Predictive Validity of a Functional Movement Screen in Professional Basketball Players

Donald L. Hoover; Clyde B. Killian; Rachel A. Tinius; David M. Bellar; Steven G. Wilkinson; Francis T. Esslinger; Lawrence W. Judge

doi:10.3390/medicina56120724

Medicina (Dec 2020)

Predictive Validity of a Functional Movement Screen in Professional Basketball Players

Donald L. Hoover,
Clyde B. Killian,
Rachel A. Tinius,
David M. Bellar,
Steven G. Wilkinson,
Francis T. Esslinger,
Lawrence W. Judge

Affiliations

Donald L. Hoover: Doctor of Physical Therapy Department, Western Michigan University, Kalamazoo, MI 49008, USA
Clyde B. Killian: Krannert School of Physical Therapy, University of Indianapolis, Indianapolis, IN 42667, USA
Rachel A. Tinius: School of Kinesiology, Recreation, and Sport, Western Michigan University, Bowling Green, KY 42101, USA
David M. Bellar: Department of Kinesiology, University of North Carolina at Charlotte, Charlotte, NC 28223, USA
Steven G. Wilkinson: Doctor of Physical Therapy Program, Rocky Mountain University of Health Professions, Provo, UT 84606, USA
Francis T. Esslinger: School of Kinesiology, Recreation, and Sport, Western Michigan University, Bowling Green, KY 42101, USA
Lawrence W. Judge: School of Kinesiology, Ball State University, Muncie, IN 47306, USA

DOI: https://doi.org/10.3390/medicina56120724
Journal volume & issue: Vol. 56, no. 12
p. 724

Abstract

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Background and objectives: Striking a balance between maximizing performance and preventing injury remains elusive in many professional sports. The purpose of this study was to assess the relative risk of non-contact injuries in professional basketball players based on predictive cut scores on the Functional Movement Screen™ (FMS). Materials and Methods: Thirty-two professional basketball players from the National Basketball Association (NBA) and Women’s National Basketball Association (WNBA) participated in this study. This observational pilot cohort study assessed and scored each participant using the FMS during training camp. Each athlete was then tracked throughout the season while recording the number, type, and time lost due to injuries. Possible exposures, actual exposures, and exposures missed due to non-contact injury (NCI) for each athlete were calculated and then used to determine the crude and specific incident rates for exposures missed due to NCI per 1000 exposures. Results: Linear regression models were used to evaluate the predictive ability of the FMS score for total missed exposures, NCI, and CI missed exposures. In all models, the FMS total score failed to attain significance as a predictor (p > 0.05). FMS scores ranged from 5 to 18. The recommended cut score of 14 showed a sensitivity of 0.474 and a specificity of 0.750. The cut score of 15 showed the best combination, exhibiting a sensitivity of 0.579 and specificity of 0.625. A total of 5784 exposures to NCI were possible for the men and women combined, and 681 possible exposures were missed. Of these, 23.5% were due to NCI, 16.5% were due to contact injuries (CI), and 60% were due to illnesses and personal reasons. Conclusions: The FMS proved to be a measure that was not associated with any injury measure in this sample of professional basketball players, suggesting the instrument lacks predictive validity in this population.

Published in Medicina

ISSN: 1010-660X (Print); 1648-9144 (Online)
Publisher: MDPI AG
Country of publisher: Switzerland
LCC subjects: Medicine: Medicine (General)
Website: https://www.mdpi.com/journal/medicina

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