Need a break? The locomotor and tackle pacing profile and loads of women's rugby league match-play following various between-match turnaround durations.

Objectives: The study investigated the locomotor and tackle pacing profile and loads of female rugby league players following various between-match turnaround durations. Specifically, the study examined the (1) pacing of locomotor and tackle loads across the time-course of a match and; (2) whole-match and peak locomotor and tackle loads of match-play.

Methods: Microtechnology data were collected from elite female rugby league players ( = 172) representing all National Rugby League Women's teams ( = 6 teams) across two seasons.

Changing gears: data-driven velocity zones to support monitoring and research in men's rugby league.

Objectives: The study aimed to (1) apply a data-mining approach to league-wide microtechnology data to identify absolute velocity zone thresholds and (2) apply the respective velocity zones to microtechnology data to examine the locomotor demands of elite match-play.

Methods: League-wide microtechnology data were collected from elite male rugby league players representing all National Rugby League (NRL) teams (n = 16 teams, one excluded due to a different microtechnology device; n = 4836 files) over one season. To identify four velocity zones, spectral clustering with a beta smoothing cut-off of 0.

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

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.

Women's Rugby League: Positional Groups and Peak Locomotor Demands.

The aims of this study were to (a) use a data-based approach to identify positional groups within National Rugby League Women's (NRLW) match-play and (b) quantify the peak locomotor demands of NRLW match-play by positional groups. Microtechnology (Global Navigational Satellite System [GNSS] and integrated inertial sensors; = 142 files; = 76 players) and match statistics ( = 238 files; = 80 players) were collected from all NRLW teams across the 2019 season. Data-based clustering of match statistics was utilized to identify positional clusters through classifying individual playing positions into distinct positional groups.

The Validity of Automated Tackle Detection in Women's Rugby League.

Cummins, C, Charlton, G, Naughton, M, Jones, B, Minahan, C, and Murphy, A. The validity of automated tackle detection in women's rugby league. J Strength Cond Res 36(7): 1951-1955, 2022-This study assessed the validity of microtechnology devices to automatically detect and differentiate tackles in elite women's rugby league match-play.