Literature DB >> 29843960

Injury risk-workload associations in NCAA American college football.

J A Sampson1, A Murray2, S Williams3, T Halseth2, J Hanisch4, G Golden2, H H K Fullagar5.   

Abstract

OBJECTIVES: To determine injury risk-workload associations in collegiate American Football.
DESIGN: Retrospective analysis.
METHODS: Workload and injury data was recorded from 52 players during a full NCAA football season. Acute, chronic, and a range of acute:chronic workload ratios (ACWR: 7:14, 7:21 and 7:28 day) calculated using rolling and exponentially weighted moving averages (EWMA) were plotted against non-contact injuries (regardless of time lost or not) sustained within 3- and 7-days. Injury risks were also determined relative to position and experience.
RESULTS: 105 non-contact injuries (18 game- and 87 training-related) were observed with almost 40% sustained during the pre-season. 7-21 day EWMA ACWR's with a 3-day injury lag were most closely associated with injury (R2=0.54). Relative injury risks were >3× greater with high compared to moderate and low ratios and magnified when combined with low 21-day chronic workloads (injury probability=92.1%). Injury risks were similar across positions. 'Juniors' presented likely and possibly increased overall injury risk compared to 'Freshman' (RR: 1.94, CI 1.07-3.52) and 'Seniors' (RR: 1.7, CI 0.92-3.14), yet no specific ACWR - experience or - position interactions were identified.
CONCLUSIONS: High injury rates during college football pre-season training may be associated with high acute loads. In-season injury risks were greatest with high ACWR and evident even when including (more common and less serious) non-time loss injuries. Substantially increased injury risks when low 21-day chronic workloads and concurrently high EWMA ACWR highlights the importance of load management for individuals with chronic game- (non-involved on game day) and or training (following injury) absences.
Copyright © 2018 Sports Medicine Australia. Published by Elsevier Ltd. All rights reserved.

Entities:  

Keywords:  GPS playerload; Injury prevention; Load monitoring; Muscle injuries

Mesh:

Year:  2018        PMID: 29843960     DOI: 10.1016/j.jsams.2018.05.019

Source DB:  PubMed          Journal:  J Sci Med Sport        ISSN: 1878-1861            Impact factor:   4.319


  14 in total

1.  The Association Between the Acute:Chronic Workload Ratio and Running-Related Injuries in Dutch Runners: A Prospective Cohort Study.

Authors:  Gustavo Nakaoka; Saulo Delfino Barboza; Evert Verhagen; Willem van Mechelen; Luiz Hespanhol
Journal:  Sports Med       Date:  2021-05-30       Impact factor: 11.136

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

Authors:  Tim J Gabbett
Journal:  J Athl Train       Date:  2020-09-01       Impact factor: 2.860

3.  Training Load and Its Role in Injury Prevention, Part 2: Conceptual and Methodologic Pitfalls.

Authors:  Franco M Impellizzeri; Alan McCall; Patrick Ward; Luke Bornn; Aaron J Coutts
Journal:  J Athl Train       Date:  2020-09-01       Impact factor: 2.860

4.  Global Positioning System-Derived Workload Metrics and Injury Risk in Team-Based Field Sports: A Systematic Review.

Authors:  Natalie Kupperman; Jay Hertel
Journal:  J Athl Train       Date:  2020-09-01       Impact factor: 2.860

Review 5.  The Association Between the Acute:Chronic Workload Ratio and Injury and its Application in Team Sports: A Systematic Review.

Authors:  Alan Griffin; Ian C Kenny; Thomas M Comyns; Mark Lyons
Journal:  Sports Med       Date:  2020-03       Impact factor: 11.136

Review 6.  The Use of Wearable Sensors for Preventing, Assessing, and Informing Recovery from Sport-Related Musculoskeletal Injuries: A Systematic Scoping Review.

Authors:  Ezio Preatoni; Elena Bergamini; Silvia Fantozzi; Lucie I Giraud; Amaranta S Orejel Bustos; Giuseppe Vannozzi; Valentina Camomilla
Journal:  Sensors (Basel)       Date:  2022-04-22       Impact factor: 3.847

7.  Is the Acute: Chronic Workload Ratio (ACWR) Associated with Risk of Time-Loss Injury in Professional Team Sports? A Systematic Review of Methodology, Variables and Injury Risk in Practical Situations.

Authors:  Renato Andrade; Eirik Halvorsen Wik; Alexandre Rebelo-Marques; Peter Blanch; Rodney Whiteley; João Espregueira-Mendes; Tim J Gabbett
Journal:  Sports Med       Date:  2020-09       Impact factor: 11.136

Review 8.  The Relationship Between Acute: Chronic Workload Ratios and Injury Risk in Sports: A Systematic Review.

Authors:  Danny Maupin; Ben Schram; Elisa Canetti; Robin Orr
Journal:  Open Access J Sports Med       Date:  2020-02-24

9.  Analysis of Non-Game Injuries in Major League Baseball.

Authors:  Amanda Esquivel; Michael T Freehill; Frank C Curriero; Kevin L Rand; Stan Conte; Thomas Tedeschi; Stephen E Lemos
Journal:  Orthop J Sports Med       Date:  2019-12-27

10.  Getting the most out of intensive longitudinal data: a methodological review of workload-injury studies.

Authors:  Johann Windt; Clare L Ardern; Tim J Gabbett; Karim M Khan; Chad E Cook; Ben C Sporer; Bruno D Zumbo
Journal:  BMJ Open       Date:  2018-10-02       Impact factor: 2.692

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