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[Event] Cape Town Cycle Tour 2019


Warren Lew

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I need to do some work! I'll pop the formula in a spread sheet and post it  this evening. Then you will be able to input your time and get a result under 2018 conditions.

 

 

Really greatly appreciated! 

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Data, glorious data!

 

Here's the key to the groups:

 

$ = 1;    @ = 2;    & = 3;    # = 4;    1A = 5;    1B = 6;    1C = 7;    1D = 8;    1E = 9;    1F = 10;    1G = 11;    1H = 12;    1J = 13;    1K = 14;    2A = 15;    2B = 16;    2C = 17;    2D = 18;    2E = 19;    2F = 20;    2G = 21;    2H = 22;    Jh = 23;    Js = 24;    Ju = 25;    2K = 26;    3A = 27;    3B = 28;    3C = 29;    3D = 30;    3E = 31;    3F = 32;    3G = 33;    3H = 34;    3J = 35;    3K = 36;    4A = 37;    4B = 38;    4C = 39;    4D = 40;    4E = 41;    4F = 42;    4G = 43;    4H = 44;    4J = 45;    4K = 46;    5A = 47;    5B = 48;    5C = 49;    5D = 50;    5E = 51;    5F = 52;    5G = 53;    5H = 54;    5J = 55;    5K = 56;    6A = 57;    6B = 58;    6C = 59;    6D = 60;    6E = 61;    6F = 62;    6G = 63;    6H = 64;    6J = 65;    6K = 66;   

 

 

this is awesome!

Can see some outliers -

1D guy beat his bunch by 5 minutes

4K two okes did a 3:12 on their own. Foreign sounding names so I'm guessing international riders with decent VO2 max.

6D two u16s doing a 3:20 odd - these kids can ride

 

 

I can't work the formula out either, but have got a low tech way to see if you were better or worse vs 2018.  Just work out what percentile you are in the finishers. I was about 15min slower, but still around the top15% of the field, so for me same result. (FYI, the 2018 argus seems to be gone from racetec currently..weird)

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Data, glorious data!

 

Here's the key to the groups:

 

$ = 1;    @ = 2;    & = 3;    # = 4;    1A = 5;    1B = 6;    1C = 7;    1D = 8;    1E = 9;    1F = 10;    1G = 11;    1H = 12;    1J = 13;    1K = 14;    2A = 15;    2B = 16;    2C = 17;    2D = 18;    2E = 19;    2F = 20;    2G = 21;    2H = 22;    Jh = 23;    Js = 24;    Ju = 25;    2K = 26;    3A = 27;    3B = 28;    3C = 29;    3D = 30;    3E = 31;    3F = 32;    3G = 33;    3H = 34;    3J = 35;    3K = 36;    4A = 37;    4B = 38;    4C = 39;    4D = 40;    4E = 41;    4F = 42;    4G = 43;    4H = 44;    4J = 45;    4K = 46;    5A = 47;    5B = 48;    5C = 49;    5D = 50;    5E = 51;    5F = 52;    5G = 53;    5H = 54;    5J = 55;    5K = 56;    6A = 57;    6B = 58;    6C = 59;    6D = 60;    6E = 61;    6F = 62;    6G = 63;    6H = 64;    6J = 65;    6K = 66;   

 

 

Amazing! You can see all those that were seeded incorrectly/ MTB rides :P !

 

That graph looks perfect!!

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Data, glorious data!

 

Here's the key to the groups:

 

$ = 1;    @ = 2;    & = 3;    # = 4;    1A = 5;    1B = 6;    1C = 7;    1D = 8;    1E = 9;    1F = 10;    1G = 11;    1H = 12;    1J = 13;    1K = 14;    2A = 15;    2B = 16;    2C = 17;    2D = 18;    2E = 19;    2F = 20;    2G = 21;    2H = 22;    Jh = 23;    Js = 24;    Ju = 25;    2K = 26;    3A = 27;    3B = 28;    3C = 29;    3D = 30;    3E = 31;    3F = 32;    3G = 33;    3H = 34;    3J = 35;    3K = 36;    4A = 37;    4B = 38;    4C = 39;    4D = 40;    4E = 41;    4F = 42;    4G = 43;    4H = 44;    4J = 45;    4K = 46;    5A = 47;    5B = 48;    5C = 49;    5D = 50;    5E = 51;    5F = 52;    5G = 53;    5H = 54;    5J = 55;    5K = 56;    6A = 57;    6B = 58;    6C = 59;    6D = 60;    6E = 61;    6F = 62;    6G = 63;    6H = 64;    6J = 65;    6K = 66;   

 

 

 

Nice post Ryan & interesting stats. What I take from this graph is that despite a few outliers the seeding system seems to be working very well until around group 35. Thereafter its everyone for themselves!

