randomwalk
randomwalk spent every release getting an R simulation to run in the browser, not on a server.
Comparison · Analytics
hoopr vs spEDM
A side-by-side editorial comparison of hoopr and spEDM — release velocity, themes, recent moves, and the top alternatives to consider.
Shared themes:breaking-changes
hoopr vs spEDM: at a glance
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.
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.
hoopr vs spEDM: editorial side-by-side
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.
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 hoopr 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 hoopr or spEDM.
fastml
fastml added survival modelling and leakage-proof resampling, moving past classification and regression.
abclass
abclass built out angle-based classifiers in 2022, then went quiet except for CRAN upkeep.
churon
churon is spending its entire release history getting a Rust ONNX binding through CRAN.
firatheme
firatheme woke up after four years and started fixing what ggplot2 changed underneath it.
bagyo
bagyo reached CRAN as a Philippine tropical cyclone dataset, with its tags stamped out of order.
Recent activity from hoopr and spEDM
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
- 4mo agospEDMData slicing for large-scale pattern causality, plus API breaks
- 4mo agohooprhoopR 3.0.0 moves every API backend to httr2 ⚡
- 6mo agospEDMspEDM 1.11
- 6mo agospEDMSpatially convergent partial cross mapping reaches the R API
- 8mo agospEDMRaster cross mapping with anisotropic embedding
- 11mo agospEDMConfigurable distance metrics and multithreaded distance computation
- 1y agospEDMSpatial logistic map exposed at the R level
- 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 hoopr and spEDM?
Both compete on the same themes — breaking-changes — within Analytics. hoopr 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 hoopr better than spEDM?
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. hoopr 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 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.
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.