Running Economy: What It Is and How to Improve It

What exactly is running economy?

Running economy describes the oxygen cost of running at a given submaximal speed. Two runners can share an identical VO2max yet differ substantially in how much oxygen each consumes at, say, 15 km/h. The one who uses less is the more economical, and over a race that efficiency compounds into a real time difference. Saunders et al. (2004) defined running economy in exactly these terms and grouped its influences into training, environmental, physiological, biomechanical and anthropometric factors.

Barnes and Kilding (2015) extend this picture, framing economy as an integrated composite of metabolic, cardiorespiratory, biomechanical and neuromuscular characteristics that are unique to each individual. That individuality matters. As Barnes and Kilding (2015) caution, a change that makes one runner more economical can make another less so. Running economy is therefore best understood not as a single lever but as the summed output of many systems working together at a set pace.

Why does running economy matter for performance?

Among trained distance runners, VO2max tends to cluster within a fairly narrow band, so it stops being the trait that separates them. Saunders et al. (2004) argued that in this population running economy becomes a key determinant of performance precisely because maximal oxygen uptake alone no longer discriminates between athletes. If two runners have the same aerobic ceiling, the one who spends less oxygen at race pace has more headroom to work with.

This is why economy is worth training deliberately rather than treating it as a fixed gift. The practical implication is that a runner who cannot easily raise VO2max further may still improve race times by lowering the oxygen cost of their pace. It is worth being honest about scale, though: the documented improvements from targeted training are typically a few percent, not transformative. Small, however, is not trivial over a 10 km or marathon, where a few percent can move a finishing time meaningfully.

Does strength training improve running economy?

This is one of the better-supported interventions. Blagrove et al. (2018) reviewed strength training added to normal endurance work and concluded it improves both running economy and time-trial performance in trained middle- and long-distance runners, chiefly through neuromuscular adaptations, and without harming VO2max or adding body mass. Denadai et al. (2017), pooling 20 effects from 16 studies, found heavy weight training improved economy by around 3.7 percent, with longer programmes producing the largest gains.

The effect is not uniform across every pace, however. Llanos-Lagos et al. (2024), a meta-analysis of 31 studies and 652 runners, reported that high-load strength training produced small improvements across roughly 8.6 to 17.9 km/h, while submaximal-load and isometric training showed no significant overall benefit. In other words, the method matters: heavy, low-repetition lifting has the most consistent support, whereas lighter resistance work is not reliably economical. Fears about lifting adding bulk or blunting aerobic fitness are not borne out in these trained-runner samples.

What about plyometrics and explosive training?

Explosive and plyometric work also has good evidence behind it. Paavolainen et al. (1999) had well-trained runners replace about a third of their endurance volume with explosive-strength training for nine weeks; 5 km time, running economy and 20 m sprint speed all improved while VO2max stayed flat, pointing to neuromuscular rather than aerobic gains. Denadai et al. (2017) put the average economy improvement from explosive or plyometric training at around 4.8 percent.

The benefit appears speed-dependent. Saunders et al. (2006) found nine weeks of added plyometrics improved economy at 18 km/h by 4.1 percent but not at 14 or 16 km/h in highly trained runners. Llanos-Lagos et al. (2024) similarly reported plyometrics helped mainly at speeds at or below 12 km/h, with combined methods giving moderate gains at intermediate speeds. The takeaway is that explosive work reliably helps, but where on the pace range it helps depends on how it is applied, so matching the stimulus to your target pace is sensible.

Can changing your running technique help?

Technique is more nuanced and the evidence more cautious. Moore (2016) reviewed the modifiable biomechanical factors linked to better economy and identified a preferred, or up to 3 percent shorter, stride length; lower vertical oscillation; greater leg stiffness; a low lower-limb moment of inertia; a maintained arm swing; and low coactivation between opposing muscles. These are the mechanical signatures associated with running more cheaply.

The important qualification is that Moore (2016) concluded an economical technique is largely self-optimised rather than universally prescribable. Runners tend to gravitate towards a stride that suits their own structure, and forcing a wholesale change to match some ideal can just as easily raise the oxygen cost. This aligns with the individuality point from Barnes and Kilding (2015). Rather than overhauling form, the evidence supports subtle work, such as trimming an overly long stride slightly or improving lower-limb stiffness through the strength and plyometric routes already described, which change mechanics indirectly.

