MCPInstall

nfl-data

NFL data via ESPN public endpoints plus an nflverse backend for schedules, weekly rosters, play-by-play, and normalized player/team stat tables. Zero config, no API keys. Use when: user asks about NFL scores, standings, team rosters, schedules, game stats, box scores, play-by-play, injuries, transactions, betting futures, depth charts, team/player statistics, NFL news, or which players are trending in fantasy adds/drops. Don't use when: user asks about football/soccer (use football-data), college football (use cfb-data), or other sports.

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Install

Works with every agent the skills CLI supports.

npx skills add https://github.com/machina-sports/sports-skills --skill nfl-data
  1. 01

    Install

    Run the command in your project. The CLI asks which agents to install for.

  2. 02

    Describe the task

    Ask your agent for something this skill covers. It loads nfl-data automatically when relevant.

  3. 03

    Review the result

    The agent follows the SKILL.md steps, scripts and references bundled with the skill.

SKILL.md

The instructions your agent reads when the skill is triggered.

NFL 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.

For nflverse-backed commands (get_nflverse_*), install the NFL extra:

pip install sports-skills[nfl]

On Python 3.10+ this installs nflreadpy (the preferred backend) plus pyarrow, which is needed for most nflverse data beyond schedules. On Python 3.9 it installs nfl-data-py instead, since nflreadpy requires 3.10+.

The nfl-data-py backend is a reduced fallback: it cannot serve get_nflverse_team_stats, which returns an explanatory error there. Use Python 3.10+ for full nflverse coverage.

Quick Start

Prefer the CLI — it avoids Python import path issues:

sports-skills nfl get_scoreboard
sports-skills nfl get_standings --season=2025
sports-skills nfl get_teams

Python SDK (alternative):

from sports_skills import nfl

scores = nfl.get_scoreboard({})
standings = nfl.get_standings({"params": {"season": "2025"}})

CRITICAL: Before Any Query

CRITICAL: Before calling any data endpoint, verify:

  • Season year is derived from the system prompt's currentDate — never hardcoded.
  • If only a team name is provided, call get_teams to resolve the team ID before using team-specific commands.

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", "this season", or doesn't specify: The NFL season runs September–February. If the current month is March–August, use season = current_year (upcoming season). If September–February, the active season started in the previous calendar year if you're in Jan/Feb, otherwise current year.

Commands

CommandDescription
get_scoreboardLive/recent NFL scores
get_standingsStandings by conference and division
get_teamsAll 32 NFL teams
get_team_rosterFull roster for a team
get_team_scheduleSchedule for a specific team; reports coverage limits
get_game_summaryDetailed box score and scoring plays
get_leadersNFL statistical leaders
get_newsNFL news articles
get_play_by_playFull play-by-play for a game
get_win_probabilityWin probability chart data
get_scheduleOne season week or ESPN's current window; never a whole season
get_injuriesInjury reports with provider-native or unresolved identity
get_transactionsRecent transactions
get_futuresFutures/odds markets
get_depth_chartDepth chart for a team
get_team_statsTeam statistical profile
get_player_statsPlayer statistical profile
get_nflverse_schedulenflverse-backed schedules/results table (carries espn_event_id)
get_nflverse_weekly_rostersnflverse-backed weekly rosters
get_nflverse_player_statsnflverse-backed player stats — season totals by default
get_nflverse_team_statsnflverse-backed team stats — season totals by default
get_nflverse_play_by_playnflverse-backed play-by-play rows
get_fantasy_trendingSleeper fantasy trending adds/drops (popularity counts, Sleeper player IDs)

See references/api-reference.md for full parameter lists and return shapes.

Do not infer a bye from an empty get_schedule response: inspect its coverage block, whose completeness is unknown or partial, never complete. For a whole team season use get_team_schedule; season-only get_schedule is refused because ESPN's scoreboard mixes and truncates it. An absent or unresolved injury record is not evidence that a player is healthy.

