football-data▌
machina-sports/sports-skills · updated Apr 8, 2026
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Soccer data across 13 leagues with standings, schedules, match stats, xG, transfers, and player profiles — no API keys required.
- ›Covers 13 leagues including Premier League, La Liga, Bundesliga, Serie A, Ligue 1, MLS, Champions League, World Cup, and others
- ›Provides match-level data: lineups, team statistics, timelines (goals, cards, substitutions), and expected goals (xG) for top 5 leagues only
- ›Includes player profiles, season leaders, transfer history via Transfermarkt, and injury/d
Football Data
Before writing queries, consult references/api-reference.md for endpoints, ID conventions, and data shapes.
Setup
Before first use, check if the CLI is available:
which sports-skills || pip install sports-skills
If pip install fails (package not found or Python version error), install from GitHub:
pip install git+https://github.com/machina-sports/sports-skills.git
The package requires Python 3.10+. If your default Python is older, use a specific version:
python3 --version # check version
# If < 3.10, try: python3.12 -m pip install sports-skills
# On macOS with Homebrew: /opt/homebrew/bin/python3.12 -m pip install sports-skills
No API keys required.
Quick Start
Prefer the CLI — it avoids Python import path issues:
sports-skills football get_daily_schedule
sports-skills football get_season_standings --season_id=premier-league-2025
Python SDK (alternative):
from sports_skills import football
standings = football.get_season_standings(season_id="premier-league-2025")
schedule = football.get_daily_schedule()
CRITICAL: Before Any Query
CRITICAL: Before calling any data endpoint, verify:
- Season ID is derived from
get_current_season(competition_id="...")— never hardcoded. - Team ID is verified via
search_team(query="...")if only a name is provided. get_event_xgandget_event_players_statistics(with xG) are only called for top-5 leagues (EPL, La Liga, Bundesliga, Serie A, Ligue 1).get_season_leadersandget_missing_playersare only called for Premier League seasons (season_id must start withpremier-league-).
Choosing the Season
Derive the current year from the system prompt's date (e.g., currentDate: 2026-02-16 → current year is 2026).
- If the user specifies a season, use it as-is.
- If the user says "current", "latest", or doesn't specify: Call
get_current_season(competition_id="...")to get the active season_id. Do NOT guess or hardcode the year. - Season format: Always
{league-slug}-{year}(e.g.,"premier-league-2025"for the 2025-26 season). The year is the start year of the season, not the end year. - MLS exception: MLS runs spring-fall within a single calendar year. Use
get_current_season(competition_id="mls").
Commands
| Command | Description |
|---|---|
get_current_season |
Detect current season for a competition |
get_competitions |
List available competitions with current season info |
get_competition_seasons |
Available seasons for a competition |
get_season_schedule |
Full season match schedule |
get_season_standings |
League table for a season |
get_season_leaders |
Top scorers/leaders (Premier League only) |
get_season_teams |
Teams in a season |
search_team |
Search for a team by name |
search_player |
Search for a player by name |
get_team_profile |
Basic team info (no squad/roster) |
get_daily_schedule |
All matches for a date across all leagues |
get_event_summary |
Match summary with scores |
get_event_lineups |
Match lineups |
get_event_statistics |
Match team statistics |
get_event_timeline |
Match timeline (goals, cards, subs) |
get_team_schedule |
Schedule for a specific team |
get_head_to_head |
UNAVAILABLE — returns empty |
get_event_xg |
xG data (top 5 leagues only) |
get_event_players_statistics |
Player-level match stats with optional xG |
get_missing_players |
Injured/doubtful players (Premier League only) |
get_season_transfers |
Transfer history via Transfermarkt |
get_player_season_stats |
Player season stats via ESPN |
get_player_profile |
Player profile (FPL and/or Transfermarkt) |
See references/api-reference.md for full parameter lists, return shapes, and data coverage table.
