Factors that affect handball execution in Australian Football.

A handball is one of two technical skills used to dispose of the ball in Australian Football. Previous research has only considered handball effectiveness in the analysis of team performance and there is a need to understand whether there are other more important characteristics of handball execution that explain effectiveness (i.e., performance). 1342 handballs from Australian Football League matches were analysed. Ten characteristic variables were created that represent the context and execution of each handball included in the analysis. A mixed effects generalised linear model was used to evaluate the effect of the (ten) characteristics on handball outcome. Three out of ten characteristics were associated with handball outcome, and these related to the posture of the handballer and the type of defensive pressure applied to the handballer and the receiver of the handball. These findings explain both how to increase handball effectiveness and how to reduce the handball effectiveness of an opposition team. Given the important role of handballing in passing sequences and maintaining ball possession, the practical application of these findings could enhance overall team performance.

Understanding passing network characteristics and their link to match outcome in elite Netball.

Player interactions in Netball are critical during attacking phases of play to ensure possession is maintained and scoring opportunities are created. This study aims to analyse the characteristics of the passing networks of elite Netball teams and their association with performance outcomes (i.e., win/loss and final margin). Five network metrics used to represent the characteristics of teamwork were calculated for all team performances (n = 112) from one season of professional Netball in Australia. A two-way ANOVA and multiple linear modelling were used to compare characteristics between teams and match outcomes and to predict score margin, respectively. Pass density (F = 65.09, df = 102, p < .001) and pass centrality (F = 7.61, df = 102, p < .01) differed (were higher) in wins/losses. They were also statistically significant contributors (p ≤ .005) to the linear model that predicted a score margin (R2 = .731). Key player centrality and mutual connectedness were different between teams but did not differ by match outcome. The results suggest that, ideally, Netball teams should maximise the number of connections between player pairings, while also relying on a subset of players to be heavily involved in passing sequences. Team cohesion (via passing) therefore appears to be an important measure of team success in elite Netball.

Real time prediction of match outcomes in Australian football.

This study aimed to determine whether machine learning models based on technical performance and not score margin could be used to predict end-of-match outcome of Australian football matches in real-time. If efficacious, these models could be used to generate insights about team performance and support the decision-making of coaches during matches. A database of 168 team technical performance indicators from 829 Australian Football League matches played between 2017 and 2021 was used. Two feature sets (data-driven and data-informed) were used to train and evaluate six models (generalised linear model, random forest and adaboost) on match outcome prediction (Win/Loss) over 120 epochs (a representation of normalised time during each match). All models performed well (mean classification accuracy = 73.5-75.8%) in comparison with a benchmark score-based model (mean classification accuracy = 77.4%). Data-informed feature sets performed better than data-driven in most cases. Classification accuracy was low at the start of a match (45.7-48.8%) but increased to a peak near the end of a match (87.2-92.7%). These findings suggest that any of the employed models can be used to formulate in-match decision support. The model which is best in practice will depend on factors such as time-cost trade-off, feasibility and the perceived value of its suggestions.

Physical movement demands of elite-level netball match-play as measured by an indoor positioning system.

Physical movement demands in elite netball match-play have been limited to notational analysis or accelerometer-derived measures, due in part to the indoor environment in which they are played. Commercially available local positioning systems (LPS) using ultra-wideband communication have been designed to bring similar capabilities as global positioning systems (GPS) to indoor environments. This study aims to quantify both spatiotemporal and traditional accelerometer-derived measures, to assess the movement demands of all playing positions, during Australian national netball league matches. Total distance, metreage per minute, acceleration density, acceleration density index, acceleration load, jumps, velocity bands, acceleration bands and PlayerLoad variables have been presented for each position. Mean total distance-covered in match-play differed substantially between positions. Centre position accumulated the highest mean distance (5462.1 ± 169.4 m), whilst the Goal Shooter consistently covered the lowest mean distance (2134 ± 102.6 m). Change of direction relative to movement area was highest for the two most restricted positions based on average acceleration per 10 m covered during match-play (Goal Shooter; 7.21 ± 0.88 m · s - 2 and Goal Keeper; 6.75 ± 0.37 m · s - 2, remaining positions; 5.71 ± 0.14 m · s - 2). The positional profiles outlined in this study can assist skill and conditioning coaches to prescribe training sessions that will optimise the athlete's physical preparation for the demands of competition.

