Fit Instances wdth32
Similar fonts
- Due Bold
- Dugas Pro Light Ultra-condensed
- Dugas Pro Thin Extra-condensed
- Dugas Pro Thin Ultra-condensed
- Fit Devanagari Extra Condensed
- Fit Devanagari Variable Extra Condensed Extra Condensed
- Fit Extra Condensed
- Fit Instances wdth19
- Fit Instances wdth20
- Fit Instances wdth21
- Fit Instances wdth22
- Fit Instances wdth23
- Fit Instances wdth24
- Fit Instances wdth25
- Fit Instances wdth26
- Fit Instances wdth27
- Fit Instances wdth28
- Fit Instances wdth31
- Fit Instances wdth32
- Fit Instances wdth33
- Fit Instances wdth34
- Fit Instances wdth35
- Fit Instances wdth36
- Fit Instances wdth37
- Fit Instances wdth38
- Fit Instances wdth39
- Fit Instances wdth40
- Fit Instances wdth41
- Fit Instances wdth42
- Fit Instances wdth43
- Fit Instances wdth44
- Fit Instances wdth45
- Sporteam Extra Bold
Details
How are we calculating this?
We analyze each font added to FontBase locally using the opentype.js library. We render the text off-canvas and measure key characteristics: stroke width; difference between bold and thin strokes; the relation of "x" letter height to capital letters; width of the letters compared to height; "i" size compared to "w" size. From these calculated numbers, we then build weight, proportion, xHeight and contrast. We also analyze the font's naming table to retrieve the basic info like font name, foundry and style names. No fonts are uploaded to our servers in the process.
How do we determine similar fonts?
Based on the characteristics we retrieve, on each font page, we select the fonts that have all the same parameter numbers. For example, if a font has 0.6 weight, we select fonts from our database that are in the range of 0.5-0.7 weight. We do this with all parameters combined, resulting in a similar font selection.