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commentators on live stream said the wind actually dropped during the day.  there probably somewhere stats on the actual winds for the day .. just to lazy to google now

I did a half 2nd lap(time constraints as I made it back too late, So went main road, Wynbgerg, M3(still open but cleared) Tokai, Spanschemat, Over the Nek in Hout Bay and then the rest of the Route) and I can tell you that the wind coming down Llandudno and towards the finish was not as strong as the 1st time I went down whilst "racing" in 1E... There were a few gusts but again not as strong as earlier on in the morning.

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I’m not a statistician. Now that we have that cleared up, have a look at this data:

Chart 1 shows the performance of 2019 CTCT cyclists relative to their 2018 performance, across race times.

Fastest 2019 cyclists to the left; slowest to the right.

Cyclists who did better than last year to the bottom; cyclists who had a bad run this year, up you go; cyclists who held their 2018 time sit on the 1.0 line.

So bottom left is fast and chuffed, while top right is slow and disappointed.

The dotted line shows the trend: it slopes upwards, i.e. the slower the rider, the greater the toll that the wind took. The first riders home were somehow impervious to the wind. The slower riders really felt it.

Chart 2 is a detailed view of the area covered by the trend line in Chart 1.

Chart 3 shows performance variance per start group. On average, all groups got pretty much equally battered by the wind – the trend line is nearly flat.

Any theories on why the faster riders, not the earlier riders, were less affected by the wind?

I was hoping that this data would allow me to claim that, despite coming in 20 minutes later than last year, I had put in a better effort this year. Sadly, the data disagrees. I came to this conclusion by offsetting my 2019 time by the average variance for my finishing time. This gave me a number that I could compare directly with my 2018 result.

Here’s the formula: 2019 race time / (0.8556952984 x 2019 race time + 0.9321198196). The result is an indication of the time you could have expected had there been no wind.

I’ve worked on the assumption that the 2019 wind was more or less consistent throughout the day and that 2018 was a peach with little to no wind all day. Are these assumptions reasonably accurate?

I scratched a little into differences across ages and genders but I didn’t pick up anything striking.

Gaps / errors in my thinking? Let me know.

 

What was the R^2 of your correlation? By the looks of the 'fit', eyeballing only, it doesn't well represent the data? If so, then using the correlation to aid interpretation will introduce an error, as I think you might be suggesting?

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Data, glorious data!

 

Here's the key to the groups:

 

$ = 1;    @ = 2;    & = 3;    # = 4;    1A = 5;    1B = 6;    1C = 7;    1D = 8;    1E = 9;    1F = 10;    1G = 11;    1H = 12;    1J = 13;    1K = 14;    2A = 15;    2B = 16;    2C = 17;    2D = 18;    2E = 19;    2F = 20;    2G = 21;    2H = 22;    Jh = 23;    Js = 24;    Ju = 25;    2K = 26;    3A = 27;    3B = 28;    3C = 29;    3D = 30;    3E = 31;    3F = 32;    3G = 33;    3H = 34;    3J = 35;    3K = 36;    4A = 37;    4B = 38;    4C = 39;    4D = 40;    4E = 41;    4F = 42;    4G = 43;    4H = 44;    4J = 45;    4K = 46;    5A = 47;    5B = 48;    5C = 49;    5D = 50;    5E = 51;    5F = 52;    5G = 53;    5H = 54;    5J = 55;    5K = 56;    6A = 57;    6B = 58;    6C = 59;    6D = 60;    6E = 61;    6F = 62;    6G = 63;    6H = 64;    6J = 65;    6K = 66;   

 

 

 

My OCD just wants to close that gap where the Jh/Js/Ju bunches sits, and see the full picture of the tornado leaning towards the right...

