1. Introduction
Upper-body muscular power is a fundamental determinant of athletic performance across a wide spectrum of sports, including combat sports, swimming, throwing events, gymnastics, and rugby, and its accurate assessment carries direct implications for talent identification, training program evaluation, and fatigue monitoring in competitive populations [
1,
2,
3]. In contrast to the extensive body of literature characterizing lower-body explosive capacity through vertical jump testing, the evaluation of upper-body power remains methodologically less mature, constrained by a comparatively smaller number of validated assessment tools and by longstanding conceptual inconsistencies in how those tools are applied and interpreted. The principal challenge is the absence of a standardized, field-deployable test that is simultaneously physically valid, analytically tractable, and free of systematic measurement bias. Addressing that challenge requires not only sound instrumentation but also a mechanically accurate kinematic model capable of translating raw observational data, such as flight time, into performance indices that correctly represent the underlying physics of upper-body ballistic motion.
The most widely established methods for assessing upper-body explosive power are the seated medicine ball throw, the bench press throw, and, more recently, the ballistic push-up (BPU). Each presents logistical or conceptual limitations. The medicine ball throw requires an arbitrary choice of implement mass and has demonstrated modest correlations with force-plate-derived power in certain populations [
4]. The bench press throw is typically executed in a Smith machine and requires a Smith machine fixture and continuous spotter presence, substantially restricting its use in large-scale field testing [
5]. The BPU has attracted growing attention precisely because it requires no specialized equipment beyond a force plate or contact mat, recruits the same musculature as the bench press, and generates a measurable flight phase during which both hands lose contact with the ground simultaneously. Wang et al. [
4] demonstrated that force-time-derived performance measures from the BPU, including peak force, mean force, net impulse, and peak velocity, exhibited moderate to very high test-retest reliability (ICC = 0.849–0.971) across 60 recreationally active men, and that BPU-derived mean force predicted one-repetition maximum bench press with R
2 = 0.837. Bartolomei et al. [
5] subsequently confirmed that the BPU provides power estimates comparable to those of the bench press throw, with very large to extremely large correlations (r = 0.70–0.89) between the two methods, without requiring a Smith machine or spotter infrastructure.
The biomechanical complexity of the plyometric push-up fundamentally distinguishes it from vertical jump-based assessment paradigms. Unlike the vertical jump, where the center of mass follows a predominantly rectilinear trajectory under gravitational deceleration, the plyometric push-up involves segmental rotation about a fixed ankle pivot, such that the hands, the shoulders, and the center of mass all trace curvilinear arcs throughout the flight phase. This constraint imposes pendular mechanics on the motion, rendering the equations of purely vertical ballistic flight physically inappropriate for quantifying hand displacement, maximum height, and take-off velocity from a measured flight time. Additionally, the stretch-shortening cycle dynamics of the upper extremities differ from their lower-body counterparts due to distinct muscle architecture, neural activation patterns, and the contribution of trunk and core musculature to proximal force transmission, all of which introduce analytical complexities absent from conventional jump models [
6,
7].
Despite these recognized characteristics, the kinematic model universally applied to BPU flight-phase scoring continues to treat the body as a freely falling point mass, yielding t
flight=2V
0/g and h
max=V
02/2g. This free-fall approach is appropriate for the vertical jump but introduces a structural error of compounding magnitude when applied to a rotationally constrained movement. Sha and Dai [
8] demonstrated, using a two-platform reference method, that single-platform methods overestimated whole-body velocities by approximately 54% (1.39 ± 0.37 m/s vs. 0.90 ± 0.23 m/s, Cohen’s d = 1.59, p < 0.05) and power by approximately 58% (1.63 ± 0.47 vs. 1.03 ± 0.29 W/body weight, Cohen’s d = 1.49, p < 0.05) relative to a two-force-platform reference method. Wang et al. [
4] separately identified that flight time alone accounted for only 43% of the variance in peak take-off velocity (r = 0.656), with arm length differences across individuals cited as a principal source of unexplained residual variance; the free-fall model provides no mechanism to correct for this geometry-dependent heterogeneity. Dhahbi et al. [
6], in a comprehensive systematic review of push-up kinetics, explicitly identified the validity of power output calculations in explosive push-ups as a contested issue and recommended that methodological rigor be prioritized when quantifying mechanical work and power from flight-phase data.
