In the last couple of years the Functional Movement Screen (FMS) has gained increasing popularity in sport. It was invented to evaluate movement pattern quality for athletes as it thought that
poor neuromuscular control increases the risk of acute injuries (10).
Based on this ides the FMS therefore serve as the basis for more complex movements (23) and therefore would be useful to identify functional movement deficits such as muscular imbalances/asymmetries (32), flexibility deficits (mobility), balance or stability (6).
The tool was used in several investigations, such as:
The only equipment required is a (measurement) stick in addition to a measurement bar.
are used to test/rate individual players’ movements.
The players will receive a score for each exercise. The highest score is a “3” and the lowest a “0”. In this regards a “3” means “perfect execution of the task”, a “2” means “execution with compensation”, a “1” means “can’t perform the task” and a “0” means “pain” (12). Therefore the player can score up to a total of 21 points. There are five tests which require bilateral testing and therefore both scores are recorded (however, the lowest test score will be recorded for the overall score).
Several studies have investigated different types of reliability for the FMS and showed good reliability values (10, 25, 30, 32). There was no difference for intra-rater reliability (meaning the athlete receives the same score on day 1 vs. day 2) (25, 30), however, there was a less clear picture for the inter-rater reliability.
It was suggested that FMS scores for one athlete couldn’t be compared to another rater’s score of the same athlete (29), while experiences/additional knowledge with the FMS improved reliability/measurement (11, 14). However, it was also seen that FMS-certification of raters did not improve reliability in a different study (30) and there was no difference between raters score with different experiences with the test (23). Among novice raters, the inter-rater reliability showed moderate to good reliability (32).
Interestingly, the one-leg squat test and the hurdle step were seen as the least reliable measurements. The ICC scores were poor, ranging from 0.52 (10) to 0.30-0.35 respectively (30). Based on the original total score of 21, a 100-point scoring system was developed which also seemed to be reliable (3). In this system different exercises were scaled differently (3).
It seems that the rating systems (1, 2 or 3) in which the athletes are getting rated holds its ground with regards to kinematic analysis (4).
Differences were seen in peak knee flexion and knee flexion excursion with the groups ranked 3 > 2 > 1. Furthermore, Group 3 exhibited greater peak hip flexion, hip flexion excursion and peak hip extension moment compared to group 1.
First of all there seemed to be a debate, what constitute an “at risk player”.
Players scoring below 14 (16) seem to be “at risk” while a score of <18 was used to classify athletes into this category (10) in a different publication. The FMS scores were not related to injuries in track and field athletes (1), basketball players (8) and a cohort of high-school (2) and collegiate (33) athletes.
Despite the information that a score of <14 was associated with an 4.2 times (20) and 15 times (13) (in combination with injury history) increased risk of injuries.
It was also concluded that the FMS can accurately identify individuals with an elevated risk of musculoskeletal injury among male professional football players, male marine officer candidates, and female college basketball, soccer, and volleyball players (18).
A couple of investigations utilizing the FMS investigated football players. The FMS was used to test athletes self-perceived proximal stability in Division II female soccer players (26), the
impact of functional limitations of muscles on the correctness of fundamental movement patterns in Polish elite football players (15), to investigate asymmetries in professional football players
(28), connections between maturation, physical performance and FMS scores (21), asymmetries and injuries mechanisms in Hungarian footballers (35) and changes in the FMS scores over the
course of a NCAA soccer season (31).
In the first study the researcher investigated if perception (pre- and post-FMS assessment) was correlated with the FMS. The players rated themselves significantly different pre- vs. post-testing. Interestingly, pre-test scores were not related to FMS score, however, the perception of the players post-FMS were significant correlated with the FMS score (26).
There were significant differences between elite and sub-elite for the tests. Elite players scored higher in the rotational stability, however the sub-elite players scored higher in the deep-squat, in-line lunge and active straight leg raise. The authors concluded that there are different functional reasons affecting values obtained in the FMS (15).
The deep-squat was shown as the exercise with the lowest score and the active straight leg raise with the highest score in general. A score of 14 was set to distinguished between a “good pattern” and “poor pattern”. Interestingly, only the “poor-performers” showed differences between the dominant and the non-dominant side for the unilateral tests (28).
Older youth players scored significant higher on all FMS scores compared to younger peers (21). Deep overhead squat, in-line lunge, active straight leg raise and rotary stability test were significantly correlated to all performance tests. In-line lunge performance explained the greatest variance in reactive strength index (47%) and reactive agility cut (38%) performance, whilst maturation was the strongest predictor of squat jump performance (46%). The conclusion of the study was that variation of physical performance in youth soccer players could be explained by a combination of both functional movement screen scores and maturation (21).
Limb asymmetries were discovered in 40% of the investigated Hungarian footballers (35).
Longitudinal assessment of the FMS was performed in collegiate soccer and volleyball players (31). However, four individual tests did show significant change. The deep squat and inline lunge scores improved across all athletes, and the active straight leg raise and rotary stability scores worsened across all athletes. A reduction in the number of asymmetries and scores of 1 was also found. The authors concluded that individual changes in FMS occur through the course of a competitive season.
Furthermore, a survey showed that the FMS was used in various Premier League Football clubs (22).
Despite the text given above, it was also mentioned that the FMS was not purported to be a diagnostic tools, however, can be used to recognize movement deficiency (2) and did not predict injuries (2, 7, 34), it therefore might not be the choice to guide exercise prescription (12). As mentioned more attention should be paid to each task compared to the sum of all scores (19).
It seems debatable if the FMS can be seen as a diagnostic tool to predict injuries. However, small research suggests its feasibility for specific populations (17, 18) with football possibly one
of them. However, and not only due to the limited data, its utilization seems questionable. Despite, it is a reliable tool that is cost-efficient and very easy to administer, it is very
time-consuming (~10-15 minutes are needed to assess one player with all seven exercises). There is definitely more research needed with regards to a football context.
Despite a lack of scientific knowledge in the mentioned areas, application of the FMS might be more useful longitudinally, compared to short-term applications of the tool. As the exercises above are described as functional movements it seems warrant to test these capacities in footballers, also with regards to functional strength training as the exercises are close to the actual exercise prescription.
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