title: Predicting playing status in junior Australian Football using physical and anthropometric parameters.
abstract: OBJECTIVE
  To use physical and anthropometric parameters to predict playing status in junior Australian Football.
  
  
  METHODS
  Cross-sectional observational.
  
  
  METHODS
  Participants were recruited from the under 18 competition within the West Australian Football League and classified into two groups; elite (state representative; n=50; 17.9 ± 0.5 y; 184.8 ± 6.9 cm; 80.6 ± 9.4 kg) and sub-elite (non-state representative; n=50; 17.8 ± 0.6 y; 179.8 ± 5.4 cm; 74.4 ± 7.9 kg). Both groups completed physical/anthropometric tests inclusive of a 5 m, 10 m and 20 m sprint, an agility test, stationary vertical jump, dynamic dominant and non-dominant foot vertical jump, 20 m multistage fitness test, standing height and body mass. A multivariate analysis of variance was used to test the main effect of 'status' on the physical/anthropometric parameters, whilst logistic regression models were used to predict playing status using the physical/anthropometric parameters.
  
  
  RESULTS
  On average, the elite group were taller, heavier, had a greater stationary vertical jump, dynamic dominant and non-dominant foot vertical jump and higher maximal aerobic capacity as measured by the multistage fitness test (p<0.05). The combination of standing height, dynamic vertical jump non-dominant foot and the 20 m multistage fitness test were the strongest predictors of status (Akaike's Information Criterion=96.35).
  
  
  CONCLUSIONS
  Despite mean differences in a number of parameters, the combination of standing height, dynamic vertical jump non-dominant foot and the multistage fitness test were the strongest predictors of status and thus important tests for initially identifying potential talent in junior Australian Football.
authors.affiliation: School of Exercise and Health Sciences, Edith Cowan University, Australia. Electronic address: c.woods@ecu.edu.au.
authors.forename: Carl T E
authors.initials: CT
authors.lastname: Woods
authors.affiliation: School of Exercise and Health Sciences, Edith Cowan University, Australia; School of Health Sciences, University of South Australia, Australia.
authors.forename: Annette J
authors.initials: AJ
authors.lastname: Raynor
authors.affiliation: School of Medical Sciences, Royal Melbourne Institute of Technology University, Australia.
authors.forename: Lyndell
authors.initials: L
authors.lastname: Bruce
authors.affiliation: School of Medical Sciences, Royal Melbourne Institute of Technology University, Australia.
authors.forename: Zane
authors.initials: Z
authors.lastname: McDonald
authors.affiliation: School of Medical Sciences, Royal Melbourne Institute of Technology University, Australia.
authors.forename: Neil
authors.initials: N
authors.lastname: Collier
mesh_terms: D000293:Adolescent; D000886:Anthropometry; D001315:Australia; D003430:Cross-Sectional Studies; D005538:Football / Q000502:physiology* / Q000706:statistics & numerical data; D006801:Humans; D016015:Logistic Models
keywords: Draft Combine; Predictive modelling; Talent identification; Team sports