Optimizing Preseason Training Loads in Australian Football.
Purpose: To investigate whether preseason training plans for Australian football can be computer generated using current training-load guidelines to optimize injury-risk reduction and performance improvement. Methods: A constrained optimization problem was defined for daily total and sprint distance...
| Publicado en: | International Journal of Sports Physiology & Performance Vol. 13; no. 2; pp. 194 - 200 |
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| Autores principales: | , , , , , , |
| Formato: | equations & formulas research tables/charts Journal Article |
| Publicado: |
Human Kinetics Publishers, Inc.
Feb2018
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=128325399&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 128325399 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 15550265 16IB jtl: International Journal of Sports Physiology & Performance issn: 15550265 maglogo: N pubinfo: dt: Feb2018 vid: 13 iid: 2 pid: 553 pub: Human Kinetics Publishers, Inc. place: Champaign, Illinois artinfo: ui: 128325399 128325399 128325399 10.1123/ijspp.2016-0695 128325399 ppf: 194 ppct: 6 formats: tig: atl: Optimizing Preseason Training Loads in Australian Football. aug: au: Carey, David L. Crow, Justin Ong, Kok-Leong Blanch, Peter Morris, Meg E. Dascombe, Ben J. Crossley, Kay M. sug: subj: Australian Football Australia Athletic Training Athletic Performance Athletic Injuries Prevention and Control Athletic Injuries Risk Factors Software Practice Guidelines Workload Australia Human Sprinting Athletes, Elite Athletic Training Programs Conceptual Framework Algorithms Simulations Fatigue Workload Measurement ab: Purpose: To investigate whether preseason training plans for Australian football can be computer generated using current training-load guidelines to optimize injury-risk reduction and performance improvement. Methods: A constrained optimization problem was defined for daily total and sprint distance, using the preseason schedule of an elite Australian football team as a template. Maximizing total training volume and maximizing Banister-model-projected performance were both considered optimization objectives. Cumulative workload and acute:chronic workload-ratio constraints were placed on training programs to reflect current guidelines on relative and absolute training loads for injury-risk reduction. Optimization software was then used to generate preseason training plans. Results: The optimization framework was able to generate training plans that satisfied relative and absolute workload constraints. Increasing the off-season chronic training loads enabled the optimization algorithm to prescribe higher amounts of "safe" training and attain higher projected performance levels. Simulations showed that using a Banister-model objective led to plans that included a taper in training load prior to competition to minimize fatigue and maximize projected performance. In contrast, when the objective was to maximize total training volume, more frequent training was prescribed to accumulate as much load as possible. Conclusions: Feasible training plans that maximize projected performance and satisfy injury-risk constraints can be automatically generated by an optimization problem for Australian football. The optimization methods allow for individualized training-plan design and the ability to adapt to changing training objectives and different training-load metrics. pubtype: Academic Journal doctype: equations & formulas research tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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