Froome's SRM data on Ventoux

[Dear Wiggo]

Re: Re:

There's a strong inverse relationship between economy (efficiency) and VO2max as measured for a dozen world-class cyclists.

I wouldn't consider an R2 of only 0.41 to be "strong".

Interpretation of the coefficient of determination is actually largely dependent on the context, in some cases a R² of .10 is impressive, while in other situations you're only going to be satisfied with your model if you found a R² of over .90. As we're dealing with physiological data and phenomena that are probably affected by multiple factors, I feel that finding such a coefficient of determination in a bivariate relationship is actually quite impressive. However, in the context we're discussing the matter, we should be warned that, in the sample of that study, there's still .59 (59% of the variance) left that you cannot account for using the relationship between VO2max and Gross Efficiency.

However, more importantly, R² is a sample statistic and the Pearson product moment correlation coefficient is only a point-estimate of the population correlation parameter. Given the low sample size (11) and relatively large standard error (0.25), the actual population parameter for the correlation may differ quite a bit from the value obtained in this sample. As the results section of the paper is severely lacking, I've reanalysed the data using the reported raw data to calculate a confidence interval for the correlation. While my correlation coefficient (-.66) is somewhat different from one reported in the paper (-.64), probably due to the fact the authors rounded the raw data to one decimal, the 95% Confidence Interval for Rho, calculated using the Fisher z' transformation method, is quite wide: 95% CI [-0.901,-0.094]. This indicates that we should not hold too much to exact value of the point-estimate of -.66 (-.64 in the paper), as it may be quite unstable over different samples. To get a more accurate or narrow estimate of the population correlation, we need more data points.

You should see Ed Coyle's paper on efficiency based on Lance Armstrong. That's filled with far worse crapola than only having 11 samples.

 

[WillemS]

Re: Re:

You should see Ed Coyle's paper on efficiency based on Lance Armstrong. That's filled with far worse crapola than only having 11 samples.

Maybe, I'm a bit short on time in the coming weeks. However, despite having only eleven data points, the paper does indicate a negative relationship between VO2max and GE with a confidence level of 95% (alpha of 0.05). However, it does not actually tell us much about the actual size of the negative relationship: It may be substantially smaller or larger than the point-estimate of -.64.

However, there's a bigger problem with using those models to estimate the (im-)probability of Froome's physique:
Those kind of estimations assume that the individual is randomly selected from the population, while we're dealing with a highly selected individual. Sure, we can assume, like some seem to do, that Froome was just that: A random cyclist that somehow got boasted by Sky magic to greatness, but that only leads to circular reasoning: If we assume Froome to be "just a random cycling", then we can use the statistical model to calculate that Froome's supposed numbers are so improbable that we can conclude that he's probably a random cyclist that got boasted by Sky magic. However, that's just circular reasoning, by assuming he was a random nobody, we proof he's a random nobody. That does not get us anywhere.

 

[Dear Wiggo]

Re: Re:

You should see Ed Coyle's paper on efficiency based on Lance Armstrong. That's filled with far worse crapola than only having 11 samples.

Maybe, I'm a bit short on time in the coming weeks. However, despite having only eleven data points, the paper does indicate a negative relationship between VO2max and GE with a confidence level of 95% (alpha of 0.05). However, it does not actually tell us much about the actual size of the negative relationship: It may be substantially smaller or larger than the point-estimate of -.64.

However, there's a bigger problem with using those models to estimate the (im-)probability of Froome's physique:
Those kind of estimations assume that the individual is randomly selected from the population, while we're dealing with a highly selected individual. Sure, we can assume, like some seem to do, that Froome was just that: A random cyclist that somehow got boasted by Sky magic to greatness, but that only leads to circular reasoning: If we assume Froome to be "just a random cycling", then we can use the statistical model to calculate that Froome's supposed numbers are so improbable that we can conclude that he's probably a random cyclist that got boasted by Sky magic. However, that's just circular reasoning, by assuming he was a random nobody, we proof he's a random nobody. That does not get us anywhere.

Surely the explanation of Froome is the best possible combination of attributes (VO2, %VO2 @ LT and efficiency) ever presented by a cyclist? Oh and some crazy adaptive physiology.

