ArticleJournal of athletic training2020
Training Load and Its Role in Injury Prevention, Part I: Back to the Future.
Article in Journal of athletic training, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 65 papers, 1 of them a synthesis that pooled it.
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Who cites it
65 citing papers in PubMed, 1 synthesis or guideline pooled it, 129 citations in OpenAlex.
- Risk Factors Associated with New Onset of Shoulder Pain and Injury Among the Athletic Population: A Systematic Review of the Literature.International journal of sports physical therapy · 2025Pooled it
- Effectiveness of tailored injury and illness prevention and management to reduce the prevalence and severity of health problems in adapted sports: a randomised controlled trial.British journal of sports medicine · 2025Trial
- The effects of plyometric training with speed and weight overloads on volleyball players' strength, power, and jumping performance.PloS one · 2025Trial
- Trial
- A Retrospective Weekly Rating of Perceived Exertion Measure May Assist Training Load Monitoring in Professional Tennis Players.Sports (Basel, Switzerland) · 2026Article
- Patient stratification in exercise oncology: matching exercise modalities to immune phenotypes to optimize immunotherapy response.Translational oncology · 2026Review
- The Relationship Between Games Missed for Rest or Load Management and Injury in the National Basketball Association, 2014-15 Through 2022-23.Sports medicine (Auckland, N.Z.) · 2026Observational
- Analyzing Workload-Monitoring Consistency and Same-Week Injury-Classification Performance in Female Adolescent Swimmers: An Exploratory Session-RPE and Neural Network Study.Life (Basel, Switzerland) · 2026Article
- Monitoring Training Effects in Athletes: A Multidimensional Framework for Decision-Making.Sports medicine (Auckland, N.Z.) · 2026Review
- The association between GPS-derived external workload metrics and soleus muscle injuries in professional football (soccer) players.Journal of experimental orthopaedics · 2026Article
- Co-Creating an Intervention to Prevent Injuries in Police Force Recruits: A Concept Mapping Study of Police Force Recruits, Police Force Staff, Health Professionals, and Research Experts.Sports medicine - open · 2026Article
- Application of Artificial Intelligence for Predicting Sports Injuries and Customizing Personalized Prevention Strategies: A Scoping Review.Bioengineering (Basel, Switzerland) · 2026Review
- Body Composition Architecture and Injury Topology in Physically Active Young Adults: A Tanglegram-Based Cophylogenetic Approach.Journal of clinical medicine · 2026Article
- Common Injuries Across Baseline, 6-Month, and 12-Month Assessments in CrossFitSports (Basel, Switzerland) · 2026Article
- Why do we have a musculoskeletal injury? - Beyond biomechanics.Sports medicine and health science · 2026Article
- Aerobic, hematological, and lipid changes after five months of endurance training in distance runners.Scientific reports · 2026Article
- Monitoring of internal load, sleep, and well-being in relation to injury and illness in professional basketball.BMC sports science, medicine & rehabilitation · 2026Article
- You Play the Way You Train: The Influence of Accumulated Weekly Training Loads on Match Physical Performance in Soccer Players.Journal of human kinetics · 2026Article
- Development and validation of a machine learning model for non-contact injury prediction based on lower limb strength asymmetry in professional football.Scientific reports · 2026Article
- Reply to the letter : To consider the exercise density in the dose-response relationship: the idea is promising, the operationalization tricky!European journal of applied physiology · 2026Article
5 more citing papers are in PubMed but not listed here.
Corrections and comments
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Authors and funding
5 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The purpose of this 2-part commentary series is† to explain why we believe our ability to control injury risk by manipulating training load (TL) in its current state is an illusion and why the foundations of this illusion are weak and unreliable. In part 1, we introduce the training process framework and contextualize the role of TL monitoring in the injury-prevention paradigm. In part 2, we describe the conceptual and methodologic pitfalls of previous authors who associated TL and injury in ways that limited their suitability for the derivation of practical recommendations. The first important step in the training process is developing the training program: the practitioner develops a strategy based on available evidence, professional knowledge, and experience. For decades, exercise strategies have been based on the fundamental training principles of overload and progression. Training-load monitoring allows the practitioner to determine whether athletes have completed training as planned and how they have coped with the physical stress. Training load and its associated metrics cannot provide a quantitative indication of whether particular load progressions will increase or decrease the injury risk, given the nature of previous studies (descriptive and at best predictive) and their methodologic weaknesses. The overreliance on TL has moved the attention away from the multifactorial nature of injury and the roles of other important contextual factors. We argue that no evidence supports the quantitative use of TL data to manipulate future training with the purpose of preventing injury. Therefore, determining "how much is too much" and how to properly manipulate and progress TL are currently subjective decisions based on generic training principles and our experience of adjusting training according to an individual athlete's response. Our message to practitioners is to stop seeking overly simplistic solutions to complex problems and instead embrace the risks and uncertainty inherent in the training process and injury prevention.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.