The purpose of this study was to evaluate intrasession reliability of countermovement jump (CMJ) and isometric mid-thigh pull (IMTP) force–time characteristics, as well as relationships between CMJ and IMTP metrics. Division I sport and club athletes (n = 112) completed two maximal effort CMJ and IMTP trials, in that order, on force plates. Relative and absolute reliability were assessed using intraclass correlation coefficients (ICCs) > 0.80 and coefficients of variation (CVs) < 10%. Intrasession reliability was acceptable for the majority of the CMJ force–time metrics except for concentric rate of force development (RFD), eccentric impulse and RFD, and lower limb stiffness. The IMTP’s time to peak force, instantaneous force at 150 ms, instantaneous net force, and RFD measures were not reliable. Statistically significant weak to moderate relationships (r = 0.20–0.46) existed between allometrically scaled CMJ and IMTP metrics, with the exception of CMJ eccentric mean power not being related with IMTP performances. A majority of CMJ and IMTP metrics met acceptable reliability standards, except RFD measures which should be used with caution. Provided CMJs and IMTPs are indicative of distinct physical fitness capabilities, it is suggested to monitor athlete performance in both tests via changes in those variables that demonstrate the greatest degree of reliability.

Merrigan, JJ, Stone, JD, Galster, SM, and Hagen, JA. Analyzing force-time curves: Comparison of commercially available automated software and custom MATLAB analyses. J Strength Cond Res 36(9): 2387–2402, 2022—With the growing prevalence of commercial force plate solutions providing automated force-time curve analysis, it is critical to understand the level of agreement across techniques. Thus, this study directly compared commercial and custom software analyses across force-time curves. Twenty-four male and female subjects completed 6 trials of countermovement, squat, and drop jumps, and isometric mid-thigh pulls on the same force plate. Vertical ground reaction forces were analyzed by automated software from Vald Performance, Hawkin Dynamics, and custom MATLAB scripts. Trials were visually assessed to verify proper landmark identifications. Systematic and proportional bias among analyses were compared via least products regressions, Bland-Altman plots, and percent error. Hawkin Dynamics had subtle differences in analysis procedures and demonstrated low percent errors across all tests (<3% error), despite demonstrating systematic and proportional bias for several metrics. ForceDecks demonstrated larger percent differences and greater biases for several metrics. These errors likely result from different identification of movement initiation, system weight, and integration techniques, which causes error to subsequent landmark identifications (e.g., braking/propulsive phases) and respective force-time metrics. Many metrics were in agreement between devices, such as isometric mid-thigh pull peak force consistently within 1 N across analyses, but some metrics are difficult and incomparable across software analyses (i.e., rate of force development). Overall, many metrics were in agreement across each commercial software and custom MATLAB analyses after visually confirming landmarks. However, because of inconsistencies, it is important to only compare metrics that are in agreement across software analyses when absolutely necessary.

Human performance optimization of tactical personnel requires accurate, meticulous, and effective monitoring of biological adaptations and systemic recovery. Due to an increased understanding of its importance and the commercial availability of assessment tools, the use of heart rate variability (HRV) to address this need is becoming more common in the tactical community. Measuring HRV is a non-invasive, practical method for objectively assessing a performer’s readiness, workload, and recovery status; when combined with additional data sources and practitioner input, it provides an affordable and scalable solution for gaining actionable information to support the facilitation and maintenance of operational performance. This narrative review discusses the non-clinical use of HRV for assessing, monitoring, and interpreting autonomic nervous system resource availability, modulation, effectiveness, and efficiency in tactical populations. Broadly, HRV metrics represent a complex series of interactions resulting from internal and external stimuli; therefore, a general overview of HRV applications in tactical personnel is discussed, including the influence of occupational specific demands, interactions between cognitive and physical domains, and recommendations on implementing HRV for training and recovery insights into critical health and performance outcomes.

