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Comparison · Analytics
Fathom Analytics vs statsmodels
A side-by-side editorial comparison of Fathom Analytics and statsmodels — release velocity, themes, recent moves, and the top alternatives to consider.
Fathom Analytics vs statsmodels: at a glance
What is Fathom Analytics?
Fathom rebuilds its query engine and bolts on Search Console, reaching for GA4's lunch.
Fathom shipped a complete analytics-engine rebuild in March 2026, paired with secondary dimensions, faster queries, and more accurate time-on-page measurement. The product is closing the feature gap with mainstream analytics tools while keeping its cookie-free, privacy-first stance. Recent additions — Google Search Console integration, entry/exit pages, dashboard ZIP exports, and a fresh layer of bot detection — directly target reasons users still keep GA4 open in another tab.
What is statsmodels?
statsmodels ships only what the ecosystem breaks — six releases, no new statistics.
Every release in this window is a compatibility release. 0.14.2 and 0.14.3 absorbed NumPy 2, 0.14.5 fixed an import failure caused by SciPy 1.16, and 0.14.6 did the same for pandas 3.0. The only additive change across two years is Pyodide support in 0.14.4, described in its own notes as one feature and no fixes. A 0.15.0.dev0 tag exists from 2023 and has not been followed by a 0.15 release.
Fathom Analytics vs statsmodels: editorial side-by-side
Fathom Analytics
1.3ANALYTICS
Fathom rebuilds its query engine and bolts on Search Console, reaching for GA4's lunch.
◆ Current state
Fathom shipped a complete analytics-engine rebuild in March 2026, paired with secondary dimensions, faster queries, and more accurate time-on-page measurement. The product is closing the feature gap with mainstream analytics tools while keeping its cookie-free, privacy-first stance. Recent additions — Google Search Console integration, entry/exit pages, dashboard ZIP exports, and a fresh layer of bot detection — directly target reasons users still keep GA4 open in another tab.
◆ Where it's heading
The roadmap is clearly aimed at making Fathom a viable single-pane replacement for Google Analytics rather than a privacy-first complement to it. Expect continued investment in detection accuracy, reporting depth (custom exports, secondary dimensions), and Google-side integrations. The new analytics engine is foundational — it is what makes the next layer of features possible.
◆ Prediction
Next likely moves are deeper UTM and campaign analytics, an experimentation or goals-funnel surface, and tighter agency tooling that builds on self-serve site transfer and shared-dashboard exports.
statsmodels
0.0ANALYTICS
statsmodels ships only what the ecosystem breaks — six releases, no new statistics.
◆ Current state
Every release in this window is a compatibility release. 0.14.2 and 0.14.3 absorbed NumPy 2, 0.14.5 fixed an import failure caused by SciPy 1.16, and 0.14.6 did the same for pandas 3.0. The only additive change across two years is Pyodide support in 0.14.4, described in its own notes as one feature and no fixes. A 0.15.0.dev0 tag exists from 2023 and has not been followed by a 0.15 release.
◆ Where it's heading
The library is being kept alive rather than developed: each release answers a break introduced upstream, and the interval between them is set by the NumPy, SciPy and pandas release calendars rather than by anything statsmodels is building. Two consecutive releases whose stated purpose was restoring the ability to import the package is the sharpest available signal about maintainer bandwidth. The 0.15 line remains a dev tag with no visible progress toward a release.
◆ Prediction
The next release is most likely another compatibility patch triggered by a NumPy, SciPy or pandas major, and nothing in these entries indicates 0.15 is close.
Alternatives to Fathom Analytics and statsmodels
Other Analytics products tracked by Sparkpulse, ranked by recent ship velocity. Each card links to a full editorial trajectory and lets you pivot into a head-to-head comparison with either Fathom Analytics or statsmodels.
OpenHouse
OpenHouse is hardening the seams where table policies and jobs quietly fail.
silx
silx 3.0 moved its default Qt binding to PySide6 — a migration for everyone embedding it.
StatsBase.jl
StatsBase.jl is in caretaker mode — correctness fixes in, dependency bumps out.
iris
Iris ships steadily on a two-a-year cadence, but its feed publishes only pointers.
shiny
Shiny made reactive apps observable, then gave them a way to tear themselves down
See all Fathom Analytics alternatives → · See all statsmodels alternatives →
Recent activity from Fathom Analytics and statsmodels
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
- 4mo agoFathom AnalyticsA new layer of bot detection to keep your analytics accurate and free from non-human traffic
- 4mo agoFathom AnalyticsTrial signup landing page (not a changelog entry)
- 5mo agoFathom AnalyticsSee where visitors land when they arrive at your site and where they leave from — right on your dashboard
- 5mo agoFathom AnalyticsWe rebuilt the analytics engine behind your Fathom dashboard from the ground up. ⚡
- 5mo agoFathom AnalyticsSee which search terms people use to find your site in search results, right inside your Fathom dashboard ⚡
- 5mo agoFathom AnalyticsUpdates and improvements to Fathom Analytics for February 2026
- 8mo agostatsmodels0.14.6: restores importing under pandas 3.0
- 1y agostatsmodels0.14.5: restores importing under SciPy 1.16
- 1y agostatsmodels0.14.4: Pyodide support
- 1y agostatsmodels0.14.3: NumPy 2 environments and corrected macOS builds
- 2y agostatsmodels0.14.2: full NumPy 2 compatibility
- 2y agostatsmodelsRelease 0.14.1
Frequently asked questions
What is the difference between Fathom Analytics and statsmodels?
They serve adjacent needs but don't currently overlap on shipped themes. Fathom Analytics is currently shipping more aggressively (velocity 1.3 vs 0.0), with 0 editorial sparks in the last 30 days against 0. See the at-a-glance table above for a side-by-side breakdown of velocity, recent sparks, and editorial themes.
Is Fathom Analytics better than statsmodels?
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. Fathom Analytics is currently shipping more aggressively (velocity 1.3 vs 0.0), with 0 editorial sparks in the last 30 days against 0. For your specific use case, the alternatives sections above list other Analytics products to evaluate alongside.
What are the best alternatives to Fathom Analytics?
Top Fathom Analytics alternatives in Analytics are ranked by recent ship velocity. Browse the "Fathom Analytics alternatives" section above for the current picks, or visit /alternatives/fathom-analytics for the full list with editorial commentary on each.
What are the best alternatives to statsmodels?
Top statsmodels alternatives in Analytics are ranked by recent ship velocity. Browse the "statsmodels alternatives" section above for the current picks, or visit /alternatives/statsmodels for the full list with editorial commentary on each.