A Data Analysis of the Dublin Marathon

Lessons Learned from 150,000 Dublin Marathon Runners


  • An analysis of 150,000 Dublin Marathon runners from 2000–2015.
  • The field is getting faster and older, but increasingly male dominated.
  • While men may be faster than women, women are more disciplined: they run a more consistent pace and they hit the wall far less often than men.


2016 is a special year for the 37th edition of Dublin City Marathon. It is Ireland’s 1916 centenary year and the marathon will mark it with a special commemorative finishers medal along with a shift from the bank holiday Monday to the Sunday for the first time. It seems to be working because the race is a sell-out with 19,500 runners, making it the largest in the event’s history, and the fourth largest marathon in Europe.

As it happens I’ve been looking at the data of the Dublin City Marathon for the last few months; just for fun you understand. Finisher results from the period 2000–2015 are readily available online, providing access to a treasure trove of data from numbers of participants, gender, age ranges, finish-times, and even the split-times for some years. All in all there are more than 150,000 finisher records and in what follows I will provide a brief summary of some of what I have found during the course of my analysis.

Who Runs the Marathon Anyway?

What sort of people are willing to put themselves through 26.2 miles of hurt, and the months of training that come before, not to mention the pain of injury or the agony of self-doubt that goes hand in hand with the marathon? Is the marathon just for the committed few? The life-long athletes? The over-achievers? Not so, it seems. When we look at the data we see all sorts of participants, young and old, male and female, fast and slow.

Certainly we are an enthusiastic bunch. The Dublin City Marathon has experienced a more or less sustained period of growth over the past 15 years. As shown below, the 7,000 or so finishers in the year 2000 almost doubled by 13,000 by 2015.

The total number of finishers per year alongside the percentage of females and older masters runners (over 40s).

While participant numbers have been growing, the last 15 years have been somewhat dominated by men. Overall the percentage of finishers who are female is about 32% and mostly falling. For instance, back in 2000 almost 46% of participants were women but by 2015 this had fallen to just 30%. That said since 2012 the percentage of women has been on the rise again.

It’s a different story when it comes to the age of participants. Overall, 57% of participants are under 40 years old (for the purpose of this article these are referred to as seniors), leaving 43% over 40 (we will refer to these as masters runners). But the proportion of older runners has been growing steadily since 2009. In 2000 only 40% of participants were over 40, but last year, for the first time, just over half of participants were over 40.

The releative percentage of runners (sub 4-hour finishers), joggers (4 to 6-hour finishers), and walkers (finishing in 6+ hours) by year.

The percentage of faster runners (those finishing within 4 hours) has also been increasing, from 25% of participants in 2000 to around 40% by 2015. Meanwhile the percentage of joggers (those finishing between 4 and 6 hours) has remained more or less constant at about 50%, while the percentage of walkers (6+ hours) has been steadily falling, from 25% in 2000 to less than 10% in 2015. Each year there are also about 30–50 elite athletes on show, with a 60/40 split between males and females.

The Fast and the Furious

The saying goes that its about finish-lines not finish-times, but still many of us are interested in getting to that finish-line as fast as we can. Below is a graph of the average finish-times for each year, measured across all participants. It also shows separate averages for men and women as well as for younger (the under 40's seniors) and older (over 40's masters) participants.

Average finish-times per year for gender and age.

On the face of it these results suggest a very significant improvement in finish-times, and not just overall, but for men and women, young and old. For example, in the year 2000 the average finish-time was 305 minutes but this improved to just over 255 minutes by 2015, a 50-minute speed-up. Way to go, Dublin!

It is also interesting to note how gender has a much greater influence on finish-times than age. For example, the difference between the finish-times of men and women varies from about 85 minutes (in 2000) to 30 minutes (in 2015); yes, women are getting faster relative to their male counterparts. By contrast, the difference in finish-times between senior (20–39 years old) and masters (40+) runners varies by only 10–15 minutes.

Certainly, an average finish-time improvement of 50 minutes is very significant. But it doesn’t quite tell the full story. For example, it could be due to participants getting faster but equally it could be due to a drop in the number of walkers or slower runners, or a mixture of both. To form a clearer picture of this, the figure below shows the distributions of finish-times for men and women for the 5-year periods from 2000–2004 (early) and 2011–2015 (recent).

The proportion of participants finishing for different finish times, comparing male and female participants during the period 2000–2004 (early) and 2011–2015 (recent).

Each individual graph shows the proportion of people who finish at different times. For example, we can see that the most common finish-time for recent (2011–2015) males (as indicated by the peak labeled as A) is 235 minutes and this is unchanged from the earlier period (2000–2004) for males. In fact both early and recent distributions for men are very similar. There are some most faster finishers recently, as indicated by the region labeled as E, and fewer slower finishers, compared to the early period, but the difference is modest.

