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The Training-Performance Puzzle: How Can the Past Inform Future Training Directions?
1Gabbett Performance Solutions, Brisbane, and Centre for Health Research, University of Southern Queensland, Ipswich, Australia.
Journal of Athletic Training
|September 29, 2020
Summary
Sudden increases in training load, not just high loads, cause athletic injuries. Athletes may be protected by higher chronic loads, better fitness, and strength, but more data is needed to prevent injuries effectively.
Area of Science:
- Sports Medicine
- Exercise Physiology
- Injury Prevention
Background:
- Research on the training-load-injury relationship has evolved significantly over the past two decades.
- Early theories focused on excessive training loads causing overuse injuries.
- Current understanding emphasizes that rapid spikes in training load are a primary injury driver.
Purpose of the Study:
- To review the evolution of thought regarding the training-load-injury relationship.
- To explore factors influencing individual susceptibility to training-related injuries.
- To discuss challenges and future directions in injury prevention research.
Main Methods:
- Review of existing literature on training load and athletic injuries.
- Analysis of the shift in understanding from chronic excessive load to acute load spikes.
- Discussion of moderating factors like chronic load, aerobic fitness, and strength.
Main Results:
- Rapid increases in training load, rather than consistently high loads, are strongly linked to athletic injuries.
- Higher chronic training loads, improved aerobic fitness, and greater lower body strength appear to offer a protective effect against load-induced injuries.
- Individual variability exists in injury susceptibility even at similar training loads.
Conclusions:
- Athletic injuries are often caused by athletes being unprepared for sudden increases in training demands.
- Factors like chronic load, fitness, and strength can mitigate injury risk.
- Solving the training-performance puzzle requires large longitudinal datasets, collaboration, and distinguishing between efficacy and effectiveness in real-world settings.
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