Friday, July 19, 2013

All Things in Moderation. Except Science.

This is my eighth year of blogging. It's a personal thing for me. I enjoy writing about training and racing with power. It's just stuff. Pub chat fodder for those four sad guys that talk about power meters in pubs. You know who you are. It's OK to come out and admit it, there's nothing wrong with it.

Occasionally I post an item that seems to be actually helpful to people, such as items on performance testing or indoor training. By posting I learn things and that's enjoyable. Hopefully others learn too. And I make mistakes. It happens.

I think I've held pretty well to the purpose as stated in my very first post.

I also used the blog to help me through difficult times, as longer term followers would be aware through sharing some of my experiences of getting back to racing after my 2007 accident and amputation. Where possible I tied the two themes together.

It's not a commercial blog and the subject matter is reasonably esoteric, and the following is modest with views numbering in the hundreds of thousands, not millions.


I also know that public online interaction forums require moderation. Again it's mostly to keep spammers at bay, but occasionally some stretch the bounds of reasonableness and need to be reeled in or reminded of some basic netiquette. Troll watch duties as well. Sometimes you forget to check the moderation queue for comment that require moderation and they get posted a bit late.

I am a forum moderator myself, at the wattage forum on Google Groups which grew from modest beginnings in 2001 and was originally hosted on Topica. Want to pull apart anything to do with power and cycling? That's the place to do it. The archives are a gold mine of information, and the early days had a high signal to noise ratio. Only very rarely does moderation occur there, it's mostly self policed and the 10,000+ crowd are generally technically or scientifically oriented, so bullshit generally gets called out early and dealt with.

or Censorship?

But what I've never understood is why some forums or blogs dedicated to performance and/or training and racing would want to prevent actual relevant science or scientific discussion from being published/referred to.

I first encountered this a few years ago when I was banned by a triathlon forum owner from posting to the Slowtwitch forum. My crime? I wanted to know why they were persistently censoring the publication of a link to new published scientific research related to pedalling a bike. They didn't like the subject matter, nor my criticism of such censorship, so I was shown the electronic door and all evidence of the matter wiped. I was not offensive, I did not abuse, swear or curse at others, I did not break published forum rules. OK, it's their privately owned business, they can do what they like and they are large so what does it matter?

But it made me think. If you censor science, or discussion of science, is it really a place worth visiting? Well obviously lots think so, because such things are but minor ripples in the ocean of posts about saddle height, cadence, new bike frames, paleo diets, and the inevitable sarcastic pseudonymous responses.

So hooray for science. Perhaps.

Fast forward to a blog followed by many who, like me, enjoy their science in accessible form - the guys at The Science of Sport blog. I've followed it for a number of years, pretty much since it began in 2007. They dissect performance matters from a range of sports, in particular running, and introduce various topics for discussion. All good stuff and I think they do a good job of it.

Eventually they started writing about cycling performance like this one talking about the 2008 TdF and the all pervasive issue of doping. As they began to inform themselves on such issues in the cycling world, they also joined the bandwagon of estimating power from climbing speeds / VAM, and what we can learn from such information. They also began to suggest what is and is not physiologically plausible sans doping.

In the early days of such posts, I helpfully explained to them via the blog comments one of the difficulties in using climbing speed to estimate power, i.e. the large unknown factor of wind, and they got that message loud and clear. They even referenced my comments in subsequent posts. And they have usually referenced the issue of wind confounding such estimates whenever this topic comes up.

In general they have also tried to steer people away from the folly of using individual data points on climbing speed (or power estimations from them) as some means to infer doping status, but rather to consider the longer term trends. All good stuff.

Wham bam, thank you pVAM

Lately though they have been publishing a lot of information derived by the pVAM methodologies, which I am less enamoured with for a couple of reasons.

Firstly, whether intentional or not, it encourages the invalid use of such information as a "dopeometer" and secondly, I'm unconvinced they have sufficiently critically assessed the validity of the pVAM and dpVAM model. I think this is bordering on a desire for publicity than on good science. Not nearly to the extent that Antoine Vayer's occasionally dodgy maths does, but are they pushing the "Publish" button a little too quickly at times?