Despite these recognized limitations, no published study has developed a formally derived mechanical model that replaces the free-fall simplification with a physically appropriate description of the rotational flight-phase trajectory of the plyometric push-up. The present study addresses this gap by formulating a rigid-body pendulum model that treats the body as a single-link pendulum pivoting about the ankle. Specifically, this investigation aimed to: (i) derive the effective pendulum length from two independent anthropometric frameworks and establish their mathematical equivalence; (ii) determine the flight time of the hands and the whole-body center of mass through analytically and numerically validated expressions; (iii) calculate the arc displacement of the hands and center of mass along their respective circular trajectories; (iv) quantify the maximum vertical height reached by both reference points from the measured take-off velocity; and (v) establish and numerically quantify the systematic divergence between free-fall and pendulum model predictions of flight time and maximum height across the full physiologically admissible parameter space.
5. Discussion
The present investigation introduced a novel pendulum-based mechanical framework for characterizing the flight-phase kinematics of the plyometric push-up, and the simulation results provide strong analytical evidence in support of its validity as a physically accurate model. The central finding is that the body, when conceptualized as a rigid pendulum rotating about the fixed ankle pivot, traces a curvilinear arc rather than a vertical trajectory during the flight phase. Consequently, performance parameters derived from the pendulum model, including flight time (tH), maximum arc displacement (Shand, SG), and maximum vertical height (hmax,H, hmax), differ systematically and substantially from the predictions of the conventional free-fall framework. Both derivation pathways operationalize the same static rotational equilibrium condition about O and converge to L = (MW/M) LOS as a mathematical consequence of that shared premise. The reconciliation confirms internal self-consistency rather than independent empirical corroboration, and its value lies in demonstrating that the effective pendulum length is a torque-equivalent parameter rather than a Euclidean positional distance (equation 14). The deviation between the Euclidean distance dOG and the dynamic length L is proportional to (1− cosθ0), which remains below 4% for initial pendulum angles θ0 ≤ 16°, encompassing the anatomical range of virtually all adult push-up configurations. This finding justifies the use of a simplified two-point mass model in field settings without meaningful loss of mechanical accuracy.
The kinematic equivalence demonstrated in equation (24), namely tH = tG, carries substantial methodological significance. It confirms that the flight time measured under the hands by a force platform or contact mat is precisely equal to the flight time of the whole-body center of mass, a property that is trivially satisfied in a rigid-body pendulum but is not guaranteed, and is indeed violated, in multi-segment models where the endpoint and center of mass follow different temporal trajectories. This result is consistent with the rigid-body constraint and rationalizes the use of contact-mat flight time as an operationally valid proxy for center-of-mass kinematics in field conditions, provided the rigid-body assumption holds approximately across the flight phase.
The simulation results detailed in
Section 4.1 and
Section 4.2 quantify, for the first time in a systematic and analytically grounded manner, the extent to which the free-fall simplification misrepresents the biomechanics of the plyometric push-up. For a pendulum arm length of L
OW = 1.00 m, representative of an adult male of average stature, the absolute flight time overestimation (Δt = t
FF − t
H) reached 0.016 s at V
H,0 = 1.50 m/s and 0.082 s at V
H,0 = 3.00 m/s, the latter representing a relative error of 13.4% relative to the free-fall estimate. Given that time-based power prediction equations in the plyometric push-up literature use flight time directly as a predictor variable [
4], with reported equations of the form P
peak = 11.0 × M + 2012.3 × t
flight − 338.0 (R
2 = 0.658, SEE = 150 W), a systematic overestimation of tflight in the range of 7–13% translates directly into non-trivial overestimations of power output that grow with athletic performance level. For t
flight ≈ 0.35 s, a 10% overestimation yields Δt
flight ≈ 0.035 s, corresponding to a power overestimation of approximately 70 W from the Wang et al. [
4] regression equation. Given that equation’s standard error of estimate (SEE = 150 W), this correction approaches but does not exceed the regression’s inherent residual uncertainty; its practical significance therefore depends on the precision demands of the specific monitoring application. This finding aligns with the broader methodological critique raised by Dhahbi et al. [
9], who identified systematic biases in force-plate-based power calculations when the rotational nature of the push-up trajectory is ignored, and by Sha and Dai [
8], who demonstrated that a single-force-platform method overestimated whole-body velocities by 54.4% (1.39 ± 0.37 m/s vs. 0.90 ± 0.23 m/s, Cohen’s d = 1.59, p < 0.05) and power by 58.3% (1.63 ± 0.47 vs. 1.03 ± 0.29 W/body weight, Cohen’s d = 1.49, p < 0.05) relative to a two-platform reference method.
