Open AccessArticle Exploratory Associations Among Lower-Limb Strength, Selected Isokinetic Knee-Extension Variables, Countermovement Jump Flight Time, and Short-Duration Anaerobic Power in Healthy Male University Students 1 Physical Education Measurement and Evaluation Laboratory, Department of Human Sports, Kangwon National University, Samcheok 25913, Republic of Korea 2 Department of Human Sports, Kangwon National University, Samcheok 25913, Republic of Korea * Author to whom correspondence should be addressed. Appl. Sci. 2026, 16(11), 5623; https://doi.org/10.3390/app16115623 (registering DOI) Submission received: 4 May 2026 / Revised: 1 June 2026 / Accepted: 2 June 2026 / Published: 4 June 2026 Featured Application This exploratory study may help inform the selection of lower-limb performance tests for similar healthy male university-student samples by describing the overlap and complementarity among maximal dynamic strength, selected isokinetic knee-extension variables, countermovement jump (CMJ) flight time, and short-duration anaerobic power assessments. Abstract Background: Lower-limb performance is commonly assessed using maximal strength, isokinetic, jump, and anaerobic power tests, but whether these assessments provide overlapping or complementary information in healthy young adults without recent regular resistance training remains unclear. Methods: This exploratory cross-sectional secondary analysis examined associations among lower-limb maximal strength, selected isokinetic knee-extension variables, countermovement jump (CMJ) flight time, and 6 s Wingate peak power in 30 healthy male university students. Maximal dynamic strength was assessed using one-repetition maximum (1RM) tests for leg press, leg extension, and leg curl. Isokinetic knee function was evaluated using 60°/s knee extension peak torque and 180°/s knee extension total work. Pearson correlations, body-mass-adjusted partial correlations, and exploratory regression models were performed. Results: Leg press 1RM was strongly correlated with 6 s Wingate peak power, but not with CMJ flight time, in the zero-order analysis. After body-mass adjustment, leg press 1RM was associated with both outcomes. In exploratory regression models, leg press 1RM showed the most consistent associations, whereas the selected isokinetic variables showed less consistent relationships. Conclusions: In this exploratory sample, leg press 1RM showed the most consistent associations with the two performance outcomes examined, particularly 6 s Wingate peak power. The selected isokinetic knee-extension variables appeared to provide more joint-specific information. These findings should be interpreted as sample-specific associations, not as evidence that one test can predict or replace another. Keywords: lower-limb function; maximal strength; isokinetic strength; CMJ flight time; anaerobic power 1. Introduction Lower-limb performance is commonly assessed using several approaches, including one-repetition maximum (1RM) testing, isokinetic dynamometry, countermovement jump testing, and short-duration anaerobic power tests. Although these methods are widely used in sports science and exercise physiology, they do not necessarily represent identical physical or biomechanical domains. The 1RM test reflects maximal dynamic force-production capacity during resistance exercise, whereas isokinetic dynamometry provides joint-specific torque or work information under controlled angular velocities. Countermovement jump (CMJ) flight time provides a field-based outcome of lower-limb performance, although flight-time-based outcomes do not fully characterize the force-, impulse-, or technique-related components of jumping. Wingate-type protocols are used primarily to assess short-duration anaerobic power output. Therefore, these assessments may provide overlapping but non-identical information about lower-limb function [ 1]. Understanding the degree of overlap among these tests is important for interpreting lower-limb performance outcomes and for selecting testing batteries that are both informative and feasible. Previous studies have generally reported positive associations between lower-limb strength-related measures and selected jump or anaerobic power outcomes. In elite soccer players, maximal squat strength has been closely associated with sprint and vertical jump performance, whereas relative multi-joint strength may be more closely related to countermovement jump performance than absolute strength [ 2, 3]. Other studies have reported meaningful relationships among lower-limb strength, countermovement jump