Average half marathon time
Two sources put the men's average within 15 seconds of each other and the women's nearly 10 minutes apart. Runsy's synthesis, with every source and its sample printed.
The short answer, and the strange thing in it
Runsy's synthesis: the average half marathon finish time is around 1:59:40 for men and 2:19:13 for women. The one source publishing an overall figure gives a median of 2:14:59.
The men's figure is the most confidently sourced number anywhere on this site. Two studies, built from different samples and reporting different statistics — one a median, one an average converted from pace — land fifteen seconds apart at 1:59:48 and 1:59:33.
The women's figure from the same two studies is nine minutes and forty seconds apart. We do not have a confident explanation for the asymmetry, and rather than average it away quietly we are putting it at the top of the page. If you are a woman trying to work out whether your 2:18 is above or below average, the honest answer is that it lands squarely inside the range where the published sources cannot agree.
How we built the figure
There is no single dataset that reports finish-time distributions for road running. So instead of picking one number and calling it the average, we did this:
- Collected every published central figure we could trace to a named source with a stated sample size.
- Discarded anything we could not trace to its origin. A magazine quoting a statistic is not a source; we followed each figure back to the study that produced it, and dropped it when the trail went cold.
- Took the unweighted mean of the surviving figures. Unweighted, deliberately: the samples overlap heavily and are not independent, so weighting by sample size would just hand the answer to whichever study counted the most rows.
- Published the range as well as the midpoint. Where the sources disagree, the disagreement is the finding.
The result is Runsy's synthesis of published data. It is not a measurement, and we do not present it as one. It is the middle of what the published record actually says, with the edges shown.
Two things the arithmetic cannot fix
We are averaging means with medians. The percentile study reports a 50th percentile; the others report an average. Finish-time distributions have a long slow tail, so the mean sits later than the median. Mixing them widens our range and pulls the midpoint slightly late. We say so rather than quietly picking whichever suits.
Some figures are converted from a published pace, not a published time. Where a source reports average pace per kilometre, we multiply by the race distance. That is arithmetic on their number, not a new number — but the mean of a set of paces is not identical to the pace of the mean time, so treat converted figures as the coarser of the two kinds. Each one is labelled below.
The three sources
Every number below is one we could trace to a named publisher who states what they measured and how many results they measured it over. Nothing here is modelled, estimated or carried over from a secondary write-up.
- RunRepeat, Compare Running Finish Times
Measures: Half marathon finish-time percentiles, overall and by sex. Sample: 35M results across all distances, 28,000+ races. Years: “last 20 years”, no end date given. Reuse terms: Publisher states material may be reused with attribution to the original report - RunRepeat / IAAF, The State of Running 2019
Measures: Average half marathon pace by sex and by nation. Sample: 107.9M results across all distances, 70,000 events, 193 countries. Years: 1986–2018. Reuse terms: “You may use material from this report as long as you refer to this original report.” - Nikolaidis, Cuk, Rosemann & Knechtle (2019), IJERPH 16(10):1777
Measures: Mean running speed by age group and sex, Ljubljana 2017 half marathon. Sample: 7,258 half marathon finishers (plus 1,853 marathon finishers). Years: 2017. Reuse terms: Peer-reviewed, open access under CC BY 4.0
The first two are the same publisher; the third, Performance and Pacing of Age Groups in Half-Marathon and Marathon (Nikolaidis, Cuk, Rosemann and Knechtle, IJERPH 2019), is independent of them but is a single race in a single year.
What the sources say, and the gap
| Source | Basis | All | Men | Women |
|---|---|---|---|---|
| Compare Running Finish Times | Median (50th percentile) | 2:14:59 | 1:59:48 | 2:24:03 |
| State of Running 2019 | Average pace × 21.0975 km (converted) | — | 1:59:33 | 2:14:19 |
| Runsy synthesis | Unweighted mean | 2:14:59 | 1:59:40 | 2:19:13 |
| Spread between sources | n/a — one source | 0:15 | 9:40 | |
| Ljubljana 2017 (single race) | Converted from mean speed | — | 1:51:59 | 2:06:56 |
The Ljubljana figures sit outside the synthesis on purpose. They are one European city race in one year and both are markedly faster than the global numbers, which is what a single well-organised destination half marathon looks like. They are here as a third reading, not a third input — and the fact that a real race can be eight minutes quicker than the global median is itself worth knowing before you compare yourself to any average.
One further note on the mean-speed conversion: the paper publishes mean running speed in metres per second (3.14 for men, 2.77 for women), and the time equivalent of a mean speed is not the same as the mean of a set of times. Treat those two figures as approximate.
