Quantifying the gap between under 18 and senior AFL football: 2003-2009 (original) (raw)
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Player movement patterns in an elite junior Australian rules football team: an exploratory study
Journal of sports science & medicine, 2007
This study explored the physical movement patterns associated with an elite Under 18 Australian Football (AF) team. Five field positions were selected with observations recording the number and relative per cent of "working "efforts (jogging, running, and sprinting), "resting "efforts (walking) and the total distances associated with "working "or "resting "efforts. Intra-observer reliability, using test- retest method, showed correlations were r = 0.98 or greater. The Wing position covered 11,877 m, the greatest total distance during an entire game, whilst the HBF and Centre positions both recorded 11,545 m and 11,537 m respectively and the Ruck position covered 9,203 m. The HBF recorded the greatest frequency of 'working' and…
Journal of science and medicine in sport, 2018
To compare game-play characteristics between elite youth and senior Australian National Rugby League (NRL) competitions. Longitudinal observational. The dataset consisted of 12 team performance indicators (e.g., 'all runs', 'offloads' and 'tackles') extracted from all 2016 national under 20 (U20) competition (elite youth; n=372 observations) and National Rugby League (NRL) (elite senior; n=378 observations) matches. Data was classified according to competition (Two levels: U20 and NRL) and modelled using two techniques. Firstly, non-metric multidimensional scaling resolved multivariate competition (dis)similarity, visualised using a two-dimensional ordination. Secondly, a conditional interference (CI) classification tree was grown to reveal the performance indicators most capable of explaining competition level. Non-metric multidimensional scaling revealed high competition dissimilarity, with U20 and NRL teams orienting distinctive positions on the first dime...
Journal of sports sciences, 2017
This study investigated age-related differences in maturity, physical and functional characteristics and playing performance in youth Australian Football (AF). Young male players (n = 156) were recruited from 12 teams across 6 age groups (U10-U15) of a recreational AF club. All players were tested for body size, maturity and fitness. Player performance was assessed during a match in which disposals (kicks and handballs) and their effectiveness were coded from a video recording and match running performance measured using Global Positioning System. Significant main effects (P < 0.01) for age group were observed for age, years to peak height velocity, body mass, height, 20 m sprint, maximal speed over 20 m, vertical jump, 20 m multistage shuttle run, match distance, high-speed running distance, peak speed, number of effective disposals and percentage of effective disposals. Age-related differences in fitness characteristics (speed, lower body power and endurance) appeared to transf...
Journal of Science and Medicine in Sport, 2014
Objectives: To determine the match-to-match variability in physical activity and technical performance measures in Australian Football, and examine the influence of playing position, time of season, and different seasons on these measures of variability. Design: Longitudinal observational study. Methods: Global positioning system, accelerometer and technical performance measures (total kicks, handballs, possessions and Champion Data rank) were collected from 33 players competing in the Australian Football League over 31 matches during 2011-2012 (N = 511 observations). The global positioning system data were categorised into total distance, mean speed (m min −1 ), high-speed running (>14.4 km h −1 ), very high-speed running (>19.9 km h −1 ), and sprint (>23.0 km h −1 ) distance while player load was collected from the accelerometer. The data were log transformed to provide coefficient of variation and the between subject standard deviation (expressed as percentages). Results: Match-to-match variability was increased for higher speed activities (high-speed running, very high-speed running, sprint distance, coefficient of variation %: 13.3-28.6%) compared to global measures (speed, total distance, player load, coefficient of variation %: 5.3-9.2%). The between-match variability was relativity stable for all measures between and within AFL seasons, with only few differences between positions. Higher speed activities (high-speed running, very high-speed running, sprint distance), but excluding mean speed, total distance and player load, were all higher in the final third phase of the season compared to the start of the season. Conclusions: While global measures of physical performance are relatively stable, higher-speed activities and technical measures exhibit a large degree of between-match variability in Australian Football. However, these measures remain relatively stable between positions, and within and between Australian Football League seasons.
Profile of position movement demands in elite junior Australian rules footballers
Journal of sports science & medicine, 2009
This study investigated the positional movement patterns in elite junior Australian Football (AF). Thirty players (17.1 ± 0.9 years) participating in this study were tracked over seven home games of the regular 2006 Victorian junior (Under 18) league season. Using lapsed-time video analysis, each position for an entire match was videotaped on three separate occasions over the course of the season. Data analysed included the number of individual efforts, duration and frequency of efforts; distance and percentage time for the classifications of standing, walking jogging, running and sprinting. Results showed that the midfield position travelled the greatest distance (4173 ± 238 m per quarter; p < 0.05; ES = .94) whilst the full forward/full back travelled the least (2605 ± 348 m per quarter, p < 0.05, ES = 1.21). For all positions, walking or jogging accounted for the greatest number of efforts (45-55%), conversely running and sprinting accounted for 5-13% of match efforts. The ...