The maximum height analysis (
Section 4.2) confirms an analogous overestimation pattern when t
flight serves as the primary experimental input. For L
OW = 0.50 m, the free-fall model overestimated h
max by 18.2% at t
flight = 0.30 s and by 28.4% at t
flight = 0.50 s. For L
OW = 1.00 m, the overestimation reached 23.6% at t
flight = 0.60 s. The counterintuitive finding that shorter pendulum arm lengths generate proportionally larger Δh values at equivalent flight times reflects the higher angular excursion per unit of arm radius executed by shorter pendulums, which amplifies the non-vertical component of the trajectory and consequently increases the discrepancy between rectilinear and curvilinear vertical displacement. This result complements the findings of Wang et al. [
4], who reported that only 43% of the variance in peak velocity could be explained by flight time alone (r = 0.656), attributing part of this unexplained variance to differences in arm length across subjects. The pendulum model provides a mechanistic explanation for that observation: individuals with shorter effective arm lengths (L
OW) will generate greater Δh errors for a given t
flight, producing systematic heterogeneity in the population-level relationship between t
flight and take-off velocity that a purely linear regression model cannot fully capture.
It is further noteworthy that the free-fall model’s error is not constant across the performance distribution but grows nonlinearly with initial velocity. This implies that elite athletes, who produce the highest V
H,0 values, are precisely those for whom the free-fall simplification generates the greatest absolute and relative errors, a characteristic that renders the model least trustworthy in the upper performance strata where measurement precision is most consequential for training program individualization. Bartolomei et al. [
5] reached a parallel conclusion in their comparison of the bench press throw and ballistic push-up, noting that time-based power indices produced systematic biases not observed with velocity-based measures, and recommended that flight-time-based predictions be used with caution. The present framework provides a formal mechanical basis for that recommendation.
The pendulum model provides a structurally sound and computationally accessible framework for correcting the systematic overestimation bias that characterizes all flight-time-based power assessments of the plyometric push-up. The model requires only four anthropometric measurements, total body mass (M), hand-supported mass (M
W), shoulder height (L
OS), and upper-limb length (L
SW), all obtainable in field conditions without specialized instrumentation. These parameters collectively determine the two governing geometric quantities, L and θ
0, from which all performance indices are derived analytically. The reliability of flight time as a force-plate-derived variable has been well established, with reported ICC values ranging from 0.80 to 0.96 across trained and sub-elite populations [
1,
2], and the present model does not alter the measurement protocol for t
flight, but rather transforms the raw flight-time value through a physically consistent kinematic model prior to performance index calculation. This approach could therefore be adopted without modification of existing testing infrastructure in laboratories or field settings using contact mats, portable force plates, or accelerometry-based devices.
