Last month I asked knitters to submit their measurements so I could gather data on calf sizes. Here are the results.
First of all, I want to say, loudly and without equivocation: I AM NOT A STATISTICIAN. In fact, I haven’t taken a math class since high school, so my data analysis skills are, ahem, a little rusty. If you think you could do a better job, please do! Here’s the data:
Click here to download the raw data as a CSV file.
Click here to download the data as I crunched it, with charts and all, as an XLSX file.
Feel free to share any extra conclusions!
So, here are MY conclusions:
- There does seems to be a general correlation between weight, shoe size, clothing size and height to calf size. Though there is a lot of variation within each group, you can generally assume calf size increases as each of those variables also increases.
- That said, measurements vary WIDELY. There’s no such thing as “normal.” If you can get a measurement you’ll be better off.
Now onto the more specific results:
Let’s start with the CLOTHING SIZE measurement. I should note that these sizes are self-reported and we all know how variable clothing sizes can be from brand to brand. The idea is to get a generalization of clothing size and go from there. Anyway, enough caveats. Here’s a chart (all data in inches):
|
Sample Size |
Median |
Lowest |
Highest |
Range |
average |
| XS |
12 |
13.00 |
10.50 |
14.50 |
4.00 |
12.88 |
| S |
38 |
14.00 |
11.75 |
17.00 |
5.25 |
13.88 |
| M |
49 |
14.50 |
11.75 |
17.50 |
5.75 |
14.65 |
| L |
38 |
15.75 |
13.00 |
19.00 |
6.00 |
15.82 |
| 1X |
28 |
16.13 |
13.00 |
19.50 |
6.50 |
16.17 |
| 2X |
13 |
16.50 |
11.50 |
21.00 |
9.50 |
17.58 |
| 3X + |
not enough data |
|
|
|
|
Sample size is the number of respondents in each size group. Unfortunately I didn’t have enough data for sizes 3X and above, so I had to exclude them from this one.
Now onto for SHOE SIZE. Here’s the data plotted out (click image for full res version):

I had excel calculate the trend line, which was y = 0.6306x + 9.8918 — I then plugged this in to each size I got the following results, rounded to the nearest quarter inch:
|
Shoe Size
(U.S. Women’s)
|
Calf Circ. (inches) |
|
|
| 5 |
13 |
| 5.5 |
13.25 |
| 6 |
13.75 |
| 6.5 |
14 |
| 7 |
14.25 |
| 7.5 |
14.5 |
| 8 |
15 |
| 8.5 |
15.25 |
| 9 |
15.5 |
| 9.5 |
16 |
| 10 |
16.25 |
| 10.5 |
16.5 |
| 11 |
16.75 |
| 11.5 |
17.25 |
| 12 |
17.5 |
To me, this one seems pretty useful. It could just be because I wear a size 9.5 and my calf size is 16″, so I happen to fall into the trend.
Next we have the HEIGHT data.

Same story here, and the trend line is y = 0.0971x + 8.8301 — the resulting data:
|
Height (inches)
|
Calf Circ. (inches) |
|
|
| 60 |
14.75 |
| 61 |
14.75 |
| 62 |
14.75 |
| 63 |
15 |
| 64 |
15 |
| 65 |
15.25 |
| 66 |
15.25 |
| 67 |
15.25 |
| 68 |
15.5 |
| 69 |
15.5 |
| 70 |
15.75 |
| 71 |
15.75 |
| 72 |
15.75 |
| 73 |
16 |
| 74 |
16 |
| 75 |
16 |
| 76 |
16.25 |
| 77 |
16.25 |
| 78 |
16.5 |
Finally we have the WEIGHT data.

This trendline was y = 0.0356x + 9.4028. On this one I removed the highest and lowest weights just to try and keep the outliers from skewing the data. I didn’t know if this was a good idea or not, but feel free to download the raw data from the link above and try it yourself. Here’s the trend results:
|
Weight (pounds)
|
Calf Circ. (inches) |
|
|
| 90 |
12.5 |
| 100 |
13 |
| 110 |
13.25 |
| 120 |
13.75 |
| 130 |
14 |
| 140 |
14.5 |
| 150 |
14.75 |
| 160 |
15 |
| 170 |
15.5 |
| 180 |
15.75 |
| 190 |
16.25 |
| 200 |
16.5 |
| 210 |
17 |
| 220 |
17.25 |
| 230 |
17.5 |
| 240 |
18 |
| 250 |
18.25 |
| 260 |
18.75 |
| 270 |
19 |
| 280 |
19.25 |
| 290 |
19.75 |
So, that’s what I have to share. I’d like to keep collecting data and revisit this in a few months to see if a larger sample set would help clarify things, so if you haven’t submitted your information yet, go for it! The more info we have, the better!
What do y’all think? Is this helpful? Will this info be a good aid in your knitting? Let me know!
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