Examples
Example 1: Premier League table User says: "Show me the Premier League table" Actions:
- Call
get_current_season(competition_id="premier-league")to get the current season_id - Call
get_season_standings(season_id=<season_id from step 1>)Result: Standings table with position, team, played, won, drawn, lost, GD, points
Example 2: Match report User says: "How did Arsenal vs Liverpool go?" Actions:
- Call
get_daily_schedule()orget_team_schedule(team_id="359")to find the event_id - Call
get_event_summary(event_id="...")for the score - Call
get_event_statistics(event_id="...")for possession, shots, etc. - Call
get_event_xg(event_id="...")for xG comparison (EPL — top 5 only) Result: Match report with scores, key stats, and xG
Example 3: Team deep dive User says: "Deep dive on Chelsea's recent form" Actions:
- Call
search_team(query="Chelsea")→ team_id=363, competition=premier-league - Call
get_team_schedule(team_id="363", competition_id="premier-league")→ find recent closed events - For each recent match, call in parallel:
get_event_xg,get_event_statistics,get_event_players_statistics - Call
get_missing_players(season_id=<season_id>)→ filter Chelsea's injured/doubtful players Result: xG trend across matches, key player stats, and injury report
Example 4: Player market value User says: "What's Saka's market value?" Actions:
- Call
get_player_profile(tm_player_id="433177")for Transfermarkt data - Optionally add
fpl_idfor FPL stats Result: Market value, value history, and transfer history
Example 5: Non-PL club User says: "Tell me about Corinthians" Actions:
- Call
search_team(query="Corinthians")→ team_id=874, competition=serie-a-brazil - Call
get_team_schedule(team_id="874", competition_id="serie-a-brazil")for fixtures - Pick a recent match and call
get_event_timeline(event_id="...")for goals, cards, subs Result: Fixtures, timeline events (note: xG, FPL stats, and season leaders NOT available for Brazilian Serie A)
Commands that DO NOT exist — never call these
— the correct command isget_standingsget_season_standings(requiresseason_id).— not available. Useget_live_scoresget_daily_schedule()for today's matches./get_team_squad—get_team_rosterget_team_profiledoes NOT return players. Useget_season_leadersfor PL player IDs, thenget_player_profile.— the correct command isget_transfersget_season_transfers(requiresseason_id+tm_player_ids)./get_match_results— useget_matchget_event_summarywith anevent_id.— useget_player_statsget_event_players_statisticsfor match-level stats, orget_player_profilefor career data./get_scores— useget_resultsget_event_summarywith anevent_id.— useget_fixturesget_daily_schedulefor today's matches orget_season_schedulefor a full season.— useget_league_tableget_season_standingswith aseason_id.
If a command is not in the Commands table above, it does not exist. Do not try commands not listed.
Error Handling
When a command fails (wrong event_id, missing data, network error, etc.), do not surface the raw error to the user. Instead:
- Catch it silently — treat the failure as an exploratory miss.
- Try alternatives — if an event_id returns no data, call
get_daily_schedule()orget_team_schedule()to discover the correct ID. - Only report failure after exhausting alternatives — use a clean message (e.g., "I couldn't find that match — can you confirm the teams or date?").
Troubleshooting
Error: sports-skills command not found
Cause: Package not installed
Solution: Run pip install sports-skills. If not on PyPI, install from GitHub: pip install git+https://github.com/machina-sports/sports-skills.git
Error: ModuleNotFoundError: No module named 'sports_skills'
Cause: Package not installed or path issue
Solution: Install the package. Prefer the CLI over Python imports to avoid path issues
Error: get_season_leaders or get_missing_players returns empty for a non-PL league
Cause: These commands only work for Premier League; they silently return empty for other leagues
Solution: Check the Data Coverage table in references/api-reference.md. For other leagues, use get_event_players_statistics for player data
Error: get_team_profile returns no players
Cause: This command does not return squad rosters — this is expected behavior
Solution: For PL teams, use get_season_leaders to find player FPL IDs, then get_player_profile(fpl_id="...")
Error: Wrong season_id format
Cause: Season ID must follow the {league-slug}-{year} format
Solution: Use get_current_season(competition_id="...") to discover the correct format. Example: "premier-league-2025", not "2025-2026" or "EPL-2025"
Error: No xG data for a recent match
Cause: Understat data may lag 24-48 hours after a match ends
Solution: If get_event_xg returns empty for a recent top-5 match, retry later. Only available for EPL, La Liga, Bundesliga, Serie A, Ligue 1
Error: Team or event ID unknown
Cause: ID was guessed instead of looked up
Solution: Use search_team(query="team name") to find team IDs, or get_daily_schedule / get_season_schedule to find event IDs. Never guess IDs.
How to use football-data on Cursor
AI-first code editor with Composer
Prerequisites
Before installing skills in Cursor, ensure your development environment meets these requirements:
- ›Cursor installed and configured on your development machine
- ›Node.js version 16.0+ with npm package manager (verify with
node --version) - ›Active project directory or workspace where you want to add football-data
Execute installation command
Execute the skills CLI command in your project's root directory to begin installation:
The skills CLI fetches football-data from GitHub repository machina-sports/sports-skills and configures it for Cursor.
Select Cursor when prompted
The CLI will show a list of available agents. Use arrow keys to navigate and space to select Cursor:
Verify installation
Confirm successful installation by checking the skill directory location:
Reload or restart Cursor to activate football-data. Access the skill through slash commands (e.g., /football-data) or your agent's skill management interface.
Security & Verification Notice
We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.
Skills execute code in your development environment. Always verify the publisher's identity, review recent commits, and test in isolated environments before production deployment.