A likely error in one of the published tables
The percentile study's men's half marathon column reads 1:58:16 at the 40th percentile, 1:59:48 at the 50th and 2:09:58 at the 60th. A 92-second step followed by a ten-minute step is not a shape finish-time distributions have. We think one of those cells is wrong, we do not know which, and we have reproduced them as published rather than silently correcting somebody else's table. It is a reason to hold the men's median a little more loosely than its two-source agreement suggests.
Where your half marathon time sits in the field
- All
- Men
- Women
| Percentile | All | Men | Women |
|---|---|---|---|
| Fastest 1% | 1:23:59 | 1:18:37 | 1:35:55 |
| Fastest 10% | 1:47:10 | 1:40:35 | 1:57:01 |
| Fastest 20% | 1:56:12 | 1:49:13 | 2:05:58 |
| Fastest 30% | 2:02:48 | 1:55:03 | 2:12:25 |
| Median | 2:14:59 | 1:59:48 | 2:24:03 |
| Slowest 20% | 2:41:05 | 2:25:57 | 2:50:31 |
| Slowest 10% | 2:59:18 | 2:42:48 | 3:08:21 |
Sub‑2 is the threshold everyone chases and the distribution supports the instinct: it puts you inside the fastest 45% of the whole field, inside the fastest 20% of women, and just about at the median for men. Sub‑1:45 is roughly the top 10%.
There is one more thing worth knowing about the half. The State of Running 2019 found that runners of both sexes post their best pace at the half marathon — faster, relative to the distance, than at 10K or 5K. Their explanation is that the half attracts trained runners without attracting the huge novice field a 5K does. If your half marathon pace looks unexpectedly strong next to your 5K, you are not imagining it, and the field average does the same thing.
Where would your time land?
Enter a finish time to read it off the same published distribution, instead of counting rows.
Faster than 74%
2:00:00 puts you in the top 26% of all finishers.
- Top 1%
- 1:23:59
- Top 10%
- 1:47:10
- Top 20%
- 1:56:12
- Top 30%
- 2:02:48
- Top 50%
- 2:14:59
- Top 80%
- 2:41:05
- Top 90%
- 2:59:18
Positions between the published anchors are linear interpolations, not measurements, and nothing is extrapolated past the fastest or slowest anchor. Source: RunRepeat, Compare Running Finish Times — finish-time percentiles by distance and sex, 35M results across 28,000+ races, publisher states “last 20 years” with no end date.
What we could not support, and left out
- An age-by-sex table of half marathon finish times. The peer-reviewed source we have publishes mean running speed by age group for one race, not finish times for a representative field. Converting one city's speeds into a table headed “average half marathon time by age” would be presenting a single race as the world. We did not.
- An explanation for the nine-minute women's gap. We can see it; we cannot account for it from what is published. Saying so is more useful than picking a side.
- A corrected version of the percentile table. We flagged the implausible cell rather than editing another publisher's data.
- Anything from parkrun or its community scrapes and dataset mirrors: their terms prohibit reuse.
For a comparison that adjusts for your age and sex against a maintained published standard rather than against whoever entered, an age-graded percentage is the sounder instrument.
Sub-2, or your first finish line
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Fair questions
What is the average half marathon time?
Runsy's synthesis puts it at about 1:59:40 for men and 2:19:13 for women; the one source publishing an overall figure gives a median of 2:14:59. The men's number is unusually well supported — two independent studies land 15 seconds apart. The women's number is not: the same two studies disagree by nine minutes and forty seconds, and we could not determine why.
Is a 2-hour half marathon good?
Yes. On the RunRepeat percentile study of 35 million race results, a sub-2 half puts you inside the fastest 45% of all finishers, inside the fastest 20% of women, and roughly at the median for men. Sub-1:45 is about the top 10%.
Why is average half marathon pace faster than average 5K pace?
Because of who enters each race, not because the half is easier. The State of Running 2019 found runners of both sexes post their best relative pace at the half marathon, and attributes it to the half attracting trained runners while the 5K is the entry distance for almost everyone who starts racing.
Why do published half marathon averages disagree so much for women?
We do not know, and we would rather say so. The two sources we traced give 2:24:03 (a median across roughly 20 years of results) and 2:14:19 (an average converted from a per-kilometre pace covering 1986–2018). Both are large samples from a credible publisher and they differ by nearly ten minutes, while the same two sources agree on the men's figure to within 15 seconds. Treat any single published women's average as one methodology's answer, not the answer.
Are these averages of all runners or just race finishers?
Just race finishers. Every dataset here is built from official results, so it counts only people who entered an event and crossed the line — fitter and more trained than the running population as a whole. There is no published dataset we could find that measures runners in general.