performance, and Wingate-derived anaerobic power in professional soccer players [ 4], while the magnitude of the strength–jump relationship may vary across sport contexts [ 5]. Evidence concerning isokinetic knee function is less consistent. For example, isokinetic quadriceps strength has been associated with Wingate peak power but not consistently with vertical jump performance in basketball players [ 6, 7]. Related work has also examined short-duration anaerobic power metrics and the relationships between jump-based and cycling-based power outcomes, further supporting the practical relevance of comparing these outcomes within the same testing battery [ 8, 9]. Collectively, these findings suggest that the degree of overlap among strength, isokinetic, jump, and anaerobic power tests may depend on the population studied and the specific variables selected. However, most available evidence has been derived from athletic populations, in whom sport-specific training history, neuromuscular specialization, and repeated exposure to performance testing may influence the observed relationships among assessment outcomes. Healthy male university students who have not recently engaged in regular resistance training represent a practically relevant but less specialized population for exercise testing, as they are frequently recruited in laboratory-based resistance-training and exercise-intervention studies. In such settings, test batteries often need to balance informativeness, participant burden, and feasibility. Relatively few studies have examined maximal dynamic strength, selected isokinetic knee-extension variables, CMJ flight time, and short-duration anaerobic power within the same healthy male university sample using a compact multicomponent test battery. In addition, the interpretation of these associations may differ depending on whether strength is considered in absolute terms, adjusted for body mass, or expressed relative to body mass. Therefore, the present exploratory cross-sectional secondary analysis aimed to examine associations among lower-limb maximal dynamic strength, selected isokinetic knee-extension variables, CMJ flight time, and 6 s Wingate peak power in healthy male university students. We specifically sought to characterize the extent to which these commonly used assessments showed overlapping versus complementary association patterns, while recognizing the exploratory and sample-specific nature of the analysis. These analyses were intended to inform interpretation and test selection in similar laboratory-based samples, rather than to establish normative values or predictive validity. 2. Materials and Methods 2.1. Study Design and Participants This study was an exploratory cross-sectional secondary analysis of pre-intervention baseline data obtained from an ongoing 8-week lower-limb resistance training project conducted at Kangwon National University, Samcheok Campus. Participants were recruited between 9 March and 23 March 2026, and baseline assessments were conducted during the same period. Healthy male university students aged 19 years or older were eligible for inclusion if they had not participated in regular resistance training during the previous 6 months and had no history of knee or lower-limb musculoskeletal injury. Participants were excluded if they had cardiovascular, respiratory, renal, or neurological disease; hypertension; thrombosis-related risk factors; recent lower-limb surgery; or any other condition considered unsuitable for exercise testing. During screening, participants were asked about recent regular exercise and training habits, and none reported regular resistance training during the previous 6 months. However, broader habitual physical activity levels and sport participation histories were not quantified using a standardized questionnaire in the parent study. A total of 30 participants were included in the present analysis. Because the present analysis used baseline data from the parent intervention study, the sample was not recruited specifically for a standalone predictive or normative study. The parent study protocol was approved by the Institutional Review Board of Kangwon National University (KWNUIRB-2026-01-004-001; approved on 5 March 2026). All participants provided written informed consent before participation. All procedures were conducted in accordance with the Declaration of Helsinki. 