(To see the charts clearly, please click to expand)
3 Peaks 2014 was held over the weekend, in much more pleasant weather than last year’s scorching heat.
Here are some charts that show a bit about this year’s ride, and also how it compared to last year’s.
This year’s 235km ride attracted 1922 entrants, up from 1543 last year. This chart shows that, despite the larger field this year, there were a lot fewer DNFs in 2014. The weather no doubt played a role in this. A total of 1639 people finished.
In percentage terms you can see that the completion rate was about 10% higher this year.
Broken down by gender you can see that women who entered had a slightly higher completion rate than men. Men were more likely to DNS and women were more likely to DNF.
On to finishing times: Here’s a chart showing finish times by 30 minute intervals. Six absolute weapons managed to crack the 8 hour mark and 75 cracked the 9 hour mark.
Times by Gender (stacked histogram) – You can see here that a lot more men participated than women.
The (ecdf) chart below shows the cumulative distribution of times by gender.
And on to the coveted average speed section. A total of four people broke the holy grail of 30km/h (including stops!). I was lucky enough to suck one of these gents’ wheels in the Sydney Rapha Gentlemen’s Race last year – I cannot imagine how painful attempting that would have been on Sunday.
The ride results contain data on how long it took to do the three monster climbs. I subtracted the time spent climbing the three major climbs from the total time and called this the time ‘descending’ (optimistic, I know). While there is a positive relationship between time spent climbing and ‘descending’, the dispersion of the points shows the enormous amount of variation.
If you divide the time spent climbing by the time ‘descending’ you can see this variation just presented in a different way.
The following charts investigates how a rider’s time up Tawonga Gap relates to their overall performance. Nobody who took more than 30 minutes to get up Tawonga Gap broke 9 hours and nobody who took more than 35 minutes broke 10 hours. Events like this are all about finding the right bunch to be a part of, so you have to make sure you don’t miss the bus on the first climb.
If we focus on just the fastest people up Tawonga Gap (those who do it sub 28 mins) you can see that the top finishers at the end of the day weren’t the fastest up TG. They all rode together
while a few others went up the road (and potentially blew up). EDIT: Andy’s comment tells us nobody went up the road from the front bunch on TG so the few posting faster times must have been slower on the Falls descent and were trying to catch the lead group or they started in a later wave.
Now, let’s have a look how people who participated last year and came back to face the challenge again this year.
The following two charts show how last year’s performance is related to this year’s. The first chart shows proportional ranking and the second shows a rider’s placing (there were a lot more entrants this year, so a given place is better (proportionally) in 2014).
This chart compares performance up Tawonga Gap in 2013 vs 2014. On average people improved over the year but the effect size is small.
70 people who did not finish in 2013 came back to tackle the event again in 2014. 9 of these 70 didn’t show up on Sunday but the good news story is that 52 of the 70 finished. The chart below groups people into their race ‘status’ (finished, DNF, DNS) from last year to see what happened to them this year. Those that finished last year were very likely to finish again this year. Those that DNS-ed last year were more likely to DNS in 2014.
Three peaks is a massive event, drawing people from all over Australia.
The following chart shows which state participants come from. Being held where it is, the biggest representation obviously comes from Victorians but A LOT of people come from NSW for this event, most from Sydney as we’ll see in a second. I know that 20+ come down from my old club alone.
Using suburb names I could determine how far people travelled (as the crow flies) to get to 3 peaks. In short, people travelled a long way to put themselves through hell. The four distinct lumps in the following density plots show people travelling from Melbourne, Sydney, Brisbane and WA respectively.