A topic that has puzzled me recently is why and when should we make cross-country comparisons.

I’ll use an analogy closer to other planturo content. Let’s say I compete in a running race and out of 100 people, I place 75th.

What can be inferred from this one data point?

  • I could conclude that my fitness is pretty bad; worse than the majority. But there might be more to the story. Maybe this particular foot race was a run up a mountain, and that suited trail-runners over road-runners – and I’d trained for the latter.
  • Some commentators might conclude that because of my poor placing, I clearly need to improve my fitness. But coming first or last might be irrelevant. It might be that all participants wish to improve their fitness, regardless of how they place.
  • Other commentators might say that I should copy the training regime of those ahead of me. But perhaps each participant has different training needs and styles, and so copying others might not work for me.
  • If I wanted to find out how to improve my fitness, the 75th placing by itself would tell me nothing. What does it mean? Should I lose weight or build strength or work on endurance? The data point itself tells nothing about the underlying causes.

From time to time I come across comparisons that are made in unhelpful or unconvincing contexts. It’s clear that data comparing things can be manipulated to suit a messenger’s purpose. The onus seems to be on those of the receiving end to dig a level deeper and ask questions such as ‘what is the whole story?’ ‘what is the implication of this?’ ‘do we care about this measure?’

Another picture from top of Mt Arawang



  • Breakfast: biscuit (plazma) and red bean paste
  • Lunch: chicken roll, apple
  • Dinner: ice cream
  • Other: coffee, chocolate, lamington, strawberries, blueberries


  • 6.5km run at 6.19min/km
    • easy peasy pace
    • average run cadence: 163 steps per minute
    • average stride length: 0.97m
    • elevation gain, loss: 35m, 31m