2.3. Statistical Analysis All statistical analyses were performed using IBM SPSS Statistics version 26.0 (IBM Corp., Armonk, NY, USA). Continuous variables are presented as mean ± standard deviation, median (interquartile range), and minimum–maximum values. Normality was assessed using the Shapiro–Wilk test. There were no missing data for the variables included in the present analysis. Analyses were organized into conceptually focused main analyses and exploratory sensitivity analyses. The main analyses focused on conceptually selected associations among multi-joint dynamic strength, selected isokinetic knee-extension variables, CMJ flight time, and 6 s Wingate peak power. Pearson correlation coefficients were used to examine bivariate associations and are reported with 95% confidence intervals calculated using Fisher’s z transformation. Because multiple exploratory correlations were examined, the Benjamini–Hochberg false discovery rate procedure was applied across all pairwise Pearson correlations in the complete exploratory correlation matrix. The unadjusted p values were retained to allow comparison with conventional correlation reporting, whereas the FDR-adjusted q values were used to guide the interpretation of exploratory correlations. This approach was chosen to improve transparency while reducing the risk of overinterpreting isolated nominally significant findings. Spearman correlation coefficients were additionally calculated as a sensitivity analysis because some strength variables showed mild non-normality, and the full Spearman correlation matrix was provided as Supplementary Material. To distinguish absolute strength, relative strength, and body-mass-adjusted associations, absolute values were used for the main presentation, while body-mass-normalized strength variables were examined in sensitivity analyses. Partial correlation analyses controlling for body mass were also conducted for selected conceptually relevant pairs of variables. Two exploratory multiple linear regression models were then constructed to examine independent cross-sectional associations. In Model 1, CMJ flight time was the dependent variable, with leg press 1RM, 60°/s knee extension peak torque, and body mass as independent variables. In Model 2, 6 s Wingate peak power was the dependent variable, with leg press 1RM, 180°/s knee extension total work, and body mass as independent variables. The selection of variables for these models was guided by their conceptual relevance to the measurement domains and by the need to maintain model parsimony given the modest sample size. No automated stepwise variable-selection procedure was used. Accordingly, one representative variable was selected from each relevant performance domain: leg press 1RM represented multi-joint dynamic lower-limb strength, 60°/s knee extension peak torque represented low-velocity maximal isokinetic torque, and 180°/s knee extension total work represented higher-velocity repeated isokinetic work. Body mass was included because it is mechanically relevant to both CMJ flight time and cycling peak-power outcomes and is commonly considered when interpreting absolute strength and power measures. These models were considered exploratory association models rather than formal prediction models. Regression assumptions were evaluated using residual plots, normal probability plots, standardized residuals, Cook’s distance, variance inflation factors, and tolerance values. Statistical significance was set at p < 0.05 for main analyses, whereas exploratory analyses emphasized effect sizes, 95% confidence intervals, FDR-adjusted results where applicable, and consistency across sensitivity analyses. Because this was a secondary baseline analysis, no formal a priori sample size calculation was conducted. A G*Power sensitivity analysis (version 3.1.9.7) indicated that, with α = 0.05, power = 0.80, three independent variables, and 30 participants, the regression models had adequate power only to detect relatively large overall effects; therefore, all regression results were interpreted as exploratory and hypothesis-generating. 3. Results 3.1. Participant Characteristics A total of 30 healthy male university students were included in this baseline cross-sectional analysis. Descriptive characteristics and baseline performance variables are presented in Table 1. The table summarizes demographic characteristics, body composition variables, maximal dynamic strength, selected isokinetic knee-extension outcomes, CMJ flight time, and 6 s Wingate peak power. Both mean ± SD and median (IQR) values are reported to provide a descriptive overview of the sample and to support interpretation of variables with mild deviations from normality. Leg press 1RM ( p = 0.004) and leg extension 1RM ( p = 0.043) showed significant deviations from normality based on the Shapiro–Wilk test, whereas the remaining variables did not show significant non-normality. 