Fantasy Trending (Sleeper)

get_fantasy_trending reads Sleeper's public trending endpoint: the NFL players most added (or dropped) in Sleeper fantasy leagues over a recent window.

sports-skills nfl get_fantasy_trending --trend_type=add --lookback_hours=24 --limit=10
sports-skills nfl get_fantasy_trending --trend_type=drop
  • trend_type: add (default) or drop. lookback_hours: whole hours, 1-168 (default 24). limit: 1-100 (default 10).
  • count is the add/drop tally Sleeper's trending API reports for the player over the window. It is a popularity signal, not a projection, ranking, or betting edge — say so when reporting it.
  • Player IDs are sleeper_player_id, Sleeper's own namespace — keep them as the identifier. There is no mapping to ESPN athlete IDs or nflverse GSIS IDs: do not attach one, and do not present a name or team match against another provider as the same confirmed player.
  • name_resolved: false means Sleeper's player catalog had no name for that ID. team and position are resolved separately and may still be filled in. If the catalog itself could not be fetched, catalog_status is unavailable and warnings[] says why; counts and IDs are still valid.
  • Report freshness from source.trending_fetched_at. Trending results are cached in memory for 5 minutes, within one process only — each new CLI call fetches them again. Sleeper's player catalog (trimmed to IDs, names, teams and positions) is also saved under $XDG_CACHE_HOME/sports-skills/sleeper/ (default ~/.cache/...) and reused across processes until 24 hours after it was fetched, since Sleeper asks clients to fetch it at most once a day. That disk cache is best effort: if it cannot be written, the call still succeeds and the next process fetches the catalog again.

Shaping Wide nflverse Results

nflverse tables are wide: one week of get_nflverse_player_stats is ~960 rows with 100+ stat columns (millions of characters). Every get_nflverse_* command accepts sort_by, descending, limit and fields so you can ask for just the rows you need:

# Week 5 passing leaders, 5 rows, 2 stat columns
sports-skills nfl get_nflverse_player_stats --season=2025 --week=5 --position=QB \
  --sort_by=passing_yards --limit=5 --fields=passing_yards,attempts
  • sort_by: one column to sort by. Numbers (and numeric strings) sort numerically; missing values always go last.
  • descending: true (default) or false; only used with sort_by.
  • limit: positive integer, applied after sorting.
  • fields: comma-separated keep-list. The identity columns below and the sort_by column are always kept.
  • An unknown sort_by/fields column returns an error listing the valid columns.
  • With any of these set, the response adds total_rows (matching rows before limit) and returned_rows. With none set, output is unchanged. They are applied after the fetch, so they never change the upstream request or its replay entry.
  • Stat columns inside stats (e.g. passing_yards) are addressable directly; fields keeps stats as an object holding only the selected keys.
CommandAlways kept by fields
get_nflverse_player_statsplayer_id, player_name, position, team, week
get_nflverse_team_statsteam, season, week, game_id
get_nflverse_play_by_playplay_id, game_id
get_nflverse_weekly_rostersplayer_id, player_name, team, position
get_nflverse_schedulegame_id, week, away_team, home_team

Using ESPN and nflverse Together

The two backends use different identifier systems. get_nflverse_schedule is the bridge: each event carries espn_event_id, which is exactly the ESPN event ID.

To combine nflverse analytics (EPA, win probability, betting lines) with ESPN detail (box scores, drives) for the same game:

  1. Call get_nflverse_schedule(season=..., week=...).
  2. Read espn_event_id off the event you want.
  3. Pass it as event_id to get_game_summary, get_play_by_play, or get_win_probability.

Two things that do not line up automatically:

  • Team abbreviations. ESPN uses LAR and WSH; nflverse uses LA and WAS. The get_nflverse_* functions accept either and translate. Going the other way (nflverse → ESPN), resolve via get_teams.
  • Player IDs. ESPN athlete IDs and nflverse GSIS IDs (00-0033873) are unrelated, and no crosswalk is available. Match on name plus team instead.

Field to watch on schedule rows: total is the combined points actually scored, while total_line is the betting over/under. Use total_line for market work.

