Ah, you’re correct of course I forgot the requisite change in BB drop.
There are a couple steel forks around 450mm and they’re all 1300g+. I think I said this earlier, the weight increase from 29"-32" makes steel almost completely untenable for gravel bikes in this wheelsize.
Although the first runs of geometry designed around suspension corrected re-purposed MTB forks probably isn’t a good thing either. I’m watching with interest, things should accelerate once the Schwalbe tires are released.
On the XC side of things, think about how long before Nino (who I think is 5’7") made the switch to 29" wheels when the field went that direction. I think it’s somewhat telling that the people who have been openly pro-32" wheels all seem to be average height to tall men. I personally will remain skeptical about them being better than 29" wheels until we start hearing more from individuals who are 5’6" or shorter. They may roll faster, but is a shorter rider (or really most of the women’s field) going to feel comfortable on technical singletrack on them?
While it’s definitely not off the table for the UCI to go backwards on something they’ve publicly and openly stated, they specifically said last Fall that they would not ban 32" wheels in MTB as they see that field as one of the more progressive bike sectors, or something like that.
I dont think that it gives tall riders an unfair advantage necessarily… there are other aspects where shorter riders have an advantage it seems. You could perhaps make an argument that tall riders have been stuck on undersized bikes this whole time. But this whole thing where all of the best equipment will now be only 32 is completely ignoring the large number of riders that will not fit on those bikes. I do think it’s unfortunate that you can no longer buy 27.5 xc race equipment.
The in vitro data I’ve seen is not super convincing for me at the moment. None of these tests perfectly replicate real-world conditions and when a benefit has been seen it’s been small enough that systematic error from a less than perfect test could explain it completely.
The physical/theoretical models of wheel and tire rolling are also not perfectly accurate as they do not account for things like the degree of variability in terrain and rider handling.
We also can’t rely on rider impression of speed as we know from the road world that this is not very accurate (witness how many years we road skinny tires at astronomical pressures).
What Id personally like to see is a race where half the competitors use 32” and the other don’t. Measure power and speed over the race then see if there’s any significant difference.
Both these points are specifically addressed in the structure behind Virtual Elevation testing, start on page 57: http://anonymous.coward.free.fr/wattage/cda/indirect-cda.pdf
The models behind tire and wheel rolling resistance are well developed but are not always visible to the end user. As I posted earlier, there are many scientific papers studying rolling resistance and other factors as a function of wheel and tire diameter. Experimentation specific to bicycle wheels and tires goes back more than 140 years and includes people like this: George Johnstone Stoney - Wikipedia
This sentiment is fairly modern but has not aged well and is structured around anecdote with little data to support. Think of it this way, before Bicycle Rolling Resistance, before really any scientific tire testing at all, people were clearly able to deduce that Gatorskins were a slower tire. They were able to determine this by the feel, by the obvious amount of additional work required on regular riding surfaces and routes. While today we may have much more data creating perception feedback loops, it is well within reason that an experienced cyclist can determine relative speed between two wheelsizes as they can between two tires. We certainly do not have much testing that indicates otherwise.
I think you may have shared the wrong link.
Regardless, if the methods are similar to what’s in there, then that’s not unreasonable. But that’s still only a single rider in real-world-ish conditions.
I wanna see the average speed difference over multiple different riders, as handling is potentially a variable here, and handling is rider-dependent. I’d also be curious about how different terrain impacts any difference, but that would be a secondary outcome.
If 32s are significantly better in the real world, it should be easy enough to show real world results that this is the case.
It’s the right link; the presentation is unnumbered and is page 1-56 of the PDF. The explanation for each slide is page 57 of the PDF but is numbered as page “1” in the document.
That’s about estimating CdA (a physical parameter) using a power meter and real world efforts.
My perspective here is that I don’t really care about what lab-tested physical parameters say about 32s, as the lab tests have important limitations that make them differ from real life usage.
I want to see if they make real people go faster in real life, compared to what I’m currently using. I don’t care about the in vitro results.
If I see that data, I’ll be convinced.
In a real world enviroment you cannot analyze crr without analyzing cda as part of the model.
Real life usage, the “laboratory of the road” only matters if it can provide a reasonably repeatable and robust statistical data set. What you are asking for is a trial or series of trials with no control. Two groups of riders each on different wheels cannot be normalized without significant statistical adjustment, which flattens the entire project into essentially noise.
The fastest road racing cyclists 40 years ago rode the narrowest tires at the highest pressure with no lab testing or statistical analysis. They produced significant outcomes supporting these equipment choices, where they correct? Or were there limitations in their real life usage?
Whether you accept it or not, lab tests have been reasonably shown to generally align with real world outcomes.
