mice
mice can finally predict, not just estimate, from multiply imputed data.
A side-by-side editorial comparison of Cursor and ggfootball — release velocity, themes, recent moves, and the top alternatives to consider.
| Feature | Cursor | ggfootball |
|---|---|---|
| Sector | Infra & APIs | Infra & APIs |
| Velocity score | 8.8 | 0.0 |
| Sparks · 30d | 3 | 0 |
| Top themes | ai-agents, autonomous-agents, event-driven, cloud-agents | sports-analytics, r-package, data-scraping, expected-goals |
| Last editorial update | 19h ago | 48m ago |
| Website | — | Visit → |
Cursor's agents stop waiting to be asked - they subscribe, and they hold a goal until it's done.
Cursor has spent two months moving agents out of the editor: cloud agents on iPhone and iPad, in Slack, on schedules, a team marketplace, a router picking the model per request, and Origin hosting repos and pull requests inside the product. This release changes how those agents are started. Cloud agents can subscribe to an event source - a PR, a Slack thread, a schedule - and wake when something happens, and /goal gives one a long-lived objective it works toward until complete. Subagents now get their own virtual machines with isolated project copies.
A football-viz package just swapped scraping for an API and broke its own output to do it.
ggfootball is a small R package for plotting expected-goals and shot data, sourced from Understat. Four releases are visible. The 0.2.x line was argument tidying and dependency pruning; 0.3.0 replaced the data-acquisition layer wholesale, moving get_match_shots() from HTML parsing onto Understat's AJAX endpoints and changing the returned column names in the process.
Cursor has spent two months moving agents out of the editor: cloud agents on iPhone and iPad, in Slack, on schedules, a team marketplace, a router picking the model per request, and Origin hosting repos and pull requests inside the product. This release changes how those agents are started. Cloud agents can subscribe to an event source - a PR, a Slack thread, a schedule - and wake when something happens, and /goal gives one a long-lived objective it works toward until complete. Subagents now get their own virtual machines with isolated project copies.
The through-line has been removing external dependencies and wait states; this release removes the human from the trigger. Agents that Cursor created now subscribe to their own pull requests and drive them to completion, fixing CI and answering bot comments unprompted. Isolated per-subagent VMs are what make that safe to parallelize - swarms can work without colliding - and steering lets a person redirect a running agent at the next tool call rather than interrupting it. Cursor is building the always-on case rather than the faster-autocomplete one.
With subscriptions limited to cloud agents for now, the obvious next step is bringing event-triggered runs to local agents, along with the controls an always-on fleet needs - spend limits, approval gates, and a way to review what ran while nobody was watching.
ggfootball is a small R package for plotting expected-goals and shot data, sourced from Understat. Four releases are visible. The 0.2.x line was argument tidying and dependency pruning; 0.3.0 replaced the data-acquisition layer wholesale, moving get_match_shots() from HTML parsing onto Understat's AJAX endpoints and changing the returned column names in the process.
The direction is away from scraped HTML and toward a thinner, more defensible package: four dependencies dropped in 0.3.0 on top of qdapRegex in 0.2.1, input validation added, error messages rewritten. Both breaking changes so far were accepted rather than deferred, which reads as a maintainer treating pre-1.0 as the window to get the shape right. The package is willing to break callers for structural reasons, not cosmetic ones.
With the scraper rebuilt and the dependency surface trimmed, the next releases are likely to stabilise the new column names and extend the plotting side, which has seen nothing since 0.2.0. A 1.0 would be the signal that the data structure is now considered fixed.
Other Infra & APIs 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 Cursor or ggfootball.
mice can finally predict, not just estimate, from multiply imputed data.
A market-microstructure toolkit that keeps adding estimators as the papers land.
A vowel-analysis package trimming dependencies after an email address got it archived.
The R half of the EMU speech database system, fixing what was quietly broken.
A Bayesian model-averaging package spending its 2.0 on memory, not methods.
tidyplots keeps rebuilding its own foundations rather than layering around them.
See all Cursor alternatives → · See all ggfootball alternatives →
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
They serve adjacent needs but don't currently overlap on shipped themes. Cursor is currently shipping more aggressively (velocity 8.8 vs 0.0), with 3 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.
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. Cursor is currently shipping more aggressively (velocity 8.8 vs 0.0), with 3 editorial sparks in the last 30 days against 0. For your specific use case, the alternatives sections above list other Infra & APIs products to evaluate alongside.
Top Cursor alternatives in Infra & APIs are ranked by recent ship velocity. Browse the "Cursor alternatives" section above for the current picks, or visit /alternatives/cursor for the full list with editorial commentary on each.
Top ggfootball alternatives in Infra & APIs are ranked by recent ship velocity. Browse the "ggfootball alternatives" section above for the current picks, or visit /alternatives/ggfootball for the full list with editorial commentary on each.