Should experienced cyclists aim for particular cycling cadence or just let the legs decide what feels 'right'? Andrew Hamilton looks at the evidence
Once you get hooked on cycling, it’s only a matter of time before the subject of optimal pedaling cadence rears its head. It’s commonly said that learning to pedal ‘correctly’ –
ie spinning the cranks at the right speed - is not something that comes to most cyclists naturally, but is a skill that when perfected, can make you faster and more efficient. But just how true is this and if it is true, what’s the best pedaling cadence to use for maximum efficiency and speed?
Freely-chosen cadence
In one fascinating study by Swiss scientists, researchers tried to answer this exact question
(1). What the scientists set out to do was as follows:
- To observe the ‘freely-chosen’ cadence among cyclists under various cycling conditions - ie the pedaling rpm each cyclist maintained when he or she was instructed to just pedal at a speed that felt ‘right’ for them.
- Compare this freely-chosen cadence with the ‘optimal’ cadence – ie the pedalling rpm that produced the lowest blood lactate concentration at constant power output.
Why did they look at blood lactate concentration and use this to work out optimal cadence? Well, if lactate production is minimised, so is muscular fatigue, which means you can pedal for longer at that given power output and pedalling cadence – exactly what all cyclists need to do in a race or time-trial situation. In addition, the researchers wanted to try and find out if a change in the incline of the road and body position on the bike changed the freely chosen cadence or the optimal cadence.
To do this, freely chosen cadence, optimal cadence, blood lactate and maximum power were analysed under two different conditions: 1) cycling on level ground in a dropped position and 2) cycling uphill in an upright position. Seven experienced cyclists cycled under these two conditions on a cycling treadmill and measurements were made. The researchers were particularly keen to see if the cyclists instinctively chose a pedaling cadence close to optimum cadence regardless of the cycling condition. The also wanted to see if the cyclists’ freely chosen cadence and optimum cadence were lower when pedaling uphill as is often anecdotally observed.
Free choice is a good choice
The first main finding was that nearly all of the cyclists freely chose a cadence that was actually very close to the optimum cadence, regardless of whether they were cycling on the flat in a dropped position or more upright up an incline. Averaged over the group as a whole, the freely chosen cadence was 82.1rpm on the flat while the optimal cadence was measured at 89.3rpm (not significantly different in statistical terms). When the cyclists rode up an incline, the average freely chosen cadence dropped slightly to 81.5rpm, while the optimal cadence also dropped to 87.7rpm. Interestingly, the researchers found that the upright position adopted for tackling the incline helped produce around 2% more power at the freely chosen cadence.
Implications for cyclists
Many cyclists, even experienced cyclists, probably wonder about their pedaling technique –
ie am I pedaling too quickly/too slowly for my speed? But what this study seems to show is firstly that it’s definitely more advantageous to use a lower cadence and a more upright body position during uphill cycling. The bigger take-home message however is that provided you’re reasonably experienced in the saddle and not a relative beginner pushing a big gear, the spin speed that feels right for you probably
is right for you (or at least not too far off the mark)! Interestingly, this research also ties in with more recent research on running stride length
(2). This has established that allowing your brain to determine your stride length when running (ie not trying to artificially shorten or lengthen it)
always results in a more efficient running action – ie requiring less energy to maintain a given pace (you can
read this article here).
References
- Int J Sports Physiol Perform. 2012 Dec;7(4):375-81
- Int J Exerc Sci. 2017 May 1;10(3):446-453