Improving Grade Adjusted Pace

Grade Adjusted Pace (GAP) estimates the equivalent flat land pace for a given running pace on hilly terrain. Running uphill requires more effort than running on a flat grade, so GAP adjusts pace to be faster than the actual running pace. Similarly, GAP is slower than actual pace on downhill terrain.

Strava Run Activity Pages have long featured GAP data to give runners a way to compare efforts on different grades. For example, in the following hilly trail race, Strava’s GAP mile splits provide a considerably better representation of actual effort than the pace splits.

While GAP has often provided an excellent representation of actual running effort, we have received feedback over time that sometimes GAP has varied significantly from a runner’s perceived effort. We decided to take a deeper dive into our GAP calculator with the goal of improving GAP accuracy.

What We Improved

GAP Adjustment Reduced for Extreme Downhills

Our original GAP implementation was inspired by the research of C.T.M. Davies [1, 2] studying environmental effects on running. Our approach used a scaling factor that adjusted pace as a function of grade, with the adjustment getting larger with increasing steepness for both uphill and downhill terrain.

More recent research [3] has shown that the downhill adjustment does not continue to increase with increasing steepness for grades below -20%. While there is still an adjustment making GAP slower than actual pace, the adjustment does not continue to grow on extremely steep downhills. Strava GAP calculations have been updated to account for this factor on steep downhill terrain.

GAP Accuracy Improved at Slow Paces

Strava’s original GAP calculator applied an adjustment to running pace that varied with grade but was independent of actual speed. This means that we adjusted running pace by the same amount on a 5% uphill regardless of whether the actual pace was 12:00 min/mi or 8:00 min/mi.

Research has shown that the energy cost of running at a given grade tends to be independent of pace, but the GAP adjustment does depend on pace. The GAP adjustment is greater for a faster runner than for a slower runner at any particular grade. Strava’s improved GAP calculator accounts for this and is particularly better at estimating GAP adjustments for slower running paces.

Extreme GAP Outliers Reduced

Our deeper investigation into GAP also revealed several notable edge cases where extreme outlying grade data could negatively affect GAP calculations. Runners would occasionally see average GAP for a run that was outside the known bounds of human performance. We improved our calculator to better detect outlying data and limit its impact on GAP calculations.

Known Limitations

Ultimately, GAP can only provide an estimate of equivalent flat land pace. While GAP calculations are derived from research on real running subjects, the scope of the research is not wide enough to provide an extremely accurate estimate for any given individual. GAP is also highly dependent on accurate elevation data, as elevation noise has a significant impact on the underlying grade calculations.

Additionally, GAP is only an estimate of the energy cost of running. It does not account for terrain surface or the technical skill involved in downhill running. It is extremely difficult to make aerobic fitness the limiting factor when running downhill, particularly on trail at steeper grades. Technical skill and motor control are almost always the limiting factor. For a constant-effort run on hilly trail, we generally see downhill GAP trending to the slow side due to these factors.

Footnotes

[1] Davies, C.T.M. et al. (1974). The Physiological Responses to Running Downhill. Journal of Applied Physiology 32, 187–194.

[2] Davies, C.T.M. (1980). Effects of wind assistance and resistance on the forward motion of a runner. Journal of Applied Physiology 48, 702–709.

[3] Minetti, A. E. et al. (2002). Energy cost of walking and running at extreme uphill and downhill slopes. Journal of Applied Physiology 93, 1039–1046.

Originally published at labs.strava.com by Steve Lloyd.