Evidence Based Application of the Functional Movement Screen: Part 1

By djpope

May 6, 2013

evidence, Functional Movement Screen, Gray Cook, research

Disclaimer: This article series is particularly for the coaches, trainers and therapists out there.  It doesn’t mean  you won’t get some great info from it if you aren’t in these fields but I wanted to really focus on this population.

We all know that I’m a huge fan of screening and assessment in the strength, fitness and general meathead population.  Fixing specific weakness and mobility issues will not only make us better athletes and help us reach our fitness goals (strength, power, monster biceps etc.) but it will also help to keep us injury free.

A popular screen that is typically used in the fitness and strength & conditioning community is the Functional Movement Screen (FMS).  I’m certified in the FMS, try to use it as often as I have someone who will benefit from it and believe it be a solid tool to keep in your toolbox.  That being said I believe we should all be following evidence based guidelines.  Let’s see what the heck the evidence says, shall we?

What is the Functional Movement Screen?

Directly from the Functional Movement Systems Website:

“The Functional Movement Screen was developed in its current form over a decade ago and has gained support in the fitness community as a way to efficiently screen and develop a corrective exercise program to improve movement patterns. As the tool has gained in popularity clinically, research has begun to be conducted that has added to the support of the screening tool. Current research on the Functional Movement Screen suggests that the test is a reliable way to objectively measure fundamental movement patterns that are modifiable and indicative of an elevated likelihood of sustaining a musculoskeletal injury.”

The FMS:

  1. Consists of 7 specific tests that utilize a variety of basic positions and movements which are thought to provide the foundation for more complex athletic movements to be performed efficiently
  2. Ranks movement on a 0 to 3 scale (0 = pain, 1 = poor movement, 3 = perfect score)
  3. Assesses movement competency
  4. Identifies asymmetries from left to right (A predictor of injury risk)
  5. Tests mobility and stability extremes in order to uncover assymetries and limitations.
  6. A total score of 14 or below has been identified as a risk factor for injury
  7. Clearing tests are included (in addition to the other 7 tests) in order to screen for individuals with pain.

If you’re interested in learning more about the 7 tests you can visit the FMS site HERE:  I’m sure you can find some great youtube video explanations as well.

As a physical therapist and strength coach, evidenced based practice is extremely important to me.  I wanted to take a look into the literature to learn more about the FMS and how it can fit into our tool box as a coach or therapist.  Based on the literature I wanted to see:

  1. Which populations has the FMS been used on?
  2. What do we know about the FMS? and maybe more importantly, what we don’t know yet.
  3. How can we apply it to our clients and patients to improve our outcomes and reduce risk of injury?

One thing to keep in mind is that even though the FMS has been around for over a decade the research is still limited in this area.  In several areas the evidence is lacking towards its efficacy.  Keep in mind though that a lack of evidence does not necessarily mean that the FMS is not an effective tool.  It really means that more research must be undertaken to judge it’s effectiveness.  I think this point is vital.  In my opinion the research has been very promising toward the effectiveness of the FMS.

Some general assumptions before we begin our discussion:

  • The #1 risk factor for a new injury is a previous history of being injured.
  • The #2 risk factor for injury is an asymmetry from left to right.

Now to get down to business, the research…

Seminal FMS studies:


  • 1st study to identify a connection between FMS score and risk of serious injury
  • n = 46 active roster of a professional american football team
  • A score of 14 or less was shown to be predictive of injury
  • Specificity of 0.91 (see considerations for explanation)
  • Sensitivity of 0.54 (see considerations for explanation)
  • Intra-rater reliability of 0.98  This means that if a practitioner performed an FMS on the same athlete twice they had a 98% chance of scoring the athlete the same.
  • Retrospective study – This study was performed by looking back on previous data
  • Injury was defined as being on the injured reserve and missing at least 3 weeks of playing time.
  • Mean FMS score of injured athletes 14.3
  • Mean score of uninjured athletes 17.4 (significant difference p<0.05)
  • Odds ratio 11.67 – This can be interpreted as a player having an eleven-fold increased chance of injury when their FMS score is 14 or less when compared to a player whose score was greater than 14 at the start of the season.

