Boston Marathon 2018 Statistics

Chad Montgomery
Apr 18, 2018 · 5 min read

A Look at Some Stats from a Soggy 2018 Boston Marathon

Photo by Joy Stamp on Unsplash

Like many marathon fans, I watched this year’s Boston Marathon with fascination and respect. Wow! The weather was said to be the worst in the past 30 years, and the grit shown by the runners, both elite and non-elite, was inspiring.

I thought it would be interesting to compare some of the statistics between 2017 and 2018. The numbers are surprising!

After following the online coverage of the elite races, I expected that the finishing times for the overall field would be much slower than last year given the elite times were quite slow by historical standards. However, the non-elites were not slower. Compared to 2017, which was relatively hot, 2018 had more “fast” times, but also more “slow” times. Details? Read on!

Weather

Here are the race day weather summaries. The 2017 weather data is from the BAA website. The 2018 weather data is based on tweets from the BAA twitter account.

The weather for 2018 varied through the morning, and the media reported gusts much higher (25+ mph) than the 4–10 mph shown in the table. However, I’m sticking with data from BAA. If they post a 2018 update on their website, I’ll update the table.

2017 vs 2018: BQ Rates at Boston

I always think it is interesting to see how many athletes manage to run a BQ time at the Boston Marathon. Comparing the percentages across years is one way of estimating the impact of weather conditions.

Surprisingly, both the total number and the percentage of BQ times was higher for both men and women in 2018. For men, 37.4% (5286) ran a BQ in 2018 vs just 31.2% (4503) in 2017. Similarly, for women the 2018 percentage was 38.1% (4418) in 2018 vs. 32.8% (3925) in 2017.

The full details by gender and age group are shown in the tables below.

2017 Men’s BQ Stats

2018 Men’s BQ Stats

2017 Women’s BQ Stats

2018 Women’s BQ Stats

For 2018, there does seem to be a bit of a falloff in the BQ percentages in the older age groups…particularly for the men. I don’t see this effect in the 2017 data. Otherwise, the data is fairly consistent across gender and age group.

Was 2018 faster or slower than 2017?

Based on the BQ percentage tables, you might guess that the average finishing times for 2018 would be faster than for 2017. Actually, the average times are quite close, but the standard deviations for 2018 are much larger.

The tables below have the summary stats for the men’s and women’s results. I’ve also included the number and percentage of finishers above and below certain time thresholds to show the effect of the increased standard deviation.

You can see from the tables that 2018 had a much larger number (and percentage) of men who went under 3:00, but it also had a larger number (and percentage) who were over 4:40. Similarly, the women’s results are much more spread out for 2018.

Do northerners have more grit?

I wondered whether runners from northern states had an advantage when the weather turns cold and miserable. As someone who runs outdoors year round in the Chicago area, I really wanted this to be true! Alas, it doesn’t seem to be!

This table shows the BQ rates by state for 2018.

The results look similar across northern and southern states. The exceptions are states with relatively few participants where the percentages tend to be more variable.

You might notice that Massachusetts has the smallest percentage of runners who BQ. I suspect that, as the home state of the marathon, it has the most charity runners who tend to run slower times on average.

For comparison, the 2017 table of Boston BQs by state is here.

Conclusion

It’s amazing to me just how tough runners are. Despite the horrible conditions this year, the times at Boston were still pretty fast.

I found it interesting that the effect of the weather was to increase the standard deviation of the finishing times rather than to increase the average finishing time. Perhaps the faster runners benefited from the cooler temperature, but the wet and cold began to take a toll on the runners who were exposed to it longest? Of course, that doesn’t explain the slow times in the elite fields. Maybe they are just too lean for these cold and wet conditions? Or, maybe they just didn’t dress properly!

There are many more possibilities for digging into this data further. For instance, it would be interesting to see how the pacing profiles differed across the two years. That investigation and others will need to wait for a future post. Maybe next year will bring more interesting weather to include in the analysis!

Chad Montgomery

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I’m an electrical engineer and MBA with an interest in statistics and endurance sports.