Does altitude training improve running economy?

Altitude is usually discussed in terms of red-blood-cell and haemoglobin changes, but it may also touch economy directly. Saunders et al. (2004), in a separate study of elite distance runners, found that 20 nights of live-high train-low using simulated moderate altitude improved submaximal running economy by around 3.3 percent compared with controls. Notably, this effect was not explained by changes in ventilation or fuel use, which suggests altitude can nudge economy independently of any rise in haemoglobin mass.

This is a single controlled study in elite athletes, so it should be read as a promising signal rather than a settled prescription. The mechanism behind the economy change is not fully worked out, and the practicalities of live-high train-low, whether via real altitude or simulation, put it out of reach for most recreational runners. For the average athlete, the strength and plyometric routes remain the more accessible and better-replicated ways to improve economy.

How should a runner actually train for economy?

The evidence points to a fairly clear hierarchy. Heavy resistance training and explosive or plyometric work are the two interventions with the most consistent support, each improving economy by roughly 3 to 5 percent in controlled trials (Denadai et al., 2017; Blagrove et al., 2018). Both work mainly through neuromuscular adaptation and, in trained runners, do so without adding mass or reducing VO2max. Longer programmes tended to yield the larger gains.

Match the method to your pace: high-load lifting helps across a broad range, while plyometrics favour slower to moderate speeds and specific plyometric gains can appear only at faster paces (Llanos-Lagos et al., 2024; Saunders et al., 2006). Keep two caveats in view. First, individuality is real, so monitor your own response rather than assuming a group average applies to you (Barnes and Kilding, 2015). Second, the gains are modest in size, so treat this as a supplement to consistent aerobic training, not a replacement for it.

What is running economy in simple terms?

Running economy is how much oxygen you use to hold a given pace. A more economical runner burns less oxygen at the same speed, so they can either sustain that pace for longer or run faster at the same effort. Saunders et al. (2004) defined it as the submaximal oxygen cost of running at a set velocity, and it is a key performance factor among runners with similar VO2max.

How much can you realistically improve running economy?

Controlled trials suggest a few percent. Denadai et al. (2017) reported roughly 3.7 percent from heavy weight training and 4.8 percent from explosive or plyometric work, with longer programmes producing larger gains. These improvements are modest but meaningful over race distances, where a few percent can shift a finishing time noticeably. They supplement, rather than replace, consistent aerobic training.

Is strength training or plyometrics better for running economy?

Both work, and the best choice partly depends on your pace. Llanos-Lagos et al. (2024) found high-load strength training improved economy across a broad speed range, while plyometrics helped mainly at speeds at or below 12 km/h. Saunders et al. (2006) saw a plyometric benefit only at 18 km/h. A combination is reasonable; match the emphasis to your target pace and monitor your own response.

Will strength training make me slower or heavier?

The evidence in trained runners says no. Blagrove et al. (2018) concluded that strength training improves running economy and time-trial performance mainly through neuromuscular adaptations, without harming VO2max or increasing body mass. The gains come from producing force more efficiently, not from added muscle bulk. This holds when heavy, low-repetition lifting is added alongside normal endurance training rather than replacing it wholesale.

Should I change my running form to run more economically?

Cautiously. Moore (2016) linked better economy to features like a preferred or slightly shorter stride, lower vertical oscillation and greater leg stiffness, but concluded that economical technique is largely self-optimised rather than universally prescribable. Forcing a major form change can raise your oxygen cost. Subtle adjustments and improving stiffness indirectly through strength and plyometric work are safer than a wholesale overhaul.

Does altitude training improve running economy?

It may, though evidence is limited. Saunders et al. (2004) found that 20 nights of simulated moderate-altitude live-high train-low improved submaximal running economy by around 3.3 percent in elite runners, an effect not explained by ventilation or fuel-use changes. This is a single study in elite athletes and the mechanism is not fully understood, so treat it as a promising signal rather than a proven method for most runners.