When it comes to analysing performance between rides and seeing training progression, should you focus on Normalized Power or average power?

Triathlon training with a power meter opens up a wealth of on-the-bike metrics and post-ride analysis but choosing which to focus on can be tricky. One of the most important ways of judging your performance is to see how much power you can sustain for a given ride duration or distance. This helps you judge progression in training and set pacing targets for your triathlon events so you can run strong off the bike.

But should you concentrate on your average power or Normalized Power (NP)?

What Is Average Power?

Before we look at Normalized Power, let’s be clear on how average power works. Throughout a ride, average power is constantly calculated on your head unit. It’s simply the total power from your ride divided by the ride’s duration.

On the face of it, averaging sounds like a great way to work out the effort you’re putting in during a session and it can be useful when it comes to closely repeatable rides. For an indoor FTP test, steady, flat time trial or repeated loops of the same course, it works just fine.

AVERAGE POWER IS often not reflective of the intensity you feel during the ride

But there’s more of a problem when it comes to more varied outdoor riding over different routes – especially those with hills. That’s because average power includes all the recoveries between intervals or zero-watt downhills as well as the big-effort sets or leg-sapping climbs.

The result is a somewhat simplified figure that’s often not reflective of the actual intensity you feel during the ride. This makes it hard to compare your power session to session to see if you’re improving.

What Is Normalized Power?

Normalized Power is a metric developed by TrainingPeaks. You might have noticed NP sitting alongside average power in your post-ride data, whether in TrainingPeaks or another online training platform.

One of the things that puts athletes off Normalized Power is how much it varies compared to average power. Sometimes it tracks closely to your average, sometimes it seems disconcertingly off – usually higher. So, why is it worth paying attention to?

In short, Normalized Power gives you comparable data ride to ride and this makes it one of the most important figures in your power-meter training arsenal.

By using an algorithm described by Training Peaks as “a little complex”, NP compensates for the literal ups and downs of your ride to better reflect the overall effort you’ve put in. The idea is that the calculated figure is the power you could have maintained if the ride had been perfectly steady.

Normalized Power Vs Average Power

To compare the value of average and Normalized Power, let’s look at an example of a one-hour climb at your FTP followed by a freewheel back down the hill.

With average power, the huge exertion of the high-intensity climb is negated somewhat by all the zero power data recorded when freewheeling back down the hill. Your average will drop right down, so the data doesn’t really represent your effort.

On the other hand, NP is clever enough to know that you’ve been working hard and gives a figure that more accurately represents this.

Normalized Power makes it much easier to compare your performance from one ride to the next

It’s for this reason that TrainingPeaks uses NP rather than average power to calculate your Training Stress Score (TSS) – the overall stress put on your body – for every bike session.

So, using Normalized Power not only allows you to get a better sense of your training load but also makes it much easier to compare your performance from one ride to the next.

It’s especially useful when you’re tackling different courses, conditions and terrains. Seeing increases in NP for similar ride durations and perceived efforts signals improving strength and fitness without having to stick to the same boring route. This also allows you to hone your goal power for racing.

All this makes Normalized Power the winner when it comes to which metric you should be paying attention to for your triathlon cycling analysis.

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