Andrew Hamilton explains the concept of critical power, and explores recent research on using it for monitoring race fitness and event pacing
Measurement is an integral part of modern science and is considered a hallmark of scientific enterprise. In short, without measurement, getting a handle on the real world and manipulating it to human advantage becomes nigh on impossible. And so it is in sports science. Athletes put lots of hours into hard training in order to try and build higher levels of fitness and performance, and need to be confident that their efforts are paying off. This of course requires measurement and monitoring of fitness levels, which then begs the question: how can an athlete be sure that the fitness measure they are monitoring will relate closely to their performance in a competitive environment?
Fitness monitoring
Unless you’re an elite athlete with regular access to sports scientists and laboratory facilities, it’s not always easy to monitor your progress - other than to see how you actually perform under race conditions. And even if you are lucky enough to have the opportunity of undergoing professional monitoring, how do you know that higher scores in the many tests you may undergo (for example, your maximum oxygen uptake, blood lactate level at a given power output or your respiratory compensation point) will automatically mean better race times?
In a professional setting, fitness monitoring will typically involve measurement of a wide range of these parameters. But for amateur athletes, with limited time and resources, what’s desirable is some kind of straightforward testing procedure that accurately and reliably reflects changes in fitness over a period of time. The use of heart rate, power outputs and lactate monitoring to determine fitness changes can all help to paint a picture. However, some research has indicated that there may be a better (and quicker) method of keeping tabs on your likely race performance using a concept known as ‘critical power’ (see figure 1).
Importance of power
Critical power (figure 1) refers to a certain power output above which metabolic changes begin to take place that renders that power output to become unsustainable. In other words, critical power is the marker separating power outputs that can be sustained (where physiological measures such as blood lactate, oxygen uptake, blood pH remain stable) and higher power outputs, where these measures become unstable, and exercise intolerance occurs.
Figure 1: Understanding critical power
The area to the right of the critical power asymptote but under the curve represents the amount of work (in joules) above critical power that can be done before exhaustion sets in. In figure 1, the grey shaded box shows how much work can be performed at 440 watts with a critical power of 320 watts (curvature constant W’). For this subject, the duration is around 150 seconds, giving a total work capacity of 66,000 joules (66kJ) before fatigue sets in. It’s important to understand that every athlete has a unique critical power curve, which has to be constructed from their own individual exercise tests.
How quickly does exercise intolerance set in once an athlete exceeds critical power? This is a topic that has been well researched, and scientists have observed that there is a hyperbolic relationship between power output and the time for which it can be sustained
(1,2). Looking at the curve in figure 1 above, you can see that when power outputs greatly exceed critical power, the time before exercise tolerance sets in is comparatively short. By contrast, when power output only slightly exceeds critical power, athletes can work for much longer before exercise intolerance occurs. In the example above, exercise duration at 510 watts is only 100 seconds (red lines) whereas at 350 watts, exercise duration before intolerance is 700 seconds (blue lines).
Critical power is typically established by having an athlete complete between three and five separate high-intensity exercise tests on different days, during which they are asked to sustain a fixed external power output for as long as possible – eg time trial conditions. These power outputs are selected to result in ‘exhaustion’ in a minimum of around 2 minutes up to a maximum of around 15 minutes. The subject’s precise ‘time to the limit of tolerance’ at each of these power outputs is then recorded. When power output is subsequently plotted against time, what is observed is that that the sustainable power output falls as exercise duration increases, eventually levelling off on the ‘critical power asymptote’. This is what we mean by ‘critical power’.
The 3-minute power test
Critical power testing offers more than academic interest – it may offer a predictive value too. One test that has become popular is a simple 3-minute ‘critical power’ test (actually this intensity is slightly above critical power as described above). This is basically the maximum average power you can maintain for a period of three minutes, and its advocates claim that it can yield a very good approximation to the fitness scores obtained by the more usual (and complex) lab testing. But is this true? Well, some research suggests that not only might this be true, but also that a critical power test could actually be a more relevant measure of fitness than other (more technical) modes of testing. In particular, a landmark study carried out by British scientists from the University of Exeter seemed to show that a 3-minute critical power test was even better at predicting race performance than some of the more common tests performed in the sports science lab
(3).
