Data transparency in cycling: necessary, utopian, and a complete can of worms

This year’s Tour de France is developing into a bit of a split race, being both exciting by stage and predictable by General Classification (GC). This was most clearly demonstrated by the blistering performance of yesterday’s stage winner Steve Cummings of MTN-Qhubeka (the African team’s first stage win, on Mandela Day, no less), followed by Chris Froome hoovering up all attacks against him. It was an eventful ride for Team Sky, with fists, saliva and urine apparently being thrown at them. They are currently the sport’s bad guys, for no reason other than dominance. The last team to dominate like Sky did was one of the liveries led by Lance Armstrong, and Sky’s tactics and public relations stance continue to draw uncomfortable parallels with the Armstrong era. This suspicion has led to calls for Sky (and others) to be more transparent about their power data in particular, since the view goes that teams with nothing to hide should hide nothing.

Something something Armstrong, something something Froome. Right, let’s SCIENCE… [Forget personalities, there’s a link in two paragraphs time in which the awesome David Wilkie uses very simple power modelling to make a bicycle fly.]

Power output and the physiological response to exercise

Mountain stages in the Tour are critical to success. One bad day in the mountains can cost you the race, and a good day can get you a Yellow Jersey. In contrast, sprint stages rarely produce gaps in the GC, and time trial stages are predictable and (to within a minute or so) run to form. That’s problematic if you’re on the wrong side of the minute, but not fatal. Gaps of over 5 minutes are sometimes seen in the mountains. In a mountain climb, where air resistance plays a more limited role, the rider who can sustain the highest power, and thus (bike and body mass accounted for) the highest speed for the duration of the all the climbs, is likely to win the Tour. Time trial specialists cannot win the Tour with time trials alone. They must train to climb (contrast Boardman’s Tour performances with those of Wiggins – riders with very similar initial backgrounds but very different training approaches to the road).

Because sustaining a high power output on a climb is crucial, there has been a great deal written about the limits of what is possible. I am not going to add to this debate, as in my view without direct measurement of power as well as an understanding of the rider’s physiological capacities (aerobic and anaerobic) there are too many assumptions to be sure that a conclusion about whether something is possible or not can be drawn. There are performances that might look suspicious, but a 4 min mile performance in running would have looked suspicious in 1935. By 1995 it was considered slow. We do, however, know a few things about what determines sustained power, thanks to scientists like AV Hill, David Wilkie, and a number of others.

The physiological response to exercise depends on the power output you produce. For “moderate” exercise, muscle oxygen uptake rises rapidly and reaches a steady state. Blood lactate either does not rise or rises only transiently. At these work rates, exercise can be sustained for many hours. For “heavy exercise”, when you exceed the lactate threshold, oxygen uptake takes longer to stabilise and does so at a higher value than you would predict from steady state responses to moderate exercise (in other words, you are less efficient). This is the result of a “slow component” of the oxygen uptake response that develops after about 2 minutes of exercise and stabilises after 15-20 minutes. In the heavy domain, exercise can be sustained for between 45-60 min and about 3-4 hours. For “severe” or “high-intensity” exercise, the oxygen uptake slow component does not stabilise (and nor does any other metabolic response) until maximal oxygen uptake (VO 2max ) is attained. Exhaustion inevitably follows soon after this occurs. The “severe-intensity domain” commences when you exceed the critical power (CP). The CP, in turn, represents the asymptote of the power-duration relationship, first noted by AV Hill in 1925. We’ve written a few papers about these concepts, which you can find here (free) and here (not free). The power-duration relationship can be defined by as few as two parameters, namely the CP and a parameter to define the shape of the curve, denoted W’. The CP is thought to reflect the power of the aerobic systems of energy delivery and the W’ is thought to reflect the “anaerobic capacity”, although we know this is a little simplistic. It is the power-duration relationship that is important for working out what is and is not possible when cycling up a hill.

Defining possible and impossible

If you know the values of CP and W’, and you know the power demand of a task, you can make a clear prediction about what the time limit of the task is. The equation, for those who want it, is:

Time limit = W’/(power output – CP)

The problem is that the above parameter values will vary between athletes and will vary day to day. The parameters and the underlying physiology that determines them can also be influenced by various acute interventions (like glycogen depletion, for example), which adds further uncertainty to any “back of the envelope” calculations that you might wish to make. To know if any performance is abnormal, you need to know what the power-duration parameter values actually are. Consider that in an elite cyclist with GC ambitions might have a CP of about 380-440 W, and a W’ of 20-30 kJ, both of which will depend, to some extent, on body mass. This means that to complete an effort lasting 40 minutes, with a W’ of 25 kJ and a CP of 420 W, the “normal” power output sustainable for this duration would be 430 W, or 6.1 W/kg for a 70 kg rider. Notice here that the contribution of the curvature constant to long duration efforts is quite small (about an extra 10 W over 40 min) and thus the most crucial determinant of mountain performance is the maximal sustainable power output, CP.

One reason why I don’t think fixating on a particular W/kg value as “possible” or “suspicious” really works is that it all depends on the value of CP. This value is unknown and variable! Obviously, for a 70 kg rider to sustain 6.1 W/kg without drawing on the W¢, CP would need to be at least 430 W. I don’t think that is unreasonable, given previously documented hour record performances and the power outputs produced during them (Bassett et al., 1999). To sustain 430 W would require an oxygen uptake of approximately 5.3 L/min (O 2 cost of ~10 mL/min/W, plus ~1 L/min for the O 2 cost of spinning the legs at 90-100 rpm), which, if capable of utilising ~90% of VO 2max , would predict a VO 2max of 5.8 L/min or 84 mL/kg/min. This is high, but certainly not unheard of. Sustaining 85% of these figures would require a VO 2max of 89 mL/kg/min. That is still not impossible. And this is all assuming a normal mechanical efficiency. Efficiency would decrease due to the development of a slow component of oxygen uptake, but this would add no more than about 200 mL/min to the tally (that is, oxygen uptake would remain submaximal even with this factored in).

