mice
mice can finally predict, not just estimate, from multiply imputed data.
A side-by-side editorial comparison of ggfootball and humind — release velocity, themes, recent moves, and the top alternatives to consider.
A football-viz package just swapped scraping for an API and broke its own output to do it.
ggfootball is a small R package for plotting expected-goals and shot data, sourced from Understat. Four releases are visible. The 0.2.x line was argument tidying and dependency pruning; 0.3.0 replaced the data-acquisition layer wholesale, moving get_match_shots() from HTML parsing onto Understat's AJAX endpoints and changing the returned column names in the process.
The MSNI humanitarian needs framework as code, rewritten and re-broken every year
humind turns household survey data into Multi-Sector Needs Index severity scores across WASH, Protection, SNFI, Food Security, Education and Health. Its version line tracks the annual MSNI framework revision — 2024.x, 2025.x, 2026.x — with narrow correctness patches between rollouts. v2026.2.0 is the current rollout and the most structural one in the visible history: water-quantity scoring moved out into a new mandatory prerequisite, food-security severity now comes from a different matrix, and the impactR4PHU runtime dependency is gone.
ggfootball is a small R package for plotting expected-goals and shot data, sourced from Understat. Four releases are visible. The 0.2.x line was argument tidying and dependency pruning; 0.3.0 replaced the data-acquisition layer wholesale, moving get_match_shots() from HTML parsing onto Understat's AJAX endpoints and changing the returned column names in the process.
The direction is away from scraped HTML and toward a thinner, more defensible package: four dependencies dropped in 0.3.0 on top of qdapRegex in 0.2.1, input validation added, error messages rewritten. Both breaking changes so far were accepted rather than deferred, which reads as a maintainer treating pre-1.0 as the window to get the shape right. The package is willing to break callers for structural reasons, not cosmetic ones.
With the scraper rebuilt and the dependency surface trimmed, the next releases are likely to stabilise the new column names and extend the plotting side, which has seen nothing since 0.2.0. A 1.0 would be the signal that the data structure is now considered fixed.
humind turns household survey data into Multi-Sector Needs Index severity scores across WASH, Protection, SNFI, Food Security, Education and Health. Its version line tracks the annual MSNI framework revision — 2024.x, 2025.x, 2026.x — with narrow correctness patches between rollouts. v2026.2.0 is the current rollout and the most structural one in the visible history: water-quantity scoring moved out into a new mandatory prerequisite, food-security severity now comes from a different matrix, and the impactR4PHU runtime dependency is gone.
Two things move together. The framework content is revised yearly — indicators added, weights corrected, instruments swapped — and the package keeps absorbing pipeline it used to delegate, most visibly by vendoring add_fcs(), add_hhs(), add_rcsi(), add_lcsi() and add_fcm_phase() locally rather than importing them. Each rollout is explicitly breaking and the release notes have grown per-function 'Action:' instructions, which reads as maintainers who expect every downstream dashboard to need rewiring on the same annual clock.
The 2025 line settled into narrow patches immediately after its rollout — 1.2, 1.3 and 1.4 fixed a separator argument, a schema rename and a shelter misclassification rather than adding indicators. Expect the 2026 line to do the same: correctness fixes against the new WASH, FCLCM and shelter-damage logic before any further framework change.
Other Infra & APIs 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 ggfootball or humind.
mice can finally predict, not just estimate, from multiply imputed data.
A market-microstructure toolkit that keeps adding estimators as the papers land.
A vowel-analysis package trimming dependencies after an email address got it archived.
The R half of the EMU speech database system, fixing what was quietly broken.
A Bayesian model-averaging package spending its 2.0 on memory, not methods.
tidyplots keeps rebuilding its own foundations rather than layering around them.
See all ggfootball alternatives → · See all humind alternatives →
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
Both compete on the same themes — r-package, breaking-changes — within Infra & APIs. humind is currently shipping more aggressively (velocity 3.8 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.
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. humind is currently shipping more aggressively (velocity 3.8 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 Infra & APIs products to evaluate alongside.
Top ggfootball alternatives in Infra & APIs are ranked by recent ship velocity. Browse the "ggfootball alternatives" section above for the current picks, or visit /alternatives/ggfootball for the full list with editorial commentary on each.
Top humind alternatives in Infra & APIs are ranked by recent ship velocity. Browse the "humind alternatives" section above for the current picks, or visit /alternatives/humind for the full list with editorial commentary on each.