The Average Domain Authority of Independent Blogs in 2026 (Data from 591 Sites)

What is the average domain authority of an independent blog? Most articles answer this question with a guess, an industry survey, or numbers borrowed from major-publication datasets. We answered it with our own data: 591 indie blogs scored across nine categories, with the Open PageRank (OPR) score for each one pulled from the same public API anyone can use to check their own site.

The headline result: the mean OPR domain authority of a vetted independent blog is 2.97 out of 10. The median is 3. The mode is also 3. The highest score in the entire directory is 5, held by 12 blogs. No indie blog in our 591-site sample reaches 6 or higher. If you've ever wondered why your own DA seems stuck around 3 no matter how long you publish — it's because that's exactly where most indie blogs live.

This piece walks through six findings from the dataset, every one of them sourced to live data the scoring engine refreshes weekly. No invented benchmarks, no extrapolation to "all bloggers everywhere" — just what 591 quality-filtered indie blogs actually look like in 2026.

How We Measured This

The sample is 591 blogs that passed our automated approval pipeline: minimum 40 points on the Awesome Score (out of 100), custom domain (no *.blogspot.com, *.wordpress.com, *.medium.com, etc.), at least 5 posts, and SSL enabled at last crawl. Domain authority for every blog comes from the Open PageRank API, pulled during our weekly score-refresh cron and stored as an integer 0–10.

A note on scales. Three different "domain authority" numbers exist in the wild and people confuse them constantly:

• Open PageRank (OPR): 0–10 scale, free public API, used in this article. The scale runs 0 (no signal) → 10 (the largest sites on the internet). Most quality indie blogs land between 1 and 5.
• Moz DA: 0–100 scale, proprietary, free API limited to ~10 calls/month. Different math, different sample.
• Ahrefs DR: 0–100 scale, paid only.

We use OPR because it's the only one we can run against 591 domains weekly without paying a per-call fee, and because it's the only scale a reader can verify against their own site at zero cost. When the on-site DA improvement guide talks about "DA out of 25," that's our internal scoring rubric — a normalized version of OPR rebucketed into our 25-point scale. This article uses raw OPR throughout.

Two of the 591 blogs returned a null from the OPR API (domains too new for the index). All percentages below are calculated against the 589 blogs with valid DA data.

The Headline Numbers

The full integer distribution:

This is not a bell curve. It's a left-skewed cluster centered on DA 3, with a thin upper tail at DA 5 and an upper bound that nothing in the dataset crosses. Roughly 68% of blogs sit between DA 2 and DA 4 — within one standard deviation of the mean — which gives you a defensible answer to "is my DA normal for an indie blog": if it's 2, 3, or 4, yes.

Finding 1: Most Indie Blogs Cluster at Exactly DA 3

The single most striking pattern in the dataset is that 38% of all approved indie blogs land at OPR 3 — the same integer score. The next-largest bucket is DA 4 at 28.7%, followed by DA 2 at 26.7%. Three integer values account for 93.4% of the entire sample.

Some of that clustering is rounding. OPR's underlying scale is decimal (the API returns values like 3.41 and 2.78), and those decimals get rounded to the nearest integer in our pipeline because the field is stored as an integer. So "DA 3" in this dataset really means "OPR raw between 2.50 and 3.49" — a band roughly one full unit wide on the underlying scale, which mechanically inflates whichever bucket the underlying mean lives closest to.

Even with that caveat, the clustering is real. The average indie blog earns enough backlinks to clear OPR's noise floor (DA 0–1) but not enough to break into the band where small-to-medium publishers live (DA 5+). The gap between DA 3 and DA 5 is wide, and it's defended by a structural moat — see Finding 2.

Finding 2: The DA 5 Ceiling

Only 12 blogs in the directory reach OPR 5, and zero break to 6 or higher. Here's the full list, sorted by total Awesome Score:

Three patterns hold across these 12:

1. Most are technical or marketing-adjacent. Ten of the 12 write for an audience of developers, marketers, or both — only Farnam Street (mental models) and James Clear (habits) sit outside that pattern. These are the audiences that publish online themselves and can return citations in kind. A recipe blog reaches readers who don't run sites; a developer blog reaches readers who do.
2. Most have run for 10+ years. A List Apart launched in 1998. Krebs on Security in 2009. ProBlogger in 2004. James Clear has been compounding since 2012. The DA 5 club is overwhelmingly an old-blog club, regardless of niche.
3. Volume varies wildly. Neil Patel has 8,187 posts indexed, Martin Fowler has 8. RSS-feed visibility doesn't capture his full archive — Fowler is the data anomaly. He's also a counter-example to the "you must publish 1,000+ posts to earn DA" assumption: he didn't, and he's at the same OPR score as Neil Patel.