Team and seasonal performance indicator evolution in the ANZ Championship netball league.

Analysis of netball has received scant attention in the literature and there is little understanding of the dynamics of netball game-play. This study aimed to analyse team and seasonal performance indicator (dis)similarity in the ANZ Championship (netball). Total season values for nine performance indicators were analysed for the ten ANZ Championship teams from 2009 to 2016. The data were analysed using a multivariate, distance-based, approach. Specifically, non-metric multidimensional scaling was used to examine seasonal and team (dis)similarity. After declining from 2009, shooting percentage, goal assists, centre pass receives, penalties and turnovers began to rise from 2011. Both penalties and turnovers declined from 2015, in addition to attempts at goal. The two-dimensional multivariate ordination plot showed relative similarity between each team and season over the observational period, suggesting stagnant game-play dynamics. Further, despite idiosyncratic seasonal profiles, teams generally followed similar directional progression across the ordination surface. Despite being observed in other team invasion sports, league-wide synchronous evolutionary tendencies were not observed within the ANZ Championships between the 2006 to 2016 seasons. However, certain teams did display seasonal fluctuation in their observed multivariate profile, with these seasonal idiosyncrasies being discussed relative to coaching and playing roster changes specific to the analysed team.

Novel Technologies Found to be Valid and Reliable for the Measurement of Vertical Jump Height With Jump-and-Reach Testing.

Brooks, ER, Benson, AC, and Bruce, LM. Novel technologies found to be valid and reliable for the measurement of vertical jump height with jump-and-reach testing. J Strength Cond Res 32(10): 2838-2845, 2018-Vertical jump testing is used by coaches and athletes across many sports and disciplines to assess lower-body power and neuromuscular fatigue. A range of devices are available to measure jump height, with recent innovations attempting to improve portability, usability, and accessibility. New devices should be evaluated for their effectiveness and dependability in specific tests before being adopted. The purpose of this study was to assess the validity and reliability of 2 novel measurement devices for jump height testing with a jump-and-reach protocol. Twenty-six healthy, active adults participated during 2 testing occasions. A wearable inertial measurement unit (VERT) and a smart device application (My Jump 2) were compared with established measures (force platform and jump-and-reach apparatus [Yardstick]). Correlations between the VERT and force platform were r = 0.95 (90% confidence interval [CI]: 0.93-0.97), and r = 0.93 (90% CI: 0.90-0.95) for the Yardstick. Correlations between the My Jump 2 app and force platform were r = 0.98 (90% CI: 0.97-0.99), and r = 0.94 (90% CI: 0.92-0.96) for the Yardstick. Reliability, measured as intraclass correlation coefficient (ICC), was 0.91 (90% CI: 0.87-0.94) for the VERT, and 0.97 (90% CI: 0.96-0.98) for the My Jump 2 app. Intrarater reliability for the My Jump 2 app was ICC = 0.99 (90% CI: 0.99-0.99). The VERT and the My Jump 2 app have both shown acceptable validity and reliability compared with both the force platform and Yardstick. However, practitioners should consider which measurement device/s to use based on the acceptable level of potential error for their population and testing objectives.

Validity of the 30-15 Intermittent Fitness Test in Subelite Female Athletes.

