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Tadej Pogacar and Mauro Giannetti

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Gianetti upgraded his Frankenstein. Tour de France will be crazy this year

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It's a bit like taking the piss isn't it?
 
As always, it is very interesting to see such large gaps in what essentially comes down to basic aerobic metabolic capacity and observe the gap within the subpopulation of the elite of the elite cyclists.

While some riders' ability to just take off is indeed the new normal, it wasn't that way 10 or even 5 years ago. Within this time frame, the peloton as a whole became more professional and competitive. Arguably the expectation then is to see gaps diminish.
I don't see what the big deal is. So I can say hey I'm going to break away here, and just nuke people, and hey I can time trial away from you all as well for 80 km. No problemo.
 
Holy schit!
For years cycling commentators avoided using the term "unbelievable" to describe outlandish performances due to the obvious implications.
Now it's making a comeback.
Check out the commentator who was asked to fill in some dead air in the final km to describe what he just witnessed.
The word "unbelievable" instinctively came out of his mouth. He checked himself for a bit before saying the word again with authority.
 
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As always, it is very interesting to see such large gaps in what essentially comes down to basic aerobic metabolic capacity and observe the gap within the subpopulation of the elite of the elite cyclists.

While some riders' ability to just take off is indeed the new normal, it wasn't that way 10 or even 5 years ago. Within this time frame, the peloton as a whole became more professional and competitive. Arguably the expectation then is to see gaps diminish.
If you assume that human aerobic capacity follows a normal bell curve then it's actually expected that the top few examples are extreme outliers. This is even more pronounced in the pro peloton, which itself does not follow a bell curve but is the rightmost slice of a bigger bell curve.

Think about it: if you are one sigma above the median, then 47.5% are within one sigma of you (34% worse, 13.5% better). Out of one million, there are 475,000 who are within one sigma of you.

If you are 2 sigmas above the norm, only about 16% are within one sigma. That's 160,000 individuals.

There are expected to be about 3 examples out of a million that are at least six sigmas to the right of the median. There are only 230 that are within one sigma of those (i.e above 5 sigmas).

Concretely, the standard deviation might be something like 6 mL/kg*min of vo2 max. So the farther out on the curve you get, the fewer others are within that constant amount of vo2 capacity.

In other words, we should expect the outliers to be very extreme, much more distant to their nominal peers than an average local enthusiast is from his or her neighbor.

At a race like SB, the advantage one would need over their peers to simply ride away is of course much less than the advantage that would be required to do so at most road races due to the nature of the course.
 
I can't help liking him. And I like the way he goes about his races, but .... that was hard to come to any conclusion much different from Pidcocks's "What the Fxxk.?"

As an endurance coach (different sport) I'm learning as much as I can at the moment about Ketones and MCTs as I can. They probably do make a difference, but you'd expect pretty much the whole peloton to be across that by now, so, unless Vingo and Pog are particularly adept at using them... there must be something else. Maybe their metabolical flexibility (everyone's is different) is off the scale.
 
If you assume that human aerobic capacity follows a normal bell curve then it's actually expected that the top few examples are extreme outliers. This is even more pronounced in the pro peloton, which itself does not follow a bell curve but is the rightmost slice of a bigger bell curve.

Think about it: if you are one sigma above the median, then 47.5% are within one sigma of you (34% worse, 13.5% better). Out of one million, there are 475,000 who are within one sigma of you.

If you are 2 sigmas above the norm, only about 16% are within one sigma. That's 160,000 individuals.

There are expected to be about 3 examples out of a million that are at least six sigmas to the right of the median. There are only 230 that are within one sigma of those (i.e above 5 sigmas).

Concretely, the standard deviation might be something like 6 mL/kg*min of vo2 max. So the farther out on the curve you get, the fewer others are within that constant amount of vo2 capacity.

In other words, we should expect the outliers to be very extreme, much more distant to their nominal peers than an average local enthusiast is from his or her neighbor.

At a race like SB, the advantage one would need over their peers to simply ride away is of course much less than the advantage that would be required to do so at most road races due to the nature of the course.
Outliers become relatively rarer the further out you go of a normal distribution. To make that comparison you need to account for both numerator and denominator.

In the total population, the difference between the 90th percentile and the 99th percentile is 1.045 σ. In the elite subpopulation of the top 0.1 %, the difference is 0.546 σ.

Another way to view the rarity of outliers is the ratio of probability density 0.1 σ apart. The ratio between +2 σ and +2.1 σ is 1 : 0.79, for +3 σ and +3.1 σ it's 1 : 0.72, and for +4 σ and +4.1 σ it's 1 : 0.65. The next step gets rarer and rarer.

Of course, for a log-normal distribution it's another matter. That's where you expect "outliers".
 