The picture for women is quite different. During 2000–2004 there was a long-tail of slower walkers, as indicated by the region marked D; these are women with finish-times in the 6–9 hour range. By 2011–2015 these slower walkers had largely disappeared, only to be replaced by women with much faster finish-times. Indeed the most common finish-time in 2000–2004 for women (labeled C) was 280 minutes compared to 265 minutes during 2011–2015 (labelled as B), a 15 minute improvement. In addition, there are many more women finishing faster than this 265-minute mark in 2011–2015 when compared to 2000–2004.

Thus, the improvement in overall finish-times in recent years has been driven by two main effects. The more minor effect is about some modest gains by faster runners; this is more evident for women than for men. The major effect, however, has been the disappearance of slower female joggers/walkers. It is possible that these slower females from 2000–2004 have speeded-up in the period 2011–2015, but it seems more likely that slower participants have left the Dublin City Marathon behind as alternative events have become popular. This is supported by the fact that the percentage of females participating has been falling over the years and has not kept pace with male participation rates.

It’s the Pace that Kills!

Finish-time is not the only performance measure for marathon runners. How a runner’s speed or pace changes over the course of a race — their pace variation — is also of interest. Pace variation is often seen as an indicator of ability and, generally speaking, less variation in pace is considered to be a sign of a more disciplined and able runner.

The average percentage pace variation for males/females and seniors/masters by finish-time.
The pace variation between the first and second-half of the marathon for men vs. women and senior (under 40s) vs masters (over 40s) participatnts.

We can compare the pace of participants during the first and second half of the marathon to calculate the percentage of pace variation. The above graph shows how this pace variation changes among men and women, senior and masters runners, for increasing finish-times.

Clearly the degree of pace variation changes with finish-time, regardless of gender or age. The fastest runners exhibit very little difference between first and second-half pacing (<5%), but as finish-times increase so too does the degree of pace variation. By the 300-minute mark, the first and second-half pace of male runners varies by more than 20%, slightly higher for younger males and lower for older males. Beyond this finish-time, pace variation tends to fall again with slower joggers and walkers maintaining a more even pacing.

Interestingly, we see that for a given finish-time female participants present with a much lower degree of pace variation than their male counterparts. This suggests that female participants are more disciplined in their pacing overall. Likewise, beyond the 4-hour mark, older (masters) male runners are better at controlling their pace than their younger (senior) counterparts. A similar effect is observed for female runners although this age-related difference begins much later, after the 300-minute mark.

Thus, there is good support for the notion that pace variation goes hand in hand with ability — faster runners exhibit less pace variation than slower joggers — while older participants and female participants tend to be more disciplined than their male and younger counterparts.

Split Personalities

As we approach race-day most of us will start to think about our pacing strategy. Should we go all-out early to compensate for an expected slow-down in the second half? Or should we take it easy during the early stages and try to speed-up later? Or is it best to keep our pace as steady as possible, as the fastest runners do? The first of these strategies, going out fast and slowing in the second half of the race, is called a positive split. The second, starting slow and speeding up in the second half of the race is called a negative split. And the third, running more or less the same pace throughout is called an even split. So, what types of pacing strategies are at play in the Dublin City Marathon?

The percentage of participants adopting even, positive, and negative pacing strategies for increasing finish-times.
The percentage of different split-types by finish-time for male and female particpants.

In the above we graph the percentage of participants who perform positive, negative, and even splits based on their finish-times. Unsurprisingly, the majority of participants (approximately 75%) perform positive splits; their second-half is slower than their first half. A little less than 20% run negative splits, completing a faster second-half than first-half. And only about 5% manage to run an even split; note that for an even split the first and second-half times must vary by less than 1%.

Generally speaking, among faster runners there are more negative and even splits (and therefore fewer positive splits), when compared to slower participants. This is consistent with the prevailing wisdom that even and negative splits correlate with ability. As we move through the finish-times, from runners to joggers, the percentage of positive splits starts to grow, but then falls again as we move from joggers to walkers. For example, over 80% of joggers (those finishing after the 4-hour mark) will run a positive split.

Calculated over all participants, the average finish-times for even, negative, and positive splitters is 246, 261, and 266 minutes, respectively, suggesting that an even pacing strategy is correlated with faster finish-times whereas a positive pacing strategy is correlated with slower times. A word of caution however: correlation is not the same as causation and so it is unwise to conclude that forcing an even split, for example, will guarantee a better finish-time.

Between a Rock and a Hard Place

We have all heard of it and many of us will hit it at some point in our racing lives. I am talking about the dreaded wall. It’s the stuff of nightmares for a marathoner. One minute you are motoring along, hammering out the miles and feeling strong, and the next things start to rapidly fall apart. Your legs feel like concrete, your breathing becomes laboured. And the will to continue is no more.

When runners hit the wall or bonk (to use the more colourful language of running lore) they tend to do so after the 20-mile mark, but the literature remains somewhat undecided on the extent of the pace changes experienced. For some, pace can slow by 20–25% while others report slow-downs of 50% or even higher. The prevailing wisdom is that bonking is caused by the depletion of the glycogen stores in our liver and muscles — the primary sources of fuel for most marathon runners — and avoiding it requires dedicated training, a sensible pacing strategy and careful race nutrition.