That was not revealed by Sky, but hidden by poor tactics, poor bike handling and bilharzia?

That's what we are to believe.

 

[WillemS]

Re: Re:

You should see Ed Coyle's paper on efficiency based on Lance Armstrong. That's filled with far worse crapola than only having 11 samples.

Maybe, I'm a bit short on time in the coming weeks. However, despite having only eleven data points, the paper does indicate a negative relationship between VO2max and GE with a confidence level of 95% (alpha of 0.05). However, it does not actually tell us much about the actual size of the negative relationship: It may be substantially smaller or larger than the point-estimate of -.64.

However, there's a bigger problem with using those models to estimate the (im-)probability of Froome's physique:
Those kind of estimations assume that the individual is randomly selected from the population, while we're dealing with a highly selected individual. Sure, we can assume, like some seem to do, that Froome was just that: A random cyclist that somehow got boasted by Sky magic to greatness, but that only leads to circular reasoning: If we assume Froome to be "just a random cycling", then we can use the statistical model to calculate that Froome's supposed numbers are so improbable that we can conclude that he's probably a random cyclist that got boasted by Sky magic. However, that's just circular reasoning, by assuming he was a random nobody, we proof he's a random nobody. That does not get us anywhere.

Surely the explanation of Froome is the best possible combination of attributes (VO2, %VO2 @ LT and efficiency) ever presented by a cyclist? Oh and some crazy adaptive physiology.

That was not revealed by Sky, but hidden by poor tactics, poor bike handling and bilharzia?

That's what we are to believe.

No, I'm not claiming anything like that, I'm just saying that the statistical reasoning (or 'evidence') used in this thread based on the referenced paper is not entirely valid, from a statistical point of view. It leads to same kind fallacious reasoning seen in some court cases, like a case famous in the Netherlands (the case of nurse "Lucia de B."). The statistical reasoning for her conviction was erroneous, so the verdict was later overturned as there was hardly any additional evidence. However, even though the statistical reasoning was off and therefore not proper evidence for her guilt, that does not imply she was innocent, just that you should not convict her based on bad statistical reasoning.

I'll try to make so time today or tomorrow to write down why I feel the statistical reasoning displayed earlier in this thread is off.

 

[carton]

Re:

Dr. Ferrari: "Certainly to ensure these aerobic powers he must have the same cardiac output of a horse or the same carriage/ peripheral utilization of O2 of a Pronghorn antelope "

Hey, he stole my comp. Feels somehow validating.
...You are fulfilling your destiny, Anakin...

 

[Merckx index]

Re: Re:

In science (not that I'm a scientist), it's quite OK to say we don't know, we don't have enough relevant information, and simply having more unhelpful or unreliable data is not going to help.

When it’s purely a scientific question, sure. But when it has social implications, it’s not that simple. One might argue that the evidence for global warming—certainly the evidence for certain scenarios that might play out in the future--is not as strong as it is for many other scientific views. But the implications of global warming demand that we take a stand. Saying I don’t know, therefore, I will do nothing, is effectively saying one doesn’t believe in the phenomenon. From a practical point of view, there really is no such thing as being neutral on the issue.

This is even clearer in elections, when voting for candidates. One might not have strong feelings about one candidate over the other. Does this mean you don’t vote? Of course not. You try to make a decision, even if it’s highly uncertain.

In the same way, the doping of riders has major implications. Saying I don’t know for a particular rider means one won’t take any action against him, which is just like saying he doesn’t dope. For someone with actual power to take action against a doper, it’s of course more complicated than this, the evidence has to be very strong, but in the Clinic, where we have no power at all other than on public opinion, I think preponderance of evidence is quite a reasonable way to go about things.

No, I'm not claiming anything like that, I'm just saying that the statistical reasoning (or 'evidence') used in this thread based on the referenced paper is not entirely valid, from a statistical point of view.

I believe you’re overthinking this. The key point is that the data don’t support in any way, shape or form a positive correlation, so a very reasonable assumption is that at best (from the point of view of calculating probabilities) one would multiply the probability of having a very high V02max by the probability of having a very high efficiency. IOW, treating them as completely independent of each other.

