STACAS
Single-cell batch correction that learned to use cell labels, then spent three releases chasing Seurat.
Comparison · Analytics
nflfastR vs sdsfun
A side-by-side editorial comparison of nflfastR and sdsfun — release velocity, themes, recent moves, and the top alternatives to consider.
nflfastR vs sdsfun: at a glance
What is nflfastR?
nflfastR is shedding surface to the rest of nflverse and consolidating on one stats API.
The play-by-play backbone of nflverse, shipping one or two releases a year with long bug-fix lists against decades of NFL data. Since 5.0.0 the package has had a single calculate_stats() entry point that replaces the older calculate_player_stats*() family, backed by an exported nfl_stats_variables table describing every returned column. The last two releases hand work outward — standings moved to nflseedR, and the loaders are now straight re-exports of nflreadr — while fast_scraper_roster(), fast_scraper_schedules() and report() are formally deprecated.
What is sdsfun?
A spatial-statistics utility package exists to be depended on, and is built accordingly.
sdsfun collects spatial data science utilities — neighbour lists, spatial constrained clustering, discretization, dummy variable generation, geographical detector statistics and projection helpers — with the computationally heavy parts implemented in Rcpp. It was assembled quickly across late 2024, adding a function set roughly every three weeks, and has slowed since to a couple of releases a year. The most recent work is corrective: no longer initializing the RNG state at load, fixing matrix inputs misread as vectors, and clearing an Armadillo deprecation.
nflfastR vs sdsfun: editorial side-by-side
nflfastR
0.0ANALYTICS
nflfastR is shedding surface to the rest of nflverse and consolidating on one stats API.
◆ Current state
The play-by-play backbone of nflverse, shipping one or two releases a year with long bug-fix lists against decades of NFL data. Since 5.0.0 the package has had a single calculate_stats() entry point that replaces the older calculate_player_stats*() family, backed by an exported nfl_stats_variables table describing every returned column. The last two releases hand work outward — standings moved to nflseedR, and the loaders are now straight re-exports of nflreadr — while fast_scraper_roster(), fast_scraper_schedules() and report() are formally deprecated.
◆ Where it's heading
nflfastR is becoming the parsing and modelling core rather than the whole toolkit. Every recent release either narrows its own API or points users at a sibling package, and the documentation strategy follows: re-exported functions are deliberately undocumented here so nflreadr stays the single source. The remaining in-house work is data correctness — duplicated play IDs, scramble identification, new penalty types — plus keeping the xgboost-backed models running as that dependency moves.
◆ Prediction
The deprecated scrapers and report() are the next things to be removed outright, and the calculate_player_stats*() family should follow, leaving calculate_stats() as the only supported path.
sdsfun
0.0ANALYTICS
A spatial-statistics utility package exists to be depended on, and is built accordingly.
◆ Current state
sdsfun collects spatial data science utilities — neighbour lists, spatial constrained clustering, discretization, dummy variable generation, geographical detector statistics and projection helpers — with the computationally heavy parts implemented in Rcpp. It was assembled quickly across late 2024, adding a function set roughly every three weeks, and has slowed since to a couple of releases a year. The most recent work is corrective: no longer initializing the RNG state at load, fixing matrix inputs misread as vectors, and clearing an Armadillo deprecation.
◆ Where it's heading
This is infrastructure for a family of packages rather than an end-user tool, and the changelog says so directly — functions were added to support gdverse and sesp, and moran_test was migrated in from geocomplexity. That migration pattern is the defining move: capability consolidates here so the downstream packages can share it instead of each carrying its own copy. Growth has slowed as that consolidation completed, leaving correctness and dependency upkeep.
◆ Prediction
Given the package moves when its dependents need something, the next release most likely brings in another shared function or responds to a downstream requirement rather than following its own plan. Armadillo and CRAN check changes remain the reliable source of maintenance work.
Alternatives to nflfastR and sdsfun
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 nflfastR or sdsfun.
ggtrace
A debugger for ggplot2's internals, hardening its grip as the internals it traces keep moving.
kde1d
A univariate density estimator that added zero-inflated data and reopened its C++ API to do it.
svines
Stationary vine copulas for time series, released in lockstep with the rest of Nagler's vine stack.
gghighlight
A single-purpose ggplot2 extension that has spent six years tracking ggplot2 instead of growing.
rtrek
A Star Trek data package that became a Memory Alpha web client and has been patching scrapers ever since.
See all nflfastR alternatives → · See all sdsfun alternatives →
Recent activity from nflfastR and sdsfun
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
- 6mo agonflfastRLoaders re-exported from nflreadr; legacy scrapers deprecated
- 10mo agosdsfunPackage load stops touching the RNG state
- 1y agonflfastRStandings handed to nflseedR; R 4.1 now required
- 1y agosdsfunUnified partial correlation testing and head/tails discretization
- 1y agosdsfunMissing-value handling added to linear trend removal
- 1y agosdsfunCovariate-based detrending and long-to-matrix spatial reshaping
- 1y agonflfastRnflfastR 5.0.0 ⚡
- 1y agosdsfunSpatially constrained hierarchical clustering and SPADE estimation
- 1y agosdsfunFast geodetector q-value estimator added
- 2y agonflfastRSeason-level conversion rate aggregation fixed
- 2y agonflfastRRaw play-by-play can now be cached and parsed locally
- 3y agonflfastRReverse-dependency tests and dplyr compatibility fixes
Frequently asked questions
What is the difference between nflfastR and sdsfun?
They serve adjacent needs but don't currently overlap on shipped themes. nflfastR and sdsfun 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.
Is nflfastR better than sdsfun?
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. nflfastR and sdsfun 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.
What are the best alternatives to nflfastR?
Top nflfastR alternatives in Analytics are ranked by recent ship velocity. Browse the "nflfastR alternatives" section above for the current picks, or visit /alternatives/nflfastr for the full list with editorial commentary on each.
What are the best alternatives to sdsfun?
Top sdsfun alternatives in Analytics are ranked by recent ship velocity. Browse the "sdsfun alternatives" section above for the current picks, or visit /alternatives/sdsfun for the full list with editorial commentary on each.