Movement patterns of players in the Australian Women's Rugby League team during international competition

Running Low: A Seasonal Analysis of Micronutrient Deficiencies on External-Load Measures in Elite Female Rugby League Players

Iron and vitamin D are essential for physiological mechanisms underpinning physical capacities characterizing team-sport performance. Yet, the impact of iron deficiency on physical capacities beyond endurance is not clear.

PURPOSE

The purpose of this study was to assess variations in seasonal micronutrient concentrations and how iron deficiency impacts external-load measures in elite female rugby league players.

METHODS

Iron and vitamin D status were measured in 28 players (age 24 [4] y, body mass 76 [11] kg) across 3 time points of the 17-week National Rugby League Women's season. Physical demands were evaluated using external-load measures (eg, total distance, PlayerLoad) for training and competition. Linear mixed-effects models were employed to assess the effect of change in serum ferritin concentration on external-load measures. Effect sizes with 95% CIs were calculated to interpret the magnitude of difference in change in indices and performance outcomes between iron-deficient and iron-sufficient players.

RESULTS

Iron-deficiency prevalence ranged from 26% to 57% across the season, and <22% of players were vitamin D deficient at each time point. Weak to strong positive associations (R2 = .3-.6) were observed between all external-load measures and moderating variables (serum ferritin, week, position, and athlete). However, these associations were largely attributable to the contribution of week and position. Differences in load measures between iron-deficient and iron-sufficient players were mostly trivial to small.

CONCLUSIONS

Iron status of elite female rugby league players had little effect on most workload measures within this cohort. However, longitudinal monitoring is warranted to identify how external-load measures are affected individually in response to fluctuations in serum ferritin.

Longitudinal changes in anthropometric, physiological, and physical qualities of international women's rugby league players

This is the first study to assess longitudinal changes in anthropometric, physiological, and physical qualities of international women's rugby league players. Thirteen forwards and 11 backs were tested three times over a 10-month period. Assessments included: standing height and body mass, body composition measured by dual x-ray absorptiometry (DXA), a blood panel, resting metabolic rate (RMR) assessed by indirect calorimetry, aerobic capacity (i.e.,[Formula: see text]) evaluated by an incremental treadmill test, and isometric force production measured by a force plate. During the pre-season phase, lean mass increased significantly by ~2% for backs (testing point 1: 47 kg; testing point 2: 48 kg) and forwards (testing point 1: 50 kg; testing point 2: 51 kg) (p = ≤ 0.05). Backs significantly increased their [Formula: see text] by 22% from testing point 1 (40 ml kg-1 min-1) to testing point 3 (49 ml kg-1 min-1) (p = ≤ 0.04). The [Formula: see text] of forwards increased by 10% from testing point 1 (41 ml kg-1 min-1) to testing point 3 (45 ml kg-1 min-1), however this change was not significant (p = ≥ 0.05). Body mass (values represent the range of means across the three testing points) (backs: 68 kg; forwards: 77-78 kg), fat mass percentage (backs: 25-26%; forwards: 30-31%), resting metabolic rate (backs: 7 MJ day-1; forwards: 7 MJ day-1), isometric mid-thigh pull (backs: 2106-2180 N; forwards: 2155-2241 N), isometric bench press (backs: 799-822 N; forwards: 999-1024 N), isometric prone row (backs: 625-628 N; forwards: 667-678 N) and bloods (backs: ferritin 21-29 ug/L, haemoglobin 137-140 g/L, iron 17-21 umol/L, transferrin 3 g/L, transferring saturation 23-28%; forwards: ferritin 31-33 ug/L, haemoglobin 141-145 g/L, iron 20-23 umol/L, transferrin 3 g/L, transferrin saturation 26-31%) did not change (p = ≥ 0.05). This study provides novel longitudinal data which can be used to better prepare women rugby league players for the unique demands of their sport, underpinning female athlete health.

Behind enemy lines: Expressing locomotor movements of athletes in the National Rugby League Women's (NRLW) competition relative to opposition data

We provide a novel analysis of the locomotor movements of athletes in the National Rugby League Women's (NRLW) competition by presenting the data of opposing teams expressed as a relative (%) difference and explore the association with match outcome. 117 rugby league athletes from the four NRLW clubs participated in this study. Mean speed (m·min-1), mean high-speed running (>12 km·h-1; m·min-1), and mean acceleration (m·s-2) were measured in 12 matches (370 individual match files) using the Global Navigation Satellite System (GNSS). Individual GNSS-derived data from each match-half were summed across each team and the association with total points and the points differential in each match-half was determined using linear mixed models. Greater high-speed running and lower mean acceleration were associated with more points being scored. A greater relative difference in mean high-speed running between competing teams was associated with a higher points differential. That is, if a team completed 10% more high-speed running than their opposition, they were likely to score an average of 3.2 points more during a given match-half. This unique analysis of GNSS-derived data may assist coaches and performance support staff to interpret the locomotor movements of female rugby league players with the appropriate considerations for the opposition team.

