STACAS
Single-cell batch correction that learned to use cell labels, then spent three releases chasing Seurat.
A side-by-side editorial comparison of cfbfastr and incase — release velocity, themes, recent moves, and the top alternatives to consider.
College football's open data client hit v2 — and now reports how many API calls you have left.
cfbfastR retrieves college football data — play-by-play, box scores, betting lines, ratings and recruiting — from the CollegeFootballData API, ESPN endpoints and the sportsdataverse data repository. Version 2.0.0 in September 2025 was the first release in over three years and rebuilt the package against CFBD's v2 API. Every load_cfb_*() function changed its underlying source to comply with CFBD's terms, the play-by-play dataset gained team and game identifiers users previously had to join in themselves, and a batch of new endpoints arrived covering opponent-adjusted metrics, FPI ratings and live scoreboard and play data.
A safer case_when that keeps hardening its guarantees while realigning to tidyverse naming.
incase supplies in_case(), switch_case(), grep_case() and fn_case() as vectorised recoding functions in the dplyr::case_when idiom, with _fct and _list variants that return factors or lists instead of forcing atomic type conversion. The 0.4.0 release deprecates the undotted preserve, default and ordered arguments in favour of dotted forms, starting a removal clock, and adds .exhaustive to error on unmatched inputs.
cfbfastR retrieves college football data — play-by-play, box scores, betting lines, ratings and recruiting — from the CollegeFootballData API, ESPN endpoints and the sportsdataverse data repository. Version 2.0.0 in September 2025 was the first release in over three years and rebuilt the package against CFBD's v2 API. Every load_cfb_*() function changed its underlying source to comply with CFBD's terms, the play-by-play dataset gained team and game identifiers users previously had to join in themselves, and a batch of new endpoints arrived covering opponent-adjusted metrics, FPI ratings and live scoreboard and play data.
The package's direction is now set by the data provider rather than by its own plans, and that provider has moved to metered access — the free tier is capped at 1,000 calls a month, with limits tied to membership level. cfbd_api_key_info() reporting a user's tier and usage is the clearest sign of that shift: quota is now something an analysis has to manage. The long gap before 2.0.0 and its arrival largely through a first-time contributor also indicate a package sustained by community effort rather than steady maintenance.
The live scoreboard and play endpoints are the natural place for the next work, since they are the ones that benefit from in-season iteration. Given the release notes warn users to check their pipelines, follow-up fixes for the changed loading functions are likely before anything new lands.
incase supplies in_case(), switch_case(), grep_case() and fn_case() as vectorised recoding functions in the dplyr::case_when idiom, with _fct and _list variants that return factors or lists instead of forcing atomic type conversion. The 0.4.0 release deprecates the undotted preserve, default and ordered arguments in favour of dotted forms, starting a removal clock, and adds .exhaustive to error on unmatched inputs.
The arc is consistently toward catching recoding mistakes at the call site rather than letting them pass silently. Early releases broadened how a match can be expressed — pattern matching, function application, factor and list returns. Recent work has shifted to guarantees about the result: correct factor level ordering relative to .default, and now an exhaustiveness check. Notably 0.4.0 reverses the 0.3.2 decision to accept arguments with or without dots, trading that flexibility for namespace safety against user-supplied case names.
The deprecation warnings introduced in 0.4.0 point to a follow-up release that removes the undotted arguments outright. Whether .exhaustive eventually becomes the default is unclear from these entries.
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 cfbfastr or incase.
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 cfbfastr alternatives → · See all incase alternatives →
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
Both compete on the same themes — r-package — within Analytics. cfbfastr and incase 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. cfbfastr and incase 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 cfbfastr alternatives in Analytics are ranked by recent ship velocity. Browse the "cfbfastr alternatives" section above for the current picks, or visit /alternatives/cfbfastr for the full list with editorial commentary on each.
Top incase alternatives in Analytics are ranked by recent ship velocity. Browse the "incase alternatives" section above for the current picks, or visit /alternatives/incase for the full list with editorial commentary on each.