What limitations, shown where and how?
No, I described a single trial where the control would be riders without 32” wheels.
Two groups of riders each on different wheels cannot be normalized without significant statistical adjustment, which flattens the entire project into essentially noise.
Not true at all!
We do this all the time with clinical trials. Patients have all sorts of different physiology. It doesn’t matter. You just enroll enough of them and look for an average difference between the groups.
If it wasn’t true, then we’d be spending billions of dollars every year for no reason, and would have no new drugs ever.
Just do a 50 person gravel race, randomly give half the riders to 32s and the other not, and see what the results are. You can even use stratified randomization by FTP if you wanna be really fancy, but simple randomization would likely be more than adequate to control for confounders here (like differences in FTP). You might wanna block it though given the small size to ensure equal groups.
That’s my ideal. Unlikely to happen because the cycling community is not big into rigorous methodology for stuff like this. It means I’ll just wait until we get more real-world data before making any conclusions. I’m not willing to spend thousands of dollars on a new bike without a good reason.
And really… if in real world conditions you can’t show any measurable performance improvement with larger wheels… then they don’t have a performance increase.
What limitations, shown where and how?
That they occurred in a lab, rather than in real world riding conditions.
This is not the process, and it does matter, for clinical trials there are many different controls, especially within the statistical analysis of outcomes.
This cannot produce the result you are expecting it to produce. Each rider is a discrete variable with their own characteristics, which cannot be ignored when determining differences between equipment choices. The outcome of one trial cannot be generalized in this manner.
For example, you cannot stratified the field by FTP because that is essentially meaningless unless expressed as w/kg. Furthermore, this number relies on also knowing each riders practical cda. As is becoming obvious; normalized variables as an attempt to control are not “real world conditions” and we have now backed into a very noisy outdoor experiment that has an excessive error range.
If lab results have repeatedly shown to replicate when applied to real world conditions, this is irrelevant. Results occurring from controlled laboratory experiments are not limited because they are only testing certain variables. A clinical trial is not analogous to analysis of different technological components and their marginal differences.
You can’t really say that if you’re gonna say this
As somebody who has run a lot of laps comparing times and equipment, I can assure you, the average person cannot tell if they are moving faster or not. “Feeling fast” is much different than “being fast”
Joe
Bingo. Your wider wheels are faster by around 6- 7 watts at 30kph btw. Thx for sending.
I’m just going to get this in now. Please quote me in the future. The year is 2030 and The Bike Industry has just discovered that 36 inch wheels are, miraculously, more compliant, faster, more aero, and save 10W at 50kph, and are the-must-have in the 2031 season. And dayglo colours are back too.
There are already a number 36er bikes out there, and wheels and tires are currently available. That’s been the case for a few years now. 32" seems to be a new happy medium between 29 and 36, like 27.5 is the happy medium between 26 and 29".
When the Santa Cruz Downhill team was testing 29ers, they felt their 26ers were faster. Then they saw their times and switched to 29.
Well, it’s not fair to cut out the specific context.
The fastest road racing cyclists 40 years ago rode the narrowest tires at the highest pressure with no lab testing or statistical analysis. They produced significant outcomes supporting these equipment choices, where they correct? Or were there limitations in their real life usage?
There are limitations to real life usage, in my estimation the additional crr from Gatorskins is/was more legible to more people than the additional crr (overall or only after breakpoint? We don’t know) of 21mm tubular tires compared to clincher tires designed for road racing use.
The standard isn’t the average person, it’s the experienced racing cyclist.
Crr 2015 Gatorskin 700cx25 100psi; 0.00606
Crr 2014 GP4000S II 700cx25; 0.00387
Crr Silk & Cotton "27"x21mm tubulars 100psi; 0.0034
Crr High Pressure Road Race tires 700cx25 100psi; 0.0034
The best tubulars and clinchers of the time had very close calculated and tested crr. The big difference other than tubular construction was weight; the 21mm tubulars were around 50-100g lighter. Of course, many or perhaps most clincher 700cx25 tires were actually 23mm or even narrower. GP4000s and Gatorskins have much greater marginal difference in crr. I think this is legible to the experienced cyclist.
Regardless, the difference in magnitude can be observed.
There are a lot of these types of anecdotes. Gary Fisher relates most of the riders who tested his 29ers were faster and also felt faster immediately.
Much like the demand for race results as proxy for the potential relative speed difference in wheelsize, this is evidence but it’s not data in the sense that we have identified or measured the marginal characteristics and classed them. To some this isn’t important, to others it is a requirement.
However, I think I took an overly restrictive or perhaps literal perspective. Race results as proxy is a reasonable way to determine equipment choice, even if it does not necessarily line up with what experimental results are produced.
