Abstract

Different equipment (jump mat [JM], jump-and-reach [JAR] device) can be used to measure the countermovement vertical jump (VJ). Physical space may dictate whether organizations (e.g., first responder wellness programs) can use either equipment, or in some instances, may need to use both. It would be beneficial to determine whether VJ predictive equations can be generated such that data is comparable between assessments using device-specific protocols. Sixty-one physically-active subjects (35 males, 26 females) completed three VJ trials each measured by the JM, JAR device, and the JM and JAR device simultaneously (using the JAR technique; JM–JAR and JAR–JM). A four-way repeated measures ANOVA with Bonferroni post hoc compared the average and best VJ trials across the four jump conditions (p<0.05). Pearson’s correlations (p<0.05) calculated between-jump relationships between the conditions. Scatter plots and predictive regression equations for the VJ measured separately (JM, JAR) and simultaneously (JM–JAR, JAR–JM) were derived. For the average and best trials, JM jump height was greater than all other jumps, JM–JAR was greater than JAR and JAR–JM, and JAR was greater than JAR–JM (p<0.001). All correlations were significant (r=0.943-0.981). The predictive equations had ~90% explained variance for the average and best trials, with the separate JM and JAR equations slightly stronger (JM and JAR: r2=0.8967-0.9064; JM–JAR and JAR–JM: r2=0.8958-0.8745). Even though greater VJ heights were recorded by the JM, given the strong relationships, it is possible to calculate a JAR device measure from a VJ performed on a JM, and vice-versa.

Keywords: countermovement jump, health and wellness, occupational health, performance testing, Vertec, vertical jump