Alright.

To those who don’t really read the blog (or really follow it attentively [don’t worry i’m not mad] for a plethora of reasons [really, not mad at all]), I made a little survey with the help of google sheets and google forms to try to figure out what shoes fit similarly. What did the survey try to accomplish? Well, I basically just asked “what fits you perfectly” and then “what fits you well, but not perfectly” and then some other metrics that I thought would be useful (sex, how you size shoes, etc) in hopes to find shoes that fit similar feet.

Before getting to the results let’s just talk frankly. Did I think this would work? Not really. Did it prove something I thought to be true? Again, not really. Will this survey even be useful in a year when all the major players change their fits completely? Again, not really.

The major disadvantage of this survey was really the lack of respondents (even with over 300 people, that isn’t that great when you think about how many types of shoes there are) and the lack of objective data. Asking someone if something fits well usually just means, “does this shoe work” or “do you like this shoe more than other shoes” which doesn’t really answer the core question of fit. Instead, the data presents the most popular shoes.

Regardless, I think this is worth showing if not only to start a conversation and maybe get some better data collected. Again: the data would have to come from everywhere with an emphasis on objectivity and would also have to standardize by amount of responses, not count. Here I presented data in it’s rawest form (count) to try to stay away from making false promises based on a single or a handful of respondents.

Results: the top foot fashions

I decided to do the top shoes that were mentioned in the survey. Again, this is just data visualization and not correlation. A more rigorous statistical analysis would have to be done to actually show relation but this is preliminary and at this stage of data collection seems like nothing would come out of the numbers.

Alright, here was how I outputed these graphs (for those who want to know)

filter the data of “perfect fit” and make sure it must contain the examined shoe (example Shaman) Use Countif to output a count of every time any shoe is mentioned in “perfect fit” or “average fit” in the new scrubbed data Sort by the sum of perfect and average fit Make a cute little graph like so:

So, here’s the first one for the Evolv Shaman. Basically, what we have is most people say that the Shaman fits perfectly and so these are other shoes that fit perfectly or above average.

What’s funny is that the Shaman is one of the shoes I’ve personally thought as a “perfect fit” for myself, personally, but would never agree that the Anasazi VCS fits the same (the heel is very loose on my foot). Weirdly it is in the top 3 of cross-fits (no pun intended) and the top “perfect fit” response.

Ah yes, the Solution. My arch (no pun intended) nemesis. The bane of my heel cup. Well, for all you people at home, it seems I am correct in thinking that the Shaman does not play nice (comes pretty close to last in the “perfect fit” category) but seems lots of people tolerate the difference in fit between the solution and the Shaman. That said, they seem like close relatives and so someone who fits a solution just okay should maybe try a Shaman (and vice versa).

Otherwise, I am pretty happy to see the team being so close as it seems those two are very close to fitting similarly. Also: the TC pro and tarantuala only have perfect fit matches. Interesting!

Another top respondent is the Miura Velcro. I chose to not group the velcro and the lace together as they are generally accepted as different shoes with different fits. That said, they are very similar based on the responses seen.

That said, the Python and the Testarossa may be a better choice if bouldering is your game over the Shaman and the Genius, even maybe over the Solution. The Solution gets mixed ratings, about half of respondents seem to say the fit isn’t perfect compared to the Miura Velcro. Again, interesting.

Finally, I decided to do a 5.10 shoe and also decided to merge the VCS and the Pinks together (I have tried both on and both seem like they are based on the same fit, subjectively).

Again, the Solution seems to be a good-but-not-great option. Otherwise, many people seem to disagree on the fits. Dragons and teams both rank high in perfect fit but also in above average fit. It seems the Testarossa also score high but to what avail (with so little data, who can be sure?)

Conclusion n’ Discussion

So what does this data tell us, more or less?

Firstly: shoe fit is very subjective. It seems that lots of people are ramming their feet into shoes and climbing and this works. Preference is often then determined by hype or performance, and thus the fit seems secondary to the actual fit preference. Getting results was hard enough, but it seems like there is no shoe that fits a particular foot or even agreed “if you like X you will like Y”. If you only just scan the “doesn’t fit me at all” data, the contradictions of fit seems endless.

Secondly: As the solution seems to be the preferred shoe of my blog and Reddit, the shoe came up a lot. It is hopefully pretty obvious by the amount of times it came in as a “didn’t fit perfectly but I still can wear it” shoe. With more data in each shoe type, i think graphs like the following could be made:

Basically, Here I sorted all the shoes based on how they rank in the “doesn’t fit” category and this is also standardized. Here you see the oxygym and the solution may be a match made in heaven, but obviously this is hard to conclude if you knew that the oxygym had 1 respondent.

Finally, I have high hopes that if someone were to collect similar data that this could be made into an actual study that could further the ease of ordering shoes online. Personally, I don’t order new shoes online as I know that there is a very real probability that the fit will be weird and it will throw me off in my hard climbing.

Anyhow, feel free to scan the google doc if you want to do your own analysis. Don’t think much statistical stuff could come out of it since it is so ripe with missing data.

Find that perfect pair,

-CC

Edit: vis-a-vis my photo usage, I do not claim to own or have created every photo on this site. I believe in fair use as this blog is non-profit for educational type stuff. What that means is that since I am using the photos sparingly for jazzing up the articles, there is really (in my own personal view) no harm to this act. If I have used your photo or image and would like credit or it removed, let me know.

Thanks Kevin for letting me know I was using a photo you created, I won’t be using it as it seemed to be an issue.