And the very fact that the sample size is so small just underscores the rarity of high values like these.

 

[bigcog]

Re: Re:

In science (not that I'm a scientist), it's quite OK to say we don't know, we don't have enough relevant information, and simply having more unhelpful or unreliable data is not going to help.

When it’s purely a scientific question, sure. But when it has social implications, it’s not that simple. One might argue that the evidence for global warming—certainly the evidence for certain scenarios that might play out in the future--is not as strong as it is for many other scientific views. But the implications of global warming demand that we take a stand. Saying I don’t know, therefore, I will do nothing, is effectively saying one doesn’t believe in the phenomenon. From a practical point of view, there really is no such thing as being neutral on the issue.

This is even clearer in elections, when voting for candidates. One might not have strong feelings about one candidate over the other. Does this mean you don’t vote? Of course not. You try to make a decision, even if it’s highly uncertain.

In the same way, the doping of riders has major implications. Saying I don’t know for a particular rider means one won’t take any action against him, which is just like saying he doesn’t dope. For someone with actual power to take action against a doper, it’s of course more complicated than this, the evidence has to be very strong, but in the Clinic, where we have no power at all other than on public opinion, I think preponderance of evidence is quite a reasonable way to go about things.

So burn the witch then in the court of public opinion, albeit a small "court", but magnified by social media ?

 

[WillemS]

Re: Re:

No, I'm not claiming anything like that, I'm just saying that the statistical reasoning (or 'evidence') used in this thread based on the referenced paper is not entirely valid, from a statistical point of view.

I believe you’re overthinking this. The key point is that the data don’t support in any way, shape or form a positive correlation, so a very reasonable assumption is that at best (from the point of view of calculating probabilities) one would multiply the probability of having a very high V02max by the probability of having a very high efficiency. IOW, treating them as completely independent of each other.

I disagree with you here, but I will explain that tomorrow, as I think that'll take some time and I don't have the luxury of that now.

And the very fact that the sample size is so small just underscores the rarity of high values like these.

Eh, no. A small sample size gives less information about the distributions in the population, not more. By your logic we would be better off measuring even fewer cyclists, as that would give us more certainty about the population distribution. The reverse is actually true, the smaller the sample, the greater the uncertainty in parameter estimation, that's why the confidence interval of the correlation parameter, see my previous post, is so wide.

As a thought experiment, if the number of people having such a rare combination of VO2max and efficiency is only 1 in every 100 (still quite common, but that actually strengthens the point), the probability of missing such a cyclist in a small sample is much larger than in a large sample.

If we assume a sufficiently large population (we usually do, else frequentists statistics does not really work well), then the probability of missing such an individual in a sample of eleven is (99/100)^11 = ~0.90%. If we increase the sample size to a more reasonable 40, the probability of missing someone like that is reduced to ~0.67.

 

[jalep]

Re:

Dr Ferrari on Froome's data on Ventoux :
http://www.53x12.com/do/show?page=forum.thread&id=7367

"Ho già commentato a suo tempo la prestazione di Froome sul Ventoux.
Picchi di 1000w per pochi secondi sono possibili, anche se tutti da verificare .
Insolita invece è la Fc a soli 160/min : può darsi che questa sia la FCmax di Froome, anche se anomala per l' età e per le caratteristiche aerobiche esplosive del britannico.
Di sicuro per garantire queste potenze aerobiche deve esserci una gittata sistolica da cavallo o un trasporto / utilizzo periferico dell' O2 da antilope Pronghorn"

"I've already commented at that time Froome performance on Ventoux.
Peaks of 1000w for a few seconds are possible, but they should be verified.
Unusual however is the hr of 160/min: it may be that this is the HRmax of Froome, but it would be odd for his age and for his characteristics of aerobic explosiveness.
Certainly to ensure these aerobic powers he must have the same cardiac output of a horse or the same carriage/ peripheral utilization of O2 of a Pronghorn antelope "

hahahhaha... finally the explanation. A galloping horse uphill - 02 saturation of a pronghorn antelope.
I'm almost satisfied Still think a satellite controlled implant is somehow involved.

