The relationship between training load and injury in men`s professional basketball
Purpose:
To establish the relationship between the acute:chronic workload ratio and lower-extremity overuse injuries in professional basketball players over the course of a competitive season.
Methods:
The acute:chronic workload ratio was determined by calculating the sum of the current week`s session rating of perceived exertion of training load (acute load) and dividing it by the average weekly training load over the previous 4 wk (chronic load). All injuries were recorded weekly using a self-report injury questionnaire (Oslo Sports Trauma Research Center Injury Questionnaire20). Workload ratios were modeled against injury data using a logistic-regression model with unique intercepts for each player.
Results:
Substantially fewer team members were injured after workload ratios of 1 to 1.49 (36%) than with very low (=0.5; 54%), low (0.5-0.99; 51%), or high (=1.5; 59%) workload ratios. The regression model provided unique workload-injury trends for each player, but all mean differences in likelihood of being injured between workload ratios were unclear.
Conclusions:
Maintaining workload ratios of 1 to 1.5 may be optimal for athlete preparation in professional basketball. An individualized approach to modeling and monitoring the training load-injury relationship, along with a symptom-based injury-surveillance method, should help coaches and performance staff with individualized training-load planning and prescription and with developing athlete-specific recovery and rehabilitation strategies.
© Copyright 2017 International Journal of Sports Physiology and Performance. All rights reserved.
| Subjects: | |
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| Notations: | biological and medical sciences sport games |
| Published in: | International Journal of Sports Physiology and Performance |
| Language: | English |
| Published: |
2017
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| Online Access: | https://doi.org/10.1123/ijspp.2016-0726 |
| Volume: | 12 |
| Issue: | 9 |
| Pages: | 1238-1242 |
| Document types: | article |
| Level: | advanced |