How hard was your workout, really? There’s a number for that

You just finished a long, hard bike ride. But how hard was it, exactly? That depends on what you measure: How far did you ride, and how fast? How hilly was the route, and what heart rate zones were you in?
In the 1970s, exercise physiologists came up with the concept of training load, which they believed could offer a fuller picture of the difficulty of a workout. Training load combines the intensity and duration of a workout into one number that’s meant to estimate the stress of a bout of exercise on the body.
By understanding how different kinds of workouts compare in terms of difficulty, the thinking went, athletes could better structure their training routines with the right mix of easy and hard days.
“It’s a brilliant concept,” said Carl Foster, a professor emeritus of exercise and sports science at the University of Wisconsin La-Crosse. For many competitive athletes, the idea is intuitive, he said. It can also be useful for the occasional exerciser who wants to get fitter.
Today, many fitness trackers and GPS watches, including those from Garmin and Coros and the most recent version of the Apple Watch, use algorithms to approximate training load and present that data alongside other stats like step count and heart rate.
While some fitness experts consider training load a useful way to gauge the effectiveness of an exercise routine, others warn that paying too much attention to a complex metric generated by an algorithm might distract you from listening to your body.
Here’s how to interpret your training load data with a critical eye.
Put simply, training load combines the length and intensity of a workout into one metric.
A harder workout will give you a higher training load number. For example, a long easy run will translate to a higher training load than a short easy run. If you up the intensity of that shorter run enough, it could produce a higher training load than the long one.
But defining the intensity of a workout can be surprisingly complicated, Dr Foster said. Today, most fitness trackers rely heavily on heart rate data to determine intensity, and they each have their own algorithms for calculating training load from there. (In the mid-1990s, Dr Foster proposed that “perceived exertion,” or how challenging a workout feels subjectively, could be simpler way to measure intensity and determine training load. That way, people can understand how hard they’re exercising “in a way they would communicate with their grandma,” he said.)
Because there’s no standardised way to calculate training load, and different trackers use different scales to express it, your stats from different trackers can vary significantly.
Garmin uses heart rate data to estimate “post-exercise oxygen consumption,” or EPOC. That measurement is meant to be a proxy for the question: “How big of an impact did that training session have on your body?” said Joe Heikes, a lead product manager at Garmin.
Coros bases intensity on heart rate or pace data – depending on the form of exercise – and rates the training load of a workout on a scale of low, medium and high.
The Apple Watch ranks the difficulty of a workout on a scale of 1 to 10, using inputs like your height, weight, exercise history and heart rate. But users can manually change the difficulty rating if it doesn’t match how they felt during the activity.
In addition to a single workout’s training load, most wearables also measure cumulative training load across a week. Those numbers can help you notice if you are ramping up too quickly. Your weekly and monthly training load should gradually – not dramatically – increase, said Darian Allberry, the head of user engagement at Coros.
For data die-hards and some athletes training for specific events, more is more.
But there’s a lot that training load does not calculate, and one number can’t tell the full story of a workout.
Some coaches, like James McKirdy, the founder and head coach of McKirdy Training, a coaching service in Flagstaff, Arizona, find the measurement unnecessary. Blindly following data from a fitness tracker, McKirdy said, can get in the way of evaluating what’s most important: How an athlete feels, and what they think they are capable of.
Chelsea Weis Passmore, a running coach in Philadelphia, echoed that sentiment. The algorithm on your fitness tracker also doesn’t know if you’re sick or taking an easy day, she added.
Both Passmore and McKirdy stressed that some amount of data – like weekly mileage totals or pace – can be helpful, as long as it’s considered in context.
Dr Foster stands by the measurement in concept, but said that you’re probably already – perhaps unknowingly – building your fitness plan based on training load. If you have a goal, you know that you can’t go all-out every day, and you can’t take it easy every day either.
A watch can tell you that, Dr Foster said, but, he added: “You can do it without a watch, because you’re smart.”
By Talya Minsberg © The New York Times Company
The article originally appeared in The New York Times.