The DA 5 ceiling is the practical glass ceiling for indie publishing. Crossing it requires either a decade of compounding citations from a technical audience (path one) or being Martin Fowler (path two: name recognition substitutes for volume).

Finding 3: Publishing Volume Correlates With DA — But Doesn't Determine It

Average post count climbs steadily with DA. Average everything else mostly doesn't.

Going from DA 1 to DA 5 corresponds to a 6.7× increase in average post count (576 → 3,848). Going across the same span, freshness moves only 2.0 points (out of 20), site speed moves 3 points (out of 100), and trust signals move 1.8 points (out of 15). Volume is the loudest correlate of DA growth in the entire dataset.

But "loudest correlate" is not "deterministic cause." The min/max within each bucket is huge. Among DA 4 blogs the post count ranges from 0 to 10,000 (the upper cap on our sitemap parser). Same range inside DA 2. Wes Bos and Marc Brooker both hit DA 4 with 0 posts visible to RSS — their authority comes from elsewhere (conference talks, GitHub, video courses) and the link graph caught up with them anyway.

The honest read: write more posts and you're more likely to earn DA, but a small minority of niche-authority blogs short-circuit that path with a different reputation lever entirely. Volume is correlated, not required.

Finding 4: Dormant Blogs Keep Their DA

This is the finding most likely to land wrong against SEO conventional wisdom, and the data flatly contradicts the assumption.

A blog that posted yesterday averages DA 3.02. A blog that hasn't posted in over a year averages DA 2.87. The gap is 0.15 — well inside the rounding noise of an integer scale.

This contradicts the "use it or lose it" framing that dominates SEO advice for content sites. Once a blog has earned its backlinks, the link graph holds those backlinks even when publishing slows or stops. Domains live in stasis. They're not punished for inactivity at the DA layer (Google's ranking layer is a separate question — dormant sites lose rankings even when DA holds, because freshness and behavioral signals shift).

The practical implication is uncomfortable. If you stop publishing on a strong indie blog, your DA persists. If you start a new blog, your DA starts from zero and crossing the noise floor takes years even with consistent output. Old domains compound an authority moat that new domains can't shortcut, which is one reason the DA 5 club is overwhelmingly old.

Finding 5: Tech & AI Blogs Outscore Every Other Category

Mean DA varies dramatically by category. Tech leads, lifestyle and creative cluster behind, food and travel trail.

The category leader (Tech & AI at 3.93) and the category laggard (Travel at 2.54) are 1.39 points apart on a 10-point scale — a wider spread than the standard deviation across the entire sample. Niche choice meaningfully shapes the ceiling.

The likely mechanism: cross-niche citation density. Tech bloggers' content gets referenced from Stack Overflow answers, GitHub READMEs, conference websites, library docs, university course pages, and other tech blogs — many of those citations come from sites with higher authority than the citing blog itself. A recipe for browned butter chicken doesn't earn that kind of citation graph. Travel content competes with corporate publishers (TripAdvisor, Lonely Planet, regional tourism boards) that defend the link graph aggressively.

This pattern also explains a curiosity in the personal finance roundup: the niche has high commercial intent, but indie DA averages are below average. Big-DA money sites (NerdWallet, Bankrate) absorb citations indie blogs would otherwise compete for.

Finding 6: .io Domains Punch Above Their Weight

The .com blogs (88.8% of the sample) sit slightly below the overall mean. The .io blogs sit 1.22 points above it. The sample size is small (n=8), so don't read this as "switch to .io and your DA jumps." Read it as: .io blogs are systematically the developer-tooling and SaaS-company-blog corner of the indie world, and that corner happens to sit higher in the link graph for the structural reasons described in Finding 5. The TLD isn't the cause; the audience selection that comes with the TLD is.

The other interesting line is .net (3.42) — older indie tech and personal blogs that registered .net before .com saturation hit. Selection effect again: anyone still on .net in 2026 is likely a long-running site that happens to pre-date the .com gold rush.

What This Means for Independent Bloggers

Six tactical reads from the data, ranked by how directly the dataset supports them:

1. Your DA is probably 2–4. That's normal. Most SEO advice that throws around DA targets ("you need DA 30+ to matter") is using the Moz 0–100 scale and quoting numbers from major publishers, not indie blogs. Indie blogs cluster low on every scale; the ceiling for indie work sits well below the ceiling for media companies. Calibrate against the indie sample, not the Forbes one.

2. Older domains beat newer domains, and there's no honest workaround. The DA 5 club is a 10+ year club for a reason. If you have an older blog you stopped publishing on, you're probably underestimating what its parked DA is worth. Reviving an old domain with new content compounds faster than starting from zero.

3. Volume matters but doesn't decide. The DA 1 → DA 5 jump correlates with a 6.7× volume increase, but Martin Fowler is at DA 5 with eight indexed posts. If you can become a citable name in your niche through a smaller body of unusually good work, that path exists. It's just rarer than the volume path because the volume path scales with effort and the name-recognition path doesn't.

