and is critical for impact techniques such as maximal-intensity kicks. Training methods such as resisted sprints and heavy squats develop this capacity alongside intermuscular coordination. RFD quantifies the speed of motor-unit recruitment during the early phases of contraction; higher values reduce movement latency, conferring a decisive advantage in tactical exchanges. Ballistic exercises and contrast-loading training effectively develop this quality. Collectively, these modalities promote specific neuromuscular adaptations: increases in maximal strength, maintenance of power output, optimization of contraction velocity, and efficiency of the stretch–shortening cycle [36]. Strategic integration enhances motor-unit activation and intermuscular coordination, enabling faster and more precise technical execution during competition.

For sport-specific adaptations, practitioners should address these indicators differentially: mean power via Olympic lifting derivatives and loaded jumps; RSImod via reactive training and plyometrics; and peak impulse and RFD via ballistic exercises or velocity-based training [37]. Integrated periodization optimizes neuromuscular coordination and technical efficiency. Sport-specific assessments also offer valuable monitoring tools, as quantifying variations in impulse and velocity after combat simulations may indicate early neuromuscular fatigue and enable timely adjustments to training load. The observed correlations—particularly between RFD (0–30% of impulse time), peak impulse, velocity (30–60% of the CMJ), and performance in TKD-specific tests—underscore the importance of training the underlying eccentric–concentric transitions of technical actions. Enhancing elite performance therefore requires the integration of bilateral and unilateral exercises, eccentric overload, and plyometrics to develop RFD, impulse, and power concurrently. Future research should define optimal CMJ power profiles under varying loads, examine the effects of velocity-based strength programs to develop athlete-specific force–velocity profiles, and analyze fatigue-induced kinetic changes during repeated actions to delimit critical neuromuscular thresholds during simulated competitions.

5. Conclusions

Mean power output and impulse during the 0–30% phase derived from the unloaded CMJ demonstrated a significant impact on the sport-specific performance of national-team TKD athletes. Furthermore, variables such as RSImod, peak impulse, mean force, and RFD at 0–30% showed significant correlations, indicating their influence on sport-specific performance in this population. These variables appear to be key determinants both for sustaining repeated high-intensity kicking efforts and for optimizing change-of-direction performance. Overall, the present findings emphasize the importance of CMJ-derived kinetic determinants in enhancing athletic performance in elite TKD athletes.