Between-day reliability of local and global muscle-tendon unit assessments in female athletes whilst standardising menstrual cycle phase.

Muscle-tendon unit (MTU) assessments can be categorised into local (e.g., tendon strain) or global (e.g., jump height) assessments. Although menstrual cycle phase may be a key consideration when implementing these assessments in female athletes, the reliability of many MTU assessments is not well defined within female populations. Therefore, the purpose of this study was to report the test-retest reliability of local and global MTU assessments during the early follicular phase of the menstrual cycle. Seventeen naturally menstruating females (age 28.5 ± 7.3 years) completed local and global MTU assessments during two testing sessions separated over 24-72 hours. Local tests included Achilles' tendon mechanical testing and isometric strength of ankle plantar flexors and knee extensors, whereas global tests included countermovement, squat, and drop jumps, and the isometric midthigh pull. Based on intraclass correlation coefficient (ICC) statistics, poor to excellent reliability was found for local measures (ICC: 0.096-0.936). Good to excellent reliability was found for all global measures (ICC: 0.788-0.985), excluding the eccentric utilisation ratio (ICC 0.738) and most rate of force development metrics (ICC: 0.635-0.912). Isometric midthigh pull peak force displayed excellent reliability (ICC: 0.966), whereas force-time metrics ranged from moderate to excellent (ICC: 0.635-0.970). Excluding rate of force development (coefficient of variation [CV]: 10.6-35.9%), global measures (CV: 1.6-12.9%) were more reproducible than local measures (CV: 3.6-64.5%). However, local metrics directly measure specific properties of the MTU, and therefore provide valuable information despite lower reproducibility. The novel data reported here provides insight into the natural variability of MTU assessments within female athletes which can be used to enhance the interpretation of other female athlete data, especially that which aims to investigate other aspects of variability, such as the menstrual cycle.