Applied sports science and sports medicine in women's rugby: systematic scoping review and Delphi study to establish future research priorities

Objectives

In part 1, the objective was to undertake a systematic scoping review of applied sports science and sports medicine in women's rugby, and in part 2 to develop a consensus statement on future research priorities.

Design

In part 1, a systematic search of PubMed (MEDLINE), Scopus and SPORTDiscus (EBSCOhost) was undertaken from the earliest records to January 2021. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) 2020, the PRISMA extension for Scoping Reviews, and the PRISMA extension protocols were followed. In part 2, 31 international experts in women's rugby (ie, elite players, sports scientists, medical clinicians, sports administrators) participated in a three-round Delphi consensus method. These experts reviewed the findings from part 1 and subsequently provided a list of priority research topics in women's rugby. Research topics were grouped into expert-based themes and expert-based subthemes via content analysis. Expert-based themes and expert-based subthemes were ranked from very low to very high research priority on a 1-5 Likert scale. Consensus was defined by ≥70% agreement. The median research priority agreement and IQR were calculated for each expert-based theme and subtheme.

Data sources

PubMed (MEDLINE), Scopus and SPORTDiscus (EBSCOhost).

Eligibility criteria for selecting studies

Studies were eligible for inclusion if they investigated applied sports science or sports medicine in women's rugby.

Results

In part 1, the systematic scoping review identified 123 studies, which were categorised into six sports science and sports medicine evidence-based themes: injury (n=48), physical performance (n=32), match characteristics (n=26), fatigue and recovery (n=6), nutrition (n=6), and psychology (n=5). In part 2, the Delphi method resulted in three expert-based themes achieving consensus on future research priority in women's rugby: injury (5.0 (1.0)), female health (4.0 (1.0)) and physical performance (4.0 (1.0)).

Summary/Conclusion

This two-part systematic scoping review and Delphi consensus is the first study to summarise the applied sports science and sports medicine evidence base in women's rugby and establish future research priorities. The summary tables from part 1 provide valuable reference information for researchers and practitioners. The three expert-based themes that achieved consensus in part 2 (injury, female health and physical performance) provide clear direction and guidance on future research priorities in women's rugby. The findings of this two-part study facilitate efficient and coordinated use of scientific resources towards high-priority research themes relevant to a wide range of stakeholders in women's rugby.

The Utility of Mixed Models in Sport Science: A Call for Further Adoption in Longitudinal Data Sets

PURPOSE

Sport-science research consistently contains repeated measures and imbalanced data sets. This study calls for further adoption of mixed models when analyzing longitudinal sport-science data sets. Mixed models were used to understand whether the level of competition affected the intensity of women's rugby league match play.

METHODS

A total of 472 observations were used to compare the mean speed of female rugby league athletes recorded during club-, state-, and international-level competition. As athletes featured in all 3 levels of competition and there were multiple matches within each competition (ie, repeated measures), the authors demonstrated that mixed models are the appropriate statistical approach for these data.

RESULTS

The authors determined that if a repeated-measures analysis of variance (ANOVA) were used for the statistical analysis in the present study, at least 48.7% of the data would have been omitted to meet ANOVA assumptions. Using a mixed model, the authors determined that mean speed recorded during Trans-Tasman Test matches was 73.4 m·min-1, while the mean speeds for National Rugby League Women and State of Origin matches were 77.6 and 81.6 m·min-1, respectively. Random effects of team, athlete, and match all accounted for variations in mean speed, which otherwise could have concealed the main effects of position and level of competition had less flexible ANOVAs been used.

CONCLUSION

These data clearly demonstrate the appropriateness of applying mixed models to typical data sets acquired in the professional sport setting. Mixed models should be more readily used within sport science, especially in observational, longitudinal data sets such as movement pattern analyses.

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 0.1 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 (0 to 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.

Strong, Fast, Fit, Lean, and Safe: A Positional Comparison of Physical and Physiological Qualities Within the 2020 Australian Women's Rugby League Team

ABSTRACT

Minahan, C, Newans, T, Quinn, K, Parsonage, J, Buxton, S, and Bellinger, P. Strong, Fast, Fit, Lean, and Safe: A positional comparison of physical and physiological qualities within the 2020 Australian Women's Rugby League team. J Strength Cond Res 35(12S): S11-S19, 2021-The purpose of the present study was to report the physical and physiological characteristics of elite women Rugby League (RL) players. Thirty-nine women (25.6 ± 4.3 years, 171.3 ± 7.7 cm, 83.5 ± 13.9 kg) from the 2020 Australian women's RL squad were recruited for this study. Players were categorized as adjustables (n = 7), backs (n = 15), or forwards (n = 17) for analysis. Each player was assessed for anthropometry, body composition (dual-energy X-ray absorptiometry), speed (5, 10 and 20 m sprint times), lower-body power (countermovement jump), upper-body power (medicine ball throw and explosive push up force), estimated one repetition maximum (e1RM) bench press, squat and bench pull, isometric mid-thigh pull strength, eccentric knee flexor strength, isometric hip abduction and adduction, and intermittent endurance performance (30-15 intermittent fitness test; 30-15 IFT). Linear mixed models were performed to compare positional groups. Forwards were significantly heavier and had greater fat mass, fat-free mass, and body fat percentage compared with backs and adjustables (P < 0.01). Backs were faster over 20 m compared with forwards (P = 0.025), whereas forwards had a lower 30-15 IFT peak velocity and estimated V̇o2peak compared with backs and adjustables. Nonetheless, when including body mass in the model, there were no differences between groups in 30-15 IFT peak velocity. There were no significant differences in other variables. These results provide contemporary benchmark physical, physiological, and anthropometric data for elite women RL players, which can inform recruitment, selection, training, and testing.

