Search

There is limited research investigating objective practice monitoring in team sports. This observational study examined the practice activities used by eight professional coaches across 72 different practice sessions in one season within a professional Australian football team. This study aimed to evaluate the extent to which these practice types differed from those shown to facilitate skill acquisition in team sports. Across the whole season (pre-season and in-season), coaches implemented seven practice types which were categorised into training-form and playing-form. Practice type frequencies were different between pre- and in-season (χ2 = 109.6, p 2 = 30.8, p

Objectives: Connectedness is a cooperative network measure that describes how well players in the team bi-directionally connect and how easily reachable they are to other players. It has been associated with an increased probability of winning competitive matches in professional Australian Football (AF), although applications towards training have not been reported. Therefore, this study investigated associations between constraints manipulated by professional AF coaches and the connectedness of cooperative passing networks during a small-sided game (SSG). Design: Data were collected describing the task constraints manipulated by professional coaches across one SSG performed on multiple occasions. The SSG focused on transitioning between defence and attack and was performed fifteen times across a whole season, resulting in 36 observations of team connectedness. Method: A linear mixed-effects model was constructed to examine the collective influence of constraints manipulations made by professional coaches (e.g. field size) and team skill characteristics (e.g. kick efficiency) on connectedness scores. Results: The number of team shots on goal and the time on task both positively contributed to connectedness scores, explaining 65% of its variance. Conclusion: The findings show that the number of shots on goal and the time on task may be used to elicit higher or lower connectedness scores in AF SSGs. Skill acquisition specialists, in conjunction with coaching staff, can use these metrics to aid practice design in professional AF or indeed other invasion-style team sports.

Augmented feedback supplements or replaces task-intrinsic feedback and is common in team sports, however, no studies have reported on augmented feedback provision in professional Australian Football (AF) practice. This study investigated the effects of practice characteristics (feedback intervention frequency, practice time, practice type, season phase, practice activity form and competitive match result) on the duration of feedback provided by professional AF coaches. Two linear mixed-effects models were constructed. The first examined the collective associations between these practice characteristics and feedback durations while the second model investigated the associations between the same practice characteristics and previous match result. Results showed the feedback intervention frequency, practice time and a practice time*feedback intervention frequency interaction explained 65% of feedback duration whenever feedback was provided. Additionally, practice time, feedback intervention frequency, a practice time*match result interaction and a match result*feedback intervention frequency interaction explained 99% of feedback duration in-season. Important factors that were hypothesised to affect feedback durations in AF such as practice type, practice activity form or season phase did not contribute any explanatory power. This study provides information on how professional AF coaches provide augmented feedback in-situ and provides opportunities for skill acquisition specialists to aid coaches when delivering augmented feedback.

Introduction: This study sought to reduce the dimensionality of commonly reported spatiotemporal characteristics obtained from Australian Football games to facilitate their practical use and interpretability. Methods: A retrospective longitudinal design was utilised with team and individual spatiotemporal variables, measured via global navigation satellite system devices, collected during official Australian Football League matched over three seasons. Two separate principal component analyses were conducted at the team and individual level to reduce correlated spatiotemporal characteristics into a smaller set of uncorrelated components. Results: At the team level, eighteen variables were reduced to five components pertaining to dispersive coordination, lateral predictability and spacing, multidirectional synchrony, longitudinal predictability and longitudinal behaviour whilst maintaining 69% of variance in the original dataset. At the individual level, fifteen variables were reduced to four components pertaining to multidirectional and spacing synchrony, unpredictability, player movement and player positioning whilst maintaining 64% of variance. Conclusion: This study is the first to provide a simplified, novel method for analysing spatiotemporal behaviour in an Australian Football context with both the team- and individual- derived metrics revealing useful information for coaches and practitioners. Components may provide insight into behaviours that emerge and persist throughout a game and allow coaches to distinguish between different playing/behavioural styles.

