Insights from an examination of a state league coach development initiative in community Australian Football (AFL) clubs

Author(s):  
Shane Pill ◽  
Deborah Agnew ◽  
Elizabeth Abery
2021 ◽  
pp. 1-10
Author(s):  
William Sheehan ◽  
Rhys Tribolet ◽  
Andrew R. Novak ◽  
Job Fransen ◽  
Mark L. Watsford

Author(s):  
Sarah Jenner ◽  
Regina Belski ◽  
Brooke Devlin ◽  
Aaron Coutts ◽  
Thomas Kempton ◽  
...  

(1) Background: Many professional Australian Football (AF) players do not meet recommended sports nutrition guidelines despite having access to nutrition advice. There are a range of factors that can influence players′ ability to meet their nutrition goals and awareness of the barriers players face is essential to ensure that dietary advice translates into practice. Therefore, this qualitative research study aimed to explore the factors influencing AF players’ dietary intakes and food choice. (2) Methods: Semi-structured interviews were conducted with twelve professional male AF players. (3) Results: Less experienced players restricted their carbohydrate intake to meet body composition goals, particularly during preseason and surrounding body composition assessment. During the competition season players had a greater focus on performance and placed more emphasis on carbohydrate intake in the lead up to matches. Players felt nutrition goals were easier to achieve when dietary choices were supported by their families and peers. One-on-one consultations provided by a sports dietitian were players′ preferred mode of nutrition intervention. Individualized nutrition advice is required for less experienced AF players who may be vulnerable to unsustainable dietary habits. Experienced AF players can support junior teammates by promoting positive team culture related to body composition, nutrition and performance.


Author(s):  
Adrian J Barake ◽  
Heather Mitchell ◽  
Constantino Stavros ◽  
Mark F Stewart ◽  
Preety Srivastava

Efficient recruitment to Australia’s most popular professional sporting competition, the Australian Football League (AFL), requires evaluators to assess athlete performances in many lower tier leagues that serve as pathways. These competitions and their games are frequent, widespread, and challenging to track. Therefore, independent, and reliable player performance statistics from these leagues are paramount. This data, however, is only meaningful to recruiters from AFL teams if accurate player positions are known, which was not the case for the competitions from which most players were recruited. This paper explains how this problem was recently solved, demonstrating a process of knowledge translation from academia to industry, that bridged an important gap between sports science, coaching and recruiting. Positional information which is only available from the AFL competition was used to benchmark and develop scientific classification methods using only predictor variables that are also measured in lower tier competitions. Specifically, a Multinomial Logistic model was constructed to allocate players into four primary positions, followed by a Binary Logit model for further refinement. This novel technique of using more complete data from top tier competitions to help fill informational deficiencies in lower leagues could be extended to other sports that face similar issues.


Author(s):  
William B. Sheehan ◽  
Rhys Tribolet ◽  
Mark L. Watsford ◽  
Andrew R. Novak ◽  
Michael Rennie ◽  
...  
Keyword(s):  

2021 ◽  
pp. 1-7
Author(s):  
Nigel A. Smith ◽  
Melinda M. Franettovich Smith ◽  
Matthew N. Bourne ◽  
Rod S. Barrett ◽  
Julie A. Hides

2015 ◽  
Vol 10 (5) ◽  
pp. 648-654 ◽  
Author(s):  
Peter Fowler ◽  
Rob Duffield ◽  
Kieran Howle ◽  
Adam Waterson ◽  
Joanna Vaile

The current study examined the effects of 10-h northbound air travel across 1 time zone on sleep quantity, together with subjective jet lag and wellness ratings, in 16 male professional Australian football (soccer) players. Player wellness was measured throughout the week before (home training week) and the week of (away travel week) travel from Australia to Japan for a preseason tour. Sleep quantity and subjective jet lag were measured 2 d before (Pre 1 and 2), the day of, and for 5 d after travel (Post 1–5). Sleep duration was significantly reduced during the night before travel (Pre 1; 4.9 [4.2−5.6] h) and night of competition (Post 2; 4.2 [3.7−4.7] h) compared with every other night (P < .01, d > 0.90). Moreover, compared with the day before travel, subjective jet lag was significantly greater for the 5 d after travel (P < .05, d > 0.90), and player wellness was significantly lower 1 d postmatch (Post 3) than at all other time points (P < .05, d > 0.90). Results from the current study suggest that sleep disruption, as a result of an early travel departure time (8 PM) and evening match (7:30 PM), and fatigue induced by competition had a greater effect on wellness ratings than long-haul air travel with a minimal time-zone change. Furthermore, subjective jet lag may have been misinterpreted as fatigue from sleep disruption and competition, especially by the less experienced players. Therefore, northbound air travel across 1 time zone from Australia to Asia appears to have negligible effects on player preparedness for subsequent training and competition.


2017 ◽  
Vol 12 (3) ◽  
pp. 344-350 ◽  
Author(s):  
Ashley J Cripps ◽  
Christopher Joyce ◽  
Carl T Woods ◽  
Luke S Hopper

This study compared biological maturation, anthropometric, physical and technical skill measures between talent and non-talent identified junior Australian footballers. Players were recruited from the under 16 Western Australian Football League and classified as talent (state representation; n = 25, 15.7 ± 0.3 y) or non-talent identified (non-state representation; n = 25, 15.6 ± 0.4 y). Players completed a battery of anthropometric, physical and technical skill assessments. Maturity was estimated using years from peak height velocity calculations. Binary logistic regression was used to identify the variables demonstrating the strongest association with the main effect of ‘status’. A receiver operating characteristic curve was used to assess the level of discrimination provided by the strongest model. Talent identified under 16 players were biologically older, had greater stationary and dynamic leaps and superior handball skill when compared to their non-talent identified counterparts. The strongest model of status included standing height, non-dominant dynamic vertical jump and handball outcomes (AUC = 83.4%, CI = 72.1%–95.1%). Biological maturation influences anthropometric and physical capacities that are advantageous for performance in Australian football; talent identification methods should factor biological maturation as a confound in the search for junior players who are most likely to succeed in senior competition.


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