A Lesson in Half Ironman Pacing

Half Pacing

One of the cool things about being a coach is getting data back from athletes and seeing that they have followed instructions perfectly and had great races. One of my athletes gave a master class in race execution at the Tauranga Half on the weekend – setting the fastest age group bike time (2.12) and winning his grade.

Happily he has given permission for me to use his files for the edification/education of all. If you’ve been wondering how power meters can add to your training/racing then this should be helpful.

The athlete under discussion is Justin Kerr, an experienced road cyclist (to the level of being a paralympic tandem pilot). My role in coaching JK is less about improving his aerobic capabilities and more about helping him apply his already high level of fitness to triathlon. He has a good grasp of training/racing with power so it’s easy for us to discuss training principles and pacing strategies.

For those of you not familiar with the WKO+ software – these are screenshots from that program (the pre-eminent cycling analysis system). Power is yellow, HR is red, Speed is blue and Cadence is Green.

Half Pacing
Power file from Tauranga Half
Half Pacing
Same data with 30s smoothing for clarity

I’ve added the dashed lines to show his average power and average HR (once it had settled down post swim).

Even if you’re not an experienced analyst it is immediately clear that the numbers are very consistent – no surges or weak patches.

Also obvious that his HR is high after the swim and takes a while to settle down into cycling rhythm. This shows one of the perils of HR based pacing – for the first half hour (for this athlete) it would have him going too easy while he tried to drop HR to the cycling target level.

Half Pacing
WKO+ Power stats

WKO+ has some very useful tools for further defining consistency and highlighting the keys to good half pacing. The image to the right is summary data from the file shown above. Much of it is self explanatory – Min/Max/Average speed, cadence, power etc.

The important stats for this discussion have been highlighted:

VI – Variability Index

The more surging and pace variation you have the higher this score will be. Naturally road races or hilly rides lead to variation and thus a higher VI score. For a flat ride like Tauranga getting as close to 1.00 (no variation) as possible is the ideal. A score of 1.01 is excellent – backing up the visual impression of consistency. A low VI is important because of its impact on TSS.

TSS – Training Stress Score

TSS is one of the key concepts in power based training. Instead of looking at distance or time to evaluate training load we use a metric that combines how hard you are working with how long you’re doing it for. It’s intuitively obvious that a 2hr hammer fest will have more impact on your body than a 3hr cruise and TSS is a method of quantifying that. You’ll see the (0.798) beside the TSS score – that is the IF (intensity factor) which is the average percentage of threshold. So this is an 80% effort, which is a good level for a half. The TSS score is made up of the average power, the VI and the duration.

So lower variation and lower time mean lower TSS. However, to get a short duration means higher power and thus higher TSS. So good Half Pacing strategy is about identifying the right balance to complete the bike in minimal time with an acceptable TSS score. For most people a score of less than 160 TSS optimises their chances to run well, so the 140 TSS here shows that JK struck the right balance between saving energy and going fast.

Pw:HR – Decoupling

HR and power are ‘coupled’ – that means you expect them to track together. A certain power means a certain HR and if you increase the power you expect the HR to rise too. Dependent variables would be another way of describing the relationship. Decoupling is when the relationship breaks down (‘it’s not you, it’s us’). The Pw:HR score tells us how far apart the two elements are moving.

The things that can lead to decoupling are dehydration – thicker blood means higher HR for the same power. Poor pacing – going out hard and fading will invariably yield a high decoupling score. Insufficient endurance – though this is hard to separate from pacing – if you don’t have the endurance to maintain a certain power level for the duration of your race then you’re setting too high a pace. But it is possible to have a target pace, lets say 80% intensity factor (as above), that is theoretically feasible for your event but you’ve not done the correct training and therefore can’t sustain it.

The decoupling score shown above is amazing – 0.05% suggests perfect pacing and going too easy. However, this is complicated by the swim. Running the numbers after the settling down period from the swim actually yields a decoupling score of 1.04% for the steady state period of the bike. Anything under 5% is good for a long triathlon so this is still great pacing and proves adequate hydration too.

The Run

There is no such thing as a well paced ride and explosion on the run. If you blow up on the run (and were well prepared for it) then you rode too hard. So JK running a 1.21 proves that the ride above was optimally paced.

Half Pacing
Run pace/HR Data

Many people can sustain higher HR on the run than on the bike and this is shown here – straight into target pace allows his HR plenty of time to reach equilibrium.

For running we use Pa:Hr (pace to heart rate) to evaluate decoupling. His score for the run was 4.7% – probably a consequence of the accumulated fatigue from swim and ride.

So while the run file shows that he paced well and was able to finish strongly – he was definitely feeling the effects of the length of the race.

We actually had a conversation to this effect when he ran past me (a short conversation as there was a significant pace difference) – he had ridden harder than at the Taupo half and was feeling the fatigue a bit more but was still able to move well.


Post Race

JK was part of the Massey Nutrition study and I’m hoping to be able to use the results from that study (once they’re sent out) to evaluate fuel intake vs burn rate. Ultimately pacing comes down to how fast you are burning stored and ingested fuel and I have various methods for assessing this too.

In the post race discussion JK noted that the advice I had given about other riders held true. He was surprised by the number of hangers on he acquired. I had warned that the risk of passing a lot of riders is that you then get tempted to surge to drop them but this is a negative for your own performance as you accumulate TSS and burn fuel faster by surging. So it is better to stick to your plan and wait for leeches to drop off.

Additionally we had discussed the need to set a target pace for the on-road segments of the run somewhat faster than overall target pace. The file above makes it clear how harmful the mount section is to average pace so if you have a target time in mind you must consider the impact of the off road segments.


Technology offers some powerful tools – using power and pace allowed me to set appropriate race targets and JK was able to execute them exactly. The tools themselves are only a feedback mechanism – not a magic bullet. There is still the need for intelligent racing by the athlete and smart planning from the coach.

As we work towards Ironman we’ll be monitoring decoupling in the long rides to make sure we can set an appropriate pace for raceday, as well as ensuring that we continue to improve power output for the target duration.

For those of you racing the 70.3 next weekend there are three main points to take from this:

  • Pacing – start at a pace you can maintain
  • Consistency – the steadier your effort is the less fatigue you will accumulate
  • Ride your own race – there will be a lot of people on the course – don’t waste energy on them




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