Improving Run Efficiency: What Research Tells Us

timclarkMetrics, Research

What is Run Efficiency?

If you study a slow-motion video of an elite distance runner they seem to bound-along effortlessly, exerting little effort to maintain speeds that mere mortals could hardly achieve sprinting flat-out!  Efficiency, in a general sense, implies doing something in the most efficient manner, i.e. wasting the least amount of resources.  Being able to run at a given speed with the least amount of effort is a desirable thing to do, and we would describe such runners as efficient.  However, scientifically, efficiency is defined as the useful work performed by a machine divided by the energy expended; as there is no useful work performed by a runner (ignoring running uphill or the small amount of work done against air resistance) all of us weekend runners have the same efficiency as the elite athlete– i.e. zero!

Instead of the term efficiency, scientists use the term running-economy, this is similar to the fuel economy of a car: a measure of the amount of fuel used to cover a specific distance.  To complicate things slightly, distance runners predominantly use two fuels: fat or carbohydrate, using more of the latter as effort increases.  Fat has a higher energy density, so we measure running economy as the distance moved at a given speed divided by the energy content of the fuel used, rather than the amount of fuel.  It has also been found that the energy usage of similarly trained athletes varies with weight, so we divide by weight (strictly mass), to produce a running economy figure measured in kcal per kg per kilometre that can be compared across athletes.

It has been shown that running economy is strongly related to running performance, a study from Italy in 1993 predicted that a 5% improvement in running economy would lead to a 3.8% reduction in time for a 5 km race, and another study from 1980 suggested that the majority of the variation in performance on a 10 km time trial was explained by running economy.

How do I improve my running economy? 

Now that we know what running economy is, and that it is an important factor for performance, the obvious question is how to improve it?  Unfortunately, research is contradictory about how much economy can be modified, or the best way to do it.

It has been found that runners with a longer history of training have better running economy, but it is unclear what the mechanism for this this change is, so it is hard to recommend specific training to maximise it.  In addition, economy has been found to fall with age, possibly due to a reduced ability to store and use elastic energy, so just getting older isn’t a good approach!

There are many potential influencers that affect running economy: weight, air resistance, muscle fibre type, nutrient metabolism to name a few. However, the period when the foot is in contact with the ground is the phase of running when almost all energy is expended, and also what is measureable with RunScribe, so that will be the focus of this article.

  • Contact time: The data on contact time (the length of time the foot is on the floor) are contradictory: some studies claim that shorter contact times lead to better economy, whilst others (including studies on other animal species) report that longer contact times produce better economy. A study of 14 sub-elite distance runners showed that economy improved as contact time got longer, and that mid-foot striking led to better economy than rear-foot, but also a produced a shorter contact time, which countered the benefits.  In contrast a Finnish study of 25 runners found that shorter ground contact time was the only variable that predicted better running economy.  In our own work we have seen mixed results, with shorter contact times predicting better economy in women, and no effect in men.  As both traditional resistance-based strength training and plyometric training have been shown to improve economy, probably by improving the ability to generate force quickly, reducing contact time by strength training is an approach that may be worth exploring.
  • Foot contact type: There has been a lot of recent publicity about barefoot and minimalist footwear, with suggestions that it leads to a more natural and efficient gait.  The actual data do not support this – in one study a group of 12 runners were given 8 weeks of gait retraining to use minimalist footwear. At the start of the training period 75% of participants ran with a rear-foot-strike when in conventional shoes, this reduced to 50% after training, but there was no change in running economy for the group.  Another study of 15 trained barefoot runners showed that there was no difference in economy between rear-foot and fore-foot striking.
  • Shoe type: In the first study mentioned above, there was a 2.7% improvement in running economy whilst wearing the minimalist shoes, in the second study there was a 2.4% improvement for forefoot running and a 3.3% reduction for rear-foot striking in minimalist shoe.  This is likely due to two effects, the lower mass of the shoes (see next section) and the fact that more elastic energy may be stored in the Achilles tendon and foot arches.  It should be noted that transitioning to minimalist shoes should be attempted cautiously to avoid injury.
  • Shoe mass and cushioning: Studies report a 1% decrease in running economy for every 100g extra shoe mass, so lower-mass shoes should help running economy, provided that there is sufficient cushioning – the cushioning hypothesis suggests that insufficient shoe cushioning requires the body to generate cushioning, with a consequent cost loss of economy.  In one study, well cushioned shoes improved economy by up to 2.8% over stiffer shoes of the same weight. In another study, it was found that 10mm of surface cushioning was better for running economy that no cushioning or 20mm of cushioning.
  • Cadence: Most runners naturally run at a cadence (frequency) that is close to optimal, and if this is changed to a mathematical optimal cadence, there is unlikely to be a significant change in running economy.  However, the same does not apply to novice runners, who typically run at too low a cadence, and may benefit from increasing their stride rate.


This has been a brief look at only a few of the factors that can affect running economy, it is clear that there is no one factor that is clearly associated with improved economy for all runners.  The reasons for this may be due to the huge variation in running styles, body size and muscle type between runners.  In order to improve economy, runners should personally experiment with these and other modifiable factors, using tools such as RunScribe to quantify changes and noting any positive or negative effects on running economy.

Dr. Ben Heller is a principal research fellow in the Centre for Sports Engineering Research (CSER) at Sheffield Hallam University where he works in rehabilitation and measurement and analysis of information for sports applications.