Preparing for an Australian Football League Women's League Season

Seasonal health tracking of Australian Football League Women's athletes

BACKGROUND

Studies evaluating the dietary intake of Australian Football League Women's (AFLW) athletes are few and limited to the preseason. This prospective observational study aims to evaluate seasonal changes in dietary intake and health parameters of professional AFLW athletes.

METHODOLOGY

Dietary intake (3-day weighed food records), body composition (bioelectrical impedance analysis, skinfolds), physical performance (global positioning system, GPS), and iron status (fasted blood sample) were assessed in 19 athletes (24 ± 5 years, 170 ± 6 cm, 22.8 ± 2.1 kg/m2) at three timepoints: start of preseason, end of preseason, and end of competition season. Sociodemographic information, sports nutrition knowledge (SNK), and risk of low energy availability (LEA) questionnaires were completed at the start of preseason.

RESULTS

Mean daily energy and carbohydrate (CHO) intakes were lower than recommendations across all seasons (p < 0.05). Mean daily CHO intake was highest at start of preseason (3.6 g/kg/day), decreased during preseason (3.1 g/day) and remained low during competition (3.2 g/day); >80% of players did not meet minimum recommendations at each timepoint (all, p < 0.05). The sum of seven skinfolds and fat mass (%) decreased during preseason (both, p < 0.05). Serum iron fell within recommended ranges for 95% of athletes at all timepoints. The total distance (m) and number of Very High Intensity (>21 km/h) efforts significantly increased across preseason and decreased during competition (all, p < 0.05). Nutrition knowledge was 'poor', and 42% of athletes were at risk of LEA.

CONCLUSIONS

AFLW athletes do not meet energy and carbohydrate requirements across the preseason and competition seasons, which may impact health and performance if deficits are sustained.

Effect of Different Nonstarter Compensatory Strategies on Training Load in Female Soccer Players: A Pilot Study

BACKGROUND

In soccer, the day of the week with the highest external load is match day (MD), with starters (>60 minutes per match) showing higher levels of physical fitness and seasonal high-intensity loading. It is necessary, therefore, to determine training strategies to reduce the differences between starters and nonstarters. The aim of this study was to analyze and compare the external load of different training compensatory strategies with match external load in female nonstarters.

HYPOTHESIS

A strategy combining small-sided games (SSG) and running-based drills (RBD) would reproduce match demands, with RBD leading to greater high-intensity running and SSG leading to a greater number of accelerations and decelerations.

STUDY DESIGN

Descriptive and comparative study.

LEVEL OF EVIDENCE

Level 4.

METHODS

The training and match external load of 14 female players belonging to the same reserve squad of a Spanish First Division Club (Liga Reto Iberdrola) was registered. In the first session after the match (MD+1), nonstarters (<60 minutes in the match) performed 1 of 3 different compensatory strategies: RBD, SSG, or a mixed intervention combining the previous strategies (RBD+SSG). Starters carried out a recovery session.

RESULTS

A marked difference in load was observed between the compensatory training strategies and MD. In comparison with MD, RBD showed greater high-intensity and sprint distances and lower acceleration, SSG showed less high-intensity running and sprint distances, lower peak velocity, and greater acceleration, and RBD+SSG registered lower accelerations. In addition, nonstarters covered greater high-intensity running and sprint distances in RBD and achieved higher accelerations in SSG.

CONCLUSION

RBD and SSG compensatory strategies could be recommended to nonstarter female soccer players in MD+1 to compensate for match external load deficits.

CLINICAL RELEVANCE

This study provides comprehensive information on the compensatory exercises of female soccer players, which can be useful for strength and conditioning coaches when developing recovery strategies during a microcycle.

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.