4. Niche matters more than people admit. A travel blogger at DA 3 is well above their category mean. A tech blogger at DA 3 is below it. Don't compare across niches without adjusting; compare against your category's mean.

5. Dormant DA is real and useful. If you have a parked domain with measurable DA, that's a head-start for any new project on that domain — significantly more valuable than launching on a fresh registration.

6. Crossing DA 5 is the actual hard problem. 30.7% of the sample reaches DA 4. Only 2% reach DA 5. None reach 6. The compounding curve flattens hard around 4, and the sites that broke through almost all did so via technical authority (engineering, security, marketing) compounded over a decade. Niche authority blogs in food, travel, and lifestyle hit a structural ceiling lower than the technical ones.

For tactical strategies on moving DA upward — link prospecting, original research, citation hunting — see the DA improvement guide.

Methodology Notes

A few things to be transparent about:

Sample selection bias is real. All 591 blogs cleared a 40-point quality bar that already filters out the very low end of the indie web. The "true" mean DA of all indie blogs (including the ones we rejected) would be lower than 2.97. This article is about vetted indie blogs, not all indie blogs.

Integer truncation costs decimal precision. We store the OPR value as an integer, which collapses (for example) 3.41 and 2.78 into the same bucket. The mean we report (2.97) is the average of those rounded integers, not the average of the underlying decimals. The underlying-decimal mean would land within ±0.5 of the integer mean for samples this size, but we can't report it precisely from the current snapshot.

OPR refreshes monthly. As of this writing, OPR last updated its index on March 28, 2026. Our snapshot reflects backlinks visible on that crawl. A site that earned major links in April 2026 won't show in our data until the next OPR refresh.

RSS is our primary post-count source. When a blog's RSS or sitemap is misconfigured (Martin Fowler is the canonical example), postCount understates reality. Treat the volume-vs-DA relationship as directionally correct, not exact.

Reproducible at the per-blog level. The Open PageRank API is public and free up to 1,000 lookups per day, so any reader can verify a single domain's score against ours by going to the OPR lookup tool and typing in the URL.

Frequently Asked Questions

Q: What is Open PageRank?

A: An open replacement for Google's defunct Toolbar PageRank, maintained by Domcop. It scores domains 0–10 based on the strength of the link graph pointing at them. The API is free for up to 1,000 lookups per day, so anyone with an email address can pull data for their own domain or any other.

Q: How does Open PageRank compare to Moz DA or Ahrefs DR?

A: All three measure the same underlying thing (link-graph strength) using different math and different sample sets, so the absolute numbers don't translate cleanly. There's no published conversion table, and case-by-case comparisons across the three scales show a lot of variance. Don't try to convert your OPR score into an "equivalent" Moz DA or Ahrefs DR — pick one scale and track movement on that scale over time. We use OPR because it's the only free public API at scale, which makes it the only one we can run weekly across 591 domains.

Q: How was the sample of 591 blogs selected?

A: Every blog submitted via our submission form gets scored automatically across seven metrics (DA, freshness, site speed, mobile readiness, content volume, SSL, and design/trust signals). Blogs scoring below 40 out of 100 are auto-rejected. Blogs on free subdomains (*.blogspot.com, *.wordpress.com, etc.) are auto-rejected. The remaining 591 form this sample.

Q: How often does this data update?

A: OPR refreshes its index monthly. Our internal scoring cron runs weekly, but only the OPR pull will actually move on a weekly cadence — and even then, only when the upstream OPR data has refreshed.

Q: Can I check my own blog's score against this data?

A: Yes. Either submit your blog through the submission form, or look up your domain directly on the Open PageRank lookup page. Within our 591-blog sample, OPR 3 puts you in the largest cluster, OPR 4 puts you in the top 30.7%, and OPR 5 puts you in the top 2%.

Q: Why is the maximum DA in the sample 5?

A: Because indie blogs that genuinely cross OPR 6 are vanishingly rare. OPR 6+ territory is occupied by mid-sized publishers (TechCrunch, The Verge, Vox, mid-tier newspapers) with full-time editorial staff and dedicated link-building. We've never seen an applicant blog cross 5, and we'd expect any that did to be a borderline indie-or-not edge case.

Q: Does DA actually predict traffic?

A: Imperfectly. DA is a long-run signal that correlates with the size of a site's backlink profile, which correlates with crawl frequency, which correlates with ranking — but the correlation is loose. A DA 3 blog with 1,000 highly relevant pages targeting low-competition keywords will out-traffic a DA 5 blog with 50 generic pages every time. DA is a useful proxy, not a destination.

The dataset behind this analysis grows weekly as new blogs are submitted, scored, and approved. If you'd like to see your own blog factored into the next refresh, submit it here — submissions take about 60 seconds and the scoring runs in real time.