There are reasons why different runners might best adopt 'slightly' different pacing strategies (profiles), even in flat corner-free road marathons, to get their optimal times - if it is critical to maintain a constant metabolic rate in skeletal muscle. One of the reasons has to do with physics, the other physiology. I thought I would try and calculate what that optimal pacing profile (for that 'mythical' flat wind-free cool road marathon) might look like for me. Just how much of a change in pace should I be aiming for if I were to make the very best use of my skeletal muscle carbohydrate stores? [The real world importance of this may be limited since it is possible that I am not limited by my carbohydrate reserves at the pace I can sustain and other runners may fail to make the best of their reserves because they start too quickly in the first place.]
It is well known that increases in muscle power-output disproportionately consume carbohydrate reserves. The reason is that the relationship between carbohydrate usage relative to fat usage is highly non-linear with pace. Since carbohydrate stores in skeletal muscle are limited, and once they are 'exhausted' fat metabolism remains as the only option and it has a relatively low rate of energy production. Thus, it is also widely accepted that near flat power-output (or metabolic rate) - of an appropriate power that 'exhausts' the carbohydrate stores by the end of the marathon - also results in the best performance.Thus, we arrive at the question; "What should the pace profile look like to achieve that flat power-output?". There are two main factors that I think we need to consider - "How does weight change during the marathon?" and "How does efficiency change during the marathon?" If weight decreases during the marathon then a steady power output should result in a proportional increase in speed (and vice versa). If efficiency decreases (which is likely) then speed will need to decrease for a constant power output to be maintained.
I thought I would do a little n=1 experiment to test this on myself. It is a reasonably good example of how a very simple set of measurements can help us address questions of pacing. The equipment I have used is easily and cheaply available and accessible to anyone wanting to investigate how they respond. Your response may be different - but, probably not that much different from a weight-scaled version of me.
This evening I did a sequence of 12 laps (2.86 km; see Strava) whilst weighing myself between each lap). I used a Salter Ultimate Accuracy domestic scales (they read to 50g) - which I had previously calibrated. I weighed myself 8 times in succession at each lap using an 'anti-defeat' protocol (these scales do not register a new weight unless it is more that ~200g different from the last one, so I alternated holding a 1.74 kg weight). I was wearing leggings, heavy trainers and a long sleeve base layer (no hat, gloves or jacket). The clothes were chosen to limit radiant heat loss but allow sweat evapouration. All weights were made wearing these clothes. The weather was mild (~13C) but the wind was reasonably strong. I set out at 4:57 mins per km pace and attempted to minimize pace and heart rate deviations - however, the wind and lack of lighting made this difficult. After each lap I returned inside and at the entrance weighed myself (it took ~2 min to make the 8 measurements). I did not use a towel or drip sweat - all weight loss, other than where indicated - was evaporative.
The graph of my weight (mean+/-SD) against distance is plotted in Figure 1. At point A I emptied my bladder and bowel and at point B I consumed (rapidly) roughly a pint of water - exact weights in figure legend. The step changes in weight were planned. As expected there was a gradual loss of weight, although careful observation reveals that at the start, after point A and after point B the first weight loss appears smaller.
Figure 2. Weight change over the course of each lap plotted against distance. |
However, it is possible that running becomes progressively less efficient and that the effect is to require greater muscle power to produce the same speed. The weight loss data should allow us to investigate this. Evaporatiing water carries away 0.54 kcal per g. In Figure 3 I have used this number to calculate the total evaporative metabolic energy loss - the best representation of muscle power that we can calculate with these data. To make this calculation I have assumed an incremental efficiency of 21% through out. The legend contains details of the calculation.
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Unfortunately the dataset is not good enough to detect the changes in efficiency on the step change loss or gain in weight (toilet and drink) - more data points or a large weight change might be necessary - and perhaps better pacing to reduce the noise. It is by no means perfect. But, I am pleased with the amount of information that can be extracted from such a simple test.
So, to conclude. Weight loss seems to occur at a rate of about 0.1% per km suggesting an optimal pace might be a negative split, but this might be offset by a potential decrease in efficiency of 0.25%, something which suggests an optimal pace might be a 2 min positive split. But, the precise value will depend upon the temperature (i.e. sweating rate) and the rate of decrease in efficiency. The 'take home' message is probably that near flat pace - for someone who does NOT drink during the marathon might be best. If you drink and gain weight during the marathon and your efficiency declines faster then a positive split profile (i.e. slowing from the very start) might be optimal for the fastest possible marathon. However, for less well trained runners there are likely to be more important factors at play. I will investigate this further in my next post.
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