Objectives: The study aimed to: 1) apply a data-mining approach to identify velocity zone thresholds for female rugby league players and 2) apply these velocity zones to examine the locomotor demands of match-play.
Methods: Microtechnology data were collected from elite female rugby league players representing all National Rugby League Women's teams (n = 85 players" n = 224 files) over one season. Spectral clustering with a beta smoothing cut-off of 0.1 was applied to each player's instantaneous match-play velocity data for the identification of four zones. To account for outliers within repeated data-points, the velocity zones for each player were calculated as the median. The overarching velocity zones were determined through an incremental search to minimise the root mean square error.
Results: Through a data-mining approach, four velocity zones were determined. Rounded to the nearest 0.5 km.h−1 the velocity values across each zone were classified as low (<11.49 km.h−1), moderate (11.50 to 17.49 km.h−1), high (17.50 to 20.99 km.h−1) and very-high (>21.00 km.h−1). Practical application of the zones demonstrated positional group differences in the absolute (effect size (ES): 0.03 to 1.77) and relative (ES: 0.04 to 1.60) locomotor demands of match-play. The back positional group covered greater absolute and relative distances at a very-high velocity than all other positions.
Conclusions: This work informs the velocity zones that could be applied consistently to women's rugby league data within practical (i.e., in the training and monitoring of players) and academic (i.e., as a model for future research to analyse locomotor demands) settings.