simlandr
Potential landscape tooling settling onto standard R generics after two rounds of renaming.
A side-by-side editorial comparison of hoopr and kde1d — release velocity, themes, recent moves, and the top alternatives to consider.
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.
A univariate density estimator that added zero-inflated data and reopened its C++ API to do it.
kde1d estimates univariate densities with local polynomial kernel methods, handling bounded, discrete and now zero-inflated variables through a single type argument, with the numerical work in a header-only C++ library usable outside R. Version 1.1.0 added the zero-inflated discrete-continuous mixture case and shipped a new C++ API as an explicit breaking change; 1.1.1 followed in June with auto-generated notes and no description.
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.
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.
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.
kde1d estimates univariate densities with local polynomial kernel methods, handling bounded, discrete and now zero-inflated variables through a single type argument, with the numerical work in a header-only C++ library usable outside R. Version 1.1.0 added the zero-inflated discrete-continuous mixture case and shipped a new C++ API as an explicit breaking change; 1.1.1 followed in June with auto-generated notes and no description.
The package has alternated between performance work and widening the class of data it accepts. The 1.0.0 release was the performance milestone — FFT-based estimation, a better integration algorithm for the p, q and r functions, deterministic jittering replacing randomness, and standalone C++ headers. The 1.1.0 release is the scope milestone, adding a third data type to the two it already handled. Releases come from the same maintainer as svines and cluster on shared dates, so changes in the underlying C++ surface across the vine and density stack tend to ship together.
With the C++ API deliberately reworked for standalone use at 1.1.0, further work most plausibly consolidates that interface rather than adding data types. What 1.1.1 actually changed is not readable from its body.
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 kde1d.
Potential landscape tooling settling onto standard R generics after two rounds of renaming.
SEM reporting helpers converging on APA output, one CRAN resubmission at a time.
A raster-to-terra migration is the only readable change in a feed of merge notes.
A nycflights13 generator whose recent work is all about the data being right.
Conditional density and log-likelihood fill out a vine copula regression package.
A drop-in string API for base R, kept alive by upstream check failures.
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
They serve adjacent needs but don't currently overlap on shipped themes. hoopr and kde1d 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.
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. hoopr and kde1d 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.
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.
Top kde1d alternatives in Analytics are ranked by recent ship velocity. Browse the "kde1d alternatives" section above for the current picks, or visit /alternatives/kde1d for the full list with editorial commentary on each.