Measured by the Same Yardstick? - Absolute and Relative Speed Zone Models in Elite Youth Soccer

Sammanfattning

In elite youth soccer, external load monitoring with sophisticated GPS systems is a common practice for academy coaches and sports scientists. However, questions regarding data interpretation arise as absolute values and thresholds may not account for the natural heterogeneity of a youth soccer squad. With significant variations in locomotor abilities, relative threshold models have been proposed to contribute more insight into player load management, compared to standardised absolute zones. At the moment, there is no consensus regarding the use of a best-practice model. The aim of this study was to compare GPS-derived external load for high-speed running, sprinting, and near-maximal sprinting across absolute, maximum sprinting speed-based (MSS), and anaerobic speed reserve-based (ASR) speed zones. Furthermore, the study aimed to examine whether absolute threshold values, under- or overestimates high-intensity running demands, and if the anaerobic speed reserve model is a relevant and applicable alternative for relative speed zone classification in Swedish academy soccer. A quantitative observational study design with repeated measurements were used in the study. GPS-derived data were collected from 19 male soccer players in a Swedish U17 academy team across 28 training sessions and games over a six-week period. Distance in high-speed running, sprinting, and near-maximal sprinting were calculated with absolute, anaerobic speed reserve-based, and maximal sprinting speed-based intensity thresholds. The models were compared with a pairwise t-test and effect sizes.Results indicate significant differences in external load output depending on which speed zone classification model was used. The ASR-based thresholds resulted in the highest distance covered across all three intensity zones, while MSS-based thresholds provided significantly lower distances compared to the absolute zones.Practitioners should be aware of the strengths and limits of each speed zone classification model when choosing a preferred load management strategy, rather than searching for a universally superior method.