The introduction of the six-again rule has increased acceleration intensity across all positions in the National Rugby League competition.

The impact of the six-again rule change on the movement of National Rugby League (NRL) athletes was examined. Player Global Navigation Satellite System (GNSS) data (10 Hz) was collected from 42 athletes who competed in 56 matches across the 2019 to 2021 NRL seasons. Maximal mean speed (m·min-1) and acceleration (m·s-2) were established across a 10 s to 10-min duration via raw GNSS files, with subsequent intercept (mean estimates) and slope values determined via power law analysis. The distributions of match distance (m) and impulse (kN·s-1) were established during ball-in-play time. To determine the significance between positions and seasons under different rules, linear mixed models were used. Effects were described using standardised effect sizes (ES) with 90% confidence limits (CL). Acceleration intercepts (power law-derived) across all positions were substantially greater (>0.6 SD) following the introduction of the six-again rule in the 2020 (mean ± SD; 1.02 ± 0.10 m·s-2) and 2021 seasons (1.05 ± 0.08 m·s-2) compared to the 2019 season (0.91 ± 0.07 m·s-2). Mean acceleration during ball-in-play time was greater in 2020 (ES; 90% CL = 0.75; ± 0.32) compared to 2019. The acceleration requirements of rugby league increased across all positional groups following the modification in NRL competition rules. Practitioners should tailor training programs for athletes to reflect the increased acceleration intensity found under the revised competition format.

Applying common filtering processes to Global Navigation Satellite System-derived acceleration during team sport locomotion.

This study aimed to observe whether there were substantial differences in acceleration during team-sport locomotion between GNSS manufacturers. Speed and acceleration were obtained from 7 professional rugby league athletes via 2 GNSS manufacturers (GPSports EVO, 10 Hz and STATSports Apex, 10 Hz) worn together during the same training sessions (n = 13). Raw GNSS data were exported from respective proprietary software and a 1 Hz, 4th-order Butterworth filter applied, with differences in speed and acceleration calculated between manufacturers. To determine the difference in acceleration and speed, a root mean square deviation (RMSD) was used. Linear mixed models were used and no substantial differences were found between manufacturers in raw and filtered speed variables. RMSD for average acceleration (m · s-2) decreased from raw (RMSD: 1.77 ± 0.37 m · s-2) to those seen at the filtered (RMSD: 0.27 ± 0.23 m · s-2) and twice filtered (0.24 ± 0.23 m · s-2) variables. Raw average acceleration (m · s-2) was substantially higher in Apex compared to EVO (Difference (Diff); CI: -0.82; -0.84 to -0.80). Following application of the common filter there was no substantial difference between GNSS models for average acceleration (Diff; CI: -0.04; -0.04 to -0.04). Acceleration variables derived from each manufacturer's proprietary software were substantially different.

The Quantification of Acceleration Events in Elite Team Sport: a Systematic Review.

BACKGROUND: Wearable tracking devices are commonly utilised to quantify the external acceleration load of team sport athletes during training and competition. The ability to accelerate is an important attribute for athletes in many team sports. However, there are many different acceleration metrics that exist in team sport research. This review aimed to provide researchers and practitioners with a clear reporting framework on acceleration variables by outlining the different metrics and calculation processes that have been adopted to quantify acceleration loads in team sport research. METHODS: A systematic review of three electronic databases (CINAHL, MEDLINE, SPORTDiscus), was performed to identify peer-reviewed studies that published external acceleration load in elite team sports during training and/or competition. Articles published between January 2010 and April 2020 were identified using Boolean search phrases in relation to team sports (population), acceleration/deceleration (comparators), and competition and/or training (outcome). The included studies were required to present external acceleration and/or deceleration load (of any magnitude) from able-bodied athletes (mean age ≥ 18 years) via wearable technologies. RESULTS: A total of 124 research articles qualified for inclusion. In total, 113/124 studies utilised GPS/GNSS technology to outline the external acceleration load of athletes. Count-based metrics of acceleration were predominant of all metrics in this review (72%). There was a lack of information surrounding the calculation process of acceleration with 13% of studies specifying the filter used in the processing of athlete data, whilst 32% outlined the minimum effort duration (MED). Markers of GPS/GNSS data quality, including horizontal dilution of precision (HDOP) and the average number of satellites connected, were outlined in 24% and 27% of studies respectively. CONCLUSIONS: Team sport research has predominantly quantified external acceleration load in training and competition with count-based metrics. Despite the influence of data filtering processes and MEDs upon acceleration, this information is largely omitted from team sport research. Future research that outlines acceleration load should present filtering processes, MEDs, HDOP, and the number of connected satellites. For GPS/GNSS systems, satellite planning tools should document evidence of available satellites for data collection to analyse tracking device performance. The development of a consistent acceleration filtering method should be established to promote consistency in the research of external athlete acceleration loads.

Quantifying Mean Peak Running Intensities in Elite Field Hockey.

ABSTRACT: Delves, RIM, Bahnisch, J, Ball, K, and Duthie, GM. Quantifying mean peak running intensities in elite field hockey. J Strength Cond Res 35(9): 2604-2610, 2021-To replicate match demands in training, field hockey (FH) coaches typically prescribe intensities based on whole-match data. Such data may underestimate peak competition periods, potentially underpreparing athletes for competition. This study then aimed to quantify maximal mean running intensities during elite FH competition to facilitate enhanced training prescription. Ten-Hertz Global Positioning System data were collected from 17 male and 11 female FH athletes who competed in the 2016 and 2017 Australian Hockey League tournaments. Maximal mean values for speed, acceleration, and metabolic power (Pmet) were calculated over a 1- to 10-minute moving average by position. Summary match statistics were also analyzed. Linear mixed models were constructed to determine the effect of position on moving average and summary variables. Pairwise comparisons between groups were made using magnitude-based inferences. In female competition, speed and Pmet intensities were greater in midfielders, whereas defenders were lowest in acceleration demands over the 10-minute window and in corresponding intercepts. In male competition, acceleration was greater in defenders during the 10-minute window and in subsequent intercepts compared with midfielders, whereas defenders were lowest in speed intercepts. In comparison with previously reported summary match variables, intensities from the 1-minute moving average interval were 50-65% greater in male competition and 30-50% greater in female competition. The 10-minute moving average framework has identified FH running intensities that are greater than previously reported whole-match averages. This information enhances the understanding of the demands of FH, assisting practitioners to prepare their athletes for the most demanding instances of play.