I get that their blog is designed to provoke discussion about sports science matters, make things accessible and to make people think more critically about stuff, and that's a good thing - but when you represent yourselves as "The Science of Sport" and present methodologies or models under that masthead that have not been peer reviewed or are based on known/published science, or without having done critical assessment against existing models, well I just think more caution is warranted before lending an overweighted amount of credibility to such things. Perhaps greater emphasis is needed on making it clear what is opinion and what is actually science.

I could of course be completely wrong and talking out of my arse. Happy to stand corrected. Most of us out here is the interwebs are not well versed in understanding the credibility differential of such material published by scientists under a heading of "The Science of ...".

It's difficult for me to strongly criticise since I'm not a scientist and not well versed in such peer review, so I just occasionally chip in with my amateur 20 cents worth and hopefully it generates some thoughts, at least in a pub chat kinda way. At the least I have a personal sense of contributing in some way, however insignificant that contribution may actually be. Which is what I did four days ago when I pointed out an error in a statement they made about the pVAM method.

This is what was written on their post:
"The error in the wind component is much larger, which has implications for the assumptions of cdA (drag co-efficients). In the model, however, the relative contribution of the wind during climbing is small, and so the total error is actually not too bad."

I then pointed out the obvious (to me anyway) physics mistake by posting this to the comments:

"The error in CdA isn't the issue, but the wind velocity most definitely is. Ignore that and you may as well throw darts at a W/kg board. That interpretation suggesting the error introduced by wind is, frankly, nonsense.

Even modestly different wind conditions for the same VAM can see estimates of power over a 1W/kg error range. The wind for the Armstrong/Pantani ascent was quite different to this year's ascent."

Perhaps my tone wasn't ideal, but nonsense is nonsense, right? And scientists generally have pretty thick skin.

For anyone wondering what I'm on about, when estimating power from steep climbing speed, if your assumption of the rider's coefficient of drag is (CdA) is wrong, well it doesn't generate a really big error in the estimate of power. It's not "sensitive" to that particular assumption. But it is most definitely sensitive to the wind velocity assumption. Get that wrong and the numbers can easily be wrong, and by a large margin.

Comment MIA

Then yesterday another SoS post about Alpe D'Heuz climbs and the pVAM and dpVAM methods appeared, so I thought I would post a comment with a link to djconnel's cool blog post which introduces a critical appraisal of the pVAM model, from both a physics and physiological basis, by comparing it with actual published and well established science models. I also provided links to a couple of charts about ADH climbing times that were easier to read than the ones they posted up.

As scientists, you think they might be interested in discussing the limitations of a model they are presenting as highly credible, or consider how it might be improved or under what circumstances we need to be very careful in using it.

Well for starters, I suggest using actual physics when estimating power from climbing speed, and also checking how the model stacks up with established physiological models.

Except my comments to them are now being moderated and have not appeared.

As Robert Chung would say, Hmmm.

Read More......

Wednesday, July 17, 2013

The Elusive Dopeometer

Readers of this blog no doubt have seen a number of examples I give about the (in)accuracy of estimating power from climbing speed, and in particular the confounding impact of wind on such estimates. Any climb with wind is going to be subject to error, and it doesn't take much wind at all to introduce quite a sizeable error.

There was my 2010 post about Alpe D'Huez ascent times, timely given the dual ascent this year, and my item yesterday about the significant error introduced by that great unknown, the wind.

I consider such W/kg estimates to be fine for a bit of pub chat fodder, but as a serious means to detect doping, really? I'll get back to this in a bit.

What has been more amusing than climb power estimates was more twitter/blogger/forum sphere musings on the power differential estimates from the Stage 11 individual time trial. Seriously. People are actually thinking they can reliably estimate the difference in power output of riders based solely on their time or speed in an individual time trial.

What complete and utter nonsense.

Aside from that affront to physics by Gazzetta dello Sport's Claudio Ghisalberti, there was also a post by the somewhat infamous Dr Ferrari about speed differentials from the same ITT and what that meant for power differences. Now Ferrari did say that this assumes all riders have the same "aerodynamic efficiency" as he calls it, which he then points out they don't.

So, given that they don't, why would you then proceed to produce and publish numbers as if they were all the same? More nonsense.

