fillpattern
Pattern fills for ggplot2, hardened against the ways users write sizes
A side-by-side editorial comparison of nflreadr and tEDM — release velocity, themes, recent moves, and the top alternatives to consider.
The nflverse data loader, whose releases are dictated by the NFL calendar and CRAN's archive policy
nflreadr is the data access layer of the nflverse, wrapping cached downloads of play-by-play, roster, contract, charting and stats releases. Its growth phase peaked with 1.3.0, which added participation data, contracts, weekly rosters, officials and the players endpoint in a single release. Since then the work has been consolidation: 1.5.0 moved to v2 players data and reorganized player stats behind nflfastR's calculate_stats() with a summary_level argument, and 1.5.1 hard-deprecated qs file support after that package was removed from CRAN in January 2026.
The temporal half of the stscl EDM pair, tracking its spatial sibling
tEDM applies empirical dynamic modeling to time series — cross mapping, convergent cross mapping and the logistic map — as the temporal counterpart to spEDM, with which it shares a maintainer and a C++ core. The recent releases are consolidation rather than expansion: index handling in cross mapping corrected, generics taught to accept varying E, k and tau, and the associated paper now cited in the README. Only three releases are visible in the feed.
nflreadr is the data access layer of the nflverse, wrapping cached downloads of play-by-play, roster, contract, charting and stats releases. Its growth phase peaked with 1.3.0, which added participation data, contracts, weekly rosters, officials and the players endpoint in a single release. Since then the work has been consolidation: 1.5.0 moved to v2 players data and reorganized player stats behind nflfastR's calculate_stats() with a summary_level argument, and 1.5.1 hard-deprecated qs file support after that package was removed from CRAN in January 2026.
Two external clocks drive this package and neither is under its control. Feature releases land before the NFL season opens — 1.5.0 says so explicitly — and breaking changes are timed to that window. The other clock is CRAN's: losing the qs dependency forced a serialization format out of the package entirely, leaving parquet, rds and csv. The upstream coupling to nflfastR is tightening too, with player and team stats now sourced from its calculation functions rather than computed here.
The pattern of a pre-season consolidation release is well established, so the next substantive version is likely timed to the following season's opener rather than to any internal roadmap.
tEDM applies empirical dynamic modeling to time series — cross mapping, convergent cross mapping and the logistic map — as the temporal counterpart to spEDM, with which it shares a maintainer and a C++ core. The recent releases are consolidation rather than expansion: index handling in cross mapping corrected, generics taught to accept varying E, k and tau, and the associated paper now cited in the README. Only three releases are visible in the feed.
tEDM moves in lockstep with spEDM. Configurable distance metrics, varying E/k/tau inputs, strict floating-point comparison and the S3 plotting font unification all appear in both packages within days or weeks, as does the maintainer surname correction. The recent balance has tilted toward correcting library and prediction index handling — the kind of repeated attention that suggests the indexing model was the weak point of the shared core.
Expect tEDM to keep inheriting the shared-core changes spEDM lands, with its own releases staying small and centred on cross-mapping parameter handling rather than new method surface.
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 nflreadr or tEDM.
Pattern fills for ggplot2, hardened against the ways users write sizes
gcube's recent releases are all packaging metadata, not simulation code
The R port of Quinlan's Cubist gets reproducibility fixes, not new modelling
ggstats keeps widening what a coefficient or Likert plot can be
ecodive rebuilt itself into a broad diversity-metric library, breaking as it went
State-space data simulation for R, filled in one function at a time
See all nflreadr alternatives → · See all tEDM alternatives →
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
Both compete on the same themes — r-package — within Analytics. nflreadr and tEDM 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. nflreadr and tEDM 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 nflreadr alternatives in Analytics are ranked by recent ship velocity. Browse the "nflreadr alternatives" section above for the current picks, or visit /alternatives/nflreadr for the full list with editorial commentary on each.
Top tEDM alternatives in Analytics are ranked by recent ship velocity. Browse the "tEDM alternatives" section above for the current picks, or visit /alternatives/tedm for the full list with editorial commentary on each.