 

[Merckx index]

Re: Re:

Eh, no. A small sample size gives less information about the distributions in the population, not more. By your logic we would be better off measuring even fewer cyclists, as that would give us more certainty about the population distribution. The reverse is actually true, the smaller the sample, the greater the uncertainty in parameter estimation, that's why the confidence interval of the correlation parameter, see my previous post, is so wide.

That's not what I meant. What I meant was that the sample size of athletes with very high efficiencies is small because such efficiencies are very rare. Of course it's harder to draw conclusions from a small sample size, but when you are looking for high efficiencies and the sample you come up with is small, that means they are rare. I wasn't making any assumptions about the probability of finding someone with a rare combination based on the sample size.

As a thought experiment, if the number of people having such a rare combination of VO2max and efficiency is only 1 in every 100 (still quite common, but that actually strengthens the point), the probability of missing such a cyclist in a small sample is much larger than in a large sample.

If we assume a sufficiently large population (we usually do, else frequentists statistics does not really work well), then the probability of missing such an individual in a sample of eleven is (99/100)^11 = ~0.90%. If we increase the sample size to a more reasonable 40, the probability of missing someone like that is reduced to ~0.67.

You mean 0.90, not 0.90%. But the sample is not eleven. The efficiencies of hundreds if not thousands of individuals have been published, and as I noted upthread, the results of these studies indicate that efficiencies above 23% are very rare. Yet in the graph that Coggan posted, 8/11 subjects have an efficiency > 24%. Therefore, it’s not representative of most of the literature.

Why the discrepancy? I believe that graph was taken from a study of elite riders. I know Coggan is pushing the idea that efficiency can be increased with training, and one might argue that elite riders therefore have a much higher mean efficiency than that of the population at large, or even of trained/competitive riders that have been the subjects of some studies. But it would take a lot more data to establish this (both that elite riders have a much higher mean efficiency, and that this is a result of training), and he noted in one of his posts that these data don’t exist. I’d expect this, given the secrecy of teams, the reduced value of such data in the power meter age (noted by Alex), and the relative infrequency in which elite riders end up in published studies.

I also reiterate the point I made in my previous post, that while the ACSM formula apparently assumes a 24% efficiency, this is at odds with a lot of the literature, and of course that formula is meant explicitly to apply to non-trained as well as trained cyclists.

 

[acoggan]

Re: Re:

[while the ACSM formula apparently assumes a 24% efficiency, this is at odds with a lot of the literature

Now try it again, but for a power of, say, 150 W.

 

[jilbiker]

A HR of 160? When I heard about that figure on Ventoux, I said absurd. Its impossible except....perhaps some form of Beta-blocker. There was a time I was taking a beta-blocker for medical reasons, it was amazing when I played high intensity games like squash, my heart was literally silent, almost oblivious to what was going on outside. As long as my legs were good, I could play for hrs.

I think we may have hit Froome's amazing juice, its some form of beta blocker. I wonder if they test for that in cycling? I know one sport that they test for that - Archery - because you rest the bow on your chest so a silent heart means you bow is more steady. Even if they test for that in cycling he may have a new not detected one.

 

[Merckx index]

Re: Re:

[while the ACSM formula apparently assumes a 24% efficiency, this is at odds with a lot of the literature

Now try it again, but for a power of, say, 150 W.

Still higher than most of the studies I have seen, many of which include cyclists well over that 150 watts figure. E.g., here's another one of competitive cyclists with an average of about 360W and 76 kg. The formula predicts 23.4%, the actual mean was about 19% efficiency:

http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3763294/

Plus the studies claiming no difference between competitive/trained, even elite, cyclists and untrained ones.

Clearly there is a lot of disagreement in this field.

 

[acoggan]

Re: Re:

[while the ACSM formula apparently assumes a 24% efficiency, this is at odds with a lot of the literature

Now try it again, but for a power of, say, 150 W.

Still higher than most of the studies I have seen

The answer, for those who might still be following along, is 20.6%.

The point, of course, is that 1) gross efficiency increases with increasing absolute exercise intensity, and 2) an efficiency of 24% at 400 W is not any higher that what you would expect for an UNtrained individual (if they could only achieve steady-state at that exercise intensity).

