Key running statistics – Part 1

Below is a list of key statistics about running derived from a number of sources, but mainly the Big Running Project’s survey, which canvased the opinions of 2,700 runners on their running practices, motivations and attitudes. Follow the links on selected items for more detail.

Section 1 – running demographics
Participation ratesSocial classGender balanceGeography (England)

Section 2 – motivations for running
Gender differencesSocial motivation and ageDifferent forms of runningCompetitiveness over the running careerCompetitiveness in lifelong women runners

Section 3 – Time and money
Who runs most? –  Spending by race preferenceSpending by motive

Section 4 – Runners and body image
Gender differences Body types and body satisfaction Body descriptor frequencies

Running Statistics

1. Participation rates

After swimming, running is the most popular participation sport in England and almost certainly the UK. Extrapolating from Sport England’s data, around 2.5 million people run at least once per week across the UK.

The chart below shows the percentage of English people (aged 16 years+) participating in a selection of sports between 2006 and 2016. Note that ‘road cycling’ is only a part of the total cycling population, which cumulatively amounts to 4.4%, slightly behind running.

Chart adapted from Sport England’ Active People Interactive.

[More on running demographics]

2. Running is largely an elite sport.

My own analysis of data from Sport England’s Active People Survey, 2016.

One of the most surprising of running statistics – at least to non-runners – is that despite the fact that running is perhaps the cheapest and most accessible of sports, requiring no special equipment or facilities, it has a distinctly middle-class participant base.

This figure shows the percentage of participants in a range of sports who come from high status ‘white collar’ occupations in blue, with the percentage from working-class backgrounds in orange. Intermediate socioeconomic groups are not portrayed.

Note that running has a higher proportion of white collar participants than golf, tennis and mountaineering – all sports that demand high levels of financial investment. The only outdoor sport with a higher proportion of white collar participants is the traditionally elite sport of sailing.

3. Overall, running has a fairly equal gender balance.

Compared to most other sports, running has a fairly even balance of male and female participants. This hasn’t always been the case, with men predominant until the early 2000s, when increasing numbers of women started to take up the sport*.

The chart below shows the mean age and the gender ratio of a range of sports, with the red lines representing the mean for the whole sample. Sports to the right of the vertical red line have more male participants, and those to the left have more female. Note that almost all sports are dominated by the young (all but golf and Pilates appear below the horizontal mean age line).

My own analysis of data from Sport England’s Active People Survey, 2016.

* See Breedveld, K. Scheerder, J. and Borgers, J. 2015. Running Across Europe: The Way Forward. In Running Across Europe. J. Scheerder, K. Breedveld and J Borgers, eds. Basingstoke: Palgrave Macmillan.

4. Running: It’s a North-South thing… a bit.

Running statistics, particularly participation rates, are often related to geography. An analysis by English region shows that the highest levels of participation are in the south, and the lowest in the north.

Chart adapted from Sport England’ Active People Interactive

In 2008, Sports Scotland reported participation rates of around 5%, which suggests Scotland might buck the trend of a falloff in participation further north.

It’s possible that this overall pattern is linked to the classed nature of running discussed in point 3, with a greater proportion of white-collar workers living in the south than in the north.

5. Gender differences in motivation

There is a clear difference between the kinds of motivations men and women prioritise in descriptions of their reasons for running. Men emphasise competitive goals, whereas women focus on goals around self-care. These include those relating to losing weight and improving their appearance and those relating to emotional wellbeing.

This table shows a selection of motivations along with the percentage of men and women who rate them as highly important to them. Those highlighted green and yellow have statistically significant differences between gender (‘get fit’ is pale green because of its lower statistical confidence level).

‘Very important’ motivations for male and female runners. Data from Big Running Survey.

6. Only social motivation increases with age.

Overall, strong motivations for running are reported less frequently amongst older runners than the young.

The only motivation that bucks this trend is socialising with other runners. As the chart shows, after teenage years this motivation drops off, only to become more important as runners age.

Data from the Big Running Survey.

7. Motives vary by form of running

Running is a diverse sport, with variants such as track athletics, fell-running and obstacle course racing attracting quite different crowds. One of the ways these runners vary is in their motivations for taking part.

This chart shows the percentage of runners from a range of forms of the sport that report a high level of selected motivations.

Data from Big Running Survey.

