Restricted access

Purchase article

USD  $24.95

Student 1 year subscription

USD  $74.00

1 year subscription

USD  $99.00

Student 2 year subscription

USD  $141.00

2 year subscription

USD  $185.00

Context: The functional movement screen (FMS) is an assessment tool for movement dysfunction, which is used to reduce the risk of injury. Although the relationship between the FMS composite score and injuries has been extensively studied, the association between FMS scores and injuries in only college basketball players remains unknown. Objective: To examine the relationship between the FMS score and injuries in basketball players. Design: Cross-sectional study. Setting: University research laboratory. Participants: Eighty-one male college basketball players (average age 20.1 [1.3] y) participated. Main Outcome Measures: The FMS composite score was calculated from 7 movement tests. The incidence of injuries over a 1-year period prior to the test day was determined based on a questionnaire. Individuals were categorized into 2 groups: injury (with a serious basketball-related injury resulting in the loss of practice and game time for at least 4 wk) and noninjury groups. Mann–Whitney U and chi-square tests were used to evaluate group differences in the composite FMS and 7 movement scores, respectively. Furthermore, the scores significant on univariate analyses were submitted to a multivariate logistic analysis, adjusting for participant characteristics. Results: The composite FMS scores of the 2 groups were not significantly different (P = .38). Among the 7 tasks, only the deep squat and hurdle step showed significant group differences (P = .03 and P = .001, respectively). The multivariate logistic analysis revealed that deep squat (odds ratio, 6.48; 95% confidence interval, 1.23–34.01; P = .03) and hurdle step scores (odds ratio, 25.80; 95% confidence interval, 1.81–368.73; P = .02) were significantly associated with injuries, even after adjustment for participant characteristics. Conclusions: Deep squat and hurdle step scores may be associated with injuries in basketball players. Further research should be conducted to confirm that these 2 scores can predict the incidence of injuries in basketball players.

The authors are with the Department of Physical Therapy, Human Health Sciences, Graduate School of Medicine, Kyoto University, Kyoto, Japan.

Aoyama (blue@hs.med.kyoto-u.ac.jp) is corresponding author.
  • 1.

    Dick R, Hertel J, Agel J, Grossman J, Marshall SW. Descriptive epidemiology of collegiate men’s basketball injuries National Collegiate Athletic Association Injury Surveillance System, 1988–1989 through 2003–2004. J Athl Train. 2007;42:194–201. PubMed ID: 17710167

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 2.

    Cumps E, Verhagen E, Meeusen R. Prospective epidemiological study of basketball injuries during one competitive season: ankle sprains and overuse knee injuries. J Sports Sci Med. 2007;6:204–211. PubMed ID: 24149330

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 3.

    Drakos MC, Domb B, Starkey C, Callahan L, Allen AA. Injury in the national basketball association: a 17-year overview. Sports Health. 2010;2; 284–290. PubMed ID: 23015949 doi:

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 4.

    Ridder RD, Witvrouw E, Dolphens M, Roosen P, Ginckel AV. Hip strength as an intrinsic risk factor for lateral ankle sprains in youth soccer players: a 3-season prospective study. Am J Sports Med. 2017;45:410–416. PubMed ID: 27852594 doi:

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 5.

    Willems TM, Witvrouw E, Delbaere K, Mahieu N, Bourdeaudhuij ID, Clercq DD. Intrinsic risk factors for inversion ankle sprains in male subjects. Am J Sports Med. 2005;33:415–423. PubMed ID: 15716258 doi:

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 6.

    Numata H, Nakase J, Kitaoka K, et al. Two-dimensional motion analysis of dynamic knee valgus identifies female high school athletes at risk of non-contact anterior cruciate ligament injury. Knee Surg Sports Traumatol Arthrosc. 2018;26:442–447. PubMed ID: 28840276 doi:

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 7.

    Hickey GJ, Fricker PA, McDonald WA. Injuries of young elite female basketball players over a six-year period. Clin J Sport Med. 1997;7:252–256. PubMed ID: 9397323 doi:

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 8.

    Kujala UM, Taimela S, Oksanen A, Salminen JJ. Lumbar mobility and low back pain during adolescence a longitudinal three-year follow-up study in athletes and controls. Am J Sports Med. 1997;25:363–368. PubMed ID: 9167818 doi:

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 9.

    Renkawitz T, Boluki D, Grifka J. The association of low back pain, neuromuscular imbalance, and trunk extension strength in athletes. Spine J. 2006;6:673–683. PubMed ID: 17088198 doi:

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 10.

    Brumitt J, Engilis A, Isaak D, Briggs A, Mattocks A. Preseason jump and hop measures in male collegiate basketball players: an epidemiologic report. Int J Sports Phys Ther. 2016;11:954–961. PubMed ID: 27904797

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 11.

    Oshima T, Nakase J, Takata Y, Numata H, Tsuchiya H. Poor static balance is a novel risk factor for non-contact anterior cruciate ligament injury . Arch Orthop Trauma Surg. 2018;138:1713–1718. doi:

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 12.

