Each running capture will display a score at the top of the Metrics Dashboard as shown below. This article will outline how the scoring algorithm was developed, what the value means, and how to use it to provide the best care to your client.
How was the score developed?
The score is determined through a robust mathematical algorithm which was developed using over 4,000 historical 3D running captures ranging from world class athletes to beginner recreational runners. The score cumulatively assesses a runner's mechanics and can be used to differentiate between runners with ideal form indicating low injury risk and runners with poor form indicating high injury risk. We used evidence based statistical methods to identify 27 significant variables which summarize the quality of a runner's gait. Generally, the algorithm calculates how much the runner's gait deviates from a healthy ideal dataset based on the clinically significant variables from their capture. The score was adapted to fit a percentage model where the higher the percentage, the better the score, with values nearing 100% representing the highest quality of gait.
What does the value mean?
The score is a useful metric for summarizing a client's overall quality of gait. A score closest to 100% is considered to be high quality, with lower scores indicative of worsening mechanics. The score increases in percentage incrementally from 40% to nearing 100%, with all scores below 40% being displayed as <40%. We find that a normal range for a runner that is 15-55 years old is going to be 40% or higher, with scores of 60-80% representing moderate changes needing to be addressed, and scores of 40-60% indicating significant running mechanics that absolutely need to be addressed. All scores stating <40% may indicate that there was an error with marker visibility. That said, aging populations and those with known pathologies that impact gait may display values less than 40% on the score and still be a good capture. If an asterisk (*) is located after <40%, there is definitely a capture issue. In all cases, it is important to check the quality of your data before delivering feedback to your client.
How do I use the score?
The score is highly reliable and sensitive to change. Be aware that this means the normal values will vary for different populations. There are several researchers investigating expected ranges among certain ages and pathologies. As our Partners help us make this score even more valuable among special populations, here are the trends we have found for most runners.
Generally, a runner with a score of 90% or greater has “good mechanics” while higher scores indicate worsening mechanics. In either case, there is always room for improvement! Naturally, the lower the score, the more likely you are to see more substantial changes with gait retraining. It’s understood that a runner at 15-minute per mile pace can drop time easier than a runner at 4-minute per mile pace. Similarly here, it is far easier for a score of 66% to rise to 80% than for a score of 92% to reach 96%.
The score is a meaningful metric, but we still always want to take a holistic look at the runner. Be sure to assess their movement capabilities and consider all the data for clinical decision making. Additionally, know that a decreasing score during gait retraining does not always indicate an ineffective cue, it may just take more time for the positive change to occur. In our internal testing we found that this is common for more experienced runners with a consistent gait pattern. For example, when using the “Knee Drive” cue the runner may drive the knee well but lean backwards to do so. In this scenario, you may want to give them multiple trials to give opportunity to naturally improve or do some fine tuning of the cue. When someone changes their form, overall muscle activity increases which may have secondary consequences. As the runner continues a gait retraining program, the cue will begin to feel more natural, and those consequences will often resolve on their own. This emphasizes the need for using motor learning principles, long-term gait retraining, and follow-up assessments for the best results.