This study sought to reduce the dimensionality of commonly reported spatiotemporal characteristics obtained from Australian Football games to facilitate their practical use and interpretability.A retrospective longitudinal design was utilised with team and individual spatiotemporal variables, measured via global navigation satellite system devices, collected during official Australian Football League matched over three seasons. Two separate principal component analyses were conducted at the team and individual level to reduce correlated spatiotemporal characteristics into a smaller set of uncorrelated components.At the team level, eighteen variables were reduced to five components pertaining to dispersive coordination, lateral predictability and spacing, multidirectional synchrony, longitudinal predictability and longitudinal behaviour whilst maintaining 69% of variance in the original dataset. At the individual level, fifteen variables were reduced to four components pertaining toThis study is the first to provide a simplified, novel method for analysing spatiotemporal behaviour in an Australian Football context with both the team- and individual- derived metrics revealing useful information for coaches and practitioners. Components may provide insight into behaviours that emerge and persist throughout a game and allow coaches to distinguish between different playing/behavioural styles.

This study measured the influence of biological maturity across numerous performance parameters for talent identification in Australian football. Anthropometry, estimated maturity status using a maturity ratio from anthropometric measurements and chronological age, motor competence, physical fitness and small-sided match involvements of 227 U13-U15 high-level academy athletes were assessed. Multivariate analysis of variance revealed significant moderate effects of maturity status on physical fitness (p = 0.008, ES = 0.07) and significant large effects on anthropometry (p = 0.001, ES = 0.20), but not on motor competence or match involvements. Univariate analyses of variance demonstrated significant large effects of maturity on anthropometry, but only one subset of physical fitness (i.e. lower-body power). U15 players selected into a U16 development programme were biologically older thandeselected players, despite selection being independent of maturity when a categorical descriptor was used. This study confirms that maturation affects anthropometry and certain measures of physical fitness in youth Australian football players, but not match involvements and motor competence. Furthermore, a player’s maturity could affect selection and progression into advanced academy programmes. Involvements and motor competence should be included in multidimensional assessment batteries for Australian Football as they appear less confounded by maturity than fitness and anthropometry.

Match simulation in team sport should sample representative constraints and behaviours to those observed in competitive matches to enhance near skill transfer. This study compared task constraints (field length, field width, length per width ratio, space per player), time-standardised skill metrics (goals, shots on goal, handballs, kicks, marks, turnovers, tackles, handball proficiency, kick proficiency) and cooperative passing metrics (connectedness, indegree variability and outdegree variability) between match simulation practice and competitive Australian Football League (AFL) games for one professional team. MANOVAs identified activity-related differences for task constraints, skill metrics and cooperative passing networks. During match simulation, goals were scored more frequently, but with less passing actions per minute. Receiving and distributing passing networks were more centralised (reliance on fewer key individuals), with less turnovers and tackles per minute compared to AFL matches. If match simulation is designed to reflect competition, then player and team skill preparation may be compromised. Furthermore, the competing demands in high-performance sport may restrict the degree of representativeness that can be achieved during practice. These findings provide valuable insight and may assist practitioners and/or coaches to understand the value of match simulation practice and to maximise near skill transfer from match simulation to competition.

Collective behaviour is an important component of team performance in team sports. This study used a binomial generalised linear mixed effects regression model to investigate the relationship between cooperative passing network characteristics and match outcomes of professional Australian Football League competition games across four seasons between 2016 and 2019. It divided a sample of 1629 observations into a training and testing partition used to develop and assess the validity of the model used in this study, respectively. The results of this study reveal that a team's connectedness is associated with the probability of winning Australian Football League games (Akaike Information Criterion = 1637.3, residual df= 1297, deviance = 1625.3). When most players within a team are involved in the team's passing network bidirectionally (i.e. a well-connected network; odds ratio = 1.053; 95% confidence interval: 4.2–6.5%, p