Replicating Maximum Periods of Play in Australian Football Matches Through Position-Specific Drills

ABSTRACT

Wing, C, Hart, NH, Ma'ayah, F, and Nosaka, K. Replicating maximum periods of play in Australian football matches through position-specific drills. J Strength Cond Res XX(X): 000-000, 2022-This study evaluated whether a position-specific drill replicates the running intensities of maximum ball in play (BiP) phases in competitive matches of Australian football (AF). Match data were collected on 32 AF players across 3 seasons (2019, 2020, 2021), with training session data collected from the same players across the 2021 season. Three position-specific training drills were created for defense, offense, and combination (defense and offense combined). Running intensities were compared between maximum BiP periods (e.g., periods with the highest metric per minute) from competitive matches and position-specific training drills, as well as between the 3 position-specific training drills using linear mixed models. The significance level was set at p < 0.05. Measures of distance (offense: 44.4 m·minute-1, defense: 83.5 m·minute-1, combination: 50.4 m·minute-1), high-speed running (offense: 76.7 m·minute-1, defense: 134.6 m·minute-1, combination: 89.6 m·minute-1), very high-speed running (offense: 26.7 m·minute-1, defense: 56.2 m·minute-1, combination: 55.0 m·minute-1), and high-intensity efforts (offense: 2.3 efforts·minute-1, defense: 3.0 efforts·minute-1, combination: 2.8 efforts·minute-1), relative to time were greater (p < 0.001) in all 3 position-specific training drills compared with BiP phases. All measured metrics were significantly (p < 0.001) greater in the defense drill compared with the offense drill, whereas distance, high-speed running, PlayerLoad, and accelerations were significantly (p < 0.001) greater when compared with the combination drill. These demonstrate that position-specific training drills that we created replicated or exceeded the running intensities recorded during matches based on maximum BiP periods. Position-specific training drills seem to be an attractive addition to AF players training regimens because it concurrently provides training for physical and technical actions (e.g., handballs).

The distribution of different intensity demanding scenarios in elite rink hockey players using an electronic performance tracking system

Despite the traditional use of average values for determining physical demands, the intermittent and fluctuating nature of team sports may lead to underestimation of the most demanding scenarios. All the most demanding scenario-related investigations to date only report one maximal scenario per game, the greatest. However, the latest research on this subject has shown additional scenarios of equal or similar magnitude that most researchers have not considered. This repetition concept started a new way of describing competition and training loads; then the study aims were: first, to quantify and assess differences between playing positions in terms of the most demanding scenarios in official matches; and second, to quantify and assess the differences between playing positions in the repetition of different intensity scenarios relative to the most demanding individual scenario. We monitored nine professional rink hockey players (7 exterior and 2 interior players) in 18 competitive matches using an electronic performance tracking system. The interior players are closest to the opponent's goal, while the exterior players are farthest from it. Peak physical demands variables included total distance (m), distance covered at >18 km·h-1 (m), the number of accelerations (≥2 m∙s-2, count) and decelerations (≤-2 m∙s-2, count) in 30 s. An average from the top three individual most demanding scenarios was used to define a reference value to quantify the distribution scenario repetition during matches. The results showed that peak demands in rink hockey are position-dependent, with more distance covered by exterior players and more accelerations performed by interior players. In addition, rink hockey matches include multiple scenario exposures that are close to the peak physical demands of a match. Using the results of this study, coaches can prepare tailored training plans for each position, focusing on distances covered or accelerations for exterior players.

Methods of performance analysis in women's Australian football: a scoping review

Background

The first women's Australian football (AF) professional competition was established in 2017, resulting in advancement in performance analysis capabilities within the sport. Given the specific constraints of women's AF, it is currently unclear what match-play performance analysis methods and techniques are implemented. Therefore, the aim of this scoping review was to describe and critically appraise physical, technical, and tactical performance analysis methods that have been employed in women's and girls' AF match-play.

Methodology

A systematic search was conducted on the 27th of June 2022 through five databases. Eligibility criteria were derived from the PCC framework with the population (P) of women and girls AF players, of any level of play; concepts (C) of interest which were measures, data, and methods related to the sport's physical, technical, and tactical performance; and the context (C) of methods that analysed any match-play performance. A narrative synthesis was conducted using extracted study characteristic data such as sample size, population, time period, collection standards, evaluation metrics for results, and application of thematic categorisations of previous sports performance reviews. Critical appraisal of eligible studies' methodologies was conducted to investigate research quality and identify methodological issues.

