Analyzing training data

So one of my ideas throughout the semester for the final project has been to see what kinds of analyses I could perform on the training data I’ve accumulated over the past few years. There was a comment awhile back asking about what kind of information is in these training logs and I’ve been meaning to make this kind of explanatory post for awhile now. At this point I consider myself pretty darn good at making insanely and probably unnecessarily complicated/intricate Excel logs, which seems to be an endless source of amusement and good-natured mockery from my friends :)

Anyway, the level of detail (and the consistency) of these training logs varies drastically over the past two years or so; the more recent they are, the more data I have tended to record, and it’s only in the past semester that I really consider my spreadsheets to contain “enough” data, just for my personal use to look back on. What degree of statistical analyses I’ll be able to perform on the rest remains to be seen.

Here is what I currently keep track of--

For all cardiovascular work:

• sport (swim, bike, run, other)
• duration
• distance (yards, miles)
• pace (min/100 yards, mph, min/mile)
• RPE (rate of perceived exertion)
• average heart rate
• max heart rate
• skill trained (endurance, force, speed, muscular endurance, anaerobic endurance, power)
• workout done (e.g. 3x8/4r = 3 reps of 8 minutes high intensity followed by 4 min recovery)
• notes on the workout: can be details about lap times (to get an idea of changing pace & HR throughout), any nagging pains or developing injuries, general comments/thoughts

Since I focus on triathlon, I have more detailed information about the following:

• SWIM: stroke used, pool or open water
• BIKE: bike ridden, route, hills (1-9), wind (from weather.com)
• RUN: shoes worn, surface (dirt, pavement, track, etc), hills (1-9)
• LIFT: sets, reps, poundages for each exercise done

I also summarize the major information for each sport for each week and make a few graphs: total weekly volume (with breakdown for each sport), total weekly distance per sport, and the overall breakdown of how much time is spent in each discipline.

If you’re not completely convinced I’m a lunatic by this point, I present you with the following screenshots!

Different colors correspond to workouts of different types (e.g. endurance, speedwork) and allow me to plan weeks out ahead of time without having to decide exactly which specific workout I will do, just by filling in an appropriate mix of colors in the boxes for all the sports on various days. I usually have the runs planned out a few weeks ahead of time since my focus has been a May marathon for which there are specific weekly mileages and distances I must make; I, then fill in the other sports at the beginning of the week, making adaptations depending on daily commitments. As you can see, the past week and a half has not gone as it should have...

An example of the sport-specific information, in this case running.

Craziness. But it's useful.

You may notice the uh, mild decrease in activity on the most recent week, where all I did was one weight session the entire week. Unfortunately I started having major iliotibial band problems during runs and have had to take some time off so that it doesn’t turn into a recurring injury. Neglecting exercise is stressful enough but it’s coupled with the likely prospect that the marathon I was training for all semester is not going to happen for me. A thought that’s more than a little devastating – but, better to lay off now and miss the race than to ignore the pain and injure myself permanently for the rest of the summer. With that in mind, I’ve been trying to think of some questions that I could ask about these data in order to use for an analysis. Here are a few:

• What factors predict incidence of joint/tendon pain or injury?
• How does weekly training volume affect paces?
• Does running surface/shoe type affect pace?
• What kind of relationship exists between heart rate, RPE, and pace?
• How does sleep impact speed, distance, RPE?
• How does daily volume relate to stress?
• Which weightlifting exercises lead to greatest strength increases?
• How much lifting volume leads to the fastest gains?

I don’t know if I have the consistency of data for a long enough period of time (e.g. a year) to fully answer these questions but if I can figure out a way to model some of these things, then in the future I can always go back and enter the increased data sets to see if the answers change. It would be really interesting to use this to find out information that would be extremely relevant to me. Combining personal life and intellectual interests so closely is definitely a unique opportunity!