In early December 2018 Runfisix was granted the opportunity to travel from Calgary to Sacramento to shoot a documentary for Telus TV Canada about our work in running injury prevention. The documentary featured a runner called Martin. A 62 year old veteran of more than 300 marathons who was looking to run his first sub 4 hour marathon since 2010. Although Martin's preparation for the California International Marathon was squeezed into a very tight 6 week schedule, he lined up at the start in Folsom in the early morning twilight injury free and ready to give his best. His eventual finish time - 3 hours 51 minutes.
In this case study we will focus on Martin's shock values as recorded by the latest version of RunScribe footpods (v3). Firstly we will look at his overall average race value, then his individual left and right race values and then show a brand new type of foot contact plot that integrates his shock values with the correlated footstrike locations under the foot.
SHOCK - the sum total acceleration peak recorded at footstrike that combines the vertical impact and the horizontal braking. It can be a very useful overall marker for how much acceleration/deceleration the body is having to deal with when the foot is striking the ground.
Martin's overall shock value for the race was 14.6G. Which compared with global normative data for his running pace and stature is a little high. Taking into account the downhill nature of the course and Martin's extreme fatigue toward the end of the race means that although this number looks a little high, it is to some extent, justifiably so. Usually Martin is extremely measured with his effort and his gait metrics change very little during a workout or a race. If we look at the bulk shock trend over the course of the race below we can see that this seems to be the case here too. His overall values appear consistent from the start line to the finish line.
Plot showing overall shock values (G) through the race with pace (min/km) and elevation (m).
However this race was different to anything he had done recently and Martin was pushing as hard as he could and running faster than he had in a marathon since 2010. So let's look at his left and right side data individually and see if he was able to remain symmetric throughout the race (as is his normal style).
Plot showing left and right shock values (G) through the race with pace (min/km) and elevation (m).
Looking at the plot above that is comparing his left side and right side values for shock we can see that for almost the entire race he exhibits some small asymmetry. It is Martin's left side that records the higher shock values. In fact his left side averages 14.9G whilst the right side averages 14.2G. This is a small difference but compared with Martin's usual near perfect symmetry this is note worthy. Interestingly his largest shock asymmetry values occur in a period just after halfway on the course, but then stabilize to being more symmetric in the final 30min to the finish line.
For the first time we can now plot a runners shock values at footstrike in a 2D view of the left and right shoes that we call the ShoePrint*. Showing the underfoot locations where Martin was striking the ground and the shock values that relate to them. We can also combine into the plot the toe off locations and the flight ratios (ratio of time on the ground vs time in the air) that relate to them. Hence generating a full foot contact display for the left and right side for the entire race.
Left and right ShoePrint (foot contact) plots. Individual points represent 2D underfoot locations for TO (toe-off) and FS (footstrike). TO colors indicate flight ratio values (%) and FS colors indicate shock values (G).
The ShoePrint plot above allows us a further step forward in insight and clearly indicates that whilst Martin's left and right side average shock values were only slightly asymmetric, his left and right shock-at-footstrike locations were significantly asymmetric. Hence Martin's shock values were being generated by footstrikes at different parts of the foot on his left side compared with his right. These footstrikes can be seen clustering around the midfoot in the yellow-orange to purple colors in the plot. Martin's left footstrikes were occurring over a wider area laterally than his right footstrikes, which occurred across a very narrow lateral extent.
The next stage of further breaking down this data is to compare these kinds of ShoePrint plots over set intervals during the race. For example every 5km or 10km. In our next case study coming soon from the 2019 Houston Marathon we will aim to do just this. In an effort to better understand if foot contact characteristics for a specific runner are holding throughout the race or changing at specific points.
*ShoePrint is the official terminology created by RunScribe in January 2019.