The 2024 New York City Marathon: Three Interesting Data Insights (Plus More)

Feature image by Anthony Quintano on FlickrCC BY 2.0

Last Sunday was the New York City Marathon.

The race set a new record for the number of finishers – over 55,000 – and New York City is once again the largest race in the world. Berlin’s stint as the record holder was short lived.

As I’ve done recently for Chicago and Berlin, I collected the results and put together a thorough analysis of the data.

The full analysis is published on Medium in Runner’s Life, but I pulled out a few visuals to share here. If you’re not a Medium subscriber, you can also request a special link to get you behind the Medium paywall.

I’ve also put together an interactive dashboard on Tableau Public. It lets you see how an individual performance stacks up against the field, explore the overall distribution of finish times, and see the breakdown of Boston qualifying data.

I’d encourage you to read the full analysis and/or check out the dashboard. But in the meantime, here are a few highlights.

The Gender Distribution

I recently wrote a series on how the gender distribution of marathon runners has changed over time. So it’s one of the first things I often look at when I dive into the data on a race.

Overall, about 55% of the field at the 2024 NYC Marathon was male and 45% was female.

That general distribution obscures an interesting trend. The younger age groups – 20-24 and 25-29 – are actually majority female. And once you move up the age ladder towards the 60’s and the 70’s, things become increasingly male.

It’s a pattern that repeats itself in most races, and over time the balance has slowly shifted to the right.

But another interesting observation I made in analyzing the Berlin Marathon was that the gender (and age) distribution of American runners was very different from that of other runners around the world. This pattern repeated itself in Chicago, which I wrote about recently.

And when I checked things out in New York, the same pattern is there.

This visual shows American runners at the top and international runners at the bottom. The purple bars represent women and the blue bars represent men. It’s broken out by age group, from under 20 to 80+.

One immediately obvious difference is that there are two groups of American runners – 20-24 and 25-29 – that have significant majorities of women. The 30-34 age group is also almost evenly split. As you move to the right, there are slightly more men, but this imbalance is smaller than it is in the overall field.

The flip side of this is that among international runners, there are more men and than women in every age group. And the difference among older runners is increasingly stark.

The other difference should notice is that the age distribution of these two groups of runners is very different. American runners tend to be younger – with 25-39 being the center of the distribution. Meanwhile, international runners trend much older – with 40-54 being the center of the distribution.

International travel could be a partial explanation for the age difference. It’s also a pattern I noticed at the London Marathon.

But that doesn’t explain the gender differences. That difference occurred both in American marathons (Chicago, New York) where international runners traveled to the United States and Berlin – where American women traveled to Germany.

I’m going to dig into this more next week and disaggregate the data by country to see if there are similarities to the data from Chicago.

Average Finish Times

Another common question people have is what the average finish time of a runner is. This varies quite a bit by gender and age, so I’ve disaggregated it by both categories.

I’ve also included four different benchmarks – the median (or average) runner, the runner who beat 75% of similar runners (slightly above average), the runner who beat 90% of similar runners (well above average), and the runner who beat 99% of similar runners (very fast).

In the visual below, the purple line represents women and the blue line represents men.

At the median, younger men (25-39) are finishing just under 4:00. For men 40-44, it’s just over 4:00, and it gradually increases from there. The jumps for runners in their 50’s and 60’s are much larger – with the average late 60’s runner finishing in around 5:00.

Meanwhile, younger women (20-29) at the median finish in around 4:30. Among women, the average time starts to increase with age earlier, and it’s 4:40 for 35-39 year olds, 4:45 for 45-49 year olds, and on up to 5:30 for women in their late 60’s.

The slightly above average runner is an interesting group, to me. It’s faster than average, but it’s also large. Many runners finish near these times. For younger men, that’s ~3:30 and for younger women that’s ~4:00. But even for the 60 year olds out there, this group is finishing well under 5:00.

Meanwhile, the top 1% of runners are just laying down extraordinary times. Young men are in the 2:30’s and young women are in the 2:50’s. There’s an interesting thing to observe here, in that ~10% of young men finish around 3:00. That’s close to time for the top 1% of women. So if you’re looking at that group of sub-3 runners, it’s going to be overwhelmingly male – and the women in there are incredibly fast.

You can explore the rest of the graph yourself. And for a more detailed look at the distribution of finish times, make sure you check out the Tableau dashboard.

The Distribution of Boston Qualifying Times

Finally, let’s look at the distribution of Boston qualifying times.

About 8% of finishers at the New York City Marathon met the new Boston qualifying time for their age group. That’s 4,778 runners. It’s actually more than last year. It’s a slightly lower percentage than. last year, but the field itself is significantly larger.

That qualification rate isn’t evenly spread throughout the field, though. Younger runners face tougher times and are less likely to qualify, while older runners make the cut at a higher rate.

The visual below shows the number of qualifiers from each age group (orange), as well as the number of qualifiers who would have qualified under the old times (green). And, if you hover over the bar you’ll see what percent of that age group qualified.

I’ll call out two things here.

One, among young men the proportion of runners who missed qualifying due to the new qualifying times is much higher than elsewhere in the field. The new 2:55 qualifying time for men under 35 is a tough standard, and it shows in how many young men ran between 2:55 and 3:00.

Two, the 60-64 age group qualifies at a much higher rate than the 55-59 age group. For both men and women. Runners over 60 still have the same qualifying times as last year, while runners under 60 all have reduced qualifying times.

As a result, the number of runners in that 60-64 age group qualifying is almost as high as the number in the 55-59 age group – despite that younger age group being much larger.

I’ll be doing a much deeper analysis on the state of the Boston qualifying process in the next few weeks, but in the meantime, you can see some more data from New York on the Tableau dashboard – including the distribution of runners’ buffers.

What Did You Think About the 2024 New York City Marathon?

One final fun tidbit: Abdi Nageeye is one of the oldest men to win the New York City Marathon. He’s 35, and only two other men – Paul Tergat (36, 2005) and Norm Higgins (35, 1971) – have won the race after turning 35.

If you want to dig deeper, again I’d encourage you to read the full analysis on Medium and/or explore the Tableau dashboard.

Did you run Sunday? Did you watch the race?

Do you have any follow up questions?

I’d love to hear about it in the comments.

I didn’t run New York year, and I watched from home on the couch (after my morning run). But I hope to qualify for the 2026 New York City Marathon. I’m running the Fred Lebow half in January, and I think I can make the cut (1:25 for a 40 year old man).

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