Knowing the possible

The above calculations are hypotheticals based on reasonable estimates. The numbers accompanying Froome’s (or Nibali’s or Contador’s or…) that appear on the internet are just as hypothetical. In short, we have no direct numbers for either physiological capacity or performance for GC riders at the time of the Tour. Values estimated from those recorded in other parts of the season are likely to underestimate the capacity of a rider who has peaked and ridden conservatively in much of the first week of racing. In addition, direct measures of rolling resistance, wind speed, temperature, altitude, and so on, are also absent. To know what’s possible would require direct power-duration measurements from Froome immediately before the Tour, as well as calibrated power data during each and every stage. It is likely that Sky possess both data sets. They most likely have a variety of physiological measures that could corroborate the power-duration data (i.e., the VO 2max , efficiency and LT data would likely fit in the same general picture). But they refuse to place these data in the public domain. Should they? The scientist in me says yes. The sports fan in me says maybe. The pragmatist in me says that there is next to no chance of these contemporary data ever seeing the light of day.

For one thing, Froome’s consent would be needed to release these data, and even if that consent was given, where would the data be stored and how would access be gained? If Froome releases his, every rider in the Peloton should be obliged to release theirs, lest there be any accusations of unfair treatment. The teams are highly unlikely to want to do this for competitive reasons. It’s much the same reason why Formula 1 teams do not release telemetry data in real time – a good rival engineer would identify engine modes, brake balance, tire wear etc and use that information to the team’s advantage. The sport would become even more about who has the best support crew rather than the best performer.

A less problematic point is that not all teams use the same power-measuring devices. Moreover, where on the bike the power is measured also matters. Although often measured at the crank or the rear wheel hub, it’s the power transferred to the road that counts (producing forward propulsion), but the power actually produced on the pedals that costs (in terms of physiological demand). Frictional losses and rolling resistance (though presumably minimised) will also differ, adding errors to any calculations of who produced watt, where and when…

The Future

There has been some chatter on Twitter and elsewhere of power files from races being used as part of the Athlete’s Biological Passport in cycling. I can see some merit in this, as within each athlete, performances can be compared to their power-duration relationship, their physiology and their blood parameters already used. The observation of abnormal power outputs alongside sudden changes in, for example, the Off-score, might trigger closer scrutiny of that athlete in the coming months.

Finally, I can see the potential for power data from grand tours being released following an agreed embargo period. This would serve an educational and scientific purpose of providing a rich seam of data to be used by anybody who wanted it. Those data could also be used as part of a retrospective anti-doping case. But they’d only ever be part of the story. If there was reasonable circumstantial evidence of doping in the absence of a positive test (like the Armstrong case, for the most part), then power files could weight to that case. But it would only be small given the number of variables involved in ultimately producing power output.

I’ve almost certainly not done this issue justice, but the above thoughts lead me to conclude that the question of data transparency in cycling and what its potential uses are does not have any easy answers.

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The contentious and irrelevant bit:

Armstrong’s shadow

The similarity between Armstrong-era cycling and today ends with what is written above. Quite a few people have asked David Walsh, the man who was instrumental in taking down Armstrong, why he is not asking Sky and Froome tough questions. I personally think that is wrong-headed. Armstrong’s transformation post-cancer was mind-blowing, whereas Froome’s ascent has been more incremental. Add to that the accumulation of damning evidence throughout Armstrong’s career, covered up by Armstrong with the help of the UCI, and in that case Walsh could ask questions about tangible things in Armstrong’s closet. Froome’s closet is bare by comparison, save for a TUE and some stunning performances on the road. So there was good reason to pursue Armstrong, but much less to pin on Froome and Sky. This is why calls for data transparency are timely.

[EDIT: I’ve got quite a few comments about the LA/CF comparison I made above both here and elsewhere. I’ve a good mind to delete it because I think it detracts from the point I’m trying to make (that power output is interpretable in context but it’s always likely to be very difficult). I’m not going to delete it, however, because it would make the post more boring, and writing really bloody boring stuff is something I’m already pretty good at. My point to those arguing over this is that (like the rest of the post, actually) context is everything. We know most of the details surrounding Armstrong’s “inverted U-shaped” career progression, in which he went from an aggressive stage racer/breakaway specialist to cancer patient to GC domination. In this, he went from not really being notable as a climber to dropping Pantani. That’s astonishing. Froome burst onto the scene in late 2011, but had been with Sky for about 18 months before that, and showed some potential between bouts of illness and injury. The impact of these is not certain because, again, of the context. Sky, due to its links with British Cycling, was and still is awash with riders who are good against the clock, so he wasn’t in the team to be the time triallist. He was clearly there to be part of the Sky train, in a team hell-bent on GC success with Bradley Wiggins. In that context, Froome’s rise to prominence was not particularly fast, but was perhaps unexpected given the circumstances at the time. Importantly, he didn’t completely change his style of riding to break through. I am not naïve enough to appreciate that there aren’t other explanations, but, again that’s not what the post is about, and I’ve tried to avoid drawing any of those conclusions. Back to the day job…]