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Single-cell batch correction that learned to use cell labels, then spent three releases chasing Seurat.
Comparison · Analytics
cfbfastr vs nmar
A side-by-side editorial comparison of cfbfastr and nmar — release velocity, themes, recent moves, and the top alternatives to consider.
cfbfastr vs nmar: 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 nmar?
NMAR landed on CRAN with two nonresponse estimators behind one interface, then started tuning it.
Three releases in seven weeks, starting from nothing. The initial CRAN release implements empirical likelihood (Qin, Leung and Shao 2002) and both parametric and nonparametric exponential tilting (Riddles, Kim and Im 2016) for estimating means under nonignorable nonresponse, all reachable through a single nmar() call with formula syntax and direct support for survey.design objects. Since then the work has been operational: a configurable bootstrap backend and stricter input validation.
cfbfastr vs nmar: 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.
nmar
0.0ANALYTICS
NMAR landed on CRAN with two nonresponse estimators behind one interface, then started tuning it.
◆ Current state
Three releases in seven weeks, starting from nothing. The initial CRAN release implements empirical likelihood (Qin, Leung and Shao 2002) and both parametric and nonparametric exponential tilting (Riddles, Kim and Im 2016) for estimating means under nonignorable nonresponse, all reachable through a single nmar() call with formula syntax and direct support for survey.design objects. Since then the work has been operational: a configurable bootstrap backend and stricter input validation.
◆ Where it's heading
The package is positioning itself as the general interface to nonignorable-nonresponse estimation rather than a reference implementation of one paper — shared architecture across engines, one formula API, and integration with the survey package so weights and stratification come for free. The follow-up releases suggest the next constraint is compute: bootstrap variance estimation is the expensive part, and it now dispatches to future.apply when a parallel plan exists.
◆ Prediction
Expect further engines under the same nmar() interface or wider bootstrap support, since the architecture was explicitly refactored to share structure across estimators.
Alternatives to cfbfastr and nmar
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 nmar.
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 nmar alternatives →
Recent activity from cfbfastr and nmar
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
- 6mo agonmarBootstrap backend now parallel-aware and configurable
- 7mo agonmarCRAN submission fixes and DOI references
- 8mo agonmarNMAR 0.1.0 ⚡
- 11mo agocfbfastrRebuilt on CFBD API v2 with metered access and live endpoints ⚡
- 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 nmar?
They serve adjacent needs but don't currently overlap on shipped themes. cfbfastr and nmar 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 nmar?
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. cfbfastr and nmar 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 nmar?
Top nmar alternatives in Analytics are ranked by recent ship velocity. Browse the "nmar alternatives" section above for the current picks, or visit /alternatives/nmar for the full list with editorial commentary on each.