MIT Publishes Findings that Link Agility & Athletic Performance to 4 Key Metrics
When we consider an elite athlete’s performance in a competition, time is often the metric used to rank their overall performance. We describe professional athletes as being fast, agile, strong, and powerful. Agility is a large component of athleticism, but what factors or strategies translate to being more agile? First let’s consider the definition of agility, of which there are two types. Agility, the ability to quickly change speed or direction, can be planned or reactive . Planned agility refers to the physical action of changing direction and is evaluated by navigating a pre-defined path. Reactive agility incorporates a cognitive component by involving perception and reaction to a cue signaling turn direction . An example of a drill that tests reactive agility is navigating a set of cones as fast as possible in response to a vocal cue.
What Makes an Athlete Agile?
Chika Eke and Leia Stirling of the Massachusetts Institute of Technology surveyed a number of human performance experts in the military, clinical, and sports domains to better understand what metrics are considered important for assessing reactive agility technique . These qualitative metrics included:
- “Foot contacts” characterized as short, quick steps within a turn and then long strides on straightaways
- “Efficient path” or minimizing path length
- “Arm motion” described as a pumping of the arms to change direction
- “Change direction” or the ability to alter course heading quickly
Eke and Stirling, along with Stephen Cain of the University of Michigan, hypothesized that biomechanical metrics relating to technique would be sensitive to the agility task performance. These quantitative metrics included:
- Number of foot contacts
- Stride length variance
- Stride frequency
- Arm swing variance
- Cumulative change in heading angle (relating to the number of 360 degree turns completed)
Eighteen recreational athletes were recruited to complete a reactive agility course while wearing 13 Opal wearable sensors used to capture raw movement data. Four cones were laid out and participants ran from the start line across another line at which point they were given a verbal cue instructing them to touch one of the four cones, and then returned to the start line. This process was repeated until four cones were touched in rapid succession.
The Biomechanics of Agility
Fewer and faster foot contacts correlated to a faster course completion time, but it should be noted that short, quick steps were employed as a successful turning strategy. This is in agreement with the finding that faster athletes had an increased stride length variance, which translates to long strides at high speed on straightaways and short strides when changing direction. Greater arm swing variance also correlated to faster completion times, as athletes used tight pumping motions to accelerate out of a cone-marked endpoint. The only metric not supported by the data was the cumulative change in heading angle. Further observations revealed various rotation strategies that were likely dependent on hand and foot dominance. Multiple participants chose to turn in a way that allowed them to plant their dominant foot on a line or use their dominant hand to touch a cone, rather than choosing to turn in the same direction every time .
Sports | Military | Clinics
Traditional motion capture systems involve extensive processing time, limit data collection to a fixed volume, and can have marker occlusions. Opal wearable sensors significantly reduce the time required for system set up and data processing, they can be used in a natural environment thus eliminating space constraints, and do not require line of sight between a camera and a marker. Kinematic data from these sensors can be used to quantify agility performance, aiding in the identification of performance weaknesses and creating athlete-specific training plans. Kinematic data is not only useful for athletes but can also aid military personnel in assessing the ergonomics of carrying heavy packs and weapons, or clinicians in monitoring their patients’ rehabilitation progress.
Portable Motion Capture Solutions
APDM Wearable Technologies offers sensor-based solutions for quantifying human movement. APDM’s research-grade sensors and sophisticated algorithms are designed to streamline biomechanical research through automated movement analysis. Motion Studio provides access to raw movement data, Mobility Lab generates spatiotemporal outcome measures for gait and balance, and Moveo Explorer produces full-body kinematic data including joint angles and range of motion. For more information, please contact firstname.lastname@example.org
- Sheppard & Young. “Agility Literature Review: Classifications, Training and Testing.” Journal of Sports Sciences. 2006
- Spiteri, Newton, & Nimphius. “Neuromuscular Strategies Contributing to Faster Multidirectional Agility Performance.” Journal of Electromyography & Kinesiology. 2015
- Eke & Stirling. “Effect of Rater Expertise on Subjective Agility Assessment.” International Conference on Applied Human Factors & Ergonomics. 2017
- Eke, Cain, & Stirling. “Strategy Quantification using Body Worn Inertial Sensors in a Reactive Agility Task.” Journal of Biomechanics. 2017