Hobby: Programming custom performance analysis
If you are putting sustainable effort to generate data, put sustainable effort to see what that data looks like... you may find something motivating.
I enjoy jogging in my spare time. After purchasing a jogging watch and heart rate monitor to track my performance, I created a script in R to analyze the data I generate on each run.
In addition to generating the typical pace, elevation, heart rate bivariate analysis charts, I also parsed GPS coordinates to generate a run map (figure 1) and created insightful analysis not found with typical running websites or applications by comparing heart rate as a function of pace (figure 2). This quantitatively shows:
- heart rate increasing to median rate as a function of pace at the start of the run
- heart rate increasing above and returning to median rate, at the sprint at the end of the run
- clustering around the median heart rate but more variability WRT pace. This quantitatively shows that while I was maintaining a median heart rate, I was experience fatigue.
Prior to this, my motivation on my jogs was listening to music. Now I find I am motivated by watching my heart rate in real time and getting a sense of measureable personal improvement.
Below is a gist file of the R markdown I wrote that parsed the data to generate these charts. Here is a link to a knitted R Markdown file.
Figure 1: map of the jog, generated by data parsed from the jogging watch
Figure 2: Heartrate [BPM] as a function of pace [mins/mile]