Riding with power has forever changed the way we train and perform, and nowadays most tri coaches and athletes who are serious about improving their cycling all use power meters. Power meters first came on the scene in the late 1980s/early 1990s in professional bike racing and although it took a while for them to catch on in triathlon, by the mid-2000s they were de rigueur in the pro triathlon ranks. Of course, there are now many different types of power meters on the market, but, at the end of your ride or race, they all produce similar data for analysis. But what do you do with this data? Are you maximizing it? We spoke to cycling coach Matt Bottrill, who works with pro triathletes such as Tim O’Donnell and Matt Hanson, to help us do a deeper dive on all things power.

What’s the first thing you look at when you open an athlete’s power file?
It depends on the ride really, but I will typically look at their Normalized Power (NP), the Intensity Factor (IF), and the Variability Index (VI). The NP is the estimate of the power the athlete could have sustained if their power output had been absolutely smooth throughout the ride. For example, if you ride steady-state for two hours, your average power and your NP are going to be fairly closely aligned, but if you do a two-hour ride with a lot of higher intensity intervals, you’ll find the athlete’s NP is a lot higher than their average power. All of this is important to factor into training stress and recovery. 

Next, I look at their IF score, which is an indication of how hard or difficult the ride was in relation to the athlete’s overall current fitness. The VI is a way to measure how smooth or variable the power output was during the ride.

If the ride was more endurance/aerobic-based, then I will also pay close attention to the EF score (Efficiency Factor). This is the ratio of Normalized Power (NP) to heart-rate. In running, you would look at the ratio of Normalized Graded Pace (NGP) to heart-rate. This helps assess the aerobic fitness of the athlete. We know that if heart-rate is rising while the intensity (power or pace) stays the same then the athlete is not operating efficiently and their aerobic capacity needs to be improved. It’s always good to compare ratios for similar workouts over a number of weeks to look for improvements in EF. (Note: the workouts and conditions need to be alike, though, for this to be a fair comparison). If you are making good aerobic progress then your EF will rise over the course of a few weeks.

Data aside, one of the most important things for a coach to look at is the athlete’s feedback/comments on how the workout went and how they felt. I really drill into all of my athletes that this is very important and I encourage them to leave as much feedback as possible. The numbers and data can only tell us so much! 

Which metrics and/or data points do you encourage your athletes to look at—in training and in racing?
In training, power, speed, and heart-rate are the key ones, as well as cadence. When it comes to racing, everything I do with my athletes is based around looking at the demands of the course, the profile of the athlete and their CDA (coefficient of aerodynamic drag). From this, we will have a pacing plan that optimizes speed, power, and aerodynamics. Ultimately, my goal is to get my athletes to ride their race with the lowest power and the best average speed. That’s the secret to unlocking their best run. 

As an athlete progresses and develops, how do all of these data points change? And do some become more important than others?
The plan is always to gain more power for a lower heart-rate—that way you know fitness is improving. Measuring EF over time is a good metric to consistently track to make sure the athlete is staying aerobically fit. With endurance athletes, I always monitor decoupling, especially going into a key event. This refers to the Pa:HR (power to heart-rate) ratio that you’ll see in TrainingPeaks. It compares the EF between the first half of your workout versus the second half, and, if you’re fit, there shouldn’t be too much variance. Going into a race like Kona, this becomes interesting to watch. You can have the best fitness in the world, but if you’ve not done your heat acclimation work then your power to heart-rate is going to go through the roof. 

Takeaways:

When it comes to reading power files and analyzing them, there’s no one piece of data that is key—in fact, they all play important parts in monitoring training and progression throughout the course of a season and over multiple seasons. Of course, it always depends on which phase of training you’re in and what you’re looking to build and develop in that phase, but learning to look at your NP (normalized power), your EF (efficiency factor), as well as your heart-rate, cadence, and speed are typically the most salient data points to monitor.

Having a clear assessment of your current fitness and how you’re looking to build that is equally important. Outlining key goals and using these data points to work towards them is the smartest, most intelligent approach. Remember, though, that the greatest gains and insights are made when you marry the objective data points (the metrics) alongside the athlete’s feedback (subjective comments).