Condensed Alcubierre Web
Similar fonts
- Cascadeur-ExtraBlack
- ckTrial Winner UltraComp Black
- Cotdien Typeface
- Darab Bold-short
- Data Trash
- Dugas Pro Thin Ultra-condensed
- Edgar Regular
- Fit Devanagari Condensed
- Fit Instances wdth100
- Fit Instances wdth110
- Fit Instances wdth111
- Fit Instances wdth35
- Fit Instances wdth38
- Fit Instances wdth50
- Fit Instances wdth51
- Fit Instances wdth52
- Fit Instances wdth53
- Fit Instances wdth55
- Fit Instances wdth66
- Fit Instances wdth75
- Fit Instances wdth85
- Fit Instances wdth88
- Fit Instances wdth89
- Fit Instances wdth90
- Fit Instances wdth93
- Fit Instances wdth95
- Fit Instances wdth98
- Jetlab Variable Squeeze Heavy High Squeeze Heavy High
- Perfora W15xH15
- Perfora W20xH20
- SeniorService-Regular
- Winner Sans UltraComp Black
- Winner Sans UltraComp 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.