November-CompressedHeavy
Similar fonts
- A2 Standard Sans XCond Bold
- Angostura W00 Black
- Artex Compressed Bold Italic
- Calps Slim Medium
- Cervo Neue Con W05 SemiBold It
- Chairdrobe-BlackItalic
- Chevy Sans Condensed Bold
- Colby Compressed Black
- Costco Sans XCondensed Micro TT Bold
- DraftNaturalHiResTwoH-Black
- DrukTextCyr-Medium
- DrukTextTrial-Medium
- FSP DEMO - Annuario Condesed Bold
- FSP DEMO - Seriguela Black It Regular
- FSP DEMO - Srgl Blck Rv t Regular
- Geogrotesque Sharp Comp SemBd
- GeogrotesqueComp-Bold
- GnuolaneRg-Bold
- GoodPro-CondBold
- Hubiron Semi Bold
- Lindau-Bold
- Marsden Compressed Bold
- Mona-Sans Bold Narrow
- NaN Holo X-Condensed TRIAL Bold
- NaN Holo X-Condensed TRIAL Extra Bold
- NaN Metrify C TRIAL XCondensed ExtraBold
- Oldschool Gtsk Cmpr Trial Bd It
- Pilat Condensed Test Bold
- Saira Extra Condensed Bold
- SohneSchmal-FettKursiv
- Staff X Condensed Test SemiBold
- TabletGothicCompressed-ExtraBoldOblique
- Venn Cd 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.