Navigating the Data Processing Maze: A Systematic Review of Jump Height Calculations Using Force Platforms. - Eythorsdottir, Ingrid; Gløersen, Øyvind; Rice, Hannah; Werkhausen, Amelie; Ettema, Gertjan; Solberg, Paul; Paulsen, Gøran (European Journal of Sport Science, 2026)
Vertical jump height estimates the ability to oppose gravity and lower body neuromuscular performance in athletes and various clinical populations. The use of force platforms for measuring jump height is increasingly popular due to technological advancements and the equipment's relative ease of use in various settings. However, when utilizing the force platform, ground reaction force (GRF) data must be processed to calculate jump height. While processing the GRF‐time data, several factors could alter the data, leading to inaccurate jump height estimates. These factors include sampling frequency, filtering, cut‐off frequencies of the filter, averaging periods of body weight, integration procedures, selection of take‐off/landing thresholds, and selection of the gravity constant. These data processing steps can alter jump height estimates, with effects ranging from minor (< 0.5%) to major (> 25%). Despite some guidelines on data processing, there is no consistency in the literature or in practice regarding how the GRF‐time data should be processed. Consequently, jump height without specifying the data processing steps may be of limited use to others. The aim of this review was to assist researchers and practitioners in navigating the complexities of data processing to better understand how it influences jump height. Highlights: The influence of data processing in force platform‐based vertical jump tests is underrated in the sports performance literature.The data processing steps may introduce large errors, including up to 26% in jump height estimates from only filtering.Jump height values can be considered valid performance metrics only when the calculation equations and data processing steps are clearly reported. Without such, results are difficult to interpret and cannot be reliably compared across studies or systems.