All this does is misinform the debate and feed Internet trolls.

OK, so people get the concept of comparing climbing performances (or attempting to) using power to body mass ratios, the now ubiquitous W/kg numbers. But can you do something similar with time trials over flatter terrain?

If you want to normalise flatter terrain ITT data, then you can make a reasonable stab at the differential of each rider's power to aerodynamic drag ratios i.e. the rider's time trial wattage output divided by the rider's coefficient of drag area (CdA), measured in units W/m^2. Of course this assumes the same wind conditions apply for the riders being compared which can be problematic in itself when the riders being compared are on course several hours apart (as was the case for instance with Tony Martin and Chris Froome).

On flatter ground, the higher your W/m^2, the faster you will go. This neat chart courtesy of Robert Chung shows the close relationship between flat road speed and power to aero drag ratio:

Hence we can reasonably say that the faster rider on the day has a higher W/m^2 (putting wind differences to one side of course). This is the flat land equivalent of the hill climber's W/kg.

What we can't say however is how much of that speed difference is due to higher power output and how much is due to a lower CdA. Indeed, it's possible for a rider to produce less power than another yet go faster if their aerodynamics is superior.

I’ve dealt with many riders of similar morphology who have significantly different CdA. I have a former team mate who was same height and weight as me (actually he was a bit heavier) and we have similar power output as well (mine was a bit better), yet his CdA is ~ 20% less than mine on our respective pursuit bikes. Our equipment was very similar. His natural body shape on the bike means he is just far more aerodynamically gifted. That’s why he medals at worlds and I don’t even make state finals.

Unless you know each individual rider’s CdA, attempting to derive power differentials from ITT speed is just pissing in the wind.

In this 2011 post I provided a short snapshot into this, with data provided by Andy Coggan who devised a draft variation to his Power Profiling tables, this time creating an Aero Profiling table:

The top of that list is a good indicator of what's required to set/break Boardman's hour record of 56.375 km (35.030 miles), now classified by the UCI as "best human effort".

Now if people think getting pro riders or their team management to release their power data is proving difficult, try getting their wind tunnel or aerodynamic field test data.

The Dopeometer

OK, so let's get back to obtaining riders' power meter data and using it as a dopeometer.

This seems to be a popular request. Greg Lemond wants the data released, as do the Bike Pure people. All over the net on forums and blogs and twitter and so on people are calling for the data to be released. The point being such transparency is a good thing, and I have no argument with that. But will it actually help? Or will it just be a public relations exercise and not really provide any additional insight into the issue?

Let us for a moment imagine that tomorrow morning we all wake up to find Froome and his professional riding colleagues and competitors release their power meter data.

Then what?

Will having more certainty over the accuracy of power data help us confirm or deny doping status?
A: No. All it will do is re-emphasise confirmation bias for those with an opinion one way or another.

What power output will confirm doping and what won't?
A: Nobody actually knows. All we have is differing opinions on the subject of what constitutes possibly suspicious performances. Yet people already have their suspicions. An SRM file isn't going to change that.

Just where is the doping power plausibility line? Can we really assign such a line? Is 6.2W/kg for an hour proof? 6.3? 6.4? 6.41?
A: In reality we simply can't put a clean line in the sand. The line for each rider may be different, and the line may vary depending on context. How long was the effort? When did it occur? What were the environmental conditions? How steep was the climb? Was it solo or with others? Was it a consistent effort or variable? Who responds better to doping?

Will it change which riders should be placed under scrutiny?
A: No, we already know who they are. They ride bikes professionally and at the elite level, win races and/or go up hills faster than the rest of us mere mortals.

Will it make doping detection easier?
A: Hardly, since proof of doping requires a positive test, a confession or reliable testimony and evidence, and we already know who should be scrutinised.

Will it prove riders aren't doping?
A: Of course not. Since it assumes there is an arbitrary upper power limit for doping to be confirmed, it does nothing to pick up any doping by riders who are below whatever that arbitrary limit is. No green jersey contender for instance is going to out ride the GC contenders on major cols. Hence such data only serves to tell us what we already know, i.e. a handful of riders finished ahead of their competition on the mountain top finishes.

