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cfbfastr vs fastglm

A side-by-side editorial comparison of cfbfastr and fastglm — release velocity, themes, recent moves, and the top alternatives to consider.

Shared themes:r-package

cfbfastr vs fastglm: at a glance

Featurecfbfastrfastglm
SectorAnalyticsAnalytics
Velocity score0.00.0
Sparks · 30d00
Top themescollege-football, sports-analytics, api-migration, rate-limitsstatistical-computing, generalized-linear-models, cpp, r-package
Last editorial update1h ago6h ago
WebsiteVisit →Visit →

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.

Read the full cfbfastr trajectory →

What is fastglm?

A fast GLM solver stops being one function and becomes a count-model family

fastglm ran C++ IRLS for standard generalized linear models for six years with almost no releases. In May 2026 it added three top-level model types — negative binomial with jointly estimated dispersion, hurdle, and zero-inflated — each with the entire fitting driver in C++ rather than an R loop around a C++ kernel. The following release generalised Firth bias reduction to every standard family across dense, sparse and streaming backends.

Read the full fastglm trajectory →

cfbfastr vs fastglm: editorial side-by-side

C
cfbfastr
ANALYTICS
0.0

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.

F
fastglm
ANALYTICS
0.0

A fast GLM solver stops being one function and becomes a count-model family

◆ Current state

fastglm ran C++ IRLS for standard generalized linear models for six years with almost no releases. In May 2026 it added three top-level model types — negative binomial with jointly estimated dispersion, hurdle, and zero-inflated — each with the entire fitting driver in C++ rather than an R loop around a C++ kernel. The following release generalised Firth bias reduction to every standard family across dense, sparse and streaming backends.

◆ Where it's heading

The package changed what it is. Through 0.0.3 it was a drop-in replacement for glm() competing on speed; from 0.1.0 it targets the models people leave base R for — MASS::glm.nb, pscl::hurdle, pscl::zeroinfl — and reimplements their full estimation loops natively. The 0.1.1 follow-up is consolidation on that new surface: Firth generalised past binomial logit, SQUAREM acceleration on the zero-inflation EM driver, and a run of clamping guards and initialization fixes on the families most prone to overflow.

◆ Prediction

The numerical-stability work in 0.1.1 clusters on Tweedie and the inverse and sqrt link families, which suggests those paths are the newest and least exercised — expect further correctness fixes there before new model types.

Alternatives to cfbfastr and fastglm

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 fastglm.

See all cfbfastr alternatives → · See all fastglm alternatives →

Recent activity from cfbfastr and fastglm

Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.

  1. 2mo agofastglmFirth generalised to all families, plus SQUAREM and stability fixes
  2. 3mo agofastglmCRAN release 0.1.0
  3. 11mo agocfbfastrRebuilt on CFBD API v2 with metered access and live endpoints
  4. 4y agofastglmC++ headers exposed for linking
  5. 4y agocfbfastrESPN endpoints and repo-backed loaders added
  6. 4y agocfbfastrAll outputs standardised as tibbles with a custom class
  7. 4y agocfbfastrCRAN release with option-restoring cleanup
  8. 4y agocfbfastrMinor fixes to betting and FPI rating functions
  9. 4y agocfbfastrESPN scoreboard and play-by-play access, with argument cleanup
  10. 7y agofastglmFirst CRAN release of the C++ IRLS solver

Frequently asked questions

What is the difference between cfbfastr and fastglm?

Both compete on the same themes — r-package — within Analytics. cfbfastr and fastglm 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 fastglm?

Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. cfbfastr and fastglm 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 fastglm?

Top fastglm alternatives in Analytics are ranked by recent ship velocity. Browse the "fastglm alternatives" section above for the current picks, or visit /alternatives/fastglm for the full list with editorial commentary on each.