Race Report: Big Shoulders 5K (Chicago, IL)

Official write-up here.
Rob Aquatics write-up here.

What the gods giveth, they can – and do – taketh away. This is Chicago, people!

Big Shoulders ’09 was a picture-perfect beach day, with calm 73-degree water. This year, the remnants of Tropical Storm Hermine blew through, giving us clouds, rain, wind, and choppy, cold water (62-63 degress F).

It’s all in the game, though, right? Open-water swimming isn’t supposed to be predictable – that’s what pools are for! Maybe you get a beach day, or maybe you get a storm. Maybe the water is calm and comfortable, or maybe it’s churning and cold. The more you can suck it up and say, “I don’t care. It’s the same water for everyone” – the more successful you’ll be.

Dare I say it? Open-water swimming is supposed to be challenging! It might be uncomfortable; it might be frustrating; it might even be vaguely dangerous. You may have to endure – god forbid! – a few negative thoughts. In open water, there are no “best times” – the clock is merely a ranking device. Instead, rewards derive from tackling challenges – distance and/or unique conditions – and overcoming them.

Which is why Big Shoulders 2010 was an instant classic.

Continue reading “Race Report: Big Shoulders 5K (Chicago, IL)”

Big Shoulders: Notes on a psych sheet

Tomorrow’s Big Shoulders 5K will have a legitimate claim as the most competitive Masters open-water race in the U.S. outside of the Waikiki Roughwater, and maybe some years of the La Jolla Roughwater. For the first time, there will be an “elite” wave of the top 50 swimmers, according to seed time. Here they are:

Continue reading “Big Shoulders: Notes on a psych sheet”

Big Shoulders Stats: Finishing times

People say times don’t matter in open water – or at least that you don’t always know what they mean. And perhaps that’s part of its attraction. While in the pool “the clock never lies,” in open water it’s not much more than a ranking device.

Even so, I’ve been surprised by how closely most of my open-water pace times have approximated my pool speed at various distances – from 1:15 at 1 mile (Huntersville), to 1:17 at 1.5 miles (Livermore), to 1:19 at 2 miles (H’ville again) up to 6K (Windsor), and 1:22 at 10K (Noblesville).

When an event has been staged for many years, though – at the same location, on the same course layout – comparing times makes a little more sense. Big Shoulders is one such event.

In that spirit, here are the finish times in Big Shoulders across the 12 years of available data, starting with the 5K race:

5K times

That chart is a little busy, so let’s unpack it:

  • Each black dot represents one swim. The dots are “jiggered” slightly to the left or right of their corresponding year (so more of them are visible). If a dot is closest to the vertical line indicating 2005, that means the swim took place in 2005.
  • The blue line connects the slowest swim in each year.
  • The green line connects the fastest swim in each year.
  • The red line connects the median swim in each year.

Make sense? Now, here are the 2.5K swims over the years:

2.5K times

What does it all mean? While the slowest and fastest swims each year will depend on “who shows up,” I think we can interpret the median swim as a broad measurement of “conditions.” In Lake Michigan, that generally means water temperature and/or surface chop (but usually not current).

For a swim in the same location, with the same course layout, which draws a reasonably large sample from the same population (people who live within a few hours’ drive of Chicago), we wouldn’t expect the median finish time to vary much over time. To the extent that it does vary, we can probably attribute it to “conditions.”

One probable exception is 2003, in which both the median and fastest times were substantially faster than usual. Not surprisingly, on an anecdotal level, it was widely assumed among those who participated in 2003 that the course was shorter than 2.5K.

Big Shoulders Stats: A local race?

More Big Shoulders stats, from my custom-made aggregate file. Here’s the proportion of Big Shoulders participants hailing from Illinois, Indiana, and “other” – i.e., anyplace besides IL and IN.

Clearly, Illinois locals still predominate, but recent years have seen a greater influx of out-of-state swimmers. In 2009, almost 30% came from outside of Illinois and Indiana – an all-time high.

Big Shoulders Stats: Participation by Age

More fun with Big Shoulders stats. We’ve been looking at participation – so what about age? Masters swimming is traditionally dominated by people in their 40’s and 50’s – is the same true here?

It seems the modal age is actually a bit younger in Big Shoulders – lots of people in their 30’s. But the “50’s” have been mounting a furious comeback (see the blue line) – perhaps a baby boomer effect.

My custom aggregate CSV file, from which I calculated these stats, is available here.

Big Shoulders Stats: Come on down, ladies!

How ’bout some more fun with stats? In yesterday’s post we saw Big Shoulders’ explosive growth over the years. How does this break down by gender?

Historically, more men than women have taken the plunge, but the gap has narrowed in recent years. In 2009, women were 43% of the total participants.

Stormy, Husky, Brawling

Less than 3 weeks ’til Big Shoulders! This race has a special place in my heart: It was at Big Shoulders ’09 where I caught the open-water bug. Without which, this summer wouldn’t have been nearly as awesome.

Little did I realize that Big Shoulders would soon be my hometown race. And I’m happy to see it prosper: In its 20th year, it reached the maximum registration of 800 swimmers for the first time. That’s an eightfold increase since 1998, the first year for which results are available on the web.

To facilitate analysis across years, I aggregated these 12 years of results (1998-2009) into a single CSV file. This is what you might call a picture of success:

— Notes —

  • 1999: first year that a 2.5K race was offered
  • 2005: 2.5K race was the USMS 1-3 mile national championship
  • All data-slinging, number-crunching, and picture-making performed with the assistance of R and ggplot2.