In my previous post "The effect of Fat burning on Carbohydrate requirements for an Ultra" I explored the effect that being an efficient fat burning can have on sparing Carbohydrates during an Ultramarathon using the data from Scottish Ultrarunner Caroline McKay and with the paper "Maximal Fat Oxidation During Exercise in Trained Men" (MFO) as a reference. Caroline has adopted a low carb Paleo style diet in the last six months and the results demonstrated outstanding fat utilization throughout her speed range. For this post I'll use this same data and techniques used to analyse Carbohydrate utilization, extending them to allow me to study the effect of uneven pacing on Carbohydrate utilization.
Analysing Fitness dataThe first step in the analysis is to establish the relationship between HR, pace, total Calories used, fat and carbohydrates used per hour. Caroline's January fitness test provided the following graph:
For a representation comparison I think scaled the fat/carb utilization data provided in the MFO to fit with Caroline's HR range and total Calorie consumption, resulting in the following graph:
Analysing Carbohydrate utilizationFor the purposes of analysing Carbohydrate usage during an Ultramarathon the key part of this data is the how much Carbohydrate is used per mile, using Caroline's HR to pace data I then combine Caroline's carbohydrate data with that provided by the MFO study, vertical axis in Calories, horizontal axis in mph:
- Caroline is using far less Carbohydrate per mile than the athletes in the MFO study, suggesting that Caroline's training and low carb diet are extremely effective at sparing Carbohydrates.
- For both Caroline and the MFO athletes the Carbohydrate increases rapidly with pace and the relationship is not linear, so a 10% increase in pace requires much more than a 10% increase in Carbohydrate utilization.
If we re-draw the graph against HR rather than Speed then we also observe a very similar relationship, and for the same reasons can expect that an even intensity - at a consistent HR will lead to least Carbohydrate utilization for a given pace.
This applies when we are going up and down hills so we'll want to aim for a consistent HR when going up hill and down hill and let the pace drop and increase to maintain the consistent level of effort. For ultra paces this will mean walking up-hills for all but the top elite runners.
The above discussion doesn't introduce the issue of HR drift during a race, as this is something that varies from individual to individual and race day to race day it's not possible to accurately account for this factor, in this analysis. HR drift over a long period won't effect the validity that consistency in HR over any particular stage in the race is likely best. I would recommend pacing short periods like going up a hill and down the other side by aiming for a consistent HR, but expect the HR to drift upwards through the day for the same pace. If you don't have a HR monitor then use your breathing intensity as guide - if you find yourself puffing up hill then you are very likely to be pushing too hard and should ease off.
Analysing the effects of overall pacing strategiesThe observation that even pacing/intensity is likely best for minimizing carbohydrate utilization doesn't just apply to one particular instant in the race, it also applies to the whole race. However, running even splits is next to impossible in an ultra for whole range of reasons, it's inevitable that we'll either go out too fast, too slow, do one or more stages too quick or hit a low point. That's even without considering the effect of changes of the terrain, weather conditions, fatigue etc. through the race. So we all will spend some time going too fast and some time going too slow during, with the ideal being constant intensity and average speed. This leads me on to the next question - which the analysis can help answer - just how much of an effect does inconsistent pacing have?
To look at this I simplified the task by considering an evenly distributed terrain and a runner than spends half their time at a higher speed, and half the time at a lower speed and comparing their total Carbohydrate utilization to that of runner than run at same average speed across the whole race. The maths behind the Carbohydrate utilization isn't effected by how the fast and slow running is distributed - so they could run a negative or positive split, or run fast and slow for alternating minutes and we'll still end up with the same result - all of these pacing strategies will all have the same consequences w.r.t overall Carbohydrate utilization, the only crucial factor is how much faster or slow that an even pace your at.
