Let’s see if we can identify any traits among those who beat the red line to apply to our own training to get us closer to our goals. I refuse to say badly, because that’s not much fun to read if it applies to you – and anyone who’s capable of running a marathon is already awesome. To the left, the runners that converted their half marathon time into a relatively good marathon time and to the right, those who did less well. We can use our red line to create two groups. Our predictor scraps the 1.06 in favour of R=1.15 (shown in red), in the sweet spot at the heart of the graph – which instantly means that our predictions are more likely to match most runners, generating more realistic and achievable goals to aim at.īut by tuning our predictor to the middle of the data, we are left with a situation where half of all runners have a very real chance to beat that prediction – and some of those who did were keen to suggest that they’d obviously done things properly! And there’s probably at least some truth in that.
Riegel number distribution for 1,071 marathon runners.
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