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Football (or soccer in the United States) is one of the world’s favorite pastimes, regardless of whether people are watching or playing it. As football continues to grow on the international stage, there is an increasing demand on footballers to push the limits of performance and remain injury free. Sports and exercise medical practitioners are therefore tasked with trying to reduce the risk of injury for individual players and mitigate the impact of overall injury rates on team performance.
At Keele University, we have examined a commonly used, clinical decision-making tool, testing its ability to measure performance of human movement and predict injury. Knowing the performance characteristics of such clinical assessments could help improve decision-making processes and reduce the burden of injury in football.
Of the many screening tests available within football, the Functional Movement Screen (FMS) is most commonly used for predicting injury. Use of the FMS is not exclusive to football: other sports clubs/authorities (e.g., NFL, NBA and NHL), public services (e.g., firefighters) and the armed services use this method of screening. The FMS requires participants to perform a series of movements, including a squat, lunge, press-up and test of shoulder mobility, for which they are scored by an assessor. The assessor awards a score based on real-time visual observation only, tracking a number of movements at different joints simultaneously to decide the score. Lower scores are assumed to be indicative of a higher injury risk due to poor movement patterns. Although the FMS is commonly used, its validity and reliability have not been objectively evaluated.
Capturing movement performance indicators in athletes performing complex 3D movements is no easy task. Therefore, to ensure that we accurately captured the footballers’ performance, we used the Vicon motion capture system based in our laboratory at Keele University. The preseason FMS scores for 24 individual players from the men’s football team were simultaneously assessed by a certified FMS assessor and calculated using the Vicon motion analysis system and the Plug-in Gait full body marker set with additional pelvis and thorax markers to compensate for marker occlusion. We then followed the footballers throughout one competitive season in a University league documenting injury patterns. From the data we were able to:
The project was not without its challenges, as the requirements of the FMS pushed the capabilities of the participants and the model to their limits, with things such as gimbal lock in the upper limb being the proverbial fly in the ointment.
The Vicon system was extremely useful for evaluation of the FMS and allowed us to highlight the complexity of the FMS scoring process and its failure to behave as a measurement scale. We were also able to determine that neither scoring process was able to predict serious injury in footballers and concluded that sports practitioners may want to reconsider using the FMS. As our research progresses, we are looking at whether there are other movement characteristics outside of the FMS framework which could help to identify injury mechanisms and we continue to explore how we can improve performance measures to help sports practitioners with decision-making processes.
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|Chest||78.7cm / 31in||85.1cm / 33.5in||87.6cm / 34.5in|
|Waist||63.5cm / 25in||68.6cm / 27in||78.7cm / 31in|
|Hips||81.3cm / 32in||86.4cm / 34in||91.4cm / 36in|
|Inside Leg||66cm / 26in||69.9cm / 27.5in||77.5cm / 30.5in|
|Chest||86.4cm / 34in||94cm / 37in||103cm / 40.6in||114.3cm / 44.5in|
|Waist||71.1cm / 28in||83.8cm / 33in||90cm / 35.4in||99.1cm / 39in|
|Hips||88.9cm / 35in||94cm / 37in||100cm / 39.4in||109.2cm / 43in|
|Inside Leg||66cm / 26in||69.2cm / 27.3in||71cm / 28.3in||81.3cm / 32in|