Word-based domains
Real English words used as the label before the dot — e.g. house.com, jump.io. Words are split into four parts of speech (POS): nouns, verbs, adjectives, adverbs. All percentages share the same denominator: domain checks performed for each POS across the tracked TLD set.
Unregistered % by label length, per part of speech
One line per POS — does the share of unregistered domains rise with longer or shorter words? Toggle a POS to focus on a subset. Hover a point for the exact figure.
Status breakdown per part of speech
For each POS, what share of probed domains was unregistered vs unused/parked vs active. Sorted by total domain checks descending.
Unregistered % heatmap — POS × label length
Each cell shows the unregistered share for a given (part of speech, word length) pair. Greener = more available; redder/orange = mostly registered. Empty cells mean no probes ran for that combination yet.
Domain checks per length
Summed across all four POS — how many word checks have run at each label length, and how they were classified.
| Length | Tracked checks | Unregistered | Unused / Parked | Active / Other | Unreg % |
|---|
About this view
Word-based labels are sampled from a curated dictionary of common English nouns, verbs, adjectives, and adverbs ≤10 characters. Each word is probed across the same TLD set as the home page: com, net, org, io, co, info, biz, online, store, app, dev, ai, xyz, me, cloud, tech, tv, cc, gg, sh. A label is checked via DNS-over-HTTPS — if there is no DNS, the domain counts as unregistered; if there is DNS but no responding website, it counts as unused / parked; otherwise it counts as active.
No per-domain detail is ever stored or returned by the public API — only the running counters for each (POS × length) bucket. WHOIS and registration data for specific domains are operated by each TLD registry or registrar; dom4in.net does not query WHOIS directly.
Signal API
Same JSON endpoint as the home page — the name-pattern rollups live under word_pos_stats:
curl https://dom4in.net/api/stats/overview | jq '.word_pos_stats'