Bruce, LM and Moule, SJ. Validity of the 30-15 intermittent fitness test in subelite female athletes. J Strength Cond Res 31(11): 3077-3082, 2017-The purpose of this study was to assess the suitability of the 30-15 Intermittent Fitness Test (IFT) as a test in netball using female athletes. Twenty-six female subelite netballers (mean age = 19.7 ± 4.6 years, mean height = 176.0 ± 6.1 cm, mean body mass = 69.7 ± 9.3 kg) completed the yo-yo intermittent recovery test level 1 (yo-yo IRT1) and the 30-15 IFT. Participants performed both assessments 1 week apart before the intervention and both tests 1 week apart after the training intervention (for a total of 4 testing sessions). A 6-week training intervention occurred between the test occasions. Pearson's correlations revealed significant very strong relationships between the 30-15 IFT and yo-yo IRT on both test occasions (test occasion 1: r = 0.71, p = 0.003 [95% confidence interval {CI} 0.35-0.89], magnitude of effect, most likely; test occasion 2: r = 0.72, p = 0.001 [95% CI: 0.42-0.88], magnitude of effect, most likely). Repeated-measures analysis of variances examining the effect of position on performance changes revealed main effects for test occasion and a position × test occasion interaction for both the 30-15 IFT and the yo-yo IRT1 (30-15 IFT: test occasion [F(1,14) = 28.68, p = 0.001, ηp = 0.67], position × test occasion interaction [F(2,14) = 9.38, p = 0.003, ηp = 0.57]; yo-yo IRT1: test occasion [F(1,15) = 11.72, p = 0.004, ηp = 0.44], position × test occasion interaction [F(2,15) = 9.96, p = 0.002, ηp = 0.57]). Results show that the 30-15 IFT is a suitable test for female netballers as it was able to detect improvements in performance after a training intervention, in addition to having a very strong significant relationship with the yo-yo IRT1.

The relationship between game-based performance indicators and developmental level in junior Australian football: Implications for coaching.

Identifying performance differences between juniors at different stages of a talent pathway may assist with the development of prospective talent. This study investigated the relationship between game-based performance indicators and developmental level in junior Australian football (AF). Players were categorised into 2 groups according to developmental level; U16 and U18. Physical and technical skill performance indicators were collated for all U16 (n = 200) and U18 (n = 244) participants of their respective 2014 national championships. Data were acquired from all 28 games (12 U16, 16 U18); resulting in 1360 player observations (568 U16, 792 U18). Microtechnology and a commercial provider facilitated the quantification of 15 performance indicators. Generalised estimating equations (GEEs) modelled the extent to which these performance indicators were associated with developmental level. The GEE model revealed that "contested marks" and "contested possessions" had the strongest association with the U16 level, while "total marks" and "clearances" had the strongest association with the U18 level. The remaining performance indicators were not developmentally discriminant. These results indicate that there are distinctive features of gameplay more associated with the U16 and U18 levels in AF. Coaches may wish to consider these results when constructing training drills designed to minimise developmental gaps.

Discriminating talent-identified junior Australian football players using a video decision-making task.

This study examined if a video decision-making task could discriminate talent-identified junior Australian football players from their non-talent-identified counterparts. Participants were recruited from the 2013 under 18 (U18) West Australian Football League competition and classified into two groups: talent-identified (State U18 Academy representatives; n = 25; 17.8 ± 0.5 years) and non-talent-identified (non-State U18 Academy selection; n = 25; 17.3 ± 0.6 years). Participants completed a video decision-making task consisting of 26 clips sourced from the Australian Football League game-day footage, recording responses on a sheet provided. A score of "1" was given for correct and "0" for incorrect responses, with the participants total score used as the criterion value. One-way analysis of variance tested the main effect of "status" on the task criterion, whilst a bootstrapped receiver operating characteristic (ROC) curve assessed the discriminant ability of the task. An area under the curve (AUC) of 1 (100%) represented perfect discrimination. Between-group differences were evident (P < 0.05) and the ROC curve was maximised with a score of 15.5/26 (60%) (AUC = 89.0%), correctly classifying 92% and 76% of the talent-identified and non-talent-identified participants, respectively. Future research should investigate the mechanisms leading to the superior decision-making observed in the talent-identified group.

The application of a multi-dimensional assessment approach to talent identification in Australian football.