As always, it is very interesting to see such large gaps in what essentially comes down to basic aerobic metabolic capacity and observe the gap within the subpopulation of the elite of the elite cyclists.

While some riders' ability to just take off is indeed the new normal, it wasn't that way 10 or even 5 years ago. Within this time frame, the peloton as a whole became more professional and competitive. Arguably the expectation then is to see gaps diminish.
I think the gap yesterday was normal. It was a large gap of about 3 minutes to guys like skujins and van gils, a natural gap because the difference of talent between them and Pogacar is huge. I'm not surprised by the gap. The top 4/5 riders of the moment always win with a good gap when they ride alone against the other humans.
 
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Holy schit!
For years cycling commentators avoided using the term "unbelievable" to describe outlandish performances due to the obvious implications.
Now it's making a comeback.
Check out the commentator who was asked to fill in some dead air in the final km to describe what he just witnessed.
The word "unbelievable" instinctively came out of his mouth. He checked himself for a bit before saying the word again with authority.

What did they say with Dawg's performance on Stage 19 attack of the '18 Giro?

Pidcock's post race interview says it all for me.
 
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Outliers become relatively rarer the further out you go of a normal distribution
Let me try this again...

Obviously Pogacar is an outlier (which is, by definition, rare). My post concerns not whether he is rare (duh) but what kind of absolute difference we expect between the biggest outliers and their closest peers. There's a myth that barely anything should separate the top few individuals, but statistics, if anything, suggests the opposite.

That is to say, IF aerobic capacity does in fact follow a normal distribution. Big if, however the data does look that way.
 
Well, it's true that the gap from 1st to 2nd is greater than the gap from 2nd to 3rd and so forth.

My point is that those differences are more pronounced in a representative sample than in a more selected sample. For the elites, the best will have smaller advantages. The more elite, the smaller advantage.

For a representative sample of 100, the expected gaps (in Z-score, so as measured in σ) from 1st to 2nd to 3rd to 4th are: 0.2726, 0.1730 & 0.1301. For a sample of the top 1 %: 0.1789, 0.1085 & 0.0788. And finally for the top 0.1 %: 0.1574, 0.0947 & 0.0684.

And that is for absolute differences. For relative differences the effect of a more elite sample is even more pronounced. So if cycling is getting more selective of talents, the best will have less margin to the rest.
 
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Roglic and Vingegaard aren't the ones dominating one day races at will. If we're talking about overall strength, then yes.
And I'd say Roglic, Vingegaard, Van Aert, Evenepoel, and MvdP all who some fallability in specific situations, but basically never Pog. Literally does everything at will, apart from getting dropped twice a year in the Tour the past 2 years.

IMO the only thing that speaks for Pog about yesterday is that Strade is probably uniquely suited to pull off a solo like this, the field was lacking the other big dogs and the chase gave up immediately
 
Well, it's true that the gap from 1st to 2nd is greater than the gap from 2nd to 3rd and so forth.

My point is that those differences are more pronounced in a representative sample than in a more selected sample. For the elites, the best will have smaller advantages. The more elite, the smaller advantage.

For a representative sample of 100, the expected gaps (in Z-score, so as measured in σ) from 1st to 2nd to 3rd to 4th are: 0.2726, 0.1730 & 0.1301. For a sample of the top 1 %: 0.1789, 0.1085 & 0.0788. And finally for the top 0.1 %: 0.1574, 0.0947 & 0.0684.

And that is for absolute differences. For relative differences the effect of a more elite sample is even more pronounced. So if cycling is getting more selective of talents, the best will have less margin to the rest.
The comparisons you are making are only sensible if you think that the population as a whole is changing in size. Since the top ~600 riders are in the pro tour, comparing the 99th percentile to the 99.9th percentile makes sense only if the population [which is humans willing and able to become bike racers, who can manage to be discovered and given an opportunity] grows by a factor of ten.

While the discoverability of talent may have grown recently, I don't have a feeling that the general population of people interested in becoming bike racers has changed that much over the years. I'm more inclined to believe that technology has expedited the fulfillment of potential than changed the constituency of the peloton.

If we are comparing the peloton of 2024 to that of 2016, perhaps the population we should be looking at is not the peloton of 2024 but the hypothetical peloton of all bike racers of the last 50 years. Pog is an outlier not just compared to his contemporaries, but also to the Rio-GVAs. We do not expect the outliers in the years-spanning population to be evenly distributed through time. However we do more or less expect the lesser talents, of whom there are a lot more, to be evenly distributed across generations. So if anything is weird, it's that we have 3 to 5 riders who are concurrently able to solo rampage for km after km, but then again sample sizes are so small at this point that we can't really conclude anything.
 
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