3.2. Pearson Correlations and Spearman Sensitivity Analysis Key Pearson correlation coefficients involving CMJ flight time and 6 s Wingate peak power are presented in Table 2. The complete exploratory Pearson correlation matrix is provided in Supplementary Table S1. In the full matrix, maximal dynamic strength variables were strongly interrelated, and several strength and isokinetic variables showed positive associations with 6 s Wingate peak power. Among the key performance-related associations, leg press 1RM showed a strong positive correlation with 6 s Wingate peak power (r = 0.729, 95% CI = 0.499 to 0.862, p < 0.001, q < 0.001), whereas its correlation with CMJ flight time was not statistically significant (r = 0.347, 95% CI = −0.015 to 0.629, p = 0.060, q = 0.071). Leg extension 1RM was correlated with both CMJ flight time (r = 0.402, 95% CI = 0.049 to 0.666, p = 0.028, q = 0.041) and 6 s Wingate peak power (r = 0.611, 95% CI = 0.321 to 0.796, p < 0.001, q = 0.001). The 60°/s extension peak torque was positively correlated with 6 s Wingate peak power (r = 0.511, 95% CI = 0.184 to 0.736, p = 0.004, q = 0.008), whereas its association with CMJ flight time was not statistically significant (r = 0.347, 95% CI = −0.015 to 0.629, p = 0.060, q = 0.071). The correlation between 180°/s extension total work and 6 s Wingate peak power was nominally significant before correction but did not remain significant after FDR adjustment (r = 0.367, 95% CI = 0.008 to 0.643, p = 0.046, q = 0.064). CMJ flight time was positively correlated with 6 s Wingate peak power (r = 0.468, 95% CI = 0.129 to 0.709, p = 0.009, q = 0.016). Spearman correlation analysis showed a generally similar pattern and is provided in Supplementary Table S2. The associations among the three 1RM variables and between strength variables and 6 s Wingate peak power were broadly consistent across Pearson and Spearman analyses. However, some associations involving CMJ flight time were weaker in the Spearman analysis, supporting the interpretation that the jump-related findings should be considered exploratory. 3.3. Body-Mass-Adjusted and Body-Mass-Normalized Analyses Partial correlations controlling for body mass are presented in Table 3. After adjustment for body mass, leg press 1RM remained positively associated with CMJ flight time (partial r = 0.562, 95% CI = 0.246 to 0.770, p = 0.002) and 6 s Wingate peak power (partial r = 0.648, 95% CI = 0.369 to 0.820, p < 0.001). The 60°/s extension peak torque also remained associated with CMJ flight time after adjustment for body mass (partial r = 0.451, 95% CI = 0.101 to 0.701, p = 0.014). In contrast, the association between 180°/s extension total work and 6 s Wingate peak power was attenuated and was not statistically significant after adjustment for body mass (partial r = 0.242, 95% CI = −0.137 to 0.559, p = 0.206). Sensitivity analyses using body-mass-normalized strength variables showed a similar pattern ( Supplementary Table S3). Relative leg press strength was associated with both CMJ flight time (Spearman ρ = 0.454, p = 0.012) and 6 s Wingate peak power (ρ = 0.531, p = 0.003). Normalized 60°/s extension peak torque was associated with CMJ flight time (ρ = 0.382, p = 0.037), whereas normalized 180°/s extension total work was not associated with 6 s Wingate peak power (ρ = 0.027, p = 0.889). 3.4. Exploratory Multiple Regression Models The exploratory multiple regression results are presented in Table 4. Visual inspection of residual plots and normal probability plots did not indicate major deviations from linearity, homoscedasticity, or residual normality. Regression diagnostics did not indicate substantial multicollinearity, with all variance inflation factor values below 1.80 and tolerance values above 0.556. Cook’s distance values were below 1.0 in both models, suggesting that no single observation exerted a disproportionate influence on the regression estimates. In Model 1, CMJ flight time was entered as the dependent variable, with leg press 1RM, 60°/s extension peak torque, and body mass entered as independent variables. The overall model was significant (R = 0.628, R 2 = 0.395, adjusted R 2 = 0.325, F(3, 26) = 5.647, p = 0.004). Leg press 1RM showed a positive independent association with CMJ flight time (B = 0.000518, 95% CI = 0.000078 to 0.000958, β = 0.495, p = 0.023), whereas body mass showed a negative independent association (B = −0.002697, 95% CI = −0.004420 to −0.000975, β = −0.561, p = 0.003). The 60°/s extension