This study investigated whether a multi-dimensional assessment could assist with talent identification in junior Australian football (AF). Participants were recruited from an elite under 18 (U18) AF competition and classified into two groups; talent identified (State U18 Academy representatives; n = 42; 17.6 ± 0.4 y) and non-talent identified (non-State U18 Academy representatives; n = 42; 17.4 ± 0.5 y). Both groups completed a multi-dimensional assessment, which consisted of physical (standing height, dynamic vertical jump height and 20 m multistage fitness test), technical (kicking and handballing tests) and perceptual-cognitive (video decision-making task) performance outcome tests. A multivariate analysis of variance tested the main effect of status on the test criterions, whilst a receiver operating characteristic curve assessed the discrimination provided from the full assessment. The talent identified players outperformed their non-talent identified peers in each test (P < 0.05). The receiver operating characteristic curve reflected near perfect discrimination (AUC = 95.4%), correctly classifying 95% and 86% of the talent identified and non-talent identified participants, respectively. When compared to single assessment approaches, this multi-dimensional assessment reflects a more comprehensive means of talent identification in AF. This study further highlights the importance of assessing multi-dimensional performance qualities when identifying talented team sports.

Reliability and validity of a GPS-enabled iPhone "app" to measure physical activity.

This study assessed the validity and reliability of an iPhone "app" and two sport-specific global positioning system (GPS) units to monitor distance, intensity and contextual physical activity. Forty (23 female, 17 male) 18-55-year-olds completed two trials of six laps around a 400-m athletics track wearing GPSports Pro and WiSpi units (5 and 1 Hz) and an iPhone(TM) with a Motion X GPS(TM) "app" that used the inbuilt iPhone location services application programming interface to obtain its sampling rate (which is likely to be ≤1 Hz). Overall, the statistical agreement, assessed using t-tests and Bland-Altman plots, indicated an underestimation of the known track distance (2.400 km) and average speed by the Motion X GPS "app" and GPSports Pro while the GPSports WiSpi(TM) device overestimated these outcomes. There was a ≤3% variation between trials for distance and average speed when measured by any of the GPS devices. Thus, the smartphone "app" trialled could be considered as an accessible alternative to provide high-quality contextualised data to enable ubiquitous monitoring and modification of programmes to ensure appropriate intensity and type of physical activity is prescribed and more importantly adhered to.

The use of skill tests to predict status in junior Australian football.

This study examined whether skill tests were predictive of status in junior Australian football. Players were recruited from the 2013 under 18 (U18) West Australian Football League competition and classified into two groups: elite (state U18 squad representative; n = 25; 17.9 ± 0.5 years) and subelite (nonstate U18 squad representative; n = 25; 17.3 ± 0.6 years). Both groups completed the Australian football kicking (AFK) and Australian football handballing (AFHB) tests, assessing kicking accuracy/ball speed and handballing accuracy on dominant and nondominant sides. A multivariate analysis of variance (MANOVA) modelled the main effect of "status", whilst logistic regression models were built for the predictive analysis using the same test parameters. Between-group differences were noted across all parameters, with the combination of kicking accuracy and ball speed on the dominant and nondominant sides being the best predictor of status for the AFK test (wi = 0.25, AUC = 89.4%) and the combination of accuracy on the dominant and nondominant sides being the best predictor of status for the AFHB test (wi = 0.80, AUC = 88.4%). The AFK and AFHB tests are predictive of status, suggesting that their use is warranted as a means of talent identification in junior Australian football.

The impact of Wheelchair Rugby classification lineup structure on possession outcome.

OBJECTIVES: To investigate the impact that the structure and combination of athlete classification within lineups has on possession outcome in Wheelchair Rugby (WR). DESIGN: Retrospective. METHODS: Analysis was conducted using data from all 18 WR matches from the 2020 Tokyo Paralympic Games. Pearson's chi-squared analysis was conducted to investigate the effect of lineup structures on performance and a nested generalised logistic mixed model (GLMM) was fitted to the data to investigate the association between independent variables and the outcome of possessions. Specifically, the impact of offensive and defensive lineup structures on possession outcome and whether the offensive and defensive lineup structures matching or not impact possession outcome. RESULTS: There was a significant relationship between the offensive lineup structure and possession outcome. Balanced lineups had greater turnovers than expected. Balanced lineups also had fewer tries than expected, whilst high-low lineups had fewer than expected turnovers. There were no significant associations between the defensive lineup structure and possession outcome. Furthermore, no significant associations were found between whether the structure of the offensive and defensive lineup matched (or not) and the possession outcome. CONCLUSIONS: The findings suggest that the offensive team's lineup structure plays a more prominent role in impacting possession outcome, compared to the defensive team's lineup structure. The present results provide valuable insights into WR performance for coaches, practitioners, and researchers.

