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Is Coaching with Running Power Better Than Pace or HR?

BY Tom Epton

While cycling power has become the standard for performance measurement and management, running power technology is relatively new. Recent advancements by device makers have shed the early inconsistencies and opened up better ways to measure output for training protocols.

Power meters on bicycles have been commercially available since 1989, and due to this extensive history, a wealth of knowledge has been developed. Running power meters have been around for a fraction of that time, with wearable devices existing since about 2014, meaning that understanding these devices’ usefulness is much more limited. Here we will talk you through some ideas around running with power and discuss how you can use this relatively new metric to add another dimension of analysis to your athletes’ training. This blog will focus on how to interpret the data that your power meter collects and use that to make decisions in training and racing that will improve your athletes’ outcomes.

Defining Power for Training

The amount of power a runner can spend in any given period of time can be seen as a type of battery. As with cycling, different power numbers mean different things to different athletes. A larger athlete will need more power to run at the same relative intensity as a smaller athlete. Running power is not as simple as “more power = better.”

The formulas that go into running power have some similarities to cycling. In a controlled environment, coaches can use running power alongside other physiological testing and running economy to set training zones. On top of this, power can be used to analyze race performance and quantify the effects of tactical decisions.

One of the most useful applications of running power meters is measuring efficiency outside the lab. During key track sessions, for example, by analyzing an athlete’s power-to-speed ratio, we would look for changes over weeks or months of training. An athlete becomes more efficient if the power needed to run at a given speed decreases. This is a way to measure the success (or not) of interventions designed to help an athlete’s run form. If your athlete is not becoming more efficient, it’s likely time to reevaluate through testing and set a new course of training.

Power vs. Pace and Heart Rate

The main argument against bothering with running power meters is the question of what they can add that pace and heart rate don’t already tell us. Power meters directly measure ‘work done,’ so they tell us how much energy an athlete has expended for an effort.

An example from an athlete preparing for the elite aquathlon European Championships in Sept.  2023 shows how his power changed throughout some 1 km repetitions on the track. The track session was relatively light as it was close to race day, with a 3km tempo leading into 3 x 1km repetitions (with 90-sec rest) at ‘race pace.’ The total run volume was around 14km, and the session was about an hour in duration.

Running Power and Heart Rate Comparison graph
Running Power and Heart Rate Comparison

As you can see in the graph, their heart rate rose steadily during the first portion of the tempo, then settled around 178bpm (this athlete can maintain 180bpm for a three-hour road race on the bike, in general, his heart rate tends to sit relatively high). The power remained steady throughout the effort. This is an example where power could be used to prescribe training intensity over heart rate, as it doesn’t have a lag in effect like heart rate.

The statistics from the kilometer repetitions are as follows:

Rep 1: 3:04.59, 373W
Rep 2: 3:03.93, 375W
Rep 3: 3:03.94, 369W

From this, we can conclude that the athlete has muscular endurance and form that allows his power-to-speed ratio not to deteriorate too much under fatigue. Given that the power reduction didn’t appear to decrease pace, we can conclude no material loss in running economy under fatigue. If the running economy dropped, we would likely see power rising simultaneously. A runner who requires more power to reach the same speed is less efficient.

Analyzing Data: Cross-Country Activity

Running Power Xc Data Image1
Click the image to see the activity in TrainingPeaks.

Let’s break down a cross-country race that I completed. I ran this race at 74kg, with an average power of 360W for the 33 minutes it took to complete the 9.6km course. It was not flat, and there were some distinguishing features when broken down lap by lap.

The lap-by-lap power and heart rate fluctuations match much better than the lap-by-lap speed and heart rate fluctuations.

In cross-country, and often in hilly road races like the Boston Marathon or Ironman St. George run course, speed is less helpful in pacing an effort. This is where we must rely on heart rate, but there are many situations where this becomes unreliable, either environmental or sensor-related problems. Using a combination of power and heart rate to measure effort on a hilly course will often be superior to pace.

Power can be used where the terrain is slower for intervals.

Even though most of this run was in Zones 2 and 3 (aerobic and tempo), according to pace, it was clearly a much harder effort with a peak 30-minute heart rate of 192 bpm — around my threshold. This data was collected with a chest strap and was in line with other numbers seen throughout the cross-country season. This was a maximal effort, yet the pace doesn’t reflect that, while the heart rate does when it catches up after the first kilometer, and power reflects the effort from the start.

Shorter intervals are hard to do via pace, as GPS data is unreliable, especially on a short loop. Heart rate is a lagging indicator of effort, but power is instantaneous, which means shorter efforts can be prescribed with power ranges. The TrainingPeaks workout builder tool can structure run training sessions with power. This is especially useful for athletes who don’t have access to a track or don’t run on the track to avoid injury.

Wrist-based Power vs. Foot Pods

As with cycling, there are several ways we can measure power. Initially popularized by Stryd, running power was predominantly measured as a pod on the foot that interlocks with the laces. More recently, watch-based power meters have come to market. Many coaches will have had experience with some rather dubious watch-based heart rate numbers and might be skeptical of wrist-based power.

I have found that wrist-based power meters are sufficient in some use cases, but if you want ‘true’ values, a foot pod is ideal. Data from a foot pod has a high enough resolution to see differences in running efficiency from changing shoes. A foot pod is also required if you’re prescribing sessions by power or pacing a race. Watch-based data is good enough for roughly checking consistency across intervals, however.

Validation studies on any power measurement devices other than those made by Stryd currently need to be improved. In contrast, studies into the Stryd unit are comprehensive and numerous. These generally conclude that power data is accurate and consistent. In the next few years, we will likely see studies comparing units from other brands, such as Garmin and COROS, for now, the Stryd is the gold standard.

TIP: Running TSS Values Seem Off?

If you see TSS values for running workouts that are unrealistically high or low for the perceived effort or compared to recent similar workouts, your device may be recording running power, and you will need to adjust your zone settings accordingly. Many new devices have running power automatically turned on.


Run Tss Displayed in TrainingPeaks

Key Takeaways for Coaches

  • Power is the rate of energy usage per unit of time; the amount of power an athlete can expend over a period of time can be viewed as their ‘battery capacity.’
  • Power is an excellent tool for analyzing biomechanical efficiency outside of a lab, especially when pace data is accurate.
  • Power can help analyze performance and pace in contexts where pace is less reliable, especially when used in conjunction with heart rate and RPE.
  • Power can be used to prescribe workouts using the TrainingPeaks workout builder tool, but coaches must ensure their athlete has accurate and current thresholds through regular testing. This is even more important with running than cycling due to the greater injury risk.
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About Tom Epton

Tom Epton is a writer and data scientist based in the South East of England. He is a founding member and principal data scientist at PyTri Ltd, a consultancy specializing in applying data science techniques to performance sports and healthcare. Tom has a first-class BSc in Physics and has worked at several well-known brands on big data and machine learning projects. Away from work, he is an elite triathlete racing a mixture of draft-legal short courses on the British Super Series to middle-distance non-drafting triathlons. Tom also offers coaching, physiological testing and endurance sport consultancy services. Email him for more information.

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