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Chart 1 shows the performance of 2019 CTCT cyclists relative to their 2018 performance, across race times.

 

wait a moment

did you get data from every cyclist who finished the 2018 and 2019 events

                 OR

just compared the group times..ie 1A '18  vs 1A '19?

 

because the first one is some serious wizardry if that's the case, but would have a smaller sample set 

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this is awesome!

Can see some outliers -

1D guy beat his bunch by 5 minutes

Guy from Bloem, he's strong. Looks like he simply rode away from them on Smitswinkel, looking at Strava Flybys

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commentators on live stream said the wind actually dropped during the day. there probably somewhere stats on the actual winds for the day .. just to lazy to google now

Post 1789

 

 

Sent from my iPhone using Tapatalk

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wait a moment

did you get data from every cyclist who finished the 2018 and 2019 events

                 OR

just compared the group times..ie 1A '18  vs 1A '19?

 

because the first one is some serious wizardry if that's the case, but would have a smaller sample set 

 

Copy. Paste. Copy. Paste. Copy. Paste. Copy. Paste. Copy. Paste...

No wizardry. 

I had to delete duplicates because I have no way of differentiating between riders with the same names. And I didn't quite get that right so there are some wobblies in the data that I should sort out sometime. As it currently stands, 14341 data points for riders who rode both this year and last.

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Whats with the sudden jump in numbers of fast riders from line 40 (4D) upward, is this where strong riders who didn't fit in the RSA seeding system start getting placed?

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commentators on live stream said the wind actually dropped during the day.  there probably somewhere stats on the actual winds for the day .. just to lazy to google now

 

Well, you are right, it was a very weird and wonky day re weather conditions....so depending where you were, the wind (and rain) was a totally different strength. For example in Blouberg (usually windy city) the whole day there was only mild wind (or very little), as it seemed there was a high-sitting low pressure to the north, which offset wind and rain (remember somebody in Langebaan saying they had rain).

The closer you got to Cape Point though, the wind was haywire (influenced by the wind direction) and was much stronger (gusty).

Anyway, nobody was at the whole route at every hour to give us reliable stats...not sure about the wind vanes around the peninsula. Nice exercise anybody?

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Well, you are right, it was a very weird and wonky day re weather conditions....so depending where you were, the wind (and rain) was a totally different strength. For example in Blouberg (usually windy city) the whole day there was only mild wind (or very little), as it seemed there was a high-sitting low pressure to the north, which offset wind and rain (remember somebody in Langebaan saying they had rain).

The closer you got to Cape Point though, the wind was haywire (influenced by the wind direction) and was much stronger (gusty).

Anyway, nobody was at the whole route at every hour to give us reliable stats...not sure about the wind vanes around the peninsula. Nice exercise anybody?

 

 

The Steenberg and Constantia to Table Mountain Range plats a big role in wind strength. You have teh warm body of water in False bay that adds energy to the wind as it picks up moisture . then there is the local high pressure at the face of the mountains, this pressure  is great for hanggliding but really crappy for wind as the high pressure converts into wind speed along the Southern Suburbs.

In Blouberg you don't feel this as much as the wind you get there is largely coming from over the hotentots holland mountains and has slowed down as it expands over the cape flats.

 

The mountains of the Peninsula is what generates that wind speed felt through the Southern suburbs.

On Sunday I don't think the larger HP system was intense enough to create stronger winds across the Cape Flats and into Blouberg. It had largely blown itself out.

Funny enough I recorded 22mm of rain through Sunday night into Monday. All from the South

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Any theories on why the faster riders, not the earlier riders, were less affected by the wind?

 

Simple aerodynamics - the faster you go, the greater the drag. You double your speed, and you square the drag. 

 

post-275-0-30466600-1552554180.jpg

 

The increase in effort for a fast rider to go from, say 30km/h to 35km/h is far greater than the effort needed by a slower rider to go from 15km/h to 20km/h.

 

In the case of Sunday, fast riders were going from 40km/h (windless) to 70km/h (assuming a 30km/h headwind). That makes the formula above explode! A LOT more force is required to overcome that drag! (Speed is the v in the formula above)

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