    Cook G, Burton L, Hoogenboom B, Voight M. Functional movement screening: the use of fundamental movements as an assessment of function: part 1. Int J Sports Phys Ther. 2014;9:396–409. PubMed ID: 24944860

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 13.

    Cook G, Burton L, Hoogenboom B, Voight M. Functional movement screening: the use of fundamental movements as an assessment of function: part 2. Int J Sports Phys Ther. 2014;9:549–563. PubMed ID: 25133083

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 14.

    Chorba RS, Chorba DJ, Bouillon LE, Overmyer CA, Landis JA. Use of a functional movement screening tool to determine injury risk in female collegiate athletes. N Am J Sports Phys Ther. 2010;5:47–54. PubMed ID: 21589661

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 15.

    Kiesel K, Plisky PJ, Voight ML. Can serious injury in professional football be predicted by a preseason functional movement screen? N Am J Sports Phys Ther. 2007;2:147–158. PubMed ID: 21522210

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 16.

    Hotta T, Nishiguchi S, Fukutani N, et al. Functional movement screen for predicting running injuries in 18- to 24-year-old competitive male runners. J Strength Cond Res. 2015;29:2808–2815. PubMed ID: 25853918 doi:

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 17.

    Tee JC, Klingbiel JF, Collins R, Lambert MI, Coopoo Y. Preseason functional movement screen component tests predict severe contact injuries in professional rugby union players. J Strength Cond Res. 2016;30:3194–3203. PubMed ID: 26982969 doi:

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 18.

    Clifton DR, Grooms DR, Onate JA. Overhead deep squat performance predicts functional movement screen score. Int J Sports Phys Ther. 2015;10:29–36.

    • Search Google Scholar
    • Export Citation
  • 19.

    Butler RJ, Contreras M, Burton LC, Plisky PJ, Goode A, Kiesel K. Modifiable risk factors predict injuries in firefighters during training academies. Work. 2013;46:11–17. PubMed ID: 23324700

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 20.

    Stiffler MR, Pennuto AP, Smith MD, Olson ME, Bell DR. Range of motion, postural alignment, and less score differences of those with and without excessive medial knee displacement. Clin J Sport Med. 2015;25:61–66. PubMed ID: 24926910 doi:

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 21.

    Butler RJ, Plisky PJ, Southers C, Scoma C, Kiesel KB. Biomechanical analysis of the different classifications of the Functional Movement Screen deep squat test. Sports Biomech. 2010;9:270–279. PubMed ID: 21309301 doi:

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 22.

    Hewett TE, Myer GD, Ford KR, et al. Biomechanical measures of neuromuscular control and valgus loading of the knee predict anterior cruciate ligament injury risk in female athletes. Am J Sports Med. 2005;33:492–501. PubMed ID: 15722287 doi:

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 23.

    Gornitzky AL, Lott A, Yellin JL, Fabricant PD, Lawrence JT, Ganley TJ. Sport-specific yearly risk and incidence of anterior cruciate ligament tears in high school athletes: a systematic review and meta-analysis. Am J Sports Med. 2016;44:2716–2723. PubMed ID: 26657853 doi:

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 24.

    Plisky PJ, Rauh MJ, Kaminski TW, Underwood FB. Star excursion balance test as a predictor of lower extremity injury in high school basketball players. J Orthop Sports Phys Ther. 2006;36:911–919. PubMed ID: 17193868 doi:

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 25.

    Choi H, Shin W. Validity of the lower extremity functional movement screen in patients with chronic ankle instability. J Phys Ther Sci. 2015;27:1923–1927. PubMed ID: 26180349 doi:

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 26.

    Choi H, Shin W. Postural control systems in two different functional movements: a comparison of subjects with and without chronic ankle instability. J Phys Ther Sci. 2016;28:102–106. PubMed ID: 26957738 doi:

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 27.

    Garrett WE. Muscle strain injuries. Am J Sports Med. 1996;24:S2–S8. doi:

  • 28.

    Bencardino JT, Mellado JM. Hamstring Injuries of the Hip. Magn Reson Imaging Clin N Am. 2005;13:667–690.

  • 29.

    Feldman DE, Shrier I, Rossignol M, Abenhaim L. Risk factors for the development of low back pain in adolescence. Am J Epidemiol. 2001;154:30–36. doi:

  • 30.

    Lorimer AV, Hume PA. Stiffness as a risk factor for Achilles tendon injury in running athletes. Sports Med. 2016;46:1921–1938. PubMed ID: 27194434 doi:

  • 31.

    Javadian Y, Akbari M, Talebi G, Taghipour-Darzi M, Janmohammadi N. Influence of core stability exercise on lumbar vertebral instability in patients presented with chronic low back pain: a randomized clinical trial. Caspian J Intern Med. 2015;6:98–102. PubMed ID: 26221508

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 32.

    Silfies SP, Ebaugh D, Pontillo M, Butowicz CM. Critical review of the impact of core stability on upper extremity athletic injury and performance. Braz J Phys Ther. 2015;19:360–368. PubMed ID: 26537806 doi:

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
All Time Past Year Past 30 Days
Abstract Views 349 349 50
Full Text Views 12 12 2
PDF Downloads 10 10 2