8. Competitiveness increases with experience – especially for women.

On average, women runners have a significantly lower level of competitive motivation than men. However, this gap narrow substantially if we look at more experienced runners. As the chart shows, whilst men’s motivation levels change little over time, women’s are much higher for those who have spent at least a couple of years involved in the sport.

Data from Big Running Survey.


9. Women who have run since childhood are just as competitive as similar men.

Another factor mitigating the finding that overall, women runners are less competitive than men, is engagement since childhood. Here we find that women who regard themselves as having been runners since they were at school are at least as competitive as their male equivalents.

Data from Big Running Survey.

This chart shows the mean competitiveness motivation score (out of 4) for male and female runners who have run since childhood, ran competitively as children then had a break before starting again as adults (hiatus), and those who only started running regularly as adults. There is a much greater difference between childhood runners and adult starters for women; and lifelong female runners score marginally higher than similar males.


10. Most frequent runners are mostly young, competitive and male

Seriously committed runners who run more than seven times per week are, at 39 years of age on average, three years younger than the average runner in the Big Running Survey, and 8 years younger that the least committed.

They are also more likely to be men than women. In fact, the proportion of male runners who run this often (3.3%) is four times that of female runners (0.8%).

Figure 10: Data from Big Running Survey

The running statistic illustrated in figure 10 is the percentage of very frequent runners who express a strong level of six types of motivation (blue bars). The orange lines represent the same statistics for the whole sample (i.e. all runners). We can see that highly frequent runners are much more likely to be competitive than other runners, and much less likely to be interested in improving their appearances or losing weight.

11. Ultra runners spend the most

Figure 11 shows the percentage of runners who participate in different kinds of race who spend at least £500 per year (silver) and at least £1000 per year (gold) on running. Clearly (given the low score for ‘none’) involvement in any form of racing is related to an increased spend, but there is significant variation in the amount of money different types of racer invest in the sport.

Out in front by some margin are the ultra distance runners. Almost half of this group report spending at least £500 per year on running, including 21% who report spending over £1000.

Figure 11: Data from Big Running Survey


12. Competitive runners spend most, appearance focused runners spend least

In figure 12 we look at spend again, this time comparing groups by their ‘very important’ motives for running. And again we’re looking at the percentage from each group who spend over £500 (silver) and over £1000 (gold).

Figure 12: Data from Big Running Survey

Once again we see the strong relationship between racing and spend, with those strongly motivated to do well in races spending the most on running. At the other end of the scale, runners motivated strongly by losing weight are the lowest spending group here, with less than half the proportion of high spenders as found amongst the more competitively minded.


13. Gender differences in runners’ body satisfaction?

We asked people to rate how happy they felt about their body shape on a scale of 1 to 7. There was a marked difference between the mean scores for men, who averaged a score of 4.8 and women who averaged 4.3.

Figure 13: Data from Big Running Survey

Figure 13 shows mean body satisfaction by gender, but divides the data in groups based on perceived talent. The two lines suggest a strong relationship between running self-confidence and body satisfaction that is quite similar for men and women.

This seems to suggest that women’s self-perceptions are systematically less positive and their self-confidence is lower compared to men across multiple domains.

14. Body image by body description

The descriptors that runners attach to their bodies have a strong relationship with how satisfied they feel with their bodies overall.

Figure 14: Data from Big Running Survey

Unsurprisingly, as shown in figure 14, both male and female runners are happiest with bodies that look like idealised runners’ bodies – slim, athletic and lean. Not only are these types of bodies the ones most associated with success in the sport, but they also fit closely with wider cultural body ideals.

15. Body descriptor frequency varies by gender

Men and women runners vary in how likely they are to self-describe using certain body attributes. This is not true across the board however, with many descriptors used roughly as often by both genders.

Figure 15 shows the percentage of male and female runners who selected a range of body descriptors. For many, the rates for men and women are close to equal. But a number stand out as particularly different.

Interestingly, men are much more likely to identify as ‘tall’, with 37% seeing themselves as such compared to 23% for women. A similar proportion of women, on the other hand, see themselves as short, at 34% compared to 17% of men.

Taken at face value, this is odd. In theory, an equal percentage of people should see themselves as short and tall. Possibly people judge themselves short or tall compared to the population as a whole, not just to people of their gender.

Figure 15: Data from the Big Running Survey

You can explore more running statistics in part 2.

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