Despite advancements in the scale of data available for quantifying the physical and spatiotemporal characteristics of match play, there is an absence of research combining these aspects in professional sport. This study sought to differentiate between phases of play in professional Australian football using novel physical and spatiotemporal metrics. Data was obtained from Australian Football League games to provide new insight into the specific characteristics of each phase of play. A retrospective cross-sectional design was utilised with team's physical and spatiotemporal variables, measured via global navigation satellite system devices. A multinomial logistic regression was conducted to determine which physical and spatiotemporal measures were associated with each phase of play (contested play, defence, offence, set shot, goal reset, umpire stoppage). The addition of the predictors to a model that contained only the intercept significantly improved the fit between the model and data, with the logistic model correctly predicting the phase of play for 63.7% of the cases. This was the first study to concurrently examine differences in physical and spatiotemporal characteristics with respect to phase of play in an Australian football context. Differences in duration, physical and spatiotemporal properties were observed, providing new insight for coaches and subsequently providing direction for conditioning and practice design.

Objectives This study aimed to provide a simplified, novel method for analysing technical skill involvements in an Australian Football context by reducing the dimensionality of commonly reported skill counts obtained from Australian Football League (AFL) games. This may facilitate their practical use and interpretability. Design Retrospective longitudinal design where individual players’ technical skill counts were collected over three seasons of official AFL games. Methods Seventy-three skill count values provided publicly by ChampionData® were collected for each match over a three-year analysis period. A principal component analysis was used to reduce the dimensionality of a large number of correlated technical skill indicators into a smaller set of uncorrelated components whilst maintaining most of the variance from the original data set. Results The principal component analysis derived four principal components pertaining to high-pressure success, low-pressure success, attacking ball movement ability and scoring ability. Conclusions This study is the first to provide a simplified, novel method for analysing technical skill counts in Australian Football. The derived metrics reveal useful information for coaches and practitioners. This may consequently ease the interpretation of skill count data available to coaches from games, guide opposition analysis, help in the design of representative practice and inform player performance ratings.

© 2018, © 2018 Informa UK Limited, trading as Taylor & Francis Group. There is limited research in talent identification in youth Australian Football (AF), especially the factors that underpin selection into higher-level development programs. Therefore, this study explored age-related differences in high-level youth AF players and investigated characteristics influencing selection into a high-level development program. Anthropometry (stature, sitting height, body mass), maturity (estimated age at peak height velocity), motor competence (Körperkoordinationstest für Kinder), fitness (change of direction speed, lower body power and upper body muscular endurance) and coach skill ratings (kicking, marking and handballing) of 277 state academy players (U13-U15) were assessed. MANOVAs identified significant age-related differences for anthropometry, fitness, and coach skill ratings. Furthermore, 90.9 and 90.0% of U15 selected and deselected players were classified correctly. Selected players were more mature, taller, heavier, more explosive, faster at changing directions, and had superior kick technique and marking results. These results demonstrate considerable age-group performance outcome differences, highlighting that high-level academies should aim to select or deselect after 15 years of age. Additionally, it appears earlier maturing players are favoured for selection into a high-level academy. While practitioners must consider the confounding effect of maturation, early maturing players may be favoured for their ability to withstand increasing demands in higher-level youth AF.

Objectives Reducing the dimensionality of commonly reported complex network characteristics obtained from Australian Football League (AFL) games to facilitate their practical use and interpretability. Design Retrospective longitudinal design where individual players’ interactions, determined through the distribution and receipt of kicks and handballs, during official AFL games were collected over three seasons. Methods A principal component analysis was used to reduce the number of characteristics related to the cooperative network analysis. Results The principal component analysis derived two individual-based principal components pertaining to in- and out-degree importance and three team-based principal components related to connectedness and in- and out-degree centralisation. Conclusions This study is the first to provide a simplified, novel method for analysing complex network structures in an Australian Football context with both the team- and individual-derived metrics revealing useful information for coaches and practitioners. This may consequently guide opposition analysis, training implementation, player performance ratings and player selection.

