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Comparison · Analytics
glmbayes vs hoopr
A side-by-side editorial comparison of glmbayes and hoopr — release velocity, themes, recent moves, and the top alternatives to consider.
glmbayes vs hoopr: at a glance
What is glmbayes?
A GPU-accelerated Bayesian GLM package buys its way into the standard R Bayesian toolchain
glmbayes fits Bayesian generalized linear models with optional OpenCL acceleration. The last four months moved it from a package with its own vocabulary to one that answers the insight and bayestestR generics the rest of the R Bayesian ecosystem is built on, while pushing the OpenCL kernels out into a separate nmathopencl dependency that carries CRAN Windows binaries. It returned to CRAN in August after an archival over a configure policy issue.
What is hoopr?
hoopR rebuilds its HTTP layer on httr2 to stop segfaulting on modern systems
hoopR is the sportsdataverse R package for basketball data, wrapping ESPN, NBA Stats, NBA G-League, NCAA and KenPom behind a single set of loaders. Version 3.0.0 replaces httr with httr2 across every one of those backends, drops httr from Imports, and routes all calls through shared internal retry and response helpers. The change is breaking, and it exists because the old stack segfaulted against libcurl 8.x and curl 7.0.0.
glmbayes vs hoopr: editorial side-by-side
glmbayes
6.3ANALYTICS
A GPU-accelerated Bayesian GLM package buys its way into the standard R Bayesian toolchain
◆ Current state
glmbayes fits Bayesian generalized linear models with optional OpenCL acceleration. The last four months moved it from a package with its own vocabulary to one that answers the insight and bayestestR generics the rest of the R Bayesian ecosystem is built on, while pushing the OpenCL kernels out into a separate nmathopencl dependency that carries CRAN Windows binaries. It returned to CRAN in August after an archival over a configure policy issue.
◆ Where it's heading
The arc is about removing reasons not to use it. GPU support was previously blocked on Windows because the OpenCL kernels were vendored; splitting them into a CRAN package with binaries fixed that. The ecosystem work does the same thing for tooling — a glmb fit now responds to get_parameters, get_priors, simulate_prior and check_prior, so it drops into workflows built around easystats rather than requiring its own. The CRAN archival and the configure fixes that followed show how much of the effort goes into distribution rather than modelling.
◆ Prediction
get_priors() returning the full prior specification rather than a marginal table is the kind of detail that invites further bayestestR integration, and the diagnostic surface is the least built-out part of what has shipped so far.
hoopr
0.0ANALYTICS
hoopR rebuilds its HTTP layer on httr2 to stop segfaulting on modern systems
◆ Current state
hoopR is the sportsdataverse R package for basketball data, wrapping ESPN, NBA Stats, NBA G-League, NCAA and KenPom behind a single set of loaders. Version 3.0.0 replaces httr with httr2 across every one of those backends, drops httr from Imports, and routes all calls through shared internal retry and response helpers. The change is breaking, and it exists because the old stack segfaulted against libcurl 8.x and curl 7.0.0.
◆ Where it's heading
The package's history is two distinct eras. Through 2021-2023 it grew by endpoint accretion — ESPN stat functions, G-League coverage, the NBA live and boxscore V3 families, on-court players in play-by-play — expanding what could be pulled. The recent work is consolidation instead: one HTTP pipeline, one messaging library, data served from the shared sportsdataverse-data releases rather than per-package repositories. The centre of gravity has moved from adding endpoints to making the plumbing survive its dependencies.
◆ Prediction
With the HTTP layer unified behind shared helpers, expect the sibling sportsdataverse packages to follow the same httr2 migration, and hoopR's own next releases to resume endpoint work now that requests run through one pipeline.
Alternatives to glmbayes and hoopr
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 glmbayes or hoopr.
gcube
gcube's recent releases are all packaging metadata, not simulation code
cubist
The R port of Quinlan's Cubist gets reproducibility fixes, not new modelling
ggstats
ggstats keeps widening what a coefficient or Likert plot can be
ecodive
ecodive rebuilt itself into a broad diversity-metric library, breaking as it went
simStateSpace
State-space data simulation for R, filled in one function at a time
See all glmbayes alternatives → · See all hoopr alternatives →
Recent activity from glmbayes and hoopr
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
- 11d agoglmbayesBack on CRAN after a configure policy fix
- 22d agoglmbayesOpenCL split out to nmathopencl; insight and bayestestR integration ⚡
- 1mo agoglmbayesMulti-response models and conjugate GLM priors
- 3mo agoglmbayesOpenCL kernels restructured and a binomial GPU bug fixed
- 3mo agoglmbayesVersion bump for CRAN resubmission
- 4mo agohooprhoopR 3.0.0 moves every API backend to httr2 ⚡
- 1y agoglmbayesCRAN-ready beta with the core S3 interface
- 2y agohooprData loaders repoint to sportsdataverse-data; NBA live endpoints
- 4y agohooprESPN stat functions and G-League coverage added
- 4y agohooprCRAN release with documented return shapes
- 4y agohooprhoopR 1.4.4
- 4y agohooprhoopR 1.4.3
Frequently asked questions
What is the difference between glmbayes and hoopr?
They serve adjacent needs but don't currently overlap on shipped themes. glmbayes is currently shipping more aggressively (velocity 6.3 vs 0.0), with 1 editorial sparks in the last 30 days against 0. See the at-a-glance table above for a side-by-side breakdown of velocity, recent sparks, and editorial themes.
Is glmbayes better than hoopr?
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. glmbayes is currently shipping more aggressively (velocity 6.3 vs 0.0), with 1 editorial sparks in the last 30 days against 0. For your specific use case, the alternatives sections above list other Analytics products to evaluate alongside.
What are the best alternatives to glmbayes?
Top glmbayes alternatives in Analytics are ranked by recent ship velocity. Browse the "glmbayes alternatives" section above for the current picks, or visit /alternatives/glmbayes for the full list with editorial commentary on each.
What are the best alternatives to hoopr?
Top hoopr alternatives in Analytics are ranked by recent ship velocity. Browse the "hoopr alternatives" section above for the current picks, or visit /alternatives/hoopr for the full list with editorial commentary on each.