Impact of Overtraining on Cognitive Function in Endurance Athletes: A Systematic Review.

BACKGROUND: Endurance sports require significant training loads to elicit the desired training effects on an athlete's body. However, if adequate recovery is not provided, overtraining may occur, with corresponding decrements in performance. As such, there is a need for measures that can be tracked, to monitor athlete adaptation to training loads, and provide early warning of possible maladaptation. The aim of this review was to determine if a relationship exists between overtraining and cognitive function in endurance athletes. METHODS: A systematic search of AMED, MEDLINE, SPORTDiscus and APA PsycINFO was conducted. Eligibility criteria included original peer reviewed research, written in English, published between January 2000 and May 2022, and using human participants. Of the 221 articles screened, a total of seven studies met the inclusion criteria and were included in this review. RESULTS: The findings of the review suggest that there is a relationship between overtraining and cognitive function with all seven studies finding that cognitive performance declined in response to athletes becoming overreached or overtrained. These studies found that reaction time (as measured by Stroop colour test) increased in response to both overreaching and overtraining. CONCLUSIONS: Cognitive function tests such as the Stroop Colour Test could be included as part of a broader programme for monitoring athlete adaptation to training.

A framework to explain the in-match decision-making of elite Australian football coaches.

The ability to make effective decisions is an important function of any football coach, whether during training, team selection, match-day performance or post-match player evaluation. It is not yet known how elite Australian football coaches make decisions during matches, in time-constrained but well-resourced environments. This study is the first to explore the decision-making of elite Australian football coaches during matches, in pursuit of identifying opportunities to improve the translation and implementation of research findings into the competitive match environment. Using semi-structured interviews and thematic analysis, a six-stage framework of the decision-making of elite Australian football coaches during matches was developed. The stages include (1) Opportunity trigger, (2) Understand the opportunity, (3) Determine the need for action, (4) Explore options, (5) Take action and (6) Evaluate the decision. Coaches relied on subjective and objective sources of information and consulted with assistant coaches, performance analysts, and sport scientists. The findings enable researchers to ensure future interventions to improve decision-making during matches are well integrated. They also provide an opportunity for coaches to reflect on their own decision-making process, identifying targeted areas for improvement in their own practice.

Reliability of live and video-based coding in netball using the NetballStats application.

Understanding reliability of performance analysis tools is important to ensure match to match comparisons can be undertaken with the knowledge of consistency between coding situations. There are few published studies examining the reliability of commonly used performance analysis tools. The aim of this project was to assess the inter- and intra-rater reliability of the NetballStats application and to make comparisons between live and video-based coding situations. Two 'coders' coded eight netball matches using the NetballStats application, coding each match live, then twice from video. Level of agreement was assessed for frequency counts across the variables coded. Results showed that intra-rater agreement was higher than inter-rater agreement and that reliability from video coding is better than from live coding. High frequency events automatically coded by the application and events that are well defined had greater levels of agreement than lower frequency events and subjectively judged events. Live coding situations underrepresent occurrence of events, particularly for high frequency events such as 'possession'. To ensure reliability between coders, clubs should provide an extensive training program to coders with clear instructions on coding subjective events. Coaches should be aware that live coding underestimates some event types and factor this into their decision making processes.

Understanding load in netball - An analysis of multiple seasons, phases, and teams.

Studies of training and competition load in sport are usually based on data that represents a sample of a league and or annual training program. These studies sometimes explore important factors that are affected by load, such as training adaptations and injury risk. The generalisability of the conclusions of these studies, can depend on how much load varies between seasons, training phases and teams. The interpretation of previous load studies and the design of future load studies should be influenced by an understanding of how load can vary across seasons, training phases and between teams. The current study compared training loads (session rating of perceived exertion x session duration) between all (8) teams in an elite Netball competition for multiple (2) season phases and (2) seasons. A total of 29,545 records of athlete session training loads were included in the analysis. Linear mixed models identified differences between seasons and training phases (p < .05). There were also differences between teams and a complex set of interactions between these three factors (season, phase, and team) (p < .05). While the absolute value of the training loads reported here are only relevant to elite netball, these results illustrate that when data is sampled from a broader context, the range and variation in load may increase. This highlights the importance of cautiously interpreting and generalisation of findings from load studies that use limited data sets.