Can power data be manipulated?
A: Yes, of course it can. Accidentally, inadvertently or deliberately. So then we'll have those on the conspiracy trail of a new doping detection avoidance technique of "data doping". Since we already know the amount of slop in power estimates from other methods, then fiddling with the numbers means no-one can really know if numbers are fiddled or not. There are of course forensic data analysis techniques that can identify some examples of that, but only if crude data manipulation methods are used. If riders and their support people are clever enough to manipulate blood to avoid detection, I'm pretty sure they'll be able to work out how to manipulate data to avoid detection.

Has "data doping" happened before? 
A: Sadly, yes as this example shows when a rider attempted to use doctored power data to prove a performance benefit from using a particular type of cycling equipment. Fortunately in this case the fraud was detected - but it took a Professor from Berkeley to point it out.

What would it cost to run such data collection in an independent manner, and free from possible manipulation?
A: Millions of dollars. Think about the number of bikes in the ProTour, the need to carefully calibrate say 1,000 SRMs, to have non-tamperable data loggers, to ensure all riders correctly perform zero-offset checks before and during races. The data collection process. Staff to manage this. Millions of dollars that perhaps would be better directed at improving doping control processes, technology, reducing testing costs, and simply performing more tests and more frequently testing in and out of competition.

I get that people want to see the data, and hope it's a short cut way to provide certainty around establishing whether a particular rider is doping. I get that release of such data may appear to increase transparency. But at the end of the day we'll just be back to where we started before all this data becomes available: i.e. none the wiser about riders' doping status.

SRM make a fine power meter, but it's not a dopeometer.

Read More......

Monday, July 15, 2013


There seem to be a lot of windbags lately.

Once again people in the twitter/forum sphere are ignoring just how much wind affects speed for the same power output, even on steep climbs where overcoming gravity is the major energy demand factor.

Let me give you a basic example.

Let's take a rider with Pro Tour level power to body mass capability as follows:

400W Functional Threshold Power
69kg body mass
and allow 8kg for bike + kit

So that's a rider with an FTP of 5.80W/kg

A few assumptions about a point along a typical climb:
Gradient: 8%
Air Density: 1.065kg/m^3 (e.g. 1010hPa, 20C, 50% humidity @ 1000m altitude)
Rolling resistance: 0.0045
CdA: 0.350m^2
Wind: none

At that point on the climb, at 400W their speed would be 20.6km/h. But that of course assumes there is zero wind.

Conversely, if we have a rider climbing an 8% gradient at 20.6km/h with those air density, mass and rolling resistance values, then they will be required to output 5.80W/kg.

Pretty straightforward so far.

So what happens to our estimated power based on speed and gradient etc if there is some wind but we don't account for it? In other words we measure their speed as 20.6km/h, but we do not know the actual wind conditions?

Well let's assume we know precisely the mass (body and the bike + kit), rolling resistance, air density and rider's coefficient of aero drag (CdA). I'll get to errors in those later.

If there was an overall tailwind, then for the same power output the rider will climb faster. But if we don't account for that tailwind when estimating power output for that faster speed, then we will over estimate the rider's power output. And conversely, if we don't account for any headwind, we will under estimate the rider's power output.

So just how wrong can we get power estimates if we rely on climbing speed alone and do not account for the wind? Well to save you the trouble, I've plotted the W/kg actually required to climb at 20.6km/h with wind speeds ranging from a tailwind of 5m/s to a headwind of 5m/s.

Just so it's clear, this chart shows the power to body mass required to ride at 20.6km/h on that 8% gradient and with the other assumptions earlier listed. We can see just how much the wind conditions impacts the power required to maintain a given speed.

Hence, if you do not know the wind speed, then you have quite a sizeable potential error in any estimate of power from the rider's speed.

I've colour coded the Beaufort Wind Scale ratings on the chart. Of those shown on chart for instance, a Gentle Breeze is when light flags are extended. Even riding into a light breeze of 2.5m/s (that's not enough to extend light flags) means an error in calculating W/kg of over 9%! If the wind were a gentle head breeze of 4.2m/s, then the error in power estimated from speed increases to over 17%!!

