This is something I wrote a while back, but recent questions I’ve received tell me it’s time to reprint it.
High performance runners are typically very efficient. You can observe this just by watching them run: there is no apparent wasted energy. They look very graceful. For cars we simply measure miles per gallon (or kilometers per liter) to determine efficiency. It is much the same for runners (or athletes in any sport). A runner’s efficiency can actually be determined in a physiology lab by measuring how much oxygen they use to produce a given submaximal running speed. Oxygen consumption is a good indicator of how much stored energy, in the form of fat and carbohydrate, was used to produce that run speed. As oxygen consumption rises, more energy is being burned. A middle-of-the-pack, age group runner will typically require much more energy to produce the same speed as a world class runner. So the age grouper is less efficient—and that could also be demonstrated in the lab.
Efficiency is therefore a very good way of gauging how fit a runner is, especially aerobic fitness. The problem is that measuring efficiency in a lab is not only inconvenient, it’s also expensive. Well, there happens to be another way of measuring efficiency that doesn’t require a lab and can be done with common, everyday training technology. On the TrainingPeaks website it’s called the Efficiency Factor (EF). By measuring your EF for submaximal, aerobic runs you can gauge your fitness on a daily basis and compare trends over time. If your EF is rising then you are becoming more efficient and therefore more aerobically fit. TrainingPeaks automatically does this analysis for you after a run is posted. All you do is open your workout and look at the data.
All it takes is a speed-and-distance device—a runner’s GPS—and a heart rate monitor. (We can do the same sort of thing for cycling with a power meter and a heart rate monitor.) The GPS device tells you how fast you were running—your performance. And, of course, the monitor reports what your average heart rate was for the run. While heart rate doesn’t tell us anything about performance, it is a good indicator of effort. Effort is just another way of saying the cost of the run. Knowing both performance and cost we essentially know your efficiency for a run. So with these two devices, and with TrainingPeaks as a post-workout analysis tool, you have your own “lab.”
So how is it that heart rate is an indicator of cost? We know that as the speed of your run increases, more energy is required and your heart rate rises accordingly to supply oxygen to the working muscles in order to produce the energy. The energy you burn and heart rate during a run therefore follow the same trend–they both rise when you speed up and drop as you slow down. When the energy required to run increases, heart rate also increases. As you become more efficient (we call this “fitness”) the energy cost of running decreases along with a decreased heart rate.
TrainingPeaks calculates EF by dividing your speed of running by the heart rate required to produce that speed. If the run was done on a flat course or a track this is a pretty simple process. But if there were hills, the changes in speed must be taken into consideration. That brings us to something TrainingPeaks calls Normalized Graded Pace (NGP). The GPS knows when you are on a hill, either going up or down. It also knows how steep the hill is. Therefore it can calculate what your speed would have been had you instead been running on flat terrain. That adjustment is the NGP for your run. It will typically show up in the post-run analysis as being faster than your average pace for the run. (In cycling Normalized Power–NP–is divided by heart rate to determine EF.)
Following the workout, and once data is uploaded, TrainingPeaks knows both your NGP and your average heart rate. It converts NGP to a Normalized Graded Speed (NGS—yards or meters per minute) and then divides that result by average heart rate. That produces EF.
Here’s an example to show you what’s going on inside of TrainingPeaks after you’ve uploaded a run workout in which the NGP was an average 7 minutes and 30 seconds per mile and the average heart rate was 150.
NGP = 7.5 min per mile
NGS = 60÷7.5
NGS = 8 mph
Yards/Minute = 234.7 (1760 yards x 8 ÷60)
Avg HR = 150
EF = 234.7 ÷150
EF = 1.56
Whew! That’s a lot of math. Good thing that the software does all of that for you. (Before TrainingPeaks added EF to the Analysis page I did this with a calculator for the athletes I coached.)
Now by comparing the EF for similar workouts over time you can gauge how your aerobic fitness and efficiency are changing. As the EF rises, aerobic fitness is improving. As it falls, aerobic fitness is decreasing. Of course, the workouts you’re comparing should be similar, meaning the course and terrain were about the same as well as the weather, your effort and a number of other elements that typically affect heart rate such as caffeine, lifestyle stress, altitude and more.
EF can also be used to measure portions of a workout, such as intervals or a long, steady hill you run up frequently. All you have to do on TrainingPeaks is use your mouse to highlight the section of the run you want data on and there is your EF along with the other details for that segment.
One of the best workouts for applying the EF concept is a workout I call the aerobic threshold (AeT) run. Warm-up and then run for a standard duration, such as 30 minutes, on a standard course while keeping your heart rate 28 to 32 bpm below your lactate/anaerobic threshold heart rate (also sometimes called the Functional Threshold Heart Rate). This is roughly your aerobic threshold. By recording your EF for that workout portion and repeating this workout frequently you will be able to determine your aerobic fitness progress. As with other markers of fitness it changes with training loads. (The same workout can be done on a bike for cyclists.)
Paying close attention to your EF over the course of several weeks is an easy way to measure your fitness improvement with field tests. It’s also much less expensive than going to a physiology lab every time you want to know.