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Talking about training and adaptation is weird because you can often see different patterns based on your perspective. So many variables are interacting that it’s really hard to isolate what’s causation, what’s correlation, what’s a confounding variable and what’s bias confirmation.
I like to frame it in terms of constellations. Looking up at the same night sky, some people will see a bull. Some will see dippers of various sizes. And some will see random, massive balls of gas that are chaotically scattered light years away. All of them are right depending on where and how you look.
The perspective-dependent relationship between training inputs and outputs is why real-world application drives most training approaches. As coach and physical therapist Joe Uhan said recently on Twitter: “Practice drives theory.” He said that in the context of studies on biomechanical changes and running economy/injuries that indicate athletes should probably not modify their form. His point is that there can be an issue of time horizon and isolating variables in these types of studies. Anecdotally, I have seen his stride coaching and similar approaches make a big positive difference for some athletes.
The perspective-dependent relationship between training inputs and outputs is why real-world application drives most training approaches. As coach and physical therapist Joe Uhan said recently on Twitter: “Practice drives theory.”
Let’s think about these issues in terms of a hypothetical study on rest days. Here are 3 possible study designs:
Group 1 takes a rest day each week; Group 2 does not; for a six-week study period. Which group gets faster?
Most likely, Group 2 gets faster. They are getting a bit of aerobic development, plus a blood-volume boost, maybe even tickling some epigenetic responses specific to daily training. This is probably the type of study you’d see in a lab setting given the manageable time horizon.
Same design, but for a six-month study period. Which group gets faster?
Now the waters are a bit murkier, but I’d guess that it’s heavily variable based on individuals and training history. Aerobic development may start to reach marginal-gains territory for some of the athletes; injuries may play a bigger role. You could probably think of a hundred other things that factor in. Are any participants listening to Ludacris when they run? That group would definitely get faster.
Same design, but for a six-year study period. Which group gets faster?
I’d argue that the rest-day group has an advantage here across the athletic population (with plenty of exceptions). Yes, the obvious things matter, like injuries and burnout and Luda raps. But where I think the rubber really hits the road involves long-term adaptation processes over many training cycles.
My hypothesis is that if you’re maxing out the stress and adaptation equation, it’s possible to push up against your present-day limits in a way that curtails longer-term growth, particularly in athletes that are not yet close to their absolute genetic potential (think Kosgei or Kipchoge). In the example above, rest days are a proxy for giving your body and brain space to relax and reset from stress, rather than the absolute necessity of fully resting for 24 to 48 hours. So maybe there are confounding variables in my hypothetical. I’m a buzzkill even in my imagination.
Where do long-term breakthroughs come from? I’d argue that sustained training at 100 percent is not usually the way to do it.
Think of it this way: pushing to 100 percent of maximum stress levels in each training cycle is likely optimal short-term as long as an athlete stays healthy and motivated, much like the hypothetical Study 1 above. But how can you compound gains to reach previously unthinkable levels? Where do long-term breakthroughs come from? I’d argue that sustained training at 100 percent is not usually the way to do it.
First, long-term training is largely about improving running economy, which often requires that an athlete feels pretty good.
Stress is good because it can lead to adaptation. But push just a bit too far, and hard training can improve the ability to withstand fatigue rather than cause the same output to take less energy. Undercooking it slightly can create a physiological context is more efficient and uses less energy, supporting year-over-year growth long after the ability to withstand fatigue gets maxed out.
Two, going just a bit too far in stress (accidentally hitting 105 percent) can lead to long-term regression.
Again, lots of these issues are weakly understood, but whether it comes from the nervous system or musculoskeletal system, there are plenty of stories of athletes peaking, stagnating and regressing over multi-year cycles without much of an obvious explanation. Like rock stars, runners can burn brightly and burn out. There’s a reason Kid Rock never became Adult Rock.
Three, it leaves little room for developing training over time.
