STACAS
Single-cell batch correction that learned to use cell labels, then spent three releases chasing Seurat.
Comparison · Analytics
cfbfastr vs spEDM
A side-by-side editorial comparison of cfbfastr and spEDM — release velocity, themes, recent moves, and the top alternatives to consider.
Shared themes:r-package
cfbfastr vs spEDM: at a glance
What is cfbfastr?
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.
What is spEDM?
Spatial causal discovery in R, one exposed method per release
spEDM brings empirical dynamic modeling to spatial data — cross mapping, convergent cross mapping and pattern causality over spatial vector and raster inputs, with the numerics in C++ behind S4 generics. The recent releases have exposed geographical pattern causality and spatially convergent partial cross mapping at the R level with vignettes, and 1.12 turns to consolidating the API. It is part of the stscl family alongside the temporal-domain tEDM, with which it shares both its C++ core and its maintainer.
cfbfastr vs spEDM: editorial side-by-side
cfbfastr
0.0ANALYTICS
College football's open data client hit v2 — and now reports how many API calls you have left.
◆ Current state
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.
◆ Where it's heading
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.
◆ Prediction
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.
spEDM
0.0ANALYTICS
Spatial causal discovery in R, one exposed method per release
◆ Current state
spEDM brings empirical dynamic modeling to spatial data — cross mapping, convergent cross mapping and pattern causality over spatial vector and raster inputs, with the numerics in C++ behind S4 generics. The recent releases have exposed geographical pattern causality and spatially convergent partial cross mapping at the R level with vignettes, and 1.12 turns to consolidating the API. It is part of the stscl family alongside the temporal-domain tEDM, with which it shares both its C++ core and its maintainer.
◆ Where it's heading
The cadence is steady and predictable: each release surfaces one more EDM method as an R-level API with a vignette, then spends the rest of its notes on parameter-handling consistency across the generics. Breaking changes are frequent and deliberate — argument renames, parameter reordering, NA-handling defaults — which reads as a package still settling its interface while the method surface expands. Shared changes appear in tEDM within days, so interface churn lands on both packages at once.
◆ Prediction
Expect the next release to expose another causality variant at the R level with an accompanying vignette, and to continue renaming or reordering parameters toward consistency across the spatial and temporal packages.
Alternatives to cfbfastr and spEDM
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 spEDM.
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 cfbfastr alternatives → · See all spEDM alternatives →
Recent activity from cfbfastr and spEDM
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
- 4mo agospEDMData slicing for large-scale pattern causality, plus API breaks
- 6mo agospEDMspEDM 1.11
- 6mo agospEDMSpatially convergent partial cross mapping reaches the R API
- 8mo agospEDMRaster cross mapping with anisotropic embedding
- 11mo agocfbfastrRebuilt on CFBD API v2 with metered access and live endpoints ⚡
- 11mo agospEDMConfigurable distance metrics and multithreaded distance computation
- 1y agospEDMSpatial logistic map exposed at the R level
- 4y agocfbfastrESPN endpoints and repo-backed loaders added
- 4y agocfbfastrAll outputs standardised as tibbles with a custom class
- 4y agocfbfastrCRAN release with option-restoring cleanup
- 4y agocfbfastrMinor fixes to betting and FPI rating functions
- 4y agocfbfastrESPN scoreboard and play-by-play access, with argument cleanup
Frequently asked questions
What is the difference between cfbfastr and spEDM?
Both compete on the same themes — r-package — within Analytics. cfbfastr and spEDM 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 cfbfastr better than spEDM?
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. cfbfastr and spEDM 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 cfbfastr?
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.
What are the best alternatives to spEDM?
Top spEDM alternatives in Analytics are ranked by recent ship velocity. Browse the "spEDM alternatives" section above for the current picks, or visit /alternatives/spedm for the full list with editorial commentary on each.