Novel Use of Generalizability Theory to Optimize Countermovement Jump Data Collection in Female Athletes

Countermovement jump (CMJ) testing is widely used to monitor neuromuscular function, but trial-to-trial reliability depends on the population and testing ecology. Previous reliability prescriptions have often been derived from male cohorts, risking misapplication to female athletes, whose anthropometry, movement strategies, and testing environments differ. This study applied Generalizability Theory (G-Theory) to quantify the within-session reliability of CMJ metrics in NCAA Division I women's volleyball, softball, soccer, and lacrosse, aiming to isolate the measurement precision independent of day-to-day biological variance. A fully crossed person × trial G-Theory analysis was performed, with the G-study phase estimating variance components and the D-study phase determining the number of trials required to reach actionable dependability (Φ ≥ 0.80). Force-time data from 103 athletes across 282 jumps were analyzed for 14 commonly monitored metrics. Results show that six concentric and takeoff indices, including force at zero velocity, phase-1 concentric impulse, total concentric impulse, jump height, takeoff velocity, and scaled power, achieved Φ ≥ 0.80 from a single trial across all sports. Second-tier variables, such as eccentric duration, phase-2 impulse, and the modified reactive strength index, stabilized within two to three trials, whereas braking impulse, countermovement depth, and deceleration RFD asymmetry required impractical sampling and were deemed fragile (i.e., requiring a greater number of trials to reach acceptable reliability). Compared with the male data, women exhibited larger between-subject variance and higher single-trial dependability for 11 of the 14 studied metrics. Findings support concise, sex-specific trial prescriptions that prioritize stable metrics and minimize unnecessary testing.