 

[Merckx index]

Re: Re:

[while the ACSM formula apparently assumes a 24% efficiency, this is at odds with a lot of the literature

Now try it again, but for a power of, say, 150 W.

Still higher than most of the studies I have seen

The answer, for those who might still be following along, is 20.6%.

The point, of course, is that 1) gross efficiency increases with increasing absolute exercise intensity, and 2) an efficiency of 24% at 400 W is not any higher that what you would expect for an UNtrained individual (if they could only achieve steady-state at that exercise intensity).

But there is disagreement over that, too. The study I linked to in my previous post measured efficiency at 250W, and it was still far below the predicted value of 22.6%. There are other studies I've seen claiming specifically that efficiency does not increase with effort. E.g., in this study the competitive group put out about twice as much watts as the untrained group, but the GE was the same:

http://www.ncbi.nlm.nih.gov/pubmed/8933490

I now see that they say their method of measuring GE is somewhat different from the usual one. How much difference does that make? (not referring to the above link, but to the link in the previous post).

 

[acoggan]

Re: Re:

here's another one of competitive cyclists with an average of about 360W and 76 kg. The formula predicts 23.4%, the actual mean was about 19% efficiency:

http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3763294/

Note that 1) power was measured (some might say estimated) using a Kingcycle air-braked cycle, and 2) the subjects were required to do the TT in the aero position.

 

[acoggan]

Re: Re:

There are other studies I've seen claiming specifically that efficiency does not increase with effort.

Over a narrow range, perhaps, but over a wide range that isn't what happens. For example, here are my wife's data from the one-and-only VO2max test she ever did (note how the slope is ~4% lower than the ACSM equation, i.e., she is more efficient than expected based on studies of untrained individuals):

 

[Merckx index]

Re: Re:

Over a narrow range, perhaps, but over a wide range that isn't what happens.

I understand there’s going to be some increase, that follows from the definition of GE, and the fact that there is a basal energy use. You begin with essentially 0% efficiency, because you’re breathing and using the oxygen, but not putting out any external force. As soon as you start putting out this force, your efficiency has to increase. The question is, how much of the increase in efficiency with power output is due to this, and how much is due to other processes that might be stimulated by exercising at increasingly greater intensity?

The four links I originally posted, several pages upthread now, seem to indicate the increase lessens as power goes up, which is what you'd expect if most of it is due to the basal effect. In the first study, they reported an increase from 130 to 165 to 230 W, but apparently nothing beyond that, though they didn't show the data.

http://www.researchgate.net/profile/Asker_Jeukendrup/publication/12050999_The_reliability_of_cycling_efficiency/links/0fcfd50b07fb536556000000.pdf

In the second study, the competitive group, with a mean V02max of about 60, showed increased efficiency as the W went up from 40-120W, but at 250W and 80% V02max, they were still at just 21.0% efficiency (compared to about 22.5% predicted from ACSM), and apparently this was not significantly different from the efficiency at 120W.

http://onlinelibrary.wiley.com/doi/10.1113/jphysiol.2005.101691/full

In the third study, the competitive group put out 10-15% as much power as the untrained group at 75% V02max, but their efficiency was not significantly different from the non-competitive group. So despite being measured at higher power, there was no difference, though perhaps you could argue the power difference was not enough to reveal this.

http://europepmc.org/abstract/med/8933490

In the fourth study, the L and M groups showed no difference in GE at 165W and at the final, highest power, about 350W. The elite group, with a mean V02max of 75, showed only a slight, non-significant increase in this transition, from about 18 to 19%. Their final power was about 400W, though efficiency could not be measured at this point.

Fig. 3 is particularly instructive. It shows efficiencies rising up to about 235W (though only the rise to 165W was apparently significant), in agreement with other studies, but then levelling off, at values still below 20%. This is actually somewhat consistent with your wife's data, in that she shows a rise up to about 260W, except that in this study, the rise is not linear--just as one would expect if much of it were from a basal value--and the plateau value is well below your wife's.

http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.469.3228&rep=rep1&type=pdf

I also want to point out that this last study was a direct response to the study that you alluded to upthread, where the graph showing an inverse relationship between V02max and efficiency was published:

http://www.ncbi.nlm.nih.gov/pubmed/?term=Lucia+AND+Hoyas+AND+efficiency

The authors of the fourth study I just summarized questioned the validity of this latter study, given that the very high efficiency values they reported are inconsistent with a great deal of other work, as I have been mentioning.

