The Primacy of the TT
If there is one thing that the Tour de France teaches us each and every year, is that it never, ever hurts to be a good time trialist if you want to aim for the GC. This year, after an incredibly exciting 18 stages of roller-coaster action, the Tour essentially came down to a mano-a-mano battle between Andy Schleck and Cadel Evans, and we all know who went in as the stronger TT rider and how that ended up.
Realistically, in the last 30 years of the Tour, Marco Pantani in 1998 and Pedro Delgado in 1988 were the only winners who could not be counted as a TT ace. That’s not just true for the Grand Tours, but for the week-long tours like the Tour de Suisse, where Levi Leipheimer took enough time out of Damiano Cunego in the final stage TT to take the GC by a mere 4 s.
And for amateur racers in weekend stage races (most often consisting of a road race, time trial, and criterium), guess which stage often creates the biggest time gaps and determines the winner? Looking through my own paltry stage racing palmares, my one noteworthy 3rd place on GC was built upon a 5th place in the TT along with pack finishes in the two road stages.
Brains over Pure Brawn
So it obviously pays to train yourself to be a strong TT rider. Not only will it help in actual TTs, but so many parts of a race, namely an attack or a bridging effort, is just a TT effort in disguise. Secondly, another important component is the willingness to suffer and pain threshold to keep that high effort going. Thirdly, there is the technical ability to ride the best lines and to negotiate the course as economically as possible without wasting power or speed. Go back again to this year’s Tour TT to see Cadel flying over speed bumps while Andy pounded over them, and also the difference in cornering ability to preserve as much speed as possible.
A fourth critical component of time trialing is proper pacing strategy, and this has been a recurring theme in my Toolbox writing. We’ve looked at it from the question of whether to go for an even versus negative (getting faster as the TT progresses) or an “all-out” (hammer hard out of the gates and then hang on for dear life) strategy.
There’s another layer to pacing strategy, and that’s in whether it is better to keep as constant a power as possible, or whether to ride a much more uneven power profile in the aim of keeping as constant a speed as possible. As anybody who has ridden with a power meter on an indoor trainer versus the real road knows, it’s very hard to actually keep a constant power profile on the road, due to even slight changes in gradient or wind. However, the basic question remains valid and important: Should I try to “attack” the hill with a higher power to try to keep my speed up, or should I try to keep a steady power?
Such a question has been extensively modeled mathematically in a number of studies, and also tested on a simulated course on CompuTrainers. However, somewhat surprisingly, this idea hasn’t really been scientifically tested out in an actual real-life riding situation. A new study by Cangley et al. (2011) from the UK sought to correct this deficiency:
Cangley et al. 2011
The design of the study was fairly straightforward while at the same time requiring some pretty complex mathematics:
• Twenty-one cyclists and regular TT riders were recruited. This is a nice improvement over the typical 10 subjects used in many physiology studies. The riders were all regular participants in local 16 km TTs.
• Subjects rode a 4 km course while maintaining a standardized bike position on their own bikes. This was done four times: twice in a “fixed power” and twice with a “variable power” strategy. Therefore, subjects acted as their own controls and comparisons. Wind speed was <5m/s and fairly constant throughout the experiment, as was traffic volume.
• The course profile was not a simple flat course, nor was it a “simulated” course with a single hill at a constant grade. Rather, it took place on a straight dual carriageway with essentially minimal flat stretches, a highly variable terrain with an average grade of 3%, and a peak of 9%. The start and finish were at the same elevation.
• In both constant and variable power conditions, the aim was to average 255 W throughout.
• It was recognized that it would be impossible for subjects to actually maintain a perfectly constant power throughout the time trial. Rather, the aim was to go for as constant a power as possible in those trials. Subjects wore an earpiece with a regular audio reminder for power at different parts of the course.
• For the variable power condition, a mathematical model was first used to construct an “optimal” power profile based on the course and an average power of 255W. Other parameters, such as maximal deviation from that average power (+/- 27%), were inputted into the model. From this, subjects had an audio program guiding them for “required” power for each 80 m segment of the time trial.
Rubber on the Road
The most important data first. The “constant power” strategy averaged 411 s to complete the 4 km, while the “variable power” profile averaged 399 s. The difference was statistically significant. This 2.9% difference would also have elevated the 10th place at the UK 10 mile championships to a 3rd place on the podium.
There are a number of important caveats and considerations in assessing the data and the conclusions:
• As expected, “constant power” still remained quite variable because of the difficulty in maintaining constant power with such a variable terrain. So if you were more successful at maintaining a constant power, the differences might become even greater. Indeed, the “constant power” strategy averaged 253W while the “variable power” strategy averaged 260W. NB. The above results were mathematically normalized to what they would be if the average was actually 255 in both conditions.
• This study was based mainly on the mechanics and physics of time trialing, rather than the physiology. The study did not test the subjects for their functional threshold power (FTP), nor did it individualize the average power goal. For example, the average power may have been well below their FTP, such that the 27% deviation above average power may not have really put them “into the red.”
• The conclusions here likely apply to many TTs on the road, where there generally are a lot of gradient changes. However, these strategies obviously do not apply to the velodrome, and likely not to an uphill TT where the climb is very steady.
In conclusion, I feel that the important messages from this study are that: 1) it is unrealistic to even try to maintain an even power profile to begin with unless the terrain is very constant, and 2) do not be afraid to attack the course and go beyond your threshold where strategically useful. This is where pre-riding the course, or simulating the course on a CompuTrainer, can be extremely useful. The other half of the equation is to couple this with knowing your own physiology and capabilities, in terms of understanding how hard and for how long you can sustain different efforts.
Ride safe and have fun!
Cangley P, Passfield L, Carter H, Bailey M (2011) The effect of variable gradients on pacing in cycling time-trials. Int J Sports Med 32: 132-136
Stephen Cheung is a Canada Research Chair at Brock University, and has published over 50 scientific articles and book chapters dealing with the effects of thermal and hypoxic stress on human physiology and performance. He has just published the book Advanced Environmental Exercise Physiology dealing with environments ranging from heat and cold through to hydration, altitude training, air pollution, and chronobiology. Stephen’s currently writing “Cutting Edge Cycling,” a book on the science of cycling due out April 2012, and can be reached for comments at firstname.lastname@example.org .