When we are talking about year-over-year growth to reach new levels, usually that requires faster running with the same energy consumption, often fueled by increases in volume or intensity. Taking your time with that process allows the body to catch up to its physiological potential, since theoretically your 100 percent will involve a higher capacity and economy given time. Instead of 80 semi-inefficient weekly miles now, give me 40 efficient miles now, 60 next year, then maybe 80 later on. The same logic can apply to a pro doing 120 miles per week rather than 150. What it means for each athlete varies a ton.
There are some athletes who can push training to the max for sustained progress. That is amazing, indicative of inspirational mental toughness and strength. Often, that group can include pro athletes since they are partially selected for that ability. Sometimes, though, I think we overemphasize the outliers. If you throw 100 eggs at the wall, some might not break. And those unbreakable eggs may wonder why every other egg doesn’t also go full speed into the wall. For every major success story from massive sustained training, there is often a lot of yolk and eggshells lying around that no one talks about.
I see that progress over many years share a few things in common. They take some down time, they eat lots, they focus on overall health (everything from sex drive to biomarkers to making time for sleep, even if it means fewer miles). In other words, they keep training at 85 percent most of the time, with purposeful, periodic pulses to 100 percent when training for big events.
So let’s zoom back to the start of the article and Uhan’s comment: practice drives theory. What elements of practice are most instructive? I like to think about athletes that progress over multiple years or age groups (and love the process along the way).
This could all be bias confirmation, but many of the athletes I see that progress over many years share a few things in common. They take some down time, they eat lots, they focus on overall health (everything from sex drive to biomarkers to making time for sleep, even if it means fewer miles). In other words, they keep training at 85 percent most of the time, with purposeful, periodic pulses to 100 percent when training for big events.
So what does that wall of text mean for your training? If you’re a very resilient egg, you can stop reading, since this might not apply to you. For everyone else, there are six lessons.
One: Don’t worry too much about the weekly mileage number.
The body doesn’t know miles; it knows stress. Chasing chronic stress in terms of weekly miles is part of training, but it’s not all of it. 2020 winner of the Bandera 100K Drew Holmen did ~50 to 70 miles per week, Kathryn Drew did ~50 miles per week before finishing top-10 at Western States, John Kelly did ~50 miles per week for a few months before winning the 268-mile Spine Race.
Big mileage can be great as a byproduct of smart training, but rarely should it be the main goal. Prioritize the little things like strength training and cross training too.
Two: Have most workouts be build-up stresses, rather than break-down stresses.
There is a time and place for very hard, all-out workouts, but most should be manageable. Smooth and sustainable now lets those all-out efforts be breakthroughs later. That’s partially why the sexiest Strava files in training sometimes precede disappointing races.
Three: Eat enough food always.
Long-term growth requires a healthy hormone balance and consistent rebuild cycles. It’s all about finding your strong.
Four: Take down time even in peak training.
Rest days are the adaptation insurance, making sure your body always has the space to grow over time. If you’re consistent and do the work, you can reach your potential whether you run six days a week or seven days a week, and failing to rest could set some athletes back. Depending on your background and physiology, that might entail anywhere from a couple rest days a week to a couple every month or two.
Five: Down weeks and months are OK.
Breakthroughs are often preceded by setbacks, likely for the same reasons discussed above. Give the body a little bit of space under 100 percent, and it can respond with growth to new levels later. Plan those steps back if you can, rather than relying on injuries or stressful life circumstances. But if it comes from injuries or sickness, that can actually be a long-term blessing as well, so don’t sweat some forced time off either. The same goes for pregnancy preceding breakthroughs for some athletes.
Six: Push your absolute limits, but in moderation to chase new levels.
Training all-out at 100 percent still matters. Go for it with massive volume and workouts, chase your biggest dreams in training as if you’re loading up a plate at the Golden Corral buffet. But the body can adapt to those stimuli in moderation. That could mean one or two really big weeks, or even a massive training cycle. Just try to avoid pushing without letting up, or often the body will make you let up.
All of this is subject to debate and there is no universal answer. I am connecting my own dots in the sky to see the patterns that I am prone to seeing. But I think that most of the time for long-term growth, being 20 percent too cautious is better than being 2 percent too aggressive.
In training, step up to the edge of your limits. Then consider taking a couple steps back to admire the view.