Multifactorial Benchmarking of Longitudinal Player Performance in the Australian Football League
Frontiers in Psychology
This study aimed to develop a model to objectively benchmark professional Australian Rules football (AF) player performance based on age, experience, positional role and both draft type and round in the Australian Football League (AFL). The secondary aims were to identify the stage of peak performance and specific breakpoints in AF player performance longitudinally. AFL Player Ratings data were obtained for all players (n = 1052) from the 1034 matches played during the 2013-2017 seasons, along with data pertaining to the abovementioned player characteristics. Two separate linear mixed models revealed that all factors influenced player performance, with age and experience the strongest in each model, respectively. Post hoc Tukey tests indicated that performance was affected by age at each level up until the age of 21 (effect ranging from 0.98 to 3.70 rating points), and by experience at the levels 1-20 and 21-40 matches in comparison to all higher levels of experience (effect ranging from 1.01 to 3.77 rating points). Two segmented models indicated that a point of marginal gains exists within longitudinal performance progression between the age levels 22 and 23, and the experience levels 41-60 and 61-80 matches. Professional sporting organisations may apply the methods provided here to support decisions regarding player recruitment and development.
Predictors of Individual Player Match Performance in Junior Australian Football
International Journal of Sports Physiology and Performance, 2015
Purpose: Player match statistics in junior Australian football (AF) are not well documented while contributors to success are poorly understood. A clearer understanding of the relationships between fitness and skill in younger age players participating at the foundation level of the performance pathway in AF has implications for the development of coaching priorities (e.g., physical or technical). The aim of this study was to investigate the relationships between indices of fitness (speed, power and endurance) and skill (coach rating) on player performance (disposals and effective disposals) in junior AF. Methods: Junior male AF players (n = 156, 10 -15 years old) were recruited from 12 teams of a single amateur recreational AF club located in metropolitan Victoria. All players were tested for fitness (20 m sprint, vertical jump, 20 m shuttle run) and rated by their coach on a 6-point Likert scale for skill (within a team in comparison to their teammates). Player performance was assessed during a single match in which disposals and their effectiveness were coded from a video recording. Results: Coach rating of skill displayed the strongest correlations and combined with 20 m shuttle test showed a good ability to predict both disposals and the number of effective disposals. None of the skill or fitness attributes adequately explained the percentage of effective disposals. The influence of team did not meaningfully contribute to the performance of any of the models. Conclusion: Skill development should be considered a high priority by coaches in junior AF.
Motion analysis of match play in New Zealand U13 to U15 age-group soccer players
Journal of strength and conditioning research / National Strength & Conditioning Association, 2016
The purpose of this study was to investigate motion analysis in 85 players (U13-U15 years) from Auckland's Metropolitan League during two competitive soccer matches. Five Hz GPS (with interpolated 10Hz output) units were used to measure total distance (absolute and relative) and time spent in standing, walking, low intensity running, medium intensity running, high intensity running and sprinting. Speed thresholds for each match activity were determined through mean 10-m flying sprint peak speed for each age-group. U15 (6600 ± 1480m) covered more absolute distance due to longer playing time than U14 (5385 ± 1296m, p=0.001) and U13 (4516 ± 702.6m, p=0.001). However, there were no differences in relative distances covered (U15: 94.5 ± 11.2 m·min, U14: 96.1 ± 11.9m·min, U15: 97.3 ± 17.6 m·min, p=0.685). Maximum speed attained during the match was faster for U15 (26.5 ± 1.68km·h) than U14 (25.4 ± 1.93 km·h, p=0.022) and U13 (23.5 ± 1.74 km·h, p=0.001); there were no differences in av...
Game movements and player performance in the Australian Football League
International Journal of Performance Analysis in Sport
This study examined the relationship between game movements and team and individual performance in Australian football. Movement data (GPS) was collected from 30 elite players from one club in 17 matches during the 2011 season. Selected movement variables were related to individual (possession number, Champion Data © player rankings and pressure points) and team [quarter points (scored) margin] performance indicators. Playing position (nomadic vs. key position), years of experience, game location (home/away), environmental conditions (wet/dry), time of day (day/night), break between games (6-12 days), quarter number (1-4) and quarter score (+/-) margin were also analysed. Overall, some small-moderate (but inconsistent) positive relationships between individual movement data and performance indicators were observed. Nomadic players had higher movement profiles and performance indicators than key position, whilst players with 7+ years' experience recorded lower movement profiles t...