Cooperative passing network features are associated with successful match outcomes in the Australian Football League

被引:11
|
作者
Fransen, Job [1 ]
Tribolet, Rhys [1 ]
Sheehan, William Bradshaw [1 ]
McBride, Ignatius [1 ,2 ]
Novak, Andrew Roman [1 ,3 ]
Watsford, Mark Langley [1 ]
机构
[1] Univ Technol Sydney, Fac Hlth, Human Performance Res Ctr, Sch Sport Exercise & Rehabil, Sydney, NSW, Australia
[2] Univ Technol Sydney, Sch Math & Phys Sci, Ultimo, Australia
[3] Rugby Australia, High Performance Dept, Moore Pk, Australia
关键词
Performance analysis; social networks; team sport; TEAM PERFORMANCE; ELITE; RULES; PATTERNS;
D O I
10.1177/17479541211052760
中图分类号
F [经济];
学科分类号
02 ;
摘要
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 < 0.001), teams have a higher probability of winning. The centralisation of a team's passing network was not significantly related to match outcomes. The classification accuracy for the model associating network characteristics with match outcomes was 69%. Collectively, these findings suggest that Australian Football League-specific network features should be incorporated within existing performance analysis methods and can provide a useful, practical tool for coaches to measure collective performance during team practice.
引用
收藏
页码:1101 / 1108
页数:8
相关论文
共 37 条
  • [1] Passing and goal scoring characteristics in Australian A-League football
    Garratt, Kylie
    Murphy, Aron
    Bower, Rob
    [J]. INTERNATIONAL JOURNAL OF PERFORMANCE ANALYSIS IN SPORT, 2017, 17 (1-2) : 77 - 85
  • [2] Real time prediction of match outcomes in Australian football
    Aarons, Mitchell F.
    Young, Chris M.
    Bruce, Lyndell
    Dwyer, Dan B.
    [J]. JOURNAL OF SPORTS SCIENCES, 2023, 41 (11) : 1115 - 1125
  • [3] Activity profiles of professional soccer, rugby league and Australian football match play
    Varley, Matthew C.
    Gabbett, Tim
    Aughey, Robert J.
    [J]. JOURNAL OF SPORTS SCIENCES, 2014, 32 (20) : 1858 - 1866
  • [4] Examination of player role in the Australian Football League using match performance data
    McIntosh, Sam
    Kovalchik, Stephanie
    Robertson, Sam
    [J]. INTERNATIONAL JOURNAL OF PERFORMANCE ANALYSIS IN SPORT, 2018, 18 (03) : 451 - 462
  • [5] Physical and psychomotor performance of Australian football and rugby league officials during a match simulation
    Elsworthy, Nathan
    Burke, Darren
    Dascombe, Ben J.
    [J]. JOURNAL OF SPORTS SCIENCES, 2016, 34 (05) : 420 - 428
  • [6] On the use of passing network indicators to predict football outcomes
    Ievoli, Riccardo
    Palazzo, Lucio
    Ragozini, Giancarlo
    [J]. KNOWLEDGE-BASED SYSTEMS, 2021, 222
  • [7] A League-Wide Evaluation of Factors Influencing Match Activity Profile in Elite Australian Football
    Esmaeili, Alireza
    Clifton, Patrick
    Aughey, Robert J.
    [J]. FRONTIERS IN SPORTS AND ACTIVE LIVING, 2020, 2
  • [8] The Distribution of Match Activities Relative to the Maximal Mean Intensities in Professional Rugby League and Australian Football
    Johnston, Rich D.
    Thornton, Heidi R.
    Wade, Jarrod A.
    Devlin, Paul
    Duthie, Grant M.
    [J]. JOURNAL OF STRENGTH AND CONDITIONING RESEARCH, 2022, 36 (05) : 1360 - 1366
  • [9] Factors associated with cooperative network connectedness in a professional Australian football small-sided game
    Tribolet, Rhys
    Sheehan, William B.
    Novak, Andrew R.
    Watsford, Mark L.
    Fransen, Job
    [J]. SCIENCE AND MEDICINE IN FOOTBALL, 2022, 6 (04) : 511 - 518
  • [10] pi-football: A Bayesian network model for forecasting Association Football match outcomes
    Constantinou, Anthony C.
    Fenton, Norman E.
    Neil, Martin
    [J]. KNOWLEDGE-BASED SYSTEMS, 2012, 36 : 322 - 339