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3 Peaks 2014 – as told by charts

March 11, 2014

(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.

finishers1
In percentage terms you can see that the completion rate was about 10% higher this year.
finishers2
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.
finishers3

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.

times1

And the accompanying density plot”
times2

Times by Gender (stacked histogram) – You can see here that a lot more men participated than women.

times3

times4

The (ecdf) chart below shows the cumulative distribution of times by gender.

times5

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.

times5

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.

prop1

If you divide the time spent climbing by the time ‘descending’ you can see this variation just presented in a different way.

prop21

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.

predict1

predict2

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.

predict31

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).

dual1

Three Peaks 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.

dual3

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.

dual4

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.

travel1

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.

travel1

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7 Comments
  1. Andy permalink

    Thanks for putting this work together. Interesting data. With regard to time up tawonga and the ‘group’ that went on to post a fast overall time compared to some who went faster up tawonga but blew up. The group at around 24 min 50 seconds were actually the front group on the road, and the ones that went on to place in the overall top 10. The faster times must have come from participants who were behind on the descent of Falls and tried to catch the front group or just went up tawonga quickly through the field.
    Thanks again.

  2. chris wallis permalink

    Your analysis shows clearly why a <10 hour jersey is not the most appropriate marker of achievement. It pays no regard to gender or age or even the conditions. Maybe the awards ought be on a percentile basis on the day. Within a defined sub group the top x% get the award. The French have it right in the Marmotte. The brevets awarded reflect results on an age and gender basis.
    Are you able to provide any age related analysis without totally screwing your private life.

    • Hi Chris, I don’t have age data unfortunately. I would have definitely done some work with it if I did. You’re right about the gender disparity – over 25% of men, but less than 10% of women break 10 hours.

  3. Valda permalink

    It’s great to see some data from the event, many thanks. As a female rider I would like to know my result based on gender. As you have the times by gender, is it possible to see the women’s results list so that I can see my placing within women in the 3 Peaks event?

  4. Andrew Smith permalink

    Andy great data! The lead group scenario would depend on when they “became” the lead group. Were they the leaders on the road by Mt Beauty,if so your contention holds that no-one went up the road, but it is entirely possible they were still passing riders at Harrietville isn’t it?
    Cheers from a 5 time 3 peaker

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