A necessarily high standard for physical readiness in tactical environments is often accompanied by high incidences of injury due to overaccumulations of neuromuscular fatigue (NMF). To account for instances of overtraining stimulated by NMF, close monitoring of neuromuscular performance is warranted. Previously validated tests, such as the countermovement jump, are useful means for monitoring performance adaptations, resiliency to fatigue, and risk for injury. Performing such tests on force plates provides an understanding of the movement strategy used to obtain the resulting outcome (e.g., jump height). Further, force plates afford numerous objective tests that are valid and reliable for monitoring upper and lower extremity muscular strength and power (thus sensitive to NMF) with less fatiguing and safer methods than traditional one-repetition maximum assessments. Force plates provide numerous software and testing application options that can be applied to military’s training but, to be effective, requires the practitioners to have sufficient knowledge of their functions. Therefore, this review aims to explain the functions of force plate testing as well as current best practices for utilizing force plates in military settings and disseminate protocols for valid and reliable testing to collect key variables that translate to physical performance capacities.

Merrigan, JJ, Strang, A, Eckerle, J, Mackowski, N, Hierholzer, K, Ray, NT, Smith, R, Hagen, JA, and Briggs, RA. Countermovement jump force-time curve analyses: reliability and comparability across force plate systems. J Strength Cond Res 38(1): 30–37, 2024—Considering the growing prevalence of commercial force plates providing automated force-time analyses, understanding levels of agreement across force plate systems is warranted. Countermovement jump (CMJ) metrics across Vald ForceDecks (FD), Hawkin Dynamics (HD), and Sparta Science (SS) force plate systems were compared. Twenty-two subjects completed CMJ testing (∼128 comparisons) on each force plate system separately with rest between jumps. Baseline testing occurred 3 times and demonstrated poor test-retest reliability for modified reactive strength index (mRSI) and rate of force development (RFD). ForceDecks and HD comparisons yielded acceptable agreement for concentric/propulsive relative force and net impulse, jump height, eccentric/braking RFD, and mRSI, but systematic and proportionate bias existed for RFD. Sparta Science jump height and reactive strength index (RSI) demonstrated systematic overestimations compared with HD and FD, but jump height had acceptable agreement according to concordance correlation coefficients (CCC = 0.92–0.95). Agreement between SS load (eccentric RFD) and HD braking RFD was acceptable (CCC = 0.91), whereas agreement between SS load and FD deceleration RFD was considered acceptable (CCC = 0.81–0.87) but demonstrated systematic and proportionate bias. ForceDecks (CCC = 0.89) and HD (CCC = 0.85) average relative concentric/propulsive force yielded acceptable agreement with SS explode (average relative concentric force), but SS explode demonstrated systematically lower values than FD and HD. Sparta Science drive (concentric impulse) yielded acceptable agreement with HD relative propulsive impulse (CCC = 0.85), but not FD concentric impulse. Human performance practitioners need to be aware of inconsistencies among testing procedures and analyses across force plate systems, such as differences in metric definitions and units of measurement, before making comparisons across systems.

Heart rate samples (n = 4500–8000) from wearables were compared to electrocardiography during a steady-state ruck (Ruck-S), maximal effort ruck (Ruck-M), submaximal cycle (Cycle), and Tabata Circuit. One device was worn at each location (wrist: Polar Grit-X, Garmin Fenix 6; chest-straps: Polar H10, Garmin HRM-Pro; armband: Polar Verity). Comparisons were made via percent error (MAPE) ≤5%, Concordance Correlation Coefficient (CCC), and ordinary least product regressions (OLP). H10 demonstrated strong agreement for all movements (MAPE = 1.28–3.40%, CCC = 0.93–0.99). During Ruck-S, Ruck-M, and Cycle, HRM-Pro (MAPE = 1.96–3.73%, CCC = 0.95–0.99) and Verity (MAPE = 1.84–5.36%, CCC = 0.98–0.99) demonstrated strong agreement. Fenix-6 demonstrated low MAPE (4.23–5.44%) and moderate to strong CCC (0.76–0.96) for Ruck-S, Ruck-M, and Cycle, while Grit-X had poor agreement (MAPE = 8.49–16.45%; CCC = 0.24–0.78). Tabata Circuit had the worst disagreement for all devices. Overall, chest straps and armbands demonstrated the strongest agreement, and should be worn when precise heart rate training is necessary.