The dual analytical framework presented in
Section 3.2 and
Section 3.3 provides practitioners and researchers with two complementary performance indices referenced either to the hands (experimentally primary) or to the center of mass (physiologically primary). The power equations at both levels (equations 34 and 46) incorporate the pendulum arm lengths and total system mass, enabling individualized computation of mean mechanical power output that accounts for body geometry, a correction absent from currently published prediction equations. Furthermore, the parametric sensitivity demonstrated in the simulations confirms that body-size normalization of power output should incorporate L
OW as a covariate in addition to body mass, given that h
max and S
hand are explicit functions of L
OW. The present model provides the mechanical basis for constructing such geometry-adjusted normalization equations, which would reduce inter-individual variability in performance comparisons across populations differing in stature.
The study has several limitations that must be acknowledged. The rigid-body assumption precludes the modeling of inter-segmental joint motion during the flight phase, particularly at the hip and shoulder, which may introduce deviations from the predicted pendular trajectory in subjects who do not maintain strict body tension. The two-point mass model for CoM location introduces positional errors proportional to (1 − cosθ
0), which, while small for typical push-up configurations, may become meaningful for subjects with unusually large L
SW/L
OS ratios. More consequentially, the use of simple pendulum dynamics, where I
O = M·L
2, neglects the rotational inertia contribution ICoM of the distributed body mass about its own center of mass. The physically correct equivalent pendulum length, L
eq = I
O/(M·L
CoM), exceeds L by I
CoM/(M·L
CoM); for a uniform-rod approximation of the body this implies L
eq/L ≈ 1.11–1.33 across physiological anthropometry [
10]. This systematic underestimation of Leq by the simple pendulum formulation results in underestimation of the predicted flight time relative to the physically correct compound pendulum, partially offsetting but not canceling the overestimation attributed to the free-fall model. Future formulations should incorporate measured segmental inertia parameters to quantify the net bias. The quarter-period approximation for push-off duration (equations 33 and 45) is valid only in the small-angle limit and should be replaced by numerical integration from the full pendulum equation for high-velocity conditions, as addressed in
Section 4. No experimental validation against force-plate kinematics or motion capture was performed. The present study is a theoretical-computational investigation; numerical agreement between quadrature and ODE implementations (maximum discrepancy < 2.5×10
−7 s) establishes computational self-consistency, not mechanical validity relative to observed human kinematics. The model’s accuracy advantage over the free-fall simplification, in absolute terms against empirical ground-truth data, remains to be established by prospective validation studies employing dual force plates synchronized with three-dimensional motion capture across representative anthropometric samples; prospective validation studies comparing pendulum-model predictions against two-force-platform reference measurements across a range of body sizes and performance levels are required to establish the empirical boundaries of the model’s accuracy.
Future investigations should extend the pendulum framework to accommodate: (i) variable initial angles across anthropometric groups to establish population-level normative corrections; (ii) sex-specific anthropometric inputs, given that the MW/M ratio and LOS differ systematically between males and females; (iii) integration with inertial measurement unit (IMU) wearable technology to enable real-time angular velocity capture at the ankle, which would allow direct validation of ω0 and therefore of all derived performance indices; and (iv) longitudinal designs examining the sensitivity of the pendulum-model indices to training-induced changes in upper-body power, to determine their practical utility as performance monitoring tools across competitive seasons.
Practical Recommendations
Practitioners applying flight-time-based protocols to assess upper-body power during the plyometric push-up should incorporate the four anthropometric measurements required by the pendulum model (M, M
W, L
OS, L
SW) into their standard testing battery. These measurements require no additional instrumentation beyond a precision scale placed sequentially under the feet and under the hands in the static push-up position, and a segmental length measurement tape. Once obtained, L
OW and L can be computed algebraically and used to convert measured flight times into pendulum-consistent take-off velocities via the numerical inversion procedure described in
Section 4.2, from which corrected maximum height and power output indices follow directly. For monitoring purposes across training cycles, reported ICC values of 0.80–0.96 for force-plate-derived flight time [
1,
2] confirm that t
H is sufficiently reliable to detect meaningful performance changes when the underlying biomechanical model is correctly specified [
11]. Flight-time-based power prediction equations [
4] should be recalibrated using pendulum-consistent velocity values rather than free-fall-derived velocities to eliminate the systematic bias that otherwise produces disproportionate overestimation at high performance levels.