Again, I'm no expert in this field, but I think the notion that efficiencies > 23% are common is highly controversial, you and your wife notwithstanding. Certainly > 25%.

Not saying you're wrong, no doubt there are a lot of critical details in such studies I'm not aware of. I am saying some people who work in the field don't seem to agree with you.

 

[Alex Simmons/RST]

Re: Re:

In science (not that I'm a scientist), it's quite OK to say we don't know, we don't have enough relevant information, and simply having more unhelpful or unreliable data is not going to help.

When it’s purely a scientific question, sure. But when it has social implications, it’s not that simple. One might argue that the evidence for global warming—certainly the evidence for certain scenarios that might play out in the future--is not as strong as it is for many other scientific views. But the implications of global warming demand that we take a stand. Saying I don’t know, therefore, I will do nothing, is effectively saying one doesn’t believe in the phenomenon. From a practical point of view, there really is no such thing as being neutral on the issue.

This is even clearer in elections, when voting for candidates. One might not have strong feelings about one candidate over the other. Does this mean you don’t vote? Of course not. You try to make a decision, even if it’s highly uncertain.

In the same way, the doping of riders has major implications. Saying I don’t know for a particular rider means one won’t take any action against him, which is just like saying he doesn’t dope. For someone with actual power to take action against a doper, it’s of course more complicated than this, the evidence has to be very strong, but in the Clinic, where we have no power at all other than on public opinion, I think preponderance of evidence is quite a reasonable way to go about things.

I'm not saying we shouldn't seek better evidence, just that more anonymous speculation on social media based on anecdote, confirmation bias and more W/kg estimates or even power files isn't it.

The issue of making a decision isn't really relevant. We don't vote for who is/is not doping. So doping is a bit more like a science question - it requires valid evidence to a certain standard. I'm just talking about what results in a sanction rather than the court of public opinion.

What matters is finding ways that will better catch those that dope. That's hard unfortunately (with perhaps the exception of those for whom it's an IQ test or are just randomly "unlucky"). Power data is fun to talk about but I'm afraid it's not a dopeometer.

Q: Which riders are such power estimates or data telling us that we need to target that are not already being targeted for anti-doping activity/checks?
A: None.

The problem is with the efficacy of legitimate anti-doping efforts.

Of course we could just lower the standard of evidence required or put it to a clinic vote.

 

[DirtyWorks]

Re: Re:

[quote="Alex Simmons/RST]
What matters is finding ways that will better catch those that dope. That's hard unfortunately (with perhaps the exception of those for whom it's an IQ test or are just randomly "unlucky"). Power data is fun to talk about but I'm afraid it's not a dopeometer.[/quote]

Actually, power data would work as a dopeometer, but it requires lots of samples, over a long time period from each athlete. In this way the bio-passport is a much better idea.

The bottom line is the federation is permitting doping. They could sanction Horner at least. Instead, they blacklist a top-20 TdF rider to not even pro continental. It reminds me of Francisco Mancebo.

The bio-passport probably works pretty well, especially with the steroid module coming online. At least cycling has no interest in running a clean sport. We know the IAAF and FIFA aren't interested.

 

[Random Direction]

Re: Re:

AST: "the problem is with the efficacy of legitimate anti-doping efforts.

Of course we could just lower the standard of evidence required or put it to a clinic vote."

Nope to both of these. The problem is cultural on the part of the entire UCI community: UCI, riders,managers, sponsors, announcers, doctors, sports scientists, nutritionists, motomen,etc. More tests won't do anything if the regulator has a vested interest in an outcome. There won't be a efficacious anti-doping regime if those who get busted know that the regulator is dependent, not independent. And therefore the whole anti-doping system is not legitimate.

 

[Alex Simmons/RST]

Re: Re:

Actually, power data would work as a dopeometer, but it requires lots of samples, over a long time period from each athlete. In this way the bio-passport is a much better idea.

Convince me of how power data can be a dopeometer.

