football-data

machina-sports/sports-skills · updated Apr 8, 2026

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$npx skills add https://github.com/machina-sports/sports-skills --skill football-data
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summary

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
skill.md

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_xg and get_event_players_statistics (with xG) are only called for top-5 leagues (EPL, La Liga, Bundesliga, Serie A, Ligue 1).
  • get_season_leaders and get_missing_players are only called for Premier League seasons (season_id must start with premier-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:

  1. Call get_current_season(competition_id="premier-league") to get the current season_id
  2. 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:

  1. Call get_daily_schedule() or get_team_schedule(team_id="359") to find the event_id
  2. Call get_event_summary(event_id="...") for the score
  3. Call get_event_statistics(event_id="...") for possession, shots, etc.
  4. 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:

  1. Call search_team(query="Chelsea") → team_id=363, competition=premier-league
  2. Call get_team_schedule(team_id="363", competition_id="premier-league") → find recent closed events
  3. For each recent match, call in parallel: get_event_xg, get_event_statistics, get_event_players_statistics
  4. 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:

  1. Call get_player_profile(tm_player_id="433177") for Transfermarkt data
  2. Optionally add fpl_id for FPL stats Result: Market value, value history, and transfer history

Example 5: Non-PL club User says: "Tell me about Corinthians" Actions:

  1. Call search_team(query="Corinthians") → team_id=874, competition=serie-a-brazil
  2. Call get_team_schedule(team_id="874", competition_id="serie-a-brazil") for fixtures
  3. 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

  • get_standings — the correct command is get_season_standings (requires season_id).
  • get_live_scores — not available. Use get_daily_schedule() for today's matches.
  • get_team_squad / get_team_rosterget_team_profile does NOT return players. Use get_season_leaders for PL player IDs, then get_player_profile.
  • get_transfers — the correct command is get_season_transfers (requires season_id + tm_player_ids).
  • get_match_results / get_match — use get_event_summary with an event_id.
  • get_player_stats — use get_event_players_statistics for match-level stats, or get_player_profile for career data.
  • get_scores / get_results — use get_event_summary with an event_id.
  • get_fixtures — use get_daily_schedule for today's matches or get_season_schedule for a full season.
  • get_league_table — use get_season_standings with a season_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:

  1. Catch it silently — treat the failure as an exploratory miss.
  2. Try alternatives — if an event_id returns no data, call get_daily_schedule() or get_team_schedule() to discover the correct ID.
  3. 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

How to use football-data on Cursor

AI-first code editor with Composer

1

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
2

Execute installation command

Execute the skills CLI command in your project's root directory to begin installation:

$npx skills add https://github.com/machina-sports/sports-skills --skill football-data

The skills CLI fetches football-data from GitHub repository machina-sports/sports-skills and configures it for Cursor.

3

Select Cursor when prompted

The CLI will show a list of available agents. Use arrow keys to navigate and space to select Cursor:

◆ Which agents do you want to install to?
│ ── Universal (.agents/skills) ── always included ────
│ • Amp
│ • Antigravity
│ • Cline
│ • Codex
│ ●Cursor(selected)
│ • Cursor
│ • Windsurf
4

Verify installation

Confirm successful installation by checking the skill directory location:

.cursor/skills/football-data

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

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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. 1.Install product management skill
  2. 2.Start with user story generation for known feature
  3. 3.Progress to competitive analysis: research 2-3 competitors
  4. 4.Use for roadmap prioritization: apply RICE/ICE scoring
  5. 5.Draft stakeholder communications and refine based on feedback
  6. 6.Build template library for recurring PM tasks
  7. 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

  1. 1Basic: user stories, feature specs, status updates
  2. 2Intermediate: competitive analysis, prioritization frameworks, PRDs
  3. 3Advanced: product strategy, go-to-market planning, OKR setting
  4. 4Expert: product vision, market positioning, business model innovation

Discussion

Product Hunt–style comments (not star reviews)
  • No comments yet — start the thread.
general reviews

Ratings

4.645 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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