TidyDensity
A distribution catalogue that grows by one family at a time, and rarely breaks anything.
A side-by-side editorial comparison of fastml and nflseedR — release velocity, themes, recent moves, and the top alternatives to consider.
fastml added survival modelling and leakage-proof resampling, moving past classification and regression.
A tidymodels-based AutoML wrapper that trains, tunes and compares many engines from one call. The 0.6.x line added engine-specific tuning parameters, class-imbalance handling, early stopping and DALEX-based explainability. The 0.7.5 release is far larger: a full survival analysis task with its own engines, MICE imputation and integrated Brier scoring, plus unbiased nested cross-validation, grouped, blocked and rolling resampling helpers, fold-wise imputation, recipe leakage checks, and a sandbox for user-supplied preprocessing.
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.
A tidymodels-based AutoML wrapper that trains, tunes and compares many engines from one call. The 0.6.x line added engine-specific tuning parameters, class-imbalance handling, early stopping and DALEX-based explainability. The 0.7.5 release is far larger: a full survival analysis task with its own engines, MICE imputation and integrated Brier scoring, plus unbiased nested cross-validation, grouped, blocked and rolling resampling helpers, fold-wise imputation, recipe leakage checks, and a sandbox for user-supplied preprocessing.
The package is moving from convenience wrapper to something that has to be defensible statistically. Nested cross-validation, fold-wise rather than up-front imputation, and explicit leakage checks are all corrections to the shortcuts that make AutoML easy and its scores optimistic. Survival adds a third task type alongside classification and regression, and it arrived with its own metrics rather than being bolted onto the existing ones. Note the entry body is cut off at 8,000 characters, so the release is larger than what is shown.
Expect the remaining survival engines to fill in and the sandboxing of custom preprocessing to tighten, since both were still being iterated on within this same release's commit list.
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.
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 fastml or nflseedR.
A distribution catalogue that grows by one family at a time, and rarely breaks anything.
College football's open data client hit v2 — and now reports how many API calls you have left.
The USA phenology data client rebuilt its entire stack and stopped handing users -9999 as a number.
GeneNMF rebuilt how it derives meta-programs, changing every result it had produced.
Publication-ready psychology tables and plots, tracking APA style as closely as the software allows.
A spatial-statistics utility package exists to be depended on, and is built accordingly.
See all fastml alternatives → · See all nflseedR alternatives →
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
They serve adjacent needs but don't currently overlap on shipped themes. fastml and nflseedR 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. fastml and nflseedR 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 fastml alternatives in Analytics are ranked by recent ship velocity. Browse the "fastml alternatives" section above for the current picks, or visit /alternatives/fastml for the full list with editorial commentary on each.
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.