Results

From 183 studies screened, twelve eligible studies were included, which examined match-play through physical (9/12, 75%), technical (4/12, 33%), and tactical analysis (2/12, 17%). Running demands and game actions analysis were the most researched in senior women's AF. Research into junior girls' AF match-play performance has not been investigated. No research has been conducted on non-running physical demands, contact demands, acceleration, and tactical aspects of women's AF. All studies utilised either inferential statistics or basic predictive models. Critical appraisal deemed most studies as low risk of bias (11/12, 92%), with the remaining study having satisfactory risk.

Conclusions

Future research utilising increased longitudinal and greater contextual data is needed to combat the prominent issue of data representativeness to better characterise performance within women's and girls' AF. Additionally, research involving junior and sub-elite AF players across the talent pathways is important to conduct, as it provides greater context and insight regarding development to support the evolving elite women's AF competition. Women's AF has been constrained by its resource environment. As such, suggestions are provided for better utilisation of existing data, as well as for the creation of new data for appropriate future research. Greater data generation enables the use of detailed machine learning predictions, neural networks, and network analysis to better represent the intertwined nature of match-play performance from technical, physical, and tactical data.

The Maximal Intensity Period: Rationalising its Use in Team Sports Practice

Quantifying the highest intensity of competition (the maximal intensity period [MIP]) for varying durations in team sports has been used to identify training targets to inform the preparation of players. However, its usefulness has recently been questioned since it may still underestimate the training intensity required to produce specific physiological adaptations. Within this conceptual review, we aimed to: (i) describe the methods used to determine the MIP; (ii) compare the data obtained using MIP or whole-match analysis, considering the influence of different contextual factors; (iii) rationalise the use of the MIP in team sports practice and (iv) provide limitations and future directions in the area. Different methods are used to determine the MIP, with MIP values far greater than those derived from averaging across the whole match, although they could be affected by contextual factors that should be considered in practice. Additionally, while the MIP might be utilised during sport-specific drills, it is inappropriate to inform the intensity of interval-based, repeated sprint and linear speed training modes. Lastly, MIP does not consider any variable of internal load, a major limitation when informing training practice. In conclusion, practitioners should be aware of the potential use or misuse of the MIP.

The Distribution of Match Physical Activities Relative to the Most Demanding Scenarios in Professional Basketball Players

The purpose of this study was to examine the distribution of physical activities relative to the most demanding scenarios across playing positions during official basketball match-play. Twelve professional basketball players were monitored during twelve matches using a local positioning system. Peak physical demands were measured via total distance covered, distance covered >18 km·h^-1, and the number of accelerations and decelerations >3 m·s^-2 captured over 30- and 60-s rolling averages. The results showed that players were exposed to more than one high-demanding scenario in all variables and time epochs examined. Additionally, total distance covered presented the greatest number of moderate-demanding scenarios (40-80% of most demanding scenarios), whereas distance covered >18 km·h^-1, and accelerations and decelerations >3 m·s^-2 presented the greatest proportion of low-demanding scenarios (<40% of most demanding scenarios). Regarding positional differences, backcourt players generally experienced a higher number of scenarios than frontcourt players in most variables, especially in total distance covered. For this variable, scenarios between 20 and 70% of most demanding scenarios during the 30-s epoch (p < 0.001; ES = 0.420.78), and scenarios between 50 and 90% of most demanding scenarios during the 60-s epoch (p < 0.001; ES = 0.400.64) showed significant differences between backcourt and frontcourt players. Our data suggest that match physical activities are position-dependent and variable-dependent. In addition, peak physical demands appear to be repeated during basketball competition. These results may be considered by practitioners to complement average values and most demanding scenarios when prescribing individualized training programs to optimize team performance.