peak torque was not independently associated with CMJ flight time in this model (B = 0.000250, 95% CI = −0.000191 to 0.000692, β = 0.217, p = 0.255). In Model 2, 6 s Wingate peak power was entered as the dependent variable, with leg press 1RM, 180°/s extension total work, and body mass entered as independent variables. The overall model was significant (R = 0.748, R 2 = 0.559, adjusted R 2 = 0.509, F(3, 26) = 11.003, p < 0.001). Leg press 1RM showed a positive independent association with 6 s Wingate peak power (B = 2.015, 95% CI = 1.012 to 3.018, β = 0.628, p < 0.001). By contrast, 180°/s extension total work (B = 0.036, 95% CI = −0.064 to 0.137, β = 0.106, p = 0.465) and body mass (B = 1.951, 95% CI = −2.679 to 6.581, β = 0.132, p = 0.394) were not independently associated with 6 s Wingate peak power. 4. Discussion The present exploratory cross-sectional analysis examined the associations among maximal dynamic lower-limb strength, selected isokinetic knee-extension variables, CMJ flight time, and 6 s Wingate peak power in healthy male university students. The main finding was that leg press 1RM showed the most consistent associations with the selected jump and anaerobic power outcomes, particularly 6 s Wingate peak power. In contrast, the selected isokinetic knee-extension variables showed less consistent associations with CMJ flight time and 6 s Wingate peak power, especially after body-mass adjustment and in the exploratory regression models. These findings suggest that commonly used lower-limb performance tests may provide overlapping but non-identical information in this specific sample. However, they should be interpreted as exploratory associations rather than evidence of prediction, causation, or test substitution. The present findings are broadly consistent with previous studies showing that greater lower-limb strength is associated with selected jump- and power-related outcomes, although much of this evidence has been derived from athletic populations and should therefore be interpreted cautiously in relation to the present sample. Wisloff et al. reported strong associations between maximal squat strength and sprint and vertical jump performance in elite soccer players [ 2], while Boraczynski et al. demonstrated meaningful interrelationships among lower-limb strength, countermovement jump performance, and Wingate-derived anaerobic power [ 4]. More recent evidence further suggests that lower-limb strength capacities may be differentially associated with sport-specific acceleration and explosive tasks, highlighting the practical relevance of multi-joint dynamic strength assessments [ 14]. In the present sample, leg press 1RM showed the strongest association with 6 s Wingate peak power and remained independently associated with this outcome in the exploratory regression model. This result may reflect the shared lower-limb force-production demands of multi-joint resistance exercise and short-duration cycling power. Nevertheless, it should not be interpreted as showing that leg press 1RM can predict or replace Wingate testing. Rather, it indicates that multi-joint dynamic strength and short-duration cycling power share a meaningful degree of variance in this group. The relationship between strength measures and CMJ flight time was more complex. Leg press 1RM was not significantly correlated with CMJ flight time in the zero-order Pearson analysis, but the association became significant after adjustment for body mass. This pattern suggests that body mass may influence the interpretation of absolute strength–jump relationships. Because CMJ flight time reflects a task-level jump outcome rather than direct measures of force production, impulse, take-off mechanics, or countermovement strategy, the present findings should not be interpreted as a comprehensive biomechanical explanation of jump performance. Instead, they suggest that body-mass-adjusted strength measures may be more informative than absolute strength alone when interpreting flight-time-based countermovement jump outcomes in similar samples. From an applied perspective, the present findings may help inform test selection in similar healthy male university samples. The results suggest that leg press 1RM and 6 s Wingate peak power may capture partly overlapping aspects of lower-limb performance, whereas selected isokinetic knee-extension variables may provide more joint-specific information. However, these findings do not imply that one test can replace another. Instead, they support the use of test batteries selected according to the specific evaluation purpose. When whole-body