The Battle of the Equations: A Systematic Review of Jump Height Calculations Using Force Platforms.

Vertical jump height measures our ability to oppose gravity and lower body neuromuscular function in athletes and various clinical populations. Vertical jump tests are principally simple, time-efficient, and extensively used for assessing athletes and generally in sport science research. Using the force platform for jump height estimates is increasingly popular owing to technological advancements and its relative ease of use in diverse settings. However, ground reaction force data can be analyzed in multiple ways to estimate jump height, leading to distinct outcome values from the same jump. In the literature, four equations have been commonly described for estimating jump height using the force platform, where jump height can vary by up to ∼ 15 cm when these equations are used on the same jump. There are advantages and disadvantages to each of the equations according to the intended use. Considerations of (i) the jump type, (ii) the reason for testing, and (iii) the definition of jump height should ideally determine which equation to apply. The different jump height equations can lead to confusion and inappropriate comparisons of jump heights. Considering the popularity of reporting jump height results, both in the literature and in practice, there is a significant need to understand how the different mathematical approaches influence jump height. This review aims to investigate how different equations affect the assessment of jump height using force platforms across various jump types, such as countermovement jumps, squat jumps, drop jumps, and loaded jumps.

Precision and accuracy of four handheld blood lactate analyzers across low to high exercise intensities.

PURPOSE: To evaluate the precision and accuracy in measured blood lactate concentrations among four commonly used handheld lactate analyzers compared to two stationary analyzers. METHODS: Venous blood samples were taken at exercise intensities ranging from low to high. The blood lactate concentration was measured simultaneously with four pairs of handheld lactate analyzers (two new units of each brand: Lactate Plus, Lactate Pro2, Lactate Scout 4, and TaiDoc TD-4289), and compared with two stationary analyzers (Biosen C-Line and YSI Sport 1500). Measurements were repeated for a range of blood lactate concentrations (measured with Biosen) from 0.88 to 4.89 mM with a median difference between measurements of 0.10 mM. RESULTS: The mean relative differences to the Biosen analyzer were - 7% (Plus), 7% (Pro), - 10% (Scout), 42% (Tai), and - 32% (Ysi). The residual standard errors after linear regression against Biosen were 0.18 mM (Plus), 0.20 mM (Pro), 0.22 mM (Scout), 0.15 mM (Tai), and 0.06 mM (Ysi). Accordingly, a blood lactate concentration of 3 mM measured with Biosen yielded 95% prediction intervals that were 0.72 mM (Plus), 0.80 mM (Pro), 0.87 mM (Scout), 0.60 mM (Tai), and 0.23 mM (Ysi) wide. CONCLUSION: Compared to our two stationary analyzers, the precision of the four handheld lactate analyzers evaluated in this study was poor. Among the four, Tai was the most precise; however, this analyzer had low accuracy with a substantial mean difference to the reference analyzer.

Strength and Power Testing of Athletes: Associations of Common Assessments Over Time.

PURPOSE: This study examined the associations among common assessments for measuring strength and power in the lower body of high-performing athletes, including both cross-sectional and longitudinal data. METHODS: A total of 100 participants, including both male (n = 83) and female (n = 17) athletes (21 [4] y, 182 [9] cm, 78 [12] kg), were recruited for the study using a multicenter approach. The participants underwent physical testing 4 times. The first 2 sessions (1 and 2) were separated by ∼1 week, followed by a period of 2 to 6 months, whereas the last 2 sessions (3 and 4) were also separated by ∼1 week. The test protocol consisted of squat jumps, countermovement jumps, jump and reach, 30-m sprint, 1-repetition-maximum squat, sprint cycling, and a leg-press test. RESULTS: There were generally acceptable correlations among all performance measures. Variables from the countermovement jumps and leg-press power correlated strongly with all performance assessments (r = .52-.79), while variables from sprint running and squat-jump power displayed more incoherent correlations (r = .21-.82). For changes over time, the correlations were mostly strong, albeit systematically weaker than for cross-sectional measures. CONCLUSIONS: The associations observed among the performance assessments seem to be consistent for both cross-sectional data and longitudinal change scores. The weaker correlations for change scores are most likely mainly caused by lower between-subjects variations in the change scores than for the cross-sectional data. The present study provides novel information, helping researchers and practitioners to better interpret the relationships across common performance assessment methods.

Strength and Power Testing of Athletes: A Multicenter Study of Test-Retest Reliability.

PURPOSE: This study examined the test-retest reliability of common assessments for measuring strength and power of the lower body in high-performing athletes. METHODS: A total of 100 participants, including both male (n = 83) and female (n = 17) athletes (21 [4] y, 182 [9] cm, and 78 [12] kg), were recruited for this study, using a multicenter approach. The participants underwent physical testing 4 times. The first 2 sessions (1 and 2) were separated by ∼1 week, followed by a period of 2 to 6 months, whereas the last 2 sessions (3 and 4) were again separated by ∼1 week. The test protocol consisted of squat jumps, countermovement jumps, jump and reach, 30-m sprint, 1-repetition-maximum squat, sprint cycling, and a leg-press test. RESULTS: The typical error (%) ranged from 1.3% to 8.5% for all assessments. The change in means ranged from -1.5% to 2.5% for all assessments, whereas the interclass correlation coefficient ranged from .85 to .97. The smallest worthwhile change (0.2 of baseline SD) ranged from 1.2% to 5.0%. The ratio between the typical error (%) and the smallest worthwhile change (%) ranged from 0.5 to 1.2. When observing the reliability across testing centers, considerable differences in reliability were observed (typical error [%] ratio: 0.44-1.44). CONCLUSIONS: Most of the included assessments can be used with confidence by researchers and coaches to measure strength and power in athletes. Our results highlight the importance of controlling testing reliability at each testing center and not relying on data from others, despite having applied the same protocol.

Validity of Force-Velocity Profiling Assessed With a Pneumatic Leg Press Device.

PURPOSE: The aim of this study was to examine the concurrent validity of force-velocity (FV) variables assessed across 5 Keiser leg press devices. METHODS: A linear encoder and 2 independent force plates (MuscleLab devices) were mounted on each of the 5 leg press devices. A total of 997 leg press executions, covering a wide range of forces and velocities, were performed by 14 participants (29 [7] y, 181 [5] cm, 82 [8] kg) across the 5 devices. Average and peak force, velocity, and power values were collected simultaneously from the Keiser and MuscleLab devices for each repetition. Individual FV profiles were fitted to each participant from peak and average force and velocity measurements. Theoretical maximal force, velocity, and power were deduced from the FV relationship. RESULTS: Average and peak force and velocity had a coefficient of variation of 1.5% to 8.6%, near-perfect correlations (.994-.999), and a systematic bias of 0.7% to 7.1% when compared with reference measurements. Average and peak power showed larger coefficient of variations (11.6% and 17.2%), despite excellent correlations (.977 and .952), and trivial to small biases (3.9% and 8.4%). Extrapolated FV variables showed near-perfect correlations (.983-.997) with trivial to small biases (1.4%-11.2%) and a coefficient of variation of 1.4% to 5.9%. CONCLUSIONS: The Keiser leg press device can obtain valid measurements over a wide range of forces and velocities across different devices. To accurately measure power, theoretical maximal power calculated from the FV profile is recommended over average and peak power values from single repetitions, due to the lower random error observed for theoretical maximal power.