STACAS
Single-cell batch correction that learned to use cell labels, then spent three releases chasing Seurat.
A side-by-side editorial comparison of nflseedR and rempsyc — release velocity, themes, recent moves, and the top alternatives to consider.
nflseedR rewrote its simulator from scratch and put the original on a deprecation clock.
nflseedR computes NFL standings, playoff seeding and draft order, and simulates seasons to produce playoff probabilities. Version 2.0.0 replaced the engine rather than extending it: nfl_standings() and nfl_simulations() are new implementations, and the original compute_division_ranks(), compute_conference_seeds(), compute_draft_order() and simulate_nfl() are all slated for deprecation. The two releases since have been correctness fixes and a CRAN-requested documentation styling change.
Publication-ready psychology tables and plots, tracking APA style as closely as the software allows.
rempsyc produces APA-formatted tables and figures for psychology research — nice_table() for results tables, plus plotting helpers for scatter plots, violin plots, densities and simple slopes. Its releases are CRAN submissions that bundle a long run of development versions, so each entry reads as a digest rather than a single change. The most recent, 0.2.0, added point labelling and per-group correlation statistics to nice_scatter and fixed nice_lm() failing on factor covariates with more than two levels.
nflseedR computes NFL standings, playoff seeding and draft order, and simulates seasons to produce playoff probabilities. Version 2.0.0 replaced the engine rather than extending it: nfl_standings() and nfl_simulations() are new implementations, and the original compute_division_ranks(), compute_conference_seeds(), compute_draft_order() and simulate_nfl() are all slated for deprecation. The two releases since have been correctness fixes and a CRAN-requested documentation styling change.
The direction is toward a leaner, faster package with fewer dependencies, and the deprecation plan is stated openly — retiring simulate_nfl() is described as the step that lets the dependency list shrink significantly. Tiebreaker coverage has been filled in to the point where only net touchdowns remain unimplemented, and load_sharpe_games() has been handed off to nflreadr. Requiring R 4.1 for the native pipe is the same instinct applied to the language floor.
The deprecations are announced but not executed, so the next substantive release most likely removes simulate_nfl() and the older standings helpers and drops the dependencies that were the stated reason for the rewrite. Net-touchdown tiebreaking is the one gap the entries explicitly leave open.
rempsyc produces APA-formatted tables and figures for psychology research — nice_table() for results tables, plus plotting helpers for scatter plots, violin plots, densities and simple slopes. Its releases are CRAN submissions that bundle a long run of development versions, so each entry reads as a digest rather than a single change. The most recent, 0.2.0, added point labelling and per-group correlation statistics to nice_scatter and fixed nice_lm() failing on factor covariates with more than two levels.
Two forces drive this package and neither is its own roadmap. The first is APA style: when the 7th edition advised against beta for standardized coefficients, the package switched its output to italic b with an asterisk. The second is the surrounding ecosystem — formatting is aligned to what lavaanExtra and afex produce, contrast handling was delegated to easystats' modelbased, and Excel correlation matrix export was handed entirely to the correlation package to cut maintenance.
The pattern of delegating functionality to specialist packages while keeping the formatting layer is well established and likely continues. Because releases bundle many small dev versions, the next one will probably again mix plotting refinements with fixes surfaced by upstream changes.
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 nflseedR or rempsyc.
Single-cell batch correction that learned to use cell labels, then spent three releases chasing Seurat.
A debugger for ggplot2's internals, hardening its grip as the internals it traces keep moving.
A univariate density estimator that added zero-inflated data and reopened its C++ API to do it.
Stationary vine copulas for time series, released in lockstep with the rest of Nagler's vine stack.
A single-purpose ggplot2 extension that has spent six years tracking ggplot2 instead of growing.
A Star Trek data package that became a Memory Alpha web client and has been patching scrapers ever since.
See all nflseedR alternatives → · See all rempsyc alternatives →
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
Both compete on the same themes — r-package — within Analytics. nflseedR and rempsyc are shipping at a similar cadence (velocity 0.0 vs 0.0, both within Sparkpulse's "active" band). 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. nflseedR and rempsyc are shipping at a similar cadence (velocity 0.0 vs 0.0, both within Sparkpulse's "active" band). For your specific use case, the alternatives sections above list other Analytics products to evaluate alongside.
Top nflseedR alternatives in Analytics are ranked by recent ship velocity. Browse the "nflseedR alternatives" section above for the current picks, or visit /alternatives/nflseedr for the full list with editorial commentary on each.
Top rempsyc alternatives in Analytics are ranked by recent ship velocity. Browse the "rempsyc alternatives" section above for the current picks, or visit /alternatives/rempsyc for the full list with editorial commentary on each.