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Explore, interpret, and draw conclusions from football data. Use when the user wants to analyse match events, compare teams or players, understand tactical patterns, build visualisations, or needs guidance on what questions to ask of their data. Adapts to the user's experience level.

Fetch, scrape, or download football data from any source. Also handles API key setup and credential management. Use when the user wants to get data from StatsBomb, Opta, FBref, Understat, SportMonks, Wyscout, Kaggle, or any football data source. Also use when they ask about API keys, authentication, setting up access to a provider, or what data is available free vs paid.

Review football data code and visualisations for correctness. Use after building a chart, data pipeline, or analysis. Dispatches specialised reviewers for data correctness, chart conventions, visual inspection, and interactive edge cases.

Fix broken data scrapers and pipelines. Use when data acquisition fails, a scraper breaks, an API returns errors, or data format has changed. Also handles submitting upstream issues or PRs when the problem is in a dependency like soccerdata or kloppy.

Choose how and where to store football data. Use when the user asks about database choices, file formats, cloud storage, data pipelines, or how to organise their football data project. Also covers publishing and sharing outputs (Streamlit, Observable, GitHub Pages).

Football data analytics — the single entry point. Use whenever the user mentions football data, xG, expected goals, match analysis, player stats, scouting, match reports, shot maps, passing networks, Premier League data, Champions League stats, scraping FBref/Understat/Transfermarkt, building football charts, or anything football analytics related. Routes to specialised sub-skills automatically. A

Learn about football analytics concepts and explore provider documentation. Use when the user asks what a metric means (xG, PPDA, expected threat, xT), wants learning resources, papers, or courses, is new to football analytics, or wants a learning path. Also use when the user asks about data provider documentation — qualifier IDs, coordinate systems, event types, API schemas, field mappings, ident

Brainstorm football data visualisations and chart designs. Use when the user wants ideas for how to visualise football data, needs inspiration for chart types, wants to explore design approaches for match reports, player profiles, team dashboards, or any football analytics graphic. Searches the web for popular approaches and real-world examples before proposing options.

Transform, filter, reshape, join, and manipulate football data. Use when the user needs to clean data, merge datasets, convert between formats, handle missing values, work with large datasets, or do any data manipulation task on football data.

Calculate derived football metrics and models. Use when the user wants to compute xG, xGOT, PPDA, passing networks, expected threat, possession value, pressing intensity, or any derived football statistic from raw data.

Use this skill when the user wants a code review before shipping, merging, or deploying. Trigger on "ship review", "review my changes", "code review", "review my diff", "is this ready to ship", "is this ready to merge", "check this over before I push", "brutal review", "kind review", "pre-ship review", or when the user says they've finished building and wants feedback. Also trigger when the user i

Use this skill when the user wants to set up, configure, or initialize the ship plugin, create or update their ship profile, change their review mode, update their product brief, or edit .claude/ship.local.md. Trigger on "ship init", "set up ship", "configure ship", "create my profile", "update my profile", "change review mode to brutal/kind", or when any other ship skill detects that .claude/ship