short-duration power-related performance is of interest, multi-joint strength and anaerobic cycling outcomes may be particularly relevant. When joint-specific knee function is of interest, isokinetic dynamometry remains informative. This interpretation is supported by recent reviews emphasizing that lower-limb strength and power assessment should combine standardized core tests with context-specific measures, rather than relying on a single universal battery [ 21]. In the same context, methodological reviews have shown that even when force platforms are used, jump-height outcomes can vary substantially depending on the equation applied, indicating that testing efficiency should be considered together with outcome-definition consistency [ 22]. 5. Conclusions Among healthy male university students, maximal dynamic strength, particularly leg press 1RM, showed the most consistent associations with the two performance outcomes examined, especially 6 s Wingate peak power. In contrast, the selected isokinetic knee-extension variables showed less consistent associations with CMJ flight time and 6 s Wingate peak power, particularly after body-mass adjustment and in the exploratory regression models. These findings suggest that commonly used lower-limb performance tests provide overlapping but non-identical information in this sample. Leg press 1RM and 6 s Wingate peak power may capture partly shared aspects of multi-joint lower-limb performance, whereas selected isokinetic knee-extension variables may provide more joint-specific information. Given the modest sample size and cross-sectional secondary-analysis design, these findings should be interpreted as exploratory and sample-specific associations rather than evidence of prediction, causation, or test substitution. Therefore, lower-limb assessment methods should be selected according to the specific purpose of evaluation. Supplementary Materials The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/app16115623/s1, Table S1: Complete Pearson correlation matrix with 95% confidence intervals, p values, and FDR-adjusted q values; Table S2: Complete Spearman correlation matrix; Table S3: Spearman correlations between body-mass-normalized strength variables and raw performance outcomes. Author Contributions Conceptualization, T.Z. and W.S.; methodology, T.Z., J.X., J.R., D.K. and W.S.; formal analysis, T.Z.; investigation, T.Z., J.X., J.R. and D.K.; data curation, T.Z.; writing—original draft preparation, T.Z.; writing—review and editing, T.Z., J.X., J.R., D.K. and W.S.; supervision, W.S.; project administration, W.S. All authors have read and agreed to the published version of the manuscript. Funding This research received no external funding. Institutional Review Board Statement The study was conducted in accordance with the Declaration of Helsinki and approved by the Institutional Review Board of Kangwon National University (KWNUIRB-2026-01-004-001; approved on 5 March 2026). Informed Consent Statement Written informed consent was obtained from all participants involved in the study. Data Availability Statement The data presented in this study are available from the corresponding author upon reasonable request. 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Variable Mean ± SD Median (IQR) Range Shapiro–Wilk pAge (years) ୨୨.୩୩ ବ୍ଦ ୨.୨୯ 22.00 (2.00) 19–27 0.060 Height (cm) ୧୭୬.୬୦ ବ୍ଦ ୪.୯୮ 178.00 (8.00) 168–187 0.118 Body mass (kg) ୭୭.୦୪ ବ୍ଦ ୧୧.୨୧ 74.30 (14.00) 55–107 0.415 BMI (kg/m 2) ୨୪.୭୦ ବ୍ଦ ୩.୪୮ 24.04 (4.78) 18.67–33.74 0.738 Skeletal muscle mass (kg) ୩୩.୭୪ ବ୍ଦ ୩.୭୮ 33.90 (4.07) 27.50–42.10 0.276 Leg press 1RM (kg) ୧୬୪.୬୭ ବ୍ଦ ୫୧.୫୧ 150.00 (72.50) 100.00–300.00 0.004 Leg extension 1RM (kg) ୬୩.୧୩ ବ୍ଦ ୧୭.୦୧ 62.00 (31.00) 40.00–92.00 0.043 Leg curl 1RM (kg) ୫୪.୧୭ ବ୍ଦ ୧୦.୯୧ 55.00 (20.00) 25.00–70.00 0.089 60°/s extension peak torque (Nm) ୧୬୩.୧୦ ବ୍ଦ ୪୬.୬୬ 151.45 (69.63) 84.10–269.40 0.188 180°/s extension total work (J) ୧୯୦୬.୦୧ ବ୍ଦ ୪୮୧.୧୫ 1862.30 (865.45) 1173.40–2888.30 0.263 CMJ flight time (s) ୦.୪୯୮ ବ୍ଦ ୦.୦୫୪ 0.502 (0.078) 0.394–0.632 0.799 6 s Wingate peak power (W) ୬୫୨.୧୩ ବ୍ଦ ୧୬୫.