# Time Trial Pacing

#### Practical advice.

###### Originally published May 1, 2014

### Introduction

In a previous post I introduced VO_{2} kinetics, thus framing the rationale for the somewhat counterintuitive “priming” warm-up. With that in mind, in this post I’ll address the next logical consideration: **how to pace a time trial.**

*Just as a reminder: this discussion is written with respect to time trials of ~40 min, where it’s just the athlete against the clock. In addition to the physiology, “racing” must also take account of tactical considerations—therefore, the ideas presented below may not be applicable to those involved in head-to-head competition.*

### Pacing

Time trials are a complex beast. As a result, any research into pacing strategies will be naturally limited in scope. That is, the optimal pacing strategies for an 800m on the track and a 10km on the road will probably differ; hence, I’ve grouped some findings from the literature according to their practical application.

### Short Time Trials

**For time trials of roughly 2–8 min, performed under fairly stable conditions, a fast/“all-out” start seems to be advised**^{2,3,5,12}. There are a number of reasons for this:

- Maximum efforts of < 8 min will likely be performed at an intensity equal to (if not greater than) VO
_{2max}^{1}. The speed at which oxygen uptake (VO_{2}) rises in response to exercise is a function of the ‘error signal’ (*the difference between the current and “required” oxygen uptake*)^{2}.**Going out fast, therefore, will accelerate the initial VO**_{2}response, increasing the contribution of aerobic (or*oxidative*) pathways to energy demands^{2,4}. Given that the anaerobic capacity is inherently finite^{6}, increasing oxidative energy contribution should enhance performance, especially in events of shorter duration. A word of caution: athletes should quickly adopt a more sustainable pace following a fast start (which should last no more than a minute, ideally less) so as to avoid premature fatigue^{3}.

- By going fast out the blocks, you minimise the time spent accelerating. All the time
*not*spent at race pace represents a performance loss. Granted, the difference is fairly small, but this difference becomes increasingly significant in shorter events^{8}. - Any momentum that you carry over the finish line is effectively wasted energy
^{24}. Thus; a fast start followed by a slower finish will reduce energy “wastage”.

NB: in light of recent research, it does not appear that a fast-start strategy is able to accelerate *overall* VO_{2} kinetics following a priming warm-up. In other words, the effects of “priming” and fast-start pacing (both known to speed VO_{2} kinetics) do not seem to be additive^{18}.

### Longer Time Trials

Things become slightly more complicated when performance time exceeds ~8 min. Unfortunately, **systematic research in this area is lacking**, and the research that does exist reports conflicting results. For example:

- When the first 4 min of a 20km (cycling) TT were manipulated to produce either a fast-start (+15% of average power output) or a slow start (-15%), overall finish times were faster with a slow-start
^{9}. - In a design similar to the one above—
*only with the addition of heat stress*—20km TT performance was unaffected by fast- and slow-start strategies (compared to a self-paced baseline)^{10}. - When the first mile of a 5km (running) TT was manipulated to produce either a fast-start (+3% of average pace) or a
*faster*-start (+6%), performance on the whole was better with a faster-start^{11}.

The general consensus among many athletes is that an “even”/constant pacing strategy is advisable for longer events. Indeed, there is research to support this assertion, especially when external conditions are relatively stable^{8,19,20,22}. However, **one cannot overlook the pacing strategy that seems to pervade virtually all world records of this duration; that is, the parabolic pacing strategy**. This involves both a fast-start and a fast-finish, with a relatively slow midsection

^{8}.

**Such a strategy is associated with virtually all the track 5km and 10km world record performances dating back to 1921**

^{12}, and is consistently observed in other sports as well

^{13,17}. This pacing behaviour is similarly observed in sub-elite athletes, and to a greater extent in those who are more experienced/competitive

^{14}.

#### What is the Rationale Behind “Parabolic” Pacing?

- It has been suggested that our innate predisposition to go out fast is an
**evolved tendency**^{2}. This seems plausible, as we would not of had the luxury of measuring our efforts when trying to evade predators/catch prey. - If we assume there exists a maximum sustainable power/pace (= critical power or CP), and a very finite capacity to work above that “threshold” (termed W′), then optimum performance cannot be achieved if power/pace drops below this CP at any point
^{15}(i.e. you cannot ‘make up for lost time’). Therefore, one of the main strengths of parabolic pacing may be that it ensures athletes**a)**do not drop below CP and**b)**deplete the entirety of their W′.

**However**, not all athletes enjoy the stable external conditions of track runners, swimmers etc. For road cyclists particularly, and runners to some extent, time trials often involve tackling variable course conditions (i.e. wind & hills), so pacing should take account of this.

I’m sure this is a question many athletes have thought over at some point:

**When tackling a course that is hilly and/or windy do you…**

**a)** Try and maintain a constant effort/power—which would result in greater pace/speed fluctuations.

**b)** Try and maintain a constant pace/speed—which would then produce a more variable effort/power profile.

Based on mathematical modelling, the latter option seems to be advised^{20,21,23}. That is, performance should be enhanced by efforts to maintain a constant speed, for cyclists at least.

NB: The resultant changes in effort/power may only be tolerable in the range of about ±5%^{22}. For example, increasing power by 5% into a headwind (relative to the average), then decreasing it by 5% with a tailwind.

### Conclusions

I’ve described some general principles for pacing according to event duration but, as with all things, **there is rarely ever a ‘one size fits all’ answer**. The best advice will always be to experiment with different strategies in training. Just as with any scientific study: control for as many confounding variables as you can, collect data, analyse, and repeat.

### References

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