Considerations and additional questions:

  • The FMS showed a high specificity, meaning that if a player scored a 14 or lower he had a 91% chance of getting injured.
  • The FMS had a low sensitivity meaning that only 54% of the players injured throughout the 4.5 months period of the study had a score of 14 or less.  (The same chance as the flip of a coin)  A screen typically seeks to have a high sensitivity.
  • Was the definition of what constitutes a serious injury (>3 weeks time lost) inclusive enough to capture all injuries?  Would a less inclusive definition of injury improve sensitivity of the test?
  • Did FMS scores match up with identifiable risk factors of injury such as previous injury?  This data was not available for analysis.
  • The population consisted solely of male professional athletes.  How does this carry over to middle school, high school and college level athletes?
  • Would a score of 14 or lower be the best predictor in lesser level/younger athletes?  At the professional level one would think that these athletes move fairly well.
  • Average FMS scores in this study did not match average FMS scores in another study utilizing professional american football athletes.  This makes me wonder if the results of this study could be re-created.


  • Authors assumption: High level athletes often use compensatory movement patterns to generate high levels of performance that may increase their risk of injury.  Does this compensatory movement predispose athletes to injury?
  • n = 38 collegiate female athletes (Division II) soccer, volleyball and basketball athletes mean age 19.24
  • Exclusion criteria: Patients did not experience an injury within the past 30 days
  • 7 athletes had a previous ACL rupture and subsequent repair
  • Average FMS score = 14.3.  Mean score of injured athletes = 13.9.  Mean score of uninjured athletes = 14.7.  This was tested 2 weeks prior to start of their competitive season.
  • Definition of injury: Athletes sought medical advice from an athletic trainer or physician.  The injury must have been sustained during athletic participation.
  • 18 total injuries recorded (17 lower extremity injuries, 1 lower back injury).
  • FMS score of 14 or less was significantly correlated with injury (p=0.0496)
  • Specificity of 0.74
  • Sensitivity of 0.58
  • A score of 14 or less on the FMS resulted in a 4-fold increase in risk of lower extremity injury in female collegiate athletes participating in these sports

Considerations and additional questions:

  • The population used in this study consisted of purely female collegiate athletes.
  • The FMS showed a fairly high specificity meaning that if a player scored a 14 or lower she had a 74% chance of getting injured.  Athletes who scored 13 or below had an 81.82% chance of injury.
  • The FMS had a low sensitivity meaning that only 58% of the players injured throughout the 4.5 months period of the study had a score of 14 or less. (Again, back to the coin flip analogy)
  • The definition of injury was more broad then in the professional football study.  Injury in this study was merely seeking medical advice from a trainer or physician.  This is not consistent with the football study.  This begs the question of how severe are the injuries these athletes are acquiring?
  • These subjects all acquired lower extremity or low back injuries.  Does the FMS pick up upper extremity injury as well?
  • Did the lower extremity FMS tests correlate with these lower extremity injuries and if we removed the upper extremity tests would the test be more sensitive?
  • If we removed the upper extremity FMS tests would we have had a better pick up of additional injury?

Perhaps the most interesting side note of this study:

  • FMS scores were higher in patients with ACL reconstruction surgery. This goes against the idea that those with a previous history of injury are more at risk for future injury.   The authors concluded that the ACL reconstruction patients may have had superior rehabilitation programs and may be less at risk of injury because of this (Keep in mind that ACL reconstruction patients are generally more at risk for another injury.  This statement by the authors goes directly against what the research has shown about ACL reconstruction patients)
  • In ACL reconstruction patients the FMS did not predict injury risk. (Again, keep in mind that previous risk of injury is the strongest predictor of reoccurrence of injury).  If previous risk of injury is the biggest risk factor for future injury then why did these athletes score so high?  The FMS is commonly recommended as a return to sport criteria and a judge of progress for ACL athletes by surgeons and therapists.  This statistic begs the question of whether or not the FMS is the most appropriate test in this population.

That’s enough research for now.  Next week we’re going to tackle research in the military and firefighting populations.  Hold onto your butts.

Part 2 HERE

I wanted to stir some conversation with this article series.  Where does the FMS best fit into a clinical and coaching practice?  Please respond in the comments below.

World’s worst rotary stability test,

Dan Pope

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