List & Monetize Your Skill
Submit your Claude Code skill and start earning
Use Cases▌
User Story & Requirements Generation
Create detailed user stories, acceptance criteria, and feature specs
Example
Generate user stories for 'password reset feature' with acceptance criteria, edge cases, and test scenarios
Reduce spec writing time by 50%, ensure comprehensive coverage
Competitive Analysis
Research competitors, compare features, identify gaps
Example
Analyze 5 competitor products, create feature comparison matrix, suggest differentiation opportunities
Complete competitive research in 2 hours instead of 2 days
Roadmap Prioritization
Evaluate features using frameworks (RICE, ICE, Kano) and create prioritized backlogs
Example
Score 20 feature ideas using RICE framework, generate prioritized roadmap with rationale
Make data-driven prioritization decisions faster
Stakeholder Communication
Draft PRDs, status updates, and stakeholder presentations
Example
Create executive summary of Q3 roadmap, monthly progress report, feature launch announcement
Save 3-5 hours/week on communication overhead
Implementation Guide▌
Prerequisites
- ›Claude Desktop or compatible AI client
- ›Access to product documentation and roadmap tools (Jira, Notion, etc.)
- ›Understanding of product management frameworks (RICE, Jobs-to-be-Done, etc.)
- ›Stakeholder contact information and communication channels
Time Estimate
30-60 minutes to see productivity improvements
Installation Steps
- 1.Install product management skill
- 2.Start with user story generation for known feature
- 3.Progress to competitive analysis: research 2-3 competitors
- 4.Use for roadmap prioritization: apply RICE/ICE scoring
- 5.Draft stakeholder communications and refine based on feedback
- 6.Build template library for recurring PM tasks
- 7.Share effective prompts with product team
Common Pitfalls
- ⚠Not validating competitive research—verify facts before sharing
- ⚠Accepting user stories without involving engineering team
- ⚠Over-relying on frameworks without qualitative judgment
- ⚠Not customizing outputs to company culture and communication style
- ⚠Skipping stakeholder validation of generated requirements
Best Practices▌
✓ Do
- +Validate research and competitive analysis with real data
- +Collaborate with engineering when generating technical requirements
- +Customize frameworks and templates to your company context
- +Use skill for first drafts, refine with stakeholder input
- +Document successful prompt patterns for PM tasks
- +Combine AI efficiency with human judgment and intuition
✗ Don't
- −Don't publish competitive analysis without fact-checking
- −Don't finalize user stories without engineering review
- −Don't make prioritization decisions solely on AI scoring
- −Don't skip customer validation of generated requirements
- −Don't ignore company-specific context and culture
💡 Pro Tips
- ★Provide context: company goals, constraints, customer feedback
- ★Ask for alternatives: 'Show 3 ways to prioritize this roadmap'
- ★Request stakeholder-specific formatting: 'Executive summary vs. engineering spec'
- ★Use skill for 70% generation + 30% customization to company needs
When to Use This▌
✓ Use When
Use for user story writing, competitive research, roadmap prioritization, stakeholder communication, and PRD drafting. Best for reducing repetitive documentation and research work.
✗ Avoid When
Avoid for strategic product vision (requires deep customer empathy), pricing decisions (needs market and financial expertise), or when face-to-face customer discovery is more valuable than speed.
Learning Path▌
- 1Basic: user stories, feature specs, status updates
- 2Intermediate: competitive analysis, prioritization frameworks, PRDs
- 3Advanced: product strategy, go-to-market planning, OKR setting
- 4Expert: product vision, market positioning, business model innovation
Discussion
Product Hunt–style comments (not star reviews)- No comments yet — start the thread.
Ratings
4.6★★★★★45 reviews- ★★★★★Kabir Liu· Dec 28, 2024
Useful defaults in football-data — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
- ★★★★★Tariq Martinez· Dec 28, 2024
We added football-data from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
- ★★★★★Jin Singh· Dec 16, 2024
Keeps context tight: football-data is the kind of skill you can hand to a new teammate without a long onboarding doc.
- ★★★★★Chaitanya Patil· Dec 12, 2024
Solid pick for teams standardizing on skills: football-data is focused, and the summary matches what you get after install.
- ★★★★★Pratham Ware· Dec 8, 2024
football-data reduced setup friction for our internal harness; good balance of opinion and flexibility.
- ★★★★★Jin Bansal· Nov 19, 2024
football-data is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
- ★★★★★Luis Sanchez· Nov 19, 2024
Solid pick for teams standardizing on skills: football-data is focused, and the summary matches what you get after install.
- ★★★★★Dev Ghosh· Nov 7, 2024
I recommend football-data for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
- ★★★★★Piyush G· Nov 3, 2024
We added football-data from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
- ★★★★★Ren Yang· Oct 26, 2024
Useful defaults in football-data — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
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