© 2020 Informa UK Limited, trading as Taylor & Francis Group. Purpose: To provide a simplified, novel method for analysing the physical demands in an Australian Football context by reducing the dimensionality of commonly reported physical characteristics obtained from match play. This may facilitate their practical use and interpretability. Methods: A retrospective longitudinal design was utilised with individual players’ physical outputs, measured via global navigation satellite system devices, collected during official Australian Football League matches over three seasons. A principal component analysis was used to reduce a large number of correlated physical characteristics related to the analysis of physical match demands into a smaller set of uncorrelated components. Results: Forty-six variables were reduced to five principal components whilst maintaining 56% of the variance in the original dataset. The principal component analysis derived five individual-based principal components pertaining to low-moderate movement volume, high speed running volume, accelerations, change of direction and impacts. Conclusions: Utilising factor loadings (eigenvectors) derived from a principal component analysis, this study is the first to provide a simplified, novel method for analysing the physical demands in an Australian Football context with the derived metrics revealing useful information for coaches and practitioners. This may consequently guide training implementation, player performance ratings and player selection. Further, these new values may facilitate the monitoring of physical player loads.

© 2018 Sports Medicine Australia Objectives: This study aimed to assess the first instance and prevalence of the Relative Age Effect (RAE) in the male Australian Football (AF) talent development pathway through to the Australian Football League (AFL). Design: Retrospective cross-sectional analysis. Methods: Birthdate distribution was accessed from an U10–U12 AF academy trial (n = 514), U13–U19 AF academy players (n = 408), AFL state, national and international combines (n = 2989), AFL Rising Star nominees (n = 50) and the top ten AFL Brownlow vote recipients (n = 50) between 2013–2017. Results: Chi-squared analysis showed significant overrepresentation to early born players in the selection year for both quartile and half-year compared to the previously known distribution at different stages of the talent pathway. Odds ratio demonstrated bias to players born in quartiles one and two of the selection year compared to players born in quartile four in every cohort examined. Conclusions: RAEs appear between ages 10–12 in the male AF development pathway and continue to senior professional competition. RAEs are amplified as the competition for positions increases and at points where selection cut-offs occur. Interestingly, players receiving votes for the AFL's best and fairest award were 12.6 times more likely to be born in the first half of the year. This may suggest a latent effect, which has long term benefits for relatively older players. Nonetheless, the RAE affects career progression in a male AF talent pathway.

© 2019 Sports Medicine Australia Objectives: Identifying talented athletes from an early age to accelerate their development requires the investment of substantial resources. Due to the need for multifactorial approaches to talent identification, motor competence assessments are increasingly prevalent in contemporary testing batteries. Therefore, the aim of this review was to evaluate the literature on the use of a product-oriented motor competence assessment tool, the Körperkoordinationstest für Kinder (KTK) in the talent pathway and determine whether it is warranted in such programs. Methods: Three electronic databases (i.e. PubMed, SPORTDiscus and Web of Science) were searched for studies that used at least one component of the KTK to assess motor competence for talent detection, identification, development and selection in athletic populations. A total of 21 articles were included in the review, of which seven used the full version of the KTK and 14 used modified versions or individual components of the battery. The quality of included studies was assessed using a modified version of the Joanna Brigg's Institute Critical Appraisal Checklist. Results: The analysed literature suggests that the KTK can successfully distinguish between athletes of different competition levels and across different sporting domains, however, findings should be interpreted with caution due to the cross-sectional nature of the studies. Furthermore, the moving sideways subtest displayed the greatest discriminative power for athletes of different competition levels. Motor competence was not affected by maturation and did not differ between genders or playing positions. Conclusions: Collectively, these findings suggest that the KTK is a useful motor competence assessment in the talent pathway.