Data Geek Alert: Stats for a year of slow running

I’ve been using Trainingpeaks (a software for performance management) on and off and now finally got time to read the book “The Runner’s Edge” by Stephen McGregor and Matt Fitzgerald from my running book list. While it dates back a bit, it is quite relevant to me and while I am digesting all the information and try to apply it to my own “beginner” situation I want to write it down and possibly learn from it. I am not in any way affiliated with Trainingspeaks, just found it super useful. Depending on your obsession with stats it might be useful for you as well. All the above can also be calculated with simple formulas and either tracked manual or via excel – I just happen to love software 😀

As in all things with life, there are 3 steps relevant to improvement:

  • Monitor
  • Analyse
  • Plan


I’ve been monitoring everything from the start, so I am covered well in this area or so I thought! Now after a year has past, I am ready to look at all the data and make some sense of it!


This is the interesting part, where I get to connect cause and effect. Initially I get to list all questions I want to answer:

  • Rate the quality of each workout: I blog about how I felt in each run, that should be enough
  • Is my Training hard enough or too hard?
  • Do I need to rest?
  • Am I getting fitter?
  • Is my training appropriately balanced?

All more or less difficult questions. So what do I do? I turn to what I know … business! What I need in business to get a clear head are KPIs.

Here is what Wikipedia tells us KPIs are:

“KPIs evaluate the success of an organization or of a particular activity in which it engages. Often success is simply the repeated, periodic achievement of some levels of operational goal … and sometimes success is defined in terms of making progress toward strategic goals. Accordingly, choosing the right KPIs relies upon a good understanding of what is important … Since there is a need to understand well what is important, various techniques to assess the present state of the business, and its key activities, are associated with the selection of performance indicators. These assessments often lead to the identification of potential improvements, so performance indicators are routinely associated with ‘performance improvement’ initiatives.”

Now if you replace “organization/business” with “runner” and are still reading you are getting my idea. In plain terms what I need to improve as a first step are an initial set of KPIs. So let me get started on a list:

My KPIs for Running

  • CTL: Chronic Training Load (how hard I’ve been training over the past 6 weeks) (see below)
  • ATL: Acute Training Load (past week’s load) (see below)
  • FORM: The result of the above or how well I can expect to perform (see below)
  • Training balance in % of heartrate zones per week (see below)
  • Average Pace for aerobic heartrate (need to be disciplined and run only at that heartrate lol)
  • MAF test results (need to get started on doing those properly!)
  • Resting Pulse (tracking this via my phone, need to find replacement)

Here is a chart showing the data for my first year:

Trainingpeaks: Performance Management Chart

The blue gradient line is my CTL. As you can see I had 3 breaks where my fitness dropped. Each red dot resembles a run. The higher the dot, the more intense the run was. The yellow line is my Form, and the pink one is the ATL. FYI that is why people taper before running their marathons: to make their form go up so they are fresh and rearing to go once dooms marathon day arrives.

Below is a look into how balanced my training was. Unfortunately it wasn’t … but I am getting better with the slowness! You can see since the start of the year the dark red is getting less and less!

Heartrate zones in % per week



I’ve tagged all my plan related posts here. In essence I still follow the 3:2:1 ratio for my runs, do one recovery week every month and if I feel bad I don’t run. I do all my runs in super slow running motion and continue on as described. I might have bad runs, but they seem to be quite rare. I will try and keep tagging them, so maybe I can spot a pattern there at some point.

Generally I follow a couple of principles:

  • never increase more than 10% per week and only intensity or duration
  • A hard day is always followed by either a rest or a recovery day
  • if I can’t keep the HR down or need some fun, I want to make sure I don’t go over 80/20 (80% easy and 20% above)
  • Do a recovery week every 4 weeks

Further thoughts

It is extremely difficult to figure out if and by how much I have become faster. In the beginning I wasn’t fit enough and I walk fast. I also ran at a much higher heartrate. This skews the data … additionally it is difficult to judge the surface. I observed this during today’s run and there was over 1:30 difference between running on soft sand vs. pebbles or rocky beach. I didn’t think it was that much …

I also noticed that my difference in pace isn’t as big if I run 130 vs 139 HR, compared to 140-145. Is this a thing or was that a surface or software bug?


6 Replies to “Data Geek Alert: Stats for a year of slow running”

  1. You are taking an admirably scientific approach to your running. I value fitness as well and notice that if I slack off dropping my gym attendance from two or three times a week to once a week my fitness can deteriorate sharply. I don’t have any fitness monitoring equipment so I know nothing about my heart rate etc. I think the great thing with you is that you are so dedicated to running, no matter what the weather and when someone is that dedicated they almost always succeed in achieving their goals.

    Liked by 1 person

  2. Wow that’s truly incredible. Seeing something as analog as running turned into this kind of data is awesome. Looks like you’re really got the hang of keeping your heartrate in the zone in the last few months 🙂 I feel shamed by my only data being whether I feel knackered or not

    Liked by 1 person

  3. I love your data charts. I especially like the way that your have done the HR in the same colour but different intensity ( high intensity exercise = high intensity colour) and the bars fade away over time as you get more aerobic. I think it’s quite arty ! 😎

    Liked by 1 person

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