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You are here: Home / Cycling / Tour de France Analysis / 2015 Tour de France / Semi-transparency, smoke, mirrors and an illustrative case

Semi-transparency, smoke, mirrors and an illustrative case

Ross Tucker · 21 Jul 2015 ·

Last updated on December 2nd, 2022 at 09:50 pm

Estimated reading time: 4 minutes

Amidst all the talk of transparency in the Tour, Sky announced that they may publish “a few” outcomes, like average power output and average cadence from a stage.

Some quick thoughts on this below:

[ribbon toplink=true]1. All or nothing. Not quite, but there’s power in numbers[/ribbon]

it makes little sense to have only 1 rider/1 team provide data. It would deny the opportunity for comparative understanding. The same goes for any data, otherwise it’s just a case study with a weak frame of reference. I would find it very difficult to interpret one isolated figure.

[ribbon toplink=true]2. Comparative AND longitudinal tracking would provide the greatest value[/ribbon]

That means across time and across riders. Both are necessary – I will try to explain some thoughts that are percolating in my mind, perhaps tomorrow during the rest day. Just as both are necessary, both also make it more difficult to ‘hide’ radical transformations, which is why I doubt this will happen. The same is true for the physiology-performance link. It should therefore be a UCI/WADA led policy, not down to any one team.

[ribbon toplink=true]3. An opportunity to lead the change[/ribbon]

That said, data from the current best team & rider would be very valuable. Sky have an opportunity to lead from front, to take that first step. They came in on a promise of transparency, but as Paul Kimmage correctly identified, it’s proven a challenge. So the opportunity has instead become a burden, and facing increased calls for transparency (most recently from Greg Lemond), we are now being offered “average cadence”.

[ribbon toplink=true]4. Thanks, but I’ll pass on the average cadence & power[/ribbon]

Maybe I am just I’m missing something in the realm of marginal gains & winning behaviours, but average cadence and power for a stage is absolutely useless in terms of the purpose of why the transparency is being called for. So thanks, but no thanks.  And don’t play it off like people aren’t interested in the offer of transparency, because you’re offering nothing worthwhile.

[ribbon toplink=true]5. Semi-transparent = fully untrustworthy[/ribbon]

One thing I believe – half transparency is worse than none, because then you don’t know if you’re being manipulated & what is being denied to you. You are better off saying no thanks to that murky transparency, & rather questioning whether you’re a victim of sleight of hand, smoke and mirrors. To be semi-transparent is to be fully untrustworthy, in my opinion.  And again, this goes for anyone.

[ribbon toplink=true]6. The transparency case of Pinot & insight into the value[/ribbon]

Here is a great example of complete transparency (it would obviously need to be independently collected of course, but the concept is the point). It comes from Thibaut Pinot, 3rd in last year’s race:

http://www.fredericgrappe.com/…/uploa…/2015/03/pinot-ppr.pdf

VO2max 85 ml/kg/min, and able to sustain 5.9W/kg for 45 min. Assuming an efficiency of 23%, then from first principles, it means he’s able to ride at approximately 85% of max for 45 min. For 20 min, 93% max (6.4W/kg) and for 30 min, 89% of max (6.1 W/kg).

Note that doping would influence all the ‘input variables’ – maximum capacity, possibly efficiency (I doubt it though) and sustainable power output as a % of maximum.  The last is the big one – published research has shown that the time to exhaustion when riding at a given % of maximum is increased significantly by doping, so the ‘marginal & magical gains’ happen in the sustainable % of max.  All things being equal, being able to ride even 2% closer to your own maximum is worth around 0.14W/kg, a significant performance difference.

So, if you tracked this kind of data longitudinally, linked to the biological passport, well, hopefully you get the idea of where the numbers might not quite add up. You can (and should) also relate it to concepts of CP and W’ (read up some work by Mark Burnley for more on this)

Note also the evolution of performance characteristics offered by the tables in that article. There is such a thing as typical, and while ‘atypical’ will not prove or disprove doping, it pays to understand it.

Ross

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2015 Tour de France, Cycling, Doping in Cycling, Tour de France Analysis

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