Literature DB >> 32991700

The Training-Performance Puzzle: How Can the Past Inform Future Training Directions?

Tim J Gabbett1.   

Abstract

Over the past 20 years, research on the training-load-injury relationship has grown exponentially. With the benefit of more data, our understanding of the training-performance puzzle has improved. What were we thinking 20 years ago, and how has our thinking changed over time? Although early investigators attributed overuse injuries to excessive training loads, it has become clear that rapid spikes in training load, above what an athlete is accustomed, explain (at least in part) a large proportion of injuries. In this respect, it appears that overuse injuries may arise from athletes being underprepared for the load they are about to perform. However, a question of interest to both athletic trainers (ATs) and researchers is why some athletes sustain injury at low training loads, while others can tolerate much greater training loads? A higher chronic training load and well-developed aerobic fitness and lower body strength appear to moderate the training-injury relationship and provide a protective effect against spikes in load. The training-performance puzzle is complex and dynamic-at any given time, multiple inputs to injury and performance exist. The challenge facing researchers is obtaining large enough longitudinal data sets to capture the time-varying nature of physiological and musculoskeletal capacities and training-load data to adequately inform injury-prevention efforts. The training-performance puzzle can be solved, but it will take collaboration between researchers and clinicians as well as an understanding that efficacy (ie, how training load affects performance and injury in an idealized or controlled setting) does not equate to effectiveness (ie, how training load affects performance and injury in the real-world setting, where many variables cannot be controlled). © by the National Athletic Trainers' Association, Inc.

Entities:  

Keywords:  athlete management; training monitoring; workload

Mesh:

Year:  2020        PMID: 32991700      PMCID: PMC7534940          DOI: 10.4085/1062/6050.422.19

Source DB:  PubMed          Journal:  J Athl Train        ISSN: 1062-6050            Impact factor:   2.860


  117 in total

1.  The Association Between Noncontact Injuries and the Acute-Chronic Workload Ratio in Elite-Level Athletes: A Critically Appraised Topic.

Authors:  Natalie L Myers; Guadalupe Mexicano; Kristin V Aguilar
Journal:  J Sport Rehabil       Date:  2020-01-01       Impact factor: 1.931

2.  Multivariate modelling of subjective and objective monitoring data improve the detection of non-contact injury risk in elite Australian footballers.

Authors:  Marcus J Colby; Brian Dawson; Peter Peeling; Jarryd Heasman; Brent Rogalski; Michael K Drew; Jordan Stares; Hassane Zouhal; Leanne Lester
Journal:  J Sci Med Sport       Date:  2017-05-25       Impact factor: 4.319

3.  Injury risk-workload associations in NCAA American college football.

Authors:  J A Sampson; A Murray; S Williams; T Halseth; J Hanisch; G Golden; H H K Fullagar
Journal:  J Sci Med Sport       Date:  2018-05-22       Impact factor: 4.319

4.  Can the workload-injury relationship be moderated by improved strength, speed and repeated-sprint qualities?

Authors:  Shane Malone; Brian Hughes; Dominic A Doran; Kieran Collins; Tim J Gabbett
Journal:  J Sci Med Sport       Date:  2018-02-02       Impact factor: 4.319

5.  Individual and combined effects of acute and chronic running loads on injury risk in elite Australian footballers.

Authors:  N B Murray; T J Gabbett; A D Townshend; B T Hulin; C P McLellan
Journal:  Scand J Med Sci Sports       Date:  2016-07-15       Impact factor: 4.221

6.  Mathematical coupling causes spurious correlation within the conventional acute-to-chronic workload ratio calculations.

Authors:  Lorenzo Lolli; Alan M Batterham; Richard Hawkins; David M Kelly; Anthony J Strudwick; Robin Thorpe; Warren Gregson; Greg Atkinson
Journal:  Br J Sports Med       Date:  2017-11-03       Impact factor: 13.800

7.  How Much? How Fast? How Soon? Three Simple Concepts for Progressing Training Loads to Minimize Injury Risk and Enhance Performance.

Authors:  Tim J Gabbett
Journal:  J Orthop Sports Phys Ther       Date:  2019-11-15       Impact factor: 4.751

8.  Are Elite Soccer Teams' Preseason Training Sessions Associated With Fewer In-Season Injuries? A 15-Year Analysis From the Union of European Football Associations (UEFA) Elite Club Injury Study.

Authors:  Jan Ekstrand; Armin Spreco; Johann Windt; Karim M Khan
Journal:  Am J Sports Med       Date:  2020-01-28       Impact factor: 6.202

9.  The Use of Relative Speed Zones in Australian Football: Are We Really Measuring What We Think We Are?

Authors:  Nick B Murray; Tim J Gabbett; Andrew D Townshend
Journal:  Int J Sports Physiol Perform       Date:  2018-05-09       Impact factor: 4.010

10.  Impact of training patterns on incidence of illness and injury during a women's collegiate basketball season.

Authors:  Laura Anderson; Travis Triplett-McBride; Carl Foster; Scott Doberstein; Glenn Brice
Journal:  J Strength Cond Res       Date:  2003-11       Impact factor: 3.775

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  2 in total

1.  Dose-Response Relationships between Training Load Measures and Physical Fitness in Professional Soccer Players.

Authors:  Saeid Younesi; Alireza Rabbani; Filipe Manuel Clemente; Rui Silva; Hugo Sarmento; António José Figueiredo
Journal:  Int J Environ Res Public Health       Date:  2021-04-19       Impact factor: 3.390

2.  Weekly Variations in the Workload of Turkish National Youth Wrestlers: A Season of Complete Preparation.

Authors:  Hadi Nobari; Rui Silva; Filipe Manuel Clemente; Zeki Akyildiz; Luca Paolo Ardigò; Jorge Pérez-Gómez
Journal:  Int J Environ Res Public Health       Date:  2021-04-06       Impact factor: 3.390

  2 in total

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