Pa:hr or the “decouple” compares your pace relative to your heart rate, so you can see when you begin to tire. For example, if your heart rate stays the same as your pace goes down, you’re becoming fatigued. The point at which the two metrics decouple and the rate at which they do so can tell you a lot about an athlete.
As a coach I start with pa:hr to gauge longer efforts, workouts, and pieces of workouts to determine how fit my athletes are, as well as to gauge how well they paced themselves in an effort. Here are three distinct situations I look for as a coach for valuable insights into my athletes.
Positive Correlation and Divergent Line
If an athlete is early on in a training cycle, you will likely see high positive correlations in their first few interval sessions, as well as their first few longer zone 2 efforts. A positive correlative value means that an athlete has a higher cost for a given pace, that is, that their heart rate will increase dramatically as their pace increases.
Furthermore, in the picture above you can see that when pace declined, the athlete maintained a high heart rate over time. This can tell us a few things 1) environmental factors (heat or humidity) played a role and athlete couldn’t cool themselves effectively, resulting in a decrease of pace as the heart continued to work hard 2) Hydration was a secondary factor to Factor #1 3) there is a significant hill on this course and pace naturally decreased while output stayed the same or 4) the athlete is simply not yet efficient at that pace for that duration.
It’s worth noting that when looking at pa:hr over hills, Training Peaks is utilizing NGP vs. Average pace for pa:hr calculations, so look closely at your data when comparing flat intervals and hill intervals.
How to use: I always look for the point of divergence to see what it has to tell me. If factors 1-3 aren’t significantly present, then I use this as a baseline note for future workouts. For example, if an athlete becomes inefficient (greater than 5% decouple) at xx:xx time, I will structure their workouts to push out that divergence point further and further.
Efficient or Flat Line
A flat line is a great thing to see when analyzing a workout, especially if this is a longer tempo or a sustained effort. I consider a flat or efficient line to be 0-5% and will assess intervals and long efforts in roughly the same manner. A flat line tells me that an athlete is running efficiently for the given pace.
A flat line may not seem like a big piece of decision making data but it does tell you that your athlete can maintain efficiency, whether it’s incidental or throughout a specific interval. This gives you good cause as a coach to increase that pace goal or heart rate goal until you start to see a divergence late in the interval or run.
How to use:
A flat line is a point of permission to increase a pace or heart rate value. You want athletes to have a little bit of stress, especially late in an interval or set of intervals. A very flat line shows a good balance of stress and rest, but may not ultimately correlate to the increasing ramp rate you’re looking for.
Negative Correlation / Convergent Line
A negative value can be perplexing for athletes; seeing pace increase while heart rate decreases seems impossible! The most common explanation is that the athlete is running downhill and they are fit enough to control heart rate and relax—in other words, their pace is increasing while heart rate is decreasing.
Despite the fact that there is a significant metabolic cost for running downhill, it can be very difficult to run downhill with an equivalent heart rate to your climbing effort.
How to use:
Most often athletes running downhill will show a negative correlation between pace and heart rate, so unless we are looking for specific information in the downhill, this is usually not the most important data point to validate against.
However, it’s worth looking for a trend in recovery values. A plummeting heart rate during, say, a jog between intervals, would tell us that the athlete is very fit and recovering well between efforts. This can ultimately help you structure more effective workouts. Did that recovery point move higher and higher throughout the workout? Did the athlete’s recovery point maintain? You can use these data points to determine the effectiveness of the workout against subjective comments from the athlete.
These three facets of pa:hr are the first place I look to determine how well a workout was executed, and how prepared the athlete is to move into a new phase of training. Understanding them can give you great insight into your own performance, and help you make informed decisions about your training.