Let's put aside the (not inconsiderable) practical issue of obtaining consistently accurate data. Assume that's not an impediment.

How would having power data result in a doping sanction?

 

[Alex Simmons/RST]

Re: Re:

AST: "the problem is with the efficacy of legitimate anti-doping efforts.

Of course we could just lower the standard of evidence required or put it to a clinic vote."

Nope to both of these. The problem is cultural on the part of the entire UCI community: UCI, riders,managers, sponsors, announcers, doctors, sports scientists, nutritionists, motomen,etc. More tests won't do anything if the regulator has a vested interest in an outcome. There won't be a efficacious anti-doping regime if those who get busted know that the regulator is dependent, not independent. And therefore the whole anti-doping system is not legitimate.

Oh I agree. IOW, as I say, the current system lacks efficacy.

Legit anti-doping efforts includes lots of things. Better and more frequent testing, better/stronger investigative resources and processes with appropriate powers, significantly increased resources (probably x 2 orders of magnitude*), proper independence of the process from those with a vested interest, better education and support for those directly involved with riders and management, strategic means to reduce the need/incentive to dope (e.g. health care programs, race programs that make sense, professional and ethical training management, much better process for rider contracts, better security for teams and staff), removal of known enablers from the sport altogether, global political will and so on.

I however, like you, am not holding my breath.

My second suggestion was just me being facetious, hence the emoticon.


* consider that the world's top sports stars each earn more than the combined global budgets of the world's anti-doping agencies. Heck, what do top sports teams pay in transfer fees? It's not really a fair fight. Never will be.

 

[miha1234]

Re:

A HR of 160? When I heard about that figure on Ventoux, I said absurd. Its impossible except....perhaps some form of Beta-blocker. There was a time I was taking a beta-blocker for medical reasons, it was amazing when I played high intensity games like squash, my heart was literally silent, almost oblivious to what was going on outside. As long as my legs were good, I could play for hrs.

I think we may have hit Froome's amazing juice, its some form of beta blocker. I wonder if they test for that in cycling? I know one sport that they test for that - Archery - because you rest the bow on your chest so a silent heart means you bow is more steady. Even if they test for that in cycling he may have a new not detected one.

This is nonsense, if you have every used beta-blockers you would know that your heard rate is suppresed and when you try to do some intense workout you can barley move...
If he would used Beta-blockers he would be the last one on every climb...

 

[Roninho]

Re: Re:

AST: "the problem is with the efficacy of legitimate anti-doping efforts.

Of course we could just lower the standard of evidence required or put it to a clinic vote."

Nope to both of these. The problem is cultural on the part of the entire UCI community: UCI, riders,managers, sponsors, announcers, doctors, sports scientists, nutritionists, motomen,etc. More tests won't do anything if the regulator has a vested interest in an outcome. There won't be a efficacious anti-doping regime if those who get busted know that the regulator is dependent, not independent. And therefore the whole anti-doping system is not legitimate.

Agreed.
Everybody that was somewhat involved in cycling knew what the situation was regarding blood-doping in the 00s. The riders, the team staff and the uci. Some teams organized it, others didnt do team wide organized doping they knew the riders where doing it. And if you look at the conversations between for example rabobank and the uci medical guys then the UCI was simply aware of it as well (in the best case scenarion, worst case they actively looked the other way).
This was a culture of doping and an organized system that facilates and tolerates doping.

Now we have had multiple big scandals forcing some people to exit the sport, but the reality is that it has just removed some individuals and sponsors from the sport. It has done nothing against the organized system and culture. A bunch of DS that were involved in the mid 00s are still present. Riders who where the top dogs in that period are still around and performing. Riders from this period are now all aboard on teams as management/trainer etc. The UCI has not changed. etc etc.

The reason is simple: Everybody in the top in this business has a history. Either they doped, or under their watch as DS or UCI it happened and they knew or worse they facilitated it.
If you actively want to end doping it will result in dopers being taken down. And many of those want to take others down with them. See Rasmussen, see Landis. And that is what stops the top decision makers from really trying to stop doping. It will eventually result in huge changes of the business landscape with likely a lot of the current players (including themselves) not involved.