Predicting successful draft outcome in Australian Rules football: Model sensitivity is superior in neural networks when compared to logistic regression

• Jacob Jennings ,

  Contributed equally to this work with: Jacob Jennings, Michael I. Kingsley

  Roles Conceptualization, Data curation, Formal analysis, Methodology, Writing – original draft, Writing – review & editing

  Affiliations Holsworth Research Initiative, La Trobe Rural Health School, La Trobe University, Bendigo, VIC, Australia, La Trobe University Bendigo Pioneers, Bendigo, Australia

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• Jay C. Perrett ,

  Roles Data curation, Formal analysis

  ¶‡ JCP, DWW, CJS and SDC also contributed equally to this work.

  Affiliation PhysiGo Ltd, Wiltshire, England, United Kingdom

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• Daniel W. Wundersitz ,

  Roles Conceptualization, Writing – review & editing

  ¶‡ JCP, DWW, CJS and SDC also contributed equally to this work.

  Affiliation Holsworth Research Initiative, La Trobe Rural Health School, La Trobe University, Bendigo, VIC, Australia

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• Courtney J. Sullivan ,

  Roles Conceptualization, Writing – review & editing

  ¶‡ JCP, DWW, CJS and SDC also contributed equally to this work.

  Affiliation Holsworth Research Initiative, La Trobe Rural Health School, La Trobe University, Bendigo, VIC, Australia

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• Stephen D. Cousins ,

  Roles Conceptualization, Writing – review & editing

  ¶‡ JCP, DWW, CJS and SDC also contributed equally to this work.

  Affiliation Holsworth Research Initiative, La Trobe Rural Health School, La Trobe University, Bendigo, VIC, Australia

  https://orcid.org/0000-0003-0024-178X

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• Michael I. Kingsley

  Contributed equally to this work with: Jacob Jennings, Michael I. Kingsley

  Roles Conceptualization, Methodology, Writing – review & editing

  * E-mail: Michael.Kingsley@Auckland.ac.nz

  Affiliations Holsworth Research Initiative, La Trobe Rural Health School, La Trobe University, Bendigo, VIC, Australia, Department of Exercise Sciences, Faculty of Science, University of Auckland, Auckland, New Zealand

  https://orcid.org/0000-0002-1953-4067

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