The Supershoe Revolution Continues. Here’s What the Latest Research Says.
Scientists consider the latest spikes, individual variability, and the pros and cons of training in racing shoes
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Earlier this month, thousands of sports scientists gathered in Denver for the American College of Sports Medicine’s annual mega-conference. In more than 1,500 presentations, they offered a peek at new and forthcoming data on the science of health and performance. In the coming days, I’m going to share a few highlights, starting with the latest findings on running shoes: how they work, what to train in, and how to pick the best model for you.
Finally, Some Data on Super Spikes
Back in 2021, I wrote about the new generation of track spikes, which like the now-ubiquitous road running supershoes combine a stiff plate with a layer of ultralight and resilient cushioning. Anecdotal evidence strongly suggested that the new spikes were indeed faster than older versions, but no one had yet quantified the effect.
A group led by Dustin Joubert of St. Edward’s University in Austin (and formerly of Stephen F. Austin State University) decided to fill this gap. They recruited 11 distance runners to come to the lab and test seven different shoes: three road supershoes, one traditional racing flat, two track super spikes, and one traditional track spike. For each shoe, they tested running economy—a measure of how much oxygen is consumed to sustain a given pace—on two occasions, at 6:00 mile pace for the men and 6:53 pace for the women.
The main result (which, for the record, has not yet undergone peer review as a conference presentation) was that the super spikes improved running economy by about 2 percent compared to the traditional spike. On average, each runner’s best spike was roughly equivalent to their best road shoe: the added cushioning in the road shoes seems to make up for their extra weight. Heavily cushioned road shoes with stack height of greater than 25 millimeters are banned for track races in international competition, Joubert and his colleagues point out, but permitted in high school and college racing.
What does a 2 percent improvement in economy translate to? I asked Geoff Burns, a physiologist with the U.S. Olympic and Paralympic Committee and co-author of Joubert’s study, to run some numbers for me. The calculations are trickier at track-running speeds than they are for marathoners (for reasons explained here), but a reasonable estimate is that improving your running economy by 1 percent will increase your racing speed by about two-thirds of a percent. So a typical 4:00.0 miler in the old spikes might expect to run 3:56.8 in the new ones—“corrected for inflation,” as Burns puts it.
There was one other wrinkle in the data, which was individual variation. In seven of the 11 subjects, the difference in running economy between their best road shoe and their best spike was greater than 0.5 percent, which is substantial. Which was better? It was the road shoe for four of them and the spike for three of them—which brings us to the next abstract.
Picking the Best Shoe for You
When Canadian Olympic runner Malindi Elmore was weighing sponsorship decisions in 2020, she headed to a local university to test her running economy in different shoe brands. The data helped her settle on Saucony, but that’s not a practical option for most of us. Joubert and his team, including Garrett Oehlert and Eric Jones, decided to test a DIY approach to comparing shoes, using a commercially available Stryd running power meter.
The concept of running power can be complicated, but in essence the Stryd meter attempts to provide a real-time estimate of how much energy you’re burning—much like the running economy tests you get in the lab. In theory, then, if you run in two shoes at the same pace, and one requires 200 watts of power while the other requires 195 watts, you’d opt for the shoe that requires the least power.
Joubert and his team tested ten collegiate runners in three supershoes and one traditional shoe, using their metabolic equipment to measure oxygen consumption (from which you can calculate running economy) while also using Stryd to measure power. The group average data showed that running power could indeed successfully differentiate between the better and worse shoes—but in the opposite direction from what you’d naively expect. The shoes with the best lab-measured running economy produced the highest power readings, and vice versa.
To understand why this happened, you have to consider the difference between metabolic power (the rate at which you’re burning energy inside the body) and mechanical power (the rate at which you’re doing work on the external world). Power meters assume there’s a constant relationship between metabolic and mechanical power: the harder you work, the proportionally faster you go. But changing shoes alters this relationship. The whole point of supershoes is that, for a given level of metabolic power, you’re able to produce more mechanical power.
Burns suggests an analogy: it’s like adding a little motor to your bike. You were pedaling at 200 watts; then you switch on a motor that adds 5 watts of propulsion. Now the power meter on your bike wheel reads 205 watts. You’re not working harder, so the higher power reading is a good thing. Supershoes don’t have a motor, of course, but the plate and foam enable them to store and release a little more energy with each stride, adding some power as measured by Stryd’s accelerometers and other motion sensors.
All this sounds great: if you try on a shoe and get a higher power reading at a given pace, it’s probably helping you. Unfortunately, that’s only for the group average data. The individual data was much more variable, with weaker correlations between running power and running economy. It’s hard to know exactly why that is, because running power algorithms are complex and confidential. Joubert told me that they see similar trends using the Garmin’s power calculations (based on data from a chest-strap heart-rate monitor). That offers some reassurance that the Stryd data isn’t affected by, say, exactly where the shoe pod is placed.
Maybe subsequent research will figure out a more reliable way of comparing shoes. For now, if you see substantial and consistent differences in running power, then the shoe with the higher power is probably the best bet. But for subtle differences, take the data with a grain of salt.
Choosing a Shoe to Train In
There’s no longer any doubt that supershoes are faster in competition. But there’s still ongoing debate about whether it makes sense to train in them. Perhaps they reduce muscle damage, speed up recovery, and enable you to rack up more miles at a faster pace, as some internal Nike data has suggested. Or perhaps they raise your risk of injury and weaken your muscles, as others have argued.
Justin Matties and Michael Rowley of California State University East Bay presented some intriguing pilot data on this topic at the ACSM meeting. They assigned eight collegiate runners to spend eight weeks doing their interval workouts and tempo runs in either the Nike Victory Waffle 5, which is a traditional lightweight racing flat, or the Nike Vaporfly Next% 2, which is a supershoe. The shoes were provided by Nike. Before and after the training period, the runners did a series of biomechanical and physiological tests, including measuring their running economy.
Bear in mind that this just pilot data. In fact, thanks to drop-outs, the flats group ended up with just two subjects, compared to six in the supershoes group, which makes the results highly speculative. Matties is planning to run a much larger study starting this fall. Still, the results are thought-provoking. The supershoe group improved their running economy by 1.0 percent on average; the flats group improved by 5.6 percent. That’s a huge difference, especially since these were experienced runners, for whom you wouldn’t expect to see such dramatic improvements. My guess is that the differences won’t be as stark once the experiment is run in a larger group. But even if the flats group improves by 2 or 3 percent, that would still be a big finding.
There was also a shoe-specific effect. Those who trained in supershoes saw a greater improvement when tested in supershoes (1.1 percent) compared to flats (0.8 percent). Conversely, those who trained in flats saw a bigger boost when tested in flats (5.8 percent) compared to supershoes (5.4 percent). That’s worth noting, but the effect is dwarfed by the difference in what shoes they trained in. Based on this data, I’d rather train in a flat regardless of what shoe I planned to race in.
It’s not quite that simple, though. Matties told me that the flats group suffered more muscle soreness and foot discomfort, which has always been the argument against doing too much training in ultralight flats or spikes. For now, I wouldn’t base any training decisions on this very preliminary data point. But consider it a reminder that the debate about training in supershoes is still very much in play, and there will be more data to come.
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