A profile of the skills, attributes, development, and employment opportunities for sport scientists in Australia.

OBJECTIVES: The purpose of this study was to document the technical and transferrable skills required for sport scientists, and perceived employment opportunities both currently and in the future with a particular emphasis on comparisons between academic and applied sport scientists. DESIGN: Cross-sectional survey methodology. METHODS: 117 Australian sport science employees completed an online survey capturing demographic information, perceptions about the importance of technical skills, transferable skills, future employment opportunities as well as free-text information on future careers, challenges, and opportunities for the profession. Descriptive statistics were used to summarise information and comparisons made between academic and applied sport science participants. RESULTS: Participants were predominantly male and 35 years or younger, with half reporting they held only one position within the industry. Most technical and transferrable skills were rated as important (>4.0 out of 5.0), with practitioner-focused skills rated somewhat more important by applied sport scientists compared to scientific-focused skills rated somewhat more important by academics, and applied sport scientists generally rating transferable skills as more important compared to academics (d > 0.5). Value and supply/demand were identified as challenges to the industry with discipline-specific roles and non-elite populations considered areas for future jobs. CONCLUSIONS: Participants felt there would be more jobs in the future and that these would be in discipline-specific roles and/or non-elite populations. Both technical and interpersonal skills were considered important for sport scientists. The greatest challenges are how sport science is valued and the potential oversupply of sport science graduates.

The effect of team formation on defensive performance in Australian football.

OBJECTIVES: Understanding the successful characteristics of team formation during different scenarios in Australian Football matches can assist coaches in making important tactical match-day and training decisions. The aims of this study were to explore the outcomes of entries inside 50 m of the goal, in Australian Football and to determine whether there was an association between team formation and team defensive performance after a turnover. DESIGN: Observational. METHODS: Global Positioning System (GPS) data, technical event data and video files from 22 matches in one season were obtained from an elite Australian Football club. Of 1092 forward 50 entries, 392 possession chains that resulted in a turnover were analysed. Variables representing team formation of players at the occurrence of turnover were compared between positive and negative outcomes of the subsequent possession chain. Logistic regression and decision tree modelling were also used to explore associations and variable importance. RESULTS: None of 18 team formation characteristics differed between positive and negative outcomes of turnovers. Multivariate modelling identified that having a team formation with greater width than length made it more likely to result in a positive outcome (Decision tree classification accuracy = 69.5%, AUROC = 0.72). CONCLUSIONS: No single characteristic of team formation affects the outcome of a turnover possession chain, however team formation that was wider than it was long may be associated with a more desirable outcome. The lack of association between most team formation characteristics and defensive outcomes, highlight the risk of over emphasising team formation in tactical planning for some phases of play.

Quantifying jumps and external load in netball using VERT inertial measurement units.

This study assesses the relationship between an inexpensive and an established inertial measurement device for the measurement of movement and jumps in netball. Twenty-five female netballers participated in this study (11 elite and 14 sub-elite). Two inertial measurement devices (Catapult ClearSky T6 and VERT Classic) were worn simultaneously during a training session. The 'Kinetic Energy' output provided by the VERT device was compared to the total PlayerLoad collected by the ClearSky T6 device. Automated total jump counts were also compared across devices. A correlation of r = 0.76 (95% confidence interval [CI]; 0.52 to 0.89) was identified between total PlayerLoad and 'Kinetic Energy'. Similarly, a correlation of r = 0.81 (95% CI; 0.61 to 0.91) was identified for the relationship between ClearSky T6 jump count and VERT jump count. Mean bias of 1.7 jumps (95% CI; -2.5 to 5.8) with 95% limits of agreement (-17.9 to 21.3) were found when comparing the jump counts between the ClearSky T6 and VERT devices. The correlations found in this study indicate that the VERT devices may be an accessible alternative for sub-elite athletes; however, the wide confidence intervals and limits of agreement warrant caution.