NikePlus Elevation Tracker


I'm taking a quick break from my KenPom data visualization work this week to talk about another project I've been working on. I'm an avid runner and have an upcoming race where I'm a little worried about the elevation changes so I thought bringing in some programming could help.

The NikePlus app that I use to track my runs does show changes in pace and elevation (see chart below) but it doesn't give you any idea of the total change in elevation for the whole run. Most people do "point-to-point" runs so the net change is zero but there is still a big difference between 100 feet up then down and 1,000 feet up then down over the course of a run.

NikePlus Pace and Elevation Chart

So, I decided to figure out how to calculate this on my own. I first used the this site by Matt Stuehler to export my data from NikePlus as .gpx files. Then I wrote a small function in R to sum all of the changes in elevation throughout the whole run[1]. I'd like to eventually convert this to a standalone Python executable but for now, here's the code.

elevationstats <- function(month,day,res=1){

## get the file and turn it into a numeric vector

setwd("[folder where the file is]")
filename <- paste("[username]_[year]_",month,"_",day,".gpx",sep="")
fullfile <- read.csv(filename,header=FALSE)
r <- gregexpr("<ele>.*?</ele>",as.character(fullfile[[1,1]]))
x <- regmatches(as.character(fullfile[[1,1]]),r)
elevation_list <- as.numeric(gsub("<ele>|</ele>","",x[[1]]))

## change resolution
new_ele <- elevation_list[c(rep(FALSE,res-1),TRUE)]

## calculate the total elevation gain and loss

total_gain <- sum(diff(new_ele)[diff(new_ele)>0])
total_loss <- sum(diff(new_ele)[diff(new_ele)<0])



Here's what that code does:

I ran this code on the run pictured above with resolution = 1 (a GPS point every ~10.9 feet over 9 miles) and got the results:

[381 meters up, 349 meters down, 4377 points]

Running it again with resolution = 10 (a GPS points every ~109 feet) gave:

[295 meters up, 262 meters down, 437 points]

The truth is probably somewhere in between, especially given the variability of GPS data.

If you're a runner who uses NikePlus and is proficient in R, let me know if this is helpful. Hopefully I can put out a more user-friendly version in the next few weeks. Happy Trails!

1. I'm just now realizing how incredibly similar this is to my KenPom drama metric. My roommate said that he realized this all along when I was talking about it and I'm an idiot.