While our race data doesn’t tell us directly whether someone actually hits the wall, we can make an educated guess by looking for participants who experience a significant slow-down in the second-half of their race. For our purposes we focus on participants who slow down by at least 30% in the second-half. For instance, we will consider a runner who runs the first-half at 6 minutes per km and then slows to 8 mins per km in the second-half (a 33% slow-down) to have bonked or hit the wall. But if this runner slows to only 7 minute per km (a 16% slow-down) we will not consider them to have hit the wall; they have slowed because they have fatigued but they have not bonked.

The percentage of participants who hit the wall as a function of finishing time.
The percentage of participants who hit the wall in the second-half of the race versus finish-time.

According to the data just under 5% of all participants bonk, but that is not the full story. The graph above charts the percentage of participants who bonk for different finish-times; as before we also show how this changes with gender and age. We can see how the tendency to hit the wall is strongly influenced by finish-time (and therefore ability). The fastest runners rarely hit the wall; the incidence of bonking among runners finishing within 3 hours is less than 1%. Beyond the 3-hour mark, however, things don’t look so good. 5% of 4-hour finishers hit the wall and for participants who finish between 5 and 6-hours almost 15% hit the wall.

But that’s not all. Once again gender appears to play a critical role, much more so than age. Male runners can be more than five times as likely to hit the wall than women, for some finish-times. For example, about 22% of 300-minute male finishers hit the wall while women with the same finish-time do so only 5% of the time. Likewise, (older) masters runners are less likely to hit the wall for a given finish-time than (younger) seniors; the wisdom of age?

As with pace variation, the incidence of bonking tends to fall again as we transition from joggers to walkers, ultimately dropping below 5%, for example, for those finishing around the 7-hour mark. These slower finishers are presumably under less extreme levels of exertion (notwithstanding their 7 hours on the course) and also have the time to re-fuel effectively during their race.

Gluttons for Punishment

There is something about marathon runners that makes us gluttons for punishment? The months of training and the 26.2 miles on the day are rough enough, but on top of that some of us will repeat the experience year after year.

In our Dublin City Marathon data we find that just over 15% of participants complete more than one marathon (at least, during the 2000–2015 period) and on average these repeaters complete an average of 3.34 marathons during this period. Men are twice as likely as women to be repeaters — over 18% of men ran multiple marathons compared to just over 9% of women — and these men ran 3.45 marathons on average compared to just 2.85 marathons for the women. Unsurprisingly, ability (in terms of finish-time), has a significant bearing on whether a participant is likely to repeat his or her marathon experience, with faster runners much more likely to be repeaters than slower runners.

Do these repeat marathoners enjoy any performance benefits? The graph below shows how finish-times and pacing tends to improve with the number of repeats. For example, average finish-times fall steadily up to about 4 repeats before stabilising somewhat. The average pace variation also decreases, with the number of repeats, indicating that more experienced marathoners are able to maintain a more consistent pace between the two-halves of the race.

We look at finish-times more closely below by comparing the distribution of finish-times for those running their first Dublin City Marathon (first-timers) to those who have run 6 or more marathons (experienced), so that we can get a better sense of where the speed-up comes from. We can see that the most common finish-time for experienced runners (label A) is 226 minutes, 12 minutes faster than the most common finish-time for the first-timers, 238 minutes indicated by B.

Moreover, there are many more slower runners (240–480 minutes) — the region marked C — among the first-timers. And there are many more experienced runners with faster finish-times in the sub-226 minute region (as indicated by D) compared to the first-timers. In other words, running more marathons does seem to have a beneficial impact on overall performance including pacing and speed.

The Road Ahead

For many, the marathon remains the ultimate race event and the Dublin City Marathon has been going from strength to strength as it continues to attract a diverse community of enthusiastic participants: men and women, young and old, fast and slow, first-timers and veterans. After analysing more than 150,000 Dublin City Marathon race results here is a quick summary of key findings and observations:

  • Participation has been growing strongly throughout the period, but the percentage of females continues to fall relative to males. It will be interesting to see whether the record 2016 participant numbers go any way to changing this.
  • Finish-times have been gradually improving, year by year, for men and women, young and old. Some of this is due to more faster runners but mostly it is due to fewer slower joggers and walkers, especially among females.
  • Gender has a larger effect on finish-times than age: men are faster on average than women and younger runners are faster than older runners, but not by as much. The speed-gap that separates the genders has been closing, minute by minute, year by year.
  • Even though women are slower than men, they are more disciplined. They exhibit less pace variation. They run fewer positive splits and more negative and even splits than their male counterparts. And they hit the wall less often; the same is true for older runners compared to younger runners although again the difference is less pronounced than for gender.
  • If you want to run a faster marathon then experience is important — repeat marathoners enjoy faster times and less pace variation — so keep trying but also control your pacing and try running even or negative splits instead of positive splits.

Good luck on October 30th!