To illustrate the effect on the uneven pacing I plotted the number of calories required for a range of deviations away from even pacing, from even pacing to high speed/low speed ratio of just over 2. The following graph illustrates the results for Caroline's excellent fat burning data, normalized so that all split combinations result in Highland Fling 10 hour finishing time:
The following graph illustrate the results for the MFO study data, again normalized so that all split combination result in Highland Fling 10 hour finishing time:
The least amount of Carbohydrates required with an even split at just over 3,500 Calories, while a 2:1 pace split requires a further 1100 Calories. A more modest split of 1.5 to 1 only requires 355 Calories. While a 1.25 to 1 pace split just requires just over 108 calories more than the minimum.
The surprising thing about these two datasets is while the baseline Carb consumption is massively different 3500 Calories for the MFO data vs 1020 for Calorline's, the additional Carb costs due to sub-optimal pacing is almost the same. However, my expectation is that it would be easier for a fat burner like Caroline to be able to cope with needing an extra couple hundred Calories of Carbs than someone who already has exhausted their glycogen stores and is now relying on consumed Carbohydrates to fuel them through the second half of the race. So while it's important that both Fat burning and Carb burners use their Carb stores efficiently by pacing evenly, it's the Carb burning that need to take the most care.
The effect of race intensity on sensitivity to uneven pacingBy setting a fixed pace split of 1.25 to 1 but varying the finishing time we can look at whether you become more sensitive to pacing errors as you increase or decrease you average running pace. The following graph plots a range of finishing times for a fat burning athlete with an assumed 1.25 to 1 pacing split:
What is very apparent is that when running near your limit rather than taking things easy it becomes far more critical to get pacing right. This means going out too fast or too slow compared to your eventually average finishing speed could significantly increase the overall Carbohydrate requirements and with it risks of missing your targets. While taking it easier you should fine mistakes in pacing far less critical.
Looking at the MFO data we see a very similar picture, with the additional carbs being almost identical to that of those more efficient at burning fat:
The relationship between Muscle Fatigue and Carb usageIn sport science literature/studies muscle fatigue has been linked to production of Reactive Oxygen Species (ROS) that are believed to cause damage, especially muscle cell membranes. ROS are particularly created during high intensity exercise, but also during pre-longed lower intensity exercise. In the book "The Art and Science of Low Carb Performance" the authors go as far as suggesting it's metabolism of Carbohydrates that creates the most damaging levels of ROS and that this may explain why low Carb athletes report quicker recovery times times after training and races.
If this is indeed the case then it's not difficult to conclude that not only does even pacing reducing Carbohydrate needs in training and racing, but also reduces the ROS production and associated muscle damage. As both muscle fatigue and glycogen depletion are amongst the biggest contributors to struggling to maintain pace towards the ends of races it suggests that even pacing and minimizing additional Carb costs is double important.
The goal of minimizing the accumulation of muscle fatigue looks to largely consistent with the goal of minimizing Carb usage, I would be inclined to go further and suggest that adopting a more conservative splits in the first half of race will result in less muscle damage so that you can continue the second half running in more comfort and with it more strongly and efficiently.
Applying these findings to race pacingLooking at splits of Ultramarathon it's clear that it's very rare indeed for any athlete to run a negative split i.e. run faster in the second half than the second. Analysis of race results show a broad correlation between faster athletes running more even splits but still even the elites do positive splits. However, even within the elites there is huge variation between individuals. Does this mean all the above analysis is somehow wrong?
From the point of view of carb sparing and reducing muscle fatigue the ideal is an even split, with a increasing cost of diverging from this. It is however extremely difficult to run a perfectly paced race, so I wouldn't worry if you don't achieve it, no one does. When deciding of race pace I'd advise you look at splits of previous races and adopt splits ratios of the runners that achieve the most even splits and finish strongest. Even if you are middle or back of the pack runner adopting splits that get nearer to the ideal of even splits will spare Carbohydrates and reduce the accumulation of muscle fatigue. It's also crucial that you are realistic about your finishing time, as great splits on paper can be terrible splits for a runner who can't keep the the pace up.
To summarize all this analysis into one sentence:
Start easy, run with even intensity, finish strong, recovery quickly.