Posted by Dave on October 18, 2011 | 2 Comments
This weekend, on a whim, I decided to run the Bridges Half Marathon in Chattanooga. It turned out to be a pretty good whim, because I set a PR in the race!
As always, I like to take a look at my GPS record of the race afterwards to see if I might have done something differently to perform even better. But as I have long suspected, when I started to look at the elevation profile of the race, it seemed to completely botch up on bridges.
Elevation data on the typical GPS trainers that runners use is notoriously bad. You can take a look at the raw GPS data from a run through Kansas and it will look like the Himalayas. To get around the problem, many running websites allow you to correct the elevations by cross-referencing against known databases maintained by NASA and the USGS.
The problem is, those databases don’t account for man-made objects. Run across a bridge, and from NASA’s perspective, you cruised across the river on your hovercraft, 100 feet below. But I hadn’t ever really come up with a clear illustration of the problem.
After uploading my data to the Garmin Connect website, here’s what my elevation profile looked like:
I don’t remember the race being nearly that hilly! The last mile, for example, was completely downhill, and this profile includes a 60-foot climb! Similarly, miles 1, 5, and 7 include major dips that weren’t actually there; I was running across bridges at the time.
I decided to take a closer look at the elevation profile while simultaneously monitoring the satellite map of the course. Based on that observation, I was able to create a modified elevation profile that I think more closely reflects what I really ran:
As you can see, the course now looks considerably flatter. I also cut out two phantom hills in miles 2 and 4 that I’m quite sure weren’t there.
So what kind of quantitative difference does this make?
Take a look at this graph comparing my pace on each mile with the uncorrected elevation gain:
There is little correspondence between my pace on miles with a lot of elevation gain and the miles with little gain. I know I slow down for hills, but this graph doesn’t show how it affected my performance in the race.
Now when I adjust the elevation for the bridge problems, the effect of hills becomes much clearer.
My slower miles, like 7 and 12, now correspond to the miles with the biggest hills. There are some exceptions, but I can remember what happened on those miles as well (on Mile 10, for example, I took a little extra time at a water stop).
It’s probably not worth it to do this kind of analysis for every run, but for important races, it could help you make critical adjustments to refine your racing plans in the future.