୨୨ 623.50 (209.25) 399.00–1059.00 0.112 Note: Data are mean ± SD, median (IQR), and range. Normality was assessed using the Shapiro–Wilk test. BMI, body mass index; 1RM, one-repetition maximum; SD, standard deviation; IQR, interquartile range. Table 2. Key Pearson correlations with CMJ flight time and 6 s Wingate peak power. Table 2. Key Pearson correlations with CMJ flight time and 6 s Wingate peak power. Variable Pair r 95% CI p FDR q Leg press 1RM vs. CMJ flight time 0.347 −0.015 to 0.629 0.060 0.071 Leg press 1RM vs. 6 s Wingate peak power 0.729 0.499 to 0.862 <0.001 <0.001 Leg extension 1RM vs. CMJ flight time 0.402 0.049 to 0.666 0.028 0.041 Leg extension 1RM vs. 6 s Wingate peak power 0.611 0.321 to 0.796 <0.001 0.001 Leg curl 1RM vs. CMJ flight time 0.122 −0.249 to 0.462 0.520 0.546 Leg curl 1RM vs. 6 s Wingate peak power 0.530 0.209 to 0.747 0.003 0.006 60°/s extension peak torque vs. CMJ flight time 0.347 −0.015 to 0.629 0.060 0.071 60°/s extension peak torque vs. 6 s Wingate peak power 0.511 0.184 to 0.736 0.004 0.008 180°/s extension total work vs. CMJ flight time 0.036 −0.328 to 0.391 0.850 0.850 180°/s extension total work vs. 6 s Wingate peak power 0.367 0.008 to 0.643 0.046 0.064 CMJ flight time vs. 6 s Wingate peak power 0.468 0.129 to 0.709 0.009 0.016 Note: Values are Pearson correlation coefficients. Confidence intervals were calculated using Fisher’s z transformation. FDR q values were calculated using the Benjamini–Hochberg false discovery rate procedure based on all correlations in the full exploratory Pearson correlation matrix. The complete Pearson correlation matrix is provided in Supplementary Table S1. 1RM, one-repetition maximum; CI, confidence interval; FDR, false discovery rate. Table 3. Partial correlations among key lower-limb performance variables controlling for body mass. Table 3. Partial correlations among key lower-limb performance variables controlling for body mass. Variable Pair Partial r 95% CI p Leg press 1RM vs. CMJ flight time 0.562 0.246 to 0.770 0.002 Leg press 1RM vs. 6 s Wingate peak power 0.648 0.369 to 0.820 <0.001 60°/s extension peak torque vs. CMJ flight time 0.451 0.101 to 0.701 0.014 180°/s extension total work vs. 6 s Wingate peak power 0.242 −0.137 to 0.559 0.206 Note: Partial correlations were adjusted for body mass. Confidence intervals were calculated using Fisher’s z transformation. 1RM, one-repetition maximum; CI, confidence interval. Table 4. Exploratory multiple linear regression models for CMJ flight time and 6 s Wingate peak power. Table 4. Exploratory multiple linear regression models for CMJ flight time and 6 s Wingate peak power. Model Independent Variable B SE 95% CI for B Std. β p VIF Model 1 Leg press 1RM 0.000518 0.000214 0.000078 to 0.000958 0.495 0.023 1.798 Model 1 60°/s extension peak torque 0.000250 0.000215 −0.000191 to 0.000692 0.217 0.255 1.487 Model 1 Body mass −0.002697 0.000838 −0.004420 to −0.000975 −0.561 0.003 1.307 Model 2 Leg press 1RM 2.015 0.488 1.012 to 3.018 0.628 <0.001 1.366 Model 2 180°/s extension total work 0.036 0.049 −0.064 to 0.137 0.106 0.465 1.195 Model 2 Body mass 1.951 2.253 −2.679 to 6.581 0.132 0.394 1.379 Note: Model 1: dependent variable = CMJ flight time; R = 0.628, R 2 = 0.395, adjusted R 2 = 0.325, F(3, 26) = 5.647, p = 0.004. Model 2: dependent variable = 6 s Wingate peak power; R = 0.748, R 2 = 0.559, adjusted R 2 = 0.509, F(3, 26) = 11.003, p < 0.001. CI, confidence interval; 1RM, one-repetition maximum; VIF, variance inflation factor. Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content. © 2026 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license. Share and Cite MDPI and ACS Style Zhao, T.; Xia, J.; Ryu, J.; Kim, D.; Son, W. Exploratory Associations Among Lower-Limb Strength, Selected Isokinetic Knee-Extension Variables, Countermovement Jump Flight Time, and Short-Duration Anaerobic Power in Healthy Male University Students. Appl. Sci. 2026, 16, 5623. https://doi.org/10.3390/app16115623 AMA Style Zhao T, Xia J, Ryu J, Kim D, Son W. Exploratory Associations Among Lower-Limb Strength, Selected Isokinetic Knee-Extension Variables, Countermovement Jump Flight Time, and Short-Duration Anaerobic Power in Healthy Male University Students. Applied Sciences. 2026; 16(11):5623. https://doi.org/10.3390/app16115623 Zhao, Tianqi, Junwei Xia, JiKwang Ryu, Dohun Kim, and Wonil Son. 2026. "Exploratory Associations Among Lower-Limb Strength, Selected Isokinetic Knee-Extension Variables, Countermovement Jump Flight Time, and Short-Duration Anaerobic Power in Healthy Male University Students" Applied Sciences 16, no. 11: 5623. https://doi.org/10.3390/app16115623 Zhao, T., Xia, J., Ryu, J., Kim, D., & Son, W. (2026). Exploratory Associations Among Lower-Limb Strength, Selected Isokinetic Knee-Extension Variables, Countermovement Jump Flight Time, and Short-Duration Anaerobic Power in Healthy Male University Students. Applied Sciences, 16(11), 5623. https://doi.org/10.3390/app16115623 Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here. Article Metrics Article metric data becomes available approximately 24 hours after publication online.