In this study, the researchers wanted to see how reliable the scores obtained in a 3-minute critical power test were for predicting the 10-mile time trial performance of ten well-trained, club-level cyclists. To do this, the cyclists first of all performed a 3-minute all-out critical power test to familiarise themselves with the procedure. In this test, they had to sustain the highest possible pace they could for three minutes after which their average power over the three minutes was recorded. After they had fully recovered, they underwent a second critical power test, an incremental test to exhaustion during which a number of physiological measurements of fitness were made, and a 10-mile time trial on the road. The researchers then analysed the results to see which of the measurements best predicted the time trial performance.
Predictive power of critical power
The results showed that the critical power test was the strongest predictor of time trial performance with a correlation score of -0.83 (on a scale of 0.00 to -1.00, a score of -1.00 would mean perfect correlation between two measurements whereas a score of 0.00 would mean there’s absolutely no correlation). The peak power obtained in the incremental test to exhaustion was also a fairly good predictor of time trial performance, scoring -0.75. However, the respiratory compensation point (the point at which breathing becomes laboured) at -0.68 was less good at predicting time trial performance, while the measure of maximum oxygen uptake (also known as VO2max and often considered as the gold standard for aerobic fitness measurement) was even less effective, scoring just -0.60!
If all this talk of correlation sounds like gobbledygook then don’t worry; the take-home message of this study for cyclists is that when it comes to assessing your race/time-trial fitness, you don’t need to worry about fancy or expensive laboratory testing. If you have access to a stationary bike that can measure your average power output (or a road bike equipped with a proper power meter), you can simply climb aboard and pedal flat out for three minutes and record your average power. If this figure rises over time, there’s every likelihood that your race or time trial performances will too. If it plateaus or drops, then it’s time to go back to the drawing board and reassess your training plan.
Exactly the same principles apply to rowers with access to a rowing ergo, while runners can achieve a good approximation by running flat out on a treadmill for three minutes and logging the distance covered; if this distance rises, it’s an indication that your race performance will likely improve too. Runners can also calculate their critical speed (the runner’s equivalent of critical power in cycling) by simply dividing the distance covered by the time taken. For example, a 5-minute test in which a runner covers 1.5kms would yield a critical speed of 1.5kms divided by one twelfth of an hour, which = 18.0kmh.
Critical power and pacing of long events
Performing critical power tests (or tests above critical power) can do more than just show how your race fitness is progressing. Research suggests it can be useful for determining pacing during longer events too. In another study carried out by UK scientists at the University of Exeter, researchers used maximum effort data from shorter races (with durations in the 2-15 minute range) to construct critical speed curves for a dozen or so world-class marathoners
(4). They then examined the best marathon times for these marathon runners and calculated how close to critical speed the runners ran during those marathons (see table 1).
Table 1: Marathon times and % of critical speed used
Column 1 = critical speed. Column 2 = each runner’s critical speed curve. Column 5 = % of a runner’s critical speed used in the race
The key finding of this analysis was that, on average, these elite athletes completed the marathon distance at 96±2% of their critical speed. This consistency in % of critical speed is remarkable for a number of reasons:
- *When constructing the critical speed curves, different race distances were necessarily used for each athlete, with some athletes not having official personal best times for distances below 10 km.
- *Personal best times were run at different times in the athletes’ careers - often several years prior to their marathon best performances. This would be expected to introduce significant error into the critical speed estimates.
- *The use of critical speed/power curves has not traditionally been applied to longer distances such as the marathon. That’s because critical speed/power estimates are determined using personal best performances over shorter race distances while in a ‘fresh’ state. Long-duration, fatiguing exercise might be expected to skew the results and lead to a reduction in critical speed/power – most likely due to a reduction in running economy (efficiency) at these distances (as neurological fatigue sets in).
The researchers concluded that – in elite athletes at least - running around four percent below critical speed could be a good strategy for pacing during a long event such as the marathon. Whether this pacing strategy applies equally to amateur or recreational athletes remains to be tested. However, it is likely to be a good starting point. What we can say for sure is that frequent excursion to and above critical speed should be avoided – unless these occur in the final section of the race – for example a long sprint finish to the line!
References
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- 1988;31:1265–1279
- Eur J Sport Sci. 2014;14(3):217-23
- Sports Med. 2017; 47(Suppl 1): 65–78