Let's put that into perspective. A 10% power variation about the variation in power output for a trained rider from out of form / off-season to their peak fitness levels. That's the level of potential error in power estimates from a light breeze we can just start to feel on our skin.

Of course the actual wind speed and direction relative to a rider changes during a climb, some climbs have more shelter than others, the amount of shelter varies (trees, vans, people, other vehicles in race convoy etc), the wind does change direction due to the shape of the mountain itself, and of course the road itself changes its direction relative to the prevailing wind. Then there is the impact of drafting other riders, which is more of a factor with increasing headwinds.

So no doubt there are some swings and roundabouts, but who can really tell what the actual wind is? Answer: No-one.

If you can see flags flapping, then forget about making sensible estimations of riders' power to mass values. And if you can't see them flapping, then at least include some error bars in the estimate, unless you know exactly what the wind was doing.

What about the other assumptions, such as CdA, Crr, mass of bike + kit?

OK, well let's examine the impact of getting each one of those assumptions wrong by say adding 10% to each. What does that do to the power required to ride at that same speed?

CdA @ 0.385m^2
Power for same speed = 404W (+0.9% error)

Crr @ 0.00495
Power for same speed = 402W (+0.5% error)

Bike+kit mass @ 8.8kg
Power for same speed = 406W (+1.4% error)

We can see that error in estimates of power from climbing speed are less sensitive to errors in CdA, Crr and bike/kit mass*, and are dwarfed by the error introduced by wind, and wind is rarely, if ever, measured with any accuracy on these mountain ascents.

* even so, it helps to get them as correct as we can

Wind matters a lot when determining cycling power from speed, no matter the gradient.

Read More......

Tuesday, July 09, 2013

Leaps and Bounds of a Watery Kind

Something a bit different today.


Just a chart showing the progression in the men's 1500 metre swimming world record since records began for the event over a century ago for long course, i.e. 50 metre pools.

The data is from this Wikipedia link

Nothing really specific, other than to post up an example of the way progression in performance has occurred over a century has not been linear nor predictable in other ways but rather occurs with quite different rates of improvement. It was prompted by a discussion about, you guessed it, using past performances (i.e. cycling mountain ascent times) or the ubiquitous estimations of power to body mass ratios as a means to calibrate a modern day "dopeometer", which is of course a path fraught with problems.

Lasting of the order of 15 to 20 minutes, the elite 1500m swim is an event dominated by an athlete's aerobic metabolic capabilities, their morphology and water drag characteristics and with quite a deal of technique/form involved, e.g. making best use of turns, and there are far more degrees of freedom of movement than say pedalling bicycle cranks permits.

Looking at the chart we can see rapid improvement occurred in the 1920s, then only gradual change until the late 1950s when there was a consistent and significant rate of improvement for 20 years through until the late 1970s. I'm guessing improved access to suitable facilities enabling more athletes to compete played a big role in helping to drive this rapid change, along with presumably improvements in training, technique and so on.

Since then the improvement has been far more incremental despite the 1990s and 2000s being the EPO era and the 2000s the era of the swimsuit technology wars. What I haven't done though is to consider the change in power demand for these more incremental performance improvements, i.e. does a small change in speed require a significant change in power? I am presently not well versed in how linear or curvilinear the speed versus power relationship is for swimmers. No doubt there has been plenty of research into this.

Of the 46 new world records plotted, 28 (61%) were by American or Australian swimmers. The only "eastern bloc" athlete in this list is Vladimir Salnikov of the former Soviet Union with 3 records set in the early 1980s. Current world record holder is Sun Yang of China with his swim at the 2012 London Olympic Games.

Edit to add:
After Charles' comment about looking at other shorter swimming events - I plotted the progression with the 400 metre world record as well, and overlayed the two - and adjusted the time scales so the relative progression can be directly compared.

A broadly similar pattern, which is not surprising as you'd expect similar means of performance improvement, but the progression with the 400m event is more consistent than for the 1500m event.

The 400m swim, from a energy demand perspective, is similar to cycling's individual pursuit, and I'd expect roughly one-quarter to one-third of the energy demand is met by anaerobic metabolism (compared with say 10% for the 1500m), the balance of course supplied by aerobic glycolosis.

Read More......