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; n = 142 files; n = 76 players) and match statistics (n = 238 files; n = 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. Moving averages (0.5, 1, 2, 3, 5, and 10 min) of peak running and average acceleration/deceleration demands were calculated via microtechnology data for each player per match. All analysis was undertaken in R (R Foundation for Statistical Computing) with positional differences determined via a linear mixed model and effect sizes (ES). Data-based clustering suggested that, when informed by match statistics, individual playing positions can be clustered into one of three positional groups. Based on the clustering of the individual positions, these groups could be broadly defined as backs (fullback, wing, and center), adjustables (halfback, five-eighth, and hooker), and forwards (prop, second-row, and lock). Backs and adjustables demonstrated greater running (backs: ES 0.51-1.00; p < 0.05; adjustables: ES 0.51-0.74, p < 0.05) and average acceleration/deceleration (backs: ES 0.48-0.87; p < 0.05; adjustables: ES 0.60-0.85, p < 0.05) demands than forwards across all durations. Smaller differences (small to trivial) were noted between backs and adjustables across peak running and average acceleration/deceleration demands. Such findings suggest an emerging need to delineate training programs in situations in which individual playing positions train in positional group based settings. Collectively, this work informs the positional groupings that could be applied when examining NRLW data and supports the development of a framework for specifically training female rugby league players for the demands of the NRLW competition.

Movement Patterns and Match Statistics in the National Rugby League Women's (NRLW) Premiership

As women's rugby league grows, the need for understanding the movement patterns of the sport is essential for coaches and sports scientists. The aims of the present study were to quantify the position-specific demographics, technical match statistics, and movement patterns of the National Rugby League Women's (NRLW) Premiership and to identify whether there was a change in the intensity of play as a function of game time played. A retrospective observational study was conducted utilizing global positioning system, demographic, and match statistics collected from 117 players from all NRLW clubs across the full 2018 and 2019 seasons and were compared between the ten positions using generalized linear mixed models. The GPS data were separated into absolute (i.e., total distance, high-speed running distance, and acceleration load) and relative movement patterns (i.e., mean speed, mean high speed (> 12 km·h^-1), and mean acceleration). For absolute external outputs, fullbacks covered the greatest distance (5,504 m), greatest high-speed distance (1,081 m), and most ball-carry meters (97 m), while five-eighths recorded the greatest acceleration load (1,697 m·s^-2). For relative external outputs, there were no significant differences in mean speed and mean high speed between positions, while mean acceleration only significantly differed between wingers and interchanges. Only interchange players significantly decreased in mean speed as their number of minutes played increased. By understanding the load of NRLW matches, coaches, high-performance staff, and players can better prepare as the NRLW Premiership expands. These movement patterns and match statistics of NRLW matches can lay the foundation for future research as women's rugby league expands. Similarly, coaches, high-performance staff, and players can also refine conditioning practices with a greater understanding of the external output of NRLW players.

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 XX(X): 000-000, 2020-This study assessed the validity of microtechnology devices to automatically detect and differentiate tackles in elite women's rugby league match-play. Elite female players (n = 17) wore a microtechnology device (OptimEye S5 device; Catapult Group International) during a representative match, which involved a total of 512 tackles of which 365 were defensive and 147 were attacking. Tackles automatically detected by Catapult's tackle detection algorithm and video-coded tackles were time synchronized. True positive, false negative and false positive events were utilized to calculate sensitivity (i.e., when a tackle occurred, did the algorithm correctly detect this event) and precision (i.e., when the algorithm reported a tackle, was this a true event based on video-coding). Of the 512 video-derived attacking and defensive tackle events, the algorithm was able to detect 389 tackles. The algorithm also produced 81 false positives and 123 false negatives. As such when a tackle occurred, the algorithm correctly identified 76.0% of these events. When the algorithm reported that a tackle occurred, this was an actual event in 82.8% of circumstances. Across all players, the algorithm was more sensitive to the detection of an attacking event (sensitivity: 78.2%) as opposed to a defensive event (sensitivity: 75.1%). The sensitivity and precision of the algorithm was higher for forwards (sensitivity: 81.8%; precision: 92.1%) when compared with backs (sensitivity: 64.5%; precision: 66.1%). Given that understanding the tackle demands of rugby league is imperative from both an injury-prevention and physical-conditioning perspective there is an opportunity to develop a specific algorithm for the detection of tackles within women's rugby league.