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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. 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. 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 (&lt;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 (&gt;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. 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.

How fast is fast? Defining velocity zones in women’s rugby league