Comparing the Current Training Running Demands of Elite Camogie Players to Competitive Match-Play

Training to meet match-play demands is a primary objective in an athlete’s preparation for their games. Despite camogie match-play running demands being available, how current training practices compare, specifically individual training components, remains unknown. This study aimed to investigate and compare current elite camogie training to match-play demands. Thirty-three (n = 33) elite camogie players wore 10 Hz Playertek GPS units during twenty-five training sessions and ten competitive matches. Training sessions were analysed using ball-in-play time and split into warm-ups, drills, small-sided games, running, and training matches. Metrics were converted into relative terms (per minute), to allow comparisons. Players cover significantly greater (p < 0.05) total distance (non-parametric standardised effect sizes (r = 0.45)), peak speed (r = 0.45), high-speed running (r = 0.13), sprint distance (r = 0.20), and total decelerations (r = 0.12−0.22) during match-play than training. Relatively, players cover significantly greater distance during running, small-sided games, and training matches compared to match-play (r = 0.21−0.29). Compared with match-play, running results in significantly greater high-speed running and sprint distance (r = 0.18−0.41), with greater accelerations (3−4 m∙s−2) during warm-ups, running, and small-sided games (r = 0.14−0.28). Current total training demands seem to fall behind match-play. However, relatively, training matches and small-sided games match or surpass competitive match-play demands. These findings may be utilised in preparing camogie teams for competition.

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.

Physical and technical demands of offence, defence, and contested phases of play in Australian Football

Background

This study compared the physical demands and effect of field location for different phases of play (offence, defence and contested), and examined the physical and technical demands of successful and unsuccessful phases of play during Australian Football matches.

Methods

Global positioning system (GPS) and technical performance data were collected from 32 male Australian Football players in one club over 19 games in the 2019 season. The GPS data was aligned with phases of play acquired using Champion Data. Linear mixed models were used to detect differences between phases of play and field location which were further contextualized using Cohen’s d effect size.

Results

Physical demands were greatest (p < 0.001) in defensive phases for backs (ES 0.61 to 1.42), and offensive phases for midfielders (ES 0.65 to 0.96) and forwards (ES 0.84 to 1.94). Additionally, distance and high-speed running were lowest in contested phases irrespective of playing position. Distance and high-speed running were greatest in larger field locations (e.g., full ground). No pattern was evident for accelerations or decelerations. Successful offensive plays demonstrated greater physical and technical outputs for midfielders and forwards, whereas the opposite was found for backs. Physical output was largely greater in unsuccessful defensive plays for all positions; however, the rate of tackles and marks was greater during successful defence.

Conclusion

These findings enable a greater understanding of the demands of Australian Football matches, and can be utilized to inform both representative training design, and the evaluation of player performance.

Physical and technical demands of Australian football: an analysis of maximum ball in play periods

BACKGROUND

This study compares ball in play (BiP) analyses and both whole game (WG) and quarter averaged data for physical and technical demands of sub-elite Australian football (AF) players competing in the West Australian Football League across playing positions.

METHODS

Microsensor data were collected from 33 male AF players in one club over 19 games of the 2019 season. BiP time periods and technical performance data (e.g., kicks) were acquired from the Champion Data timeline of statistics, and time matched to the microsensor data. Linear mixed modelling was utilised to establish differences between maximum BiP periods and averaged data.

RESULTS

The analyses indicated significant differences (p < 0.0001) between maximum BiP and WG data for all metrics and all playing position (half-line, key position, and midfielders). The percentage difference was greatest for very high-speed running (171-178%), accelerations (136-142%), high-intensity efforts (128-139%), and high-speed running (134-147%) compared to PlayerLoad™ (50-56%) and total running distance (56-59%). No significant (p > 0.05) differences were evident for maximum BiP periods when they were compared between playing positions (i.e., half line vs key position vs midfield). Significant (p < 0.0001) differences were also noted between maximum BiP phases and averaged data across all 4 quarters, for each microsensor metric, and all playing positions. Technical actions (e.g., kicks and handballs) were observed in 21-48% of maximum BiP phases, depending on playing positions and microsensor metric assessed, with kicks and handballs constituting > 50% of all actions performed.

CONCLUSIONS

These results show the BiP analysis method provides a more accurate assessment of the physical demands and technical actions performed by AF players, which are underestimated when using averaged data. The data presented in this study may be used to inform the design and monitoring of representative practice, ensuring that athletes are prepared for both the physical and technical demands of the most demanding passages of play.