As the saying goes, "If it's not on Strava/Nike+/Runkeeper/MapMyRun/Garmin/Fitbit, it never happened."
We runners love to track our performance. Whether it be to see how we're improving, how many miles we've run in a year, or even just showing off our running pride on social media, we're in an age where every step we take, every move we make, somebody (or something) is watching us.
But, what does one really do with all that data? There are so many data points collected, it can be overwhelming to decipher and understand how to process to effectively optimize our performance. Honestly, this runner is in the same boat as many, and would rather hand over all the data to NASA to write me up a personal plan to make me a better runner.
I can't afford that luxury.
So, I've approached a method that leverages my passions outside the act of running to help me decode my run and look for ways to improve. Admittedly, it's a little nerdy and takes some work on the old Excel, but I have seen noticeable improvements on race day because of it. But, before we get into the process, there's another tidbit you need to know.
I love music.
I've always had a profound love for this art and as a musician, music is at the heart of everything. Every moment of my day is filled with rhythm, pitch, timber and melody. I literally wake up to songs in my head and from the moment I hit the door, my earbuds are pulsing with the sounds of John Williams, Aaron Copland, Glenn Miller, Tommy Dorsey and a host of contemporary artists. So, how does that make me a better runner?
Well, like many of my fellow runners, I can't take one step without my tunes. It is truly one of the necessities of my run. Because of that, my playlist has to be perfect mix of uplifting and energetic for those shorter races (5k/10k), to energetic but also relaxing for those long mileage races (Half/Full) to keep my even. But, it's how I setup the playlist is paramount to my success. Here's how I go about it.
Using my running tracking data, I'll combine similar distance runs in Excel to map my performance. From there, I'll look at where there are nuances (good and bad) in my performance to see where there are areas for opportunity. I'll then make a note of those areas and adjust my playlist accordingly. If there are areas where I'm running too fast, I'll adjust the playlist to play a more soothing song to slow me down. If I'm dipping in time, I'll schedule a more uptempo and energetic song to get me back to my goal pace.
If you think this is a little nutty, well it is. But, it happens everywhere. Restaurants have been doing it for years. In the daytime they'll play more energetic music to get you to eat faster and thus, more patrons for them. At night, their music selection will be calmer, soothing for the meal, but then also to make you tired. It's also a very common trick in advertising. Pay attention to the music you hear at your favorite sit-down restaurant the next couple of times. Oh, and yes, Disney is famous for this, too.
Okay, so this all may be a little tricky to comprehend via writing, so I've created an example for you to follow along below.
In this example, I've mapped four consecutive 10-mile runs that have all happened within two weeks of each other. Runs #1, #2, #3 are all without a optimized playlist. Run #4 is after I've adjusted my playlist.
As you can see in Fig. 1, Runs 1, 2, 3 have suffered roughly the same issue, I go out too fast and subsequently, because of that my performance dips around miles 7-9.
Looking at Figure 2, you can see at roughly 32 to 35 minutes into my run, my performance historically dips, so I could just add some high energy music at that time to boost me into gear. However, if I don't address what's happening at the start of my run I may not have the energy to pick it up when that high energy music kicks in. First, we need to look at what's happening at the start of the run.
As you can see in Figure 3, my pace per mile is significantly faster at miles 3-4, which one could infer as to why I'm sucking wind later in my run. Therefore, my playlist could be too top heavy at the start of my run. Perhaps, I could try something a little easier about 15 minutes into my run.
Lastly, in Figure 4, run #4 (blue) is relatively consistent due to my adjustment of my playlist. Because of the smoother music at the front of my run, I was able to conserve energy to push through the later miles, and even kick in a little harder at the end.
This has become so commonplace with me, I can use the music queues rather than my watch to determine how I'm doing. If I'm cranking and a slower song comes on, I know to slow down and get back to a comfortable place.
I've even extended this process to the corrals pre race. Because of the energy of the corrals, I've found myself getting caught up in the excitement of the start, so I developed a Corral Chill Out mix of more easy listening music to keep my energy at bay.
If you find this is all a bit crazy, I agree. But, I've found it very effective. Instead of pouring over data and trying to develop some MENSA-based algorithm, I've tapped into a staple of my life (music) to train me to be a better runner. Honestly, I think that's a pretty smart move.