Nov 9 2009
Then, man—has Speedplay got the pair of pedals for you.
In a claim worthy of Chesterfield Cigarettes, Speedplay has asserted that wind tunnel testing has proved its pedals will save you an astounding 33 seconds per hour if you use the four bolt attachment.
There are, of course, the obvious problems with this wind-tunnel derived claim—you don’t ride hour-long time trials; even if you did, you couldn’t ride them a consistent 30mph; even you could, they have hills and corners, and you’re overweight and a lousy bike handler. Then there are cross-winds, other competitors, traffic, mental toughness, etc.
But in this post I will ignore these things. Instead, I want to focus on highlighting Speedplay’s ill-conceived methodology and misleading conclusions.
“…the testing of a single component by itself raises questions as to whether or not the component will perform in the same way when installed on a bicycle and used outside of the tunnel.
With this in mind, we mechanized a life-size, lower-half of a mannequin so the mannequin, rather than a person, would pedal the bike.
Yes, you read that correctly—the problem with wind tunnel tests is that they’re not like real life, so we replaced a real life person with a torso-less pair of mechanical legs. Does its motion churn the surrounding air like a real human set of legs? Are its proportions correct? What about foot position—idealized by biomechanics, or average observed foot position of pro riders? These are questions Speedplay didn’t feel like addressing.
At any rate, Speedplay’s use of de-torsoed legs in means that the results—in the unit-less and not particularly useful form of coefficient of drag—apply only to this mannequin. When this bodiless apparatus is wears shoes with 4-bolt-mounted Speedplays, that coefficient is .237.
However, Biomechanics and Biology of Movement found that “a cyclist on a standard road bike in racing position” has a drag coefficient of 0.78. That 200% increase reflects all the things Speedplay’s disembodied legs left out of their results.
So what appeared to be a small difference in coefficient of drag—2.5%—is actually an all-but-insignificant 0.7%*. And even that minor change requires to you have faith in the reliability of Speedplay’s procedures. Measuring drag coefficient to three significant digits—the finest measure available from the wind tunnel if Speedplay’s videos are any indication—and coming away with a single thousandth of variation invites far closer scrutiny of the study.
Sadly, Speedplay states only that the tests ran for five minutes, at a cadence of 100 rpm, and a headwind of 30mph. Data on number of trials for each pedal design, and variation in wind speed during the course of each trial would be more than welcome, but are entirely lacking.
Speedplay offers similarly little help in saying exactly what “available data” lead them to infer that the advantage to their pedal is “equivalent to the speed gained when switching from a standard front wheel to a deep-profile, aerodynamic front wheel.” The only data I could find using coefficient of drag were from Greenwell, which describes aero wheel advantages roughly two to ten times more pronounced than anything measured by Speedplay in this testing.
So, Speedplay—as far as I can tell, you’re lying to sell more gear. You certainly wouldn’t be the only ones. But I’d hate to stand here casting such aspersions without giving you a chance explain or clarify your findings.
I want to see the precise data behind this test—with detailed descriptions of apparatus, methods, and raw results. I’d also like to know the names and qualifications of those who designed and carried out this test. Finally, I’d like to see what research you used to conclude that, based on the data in this test, Speedplay pedals deliver such marked aerodynamic savings.
My request for this data is genuine. Readers and tech editors alike will tell you I’m receptive to criticism and more than willing publish your response.
*actually, I’m told that the increased surface area of a full-sized rider would make the coefficient of drag an even less relevant than the absolute value I’ve derived here.