Examples

Example 1: Today's scores User says: "What are today's NFL scores?" Actions:

  1. Call get_scoreboard() Result: All live and recent NFL games with scores and status

Example 2: Conference standings User says: "Show me the AFC standings" Actions:

  1. Derive season year from currentDate
  2. Call get_standings(season=<derived_year>)
  3. Filter results for AFC conference Result: AFC standings table with W-L-T, PCT, PF, PA per team

Example 3: Team roster User says: "Who's on the Chiefs roster?" Actions:

  1. Call get_team_roster(team_id="12") Result: Full Chiefs roster with name, position, jersey number, height, weight

Example 4: Super Bowl box score User says: "How did the Super Bowl go?" Actions:

  1. Call get_schedule(week=23) to find the Super Bowl event_id
  2. Call get_game_summary(event_id=<id>) for full box score Result: Complete box score with passing/rushing/receiving stats and scoring plays

Example 5: Injury report User says: "Who's injured on the Chiefs?" Actions:

  1. Call get_injuries()
  2. Filter results for Kansas City Chiefs (team_id=12) Result: Chiefs injury list with player name, position, status, and injury type

Example 6: Player statistics User says: "Show me Patrick Mahomes' stats this season" Actions:

  1. Derive season year from currentDate
  2. Call get_player_stats(player_id="3139477", season_year=<derived_year>) Result: Season stats by category with value, rank, and per-game averages

Example 7: nflverse weekly rosters User says: "Give me the Week 1 Chiefs roster from the data table backend" Actions:

  1. Derive season year from currentDate
  2. Call get_nflverse_weekly_rosters(season=<derived_year>, week=1, team="KC") Result: Weekly roster rows normalized for team, player, position, jersey, and status

Example 8: nflverse play-by-play User says: "Pull Bills Week 3 play-by-play" Actions:

  1. Derive season year from currentDate
  2. Call get_nflverse_play_by_play(season=<derived_year>, week=3, team="BUF") Result: Play rows with game_id, down/distance, description, EPA, WP/WPA, and score state

Example 9: Fantasy waiver-wire buzz User says: "Who are fantasy players picking up this week?" Actions:

  1. Call get_fantasy_trending(trend_type="add", lookback_hours=24, limit=10)
  2. Report name, team, position and count, with source.trending_fetched_at Result: The most-added players on Sleeper, described as popularity among Sleeper users rather than a recommendation

Commands that DO NOT exist — never call these

  • get_odds / get_betting_odds — not available. For prediction market odds, use the polymarket or kalshi skill.
  • search_teams — does not exist. Use get_teams instead.
  • get_box_score — does not exist. Use get_game_summary instead.
  • get_player_ratings — does not exist. Use get_player_stats instead.

If a command is not listed in the Commands table above, it does not exist.

Error Handling

When a command fails, do not surface raw errors to the user. Instead:

  1. Catch silently and try alternatives
  2. If team name given instead of ID, use get_teams to find the ID first
  3. Only report failure with a clean message after exhausting alternatives

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: nflverse backend unavailable Cause: Optional NFL backend extra not installed Solution: Install sports-skills[nfl] so the nflverse provider (nflreadpy or compatibility fallback) is available

Error: Team not found by ID Cause: Wrong or outdated ESPN team ID used Solution: Call get_teams to get the current list of all 32 NFL teams with their IDs

Error: No data returned for a future game Cause: ESPN only returns data for completed or in-progress games Solution: Use get_schedule to see upcoming game details; get_scoreboard only covers active/recent games

Error: Postseason week number returns no results Cause: Postseason uses unified week numbers (19-23) that differ from regular season Solution: Use week 19 for Wild Card, 20 for Divisional, 21 for Conference Championship, 23 for Super Bowl

FAQ

What does the nfl-data skill do?

NFL data via ESPN public endpoints plus an nflverse backend for schedules, weekly rosters, play-by-play, and normalized player/team stat tables. Zero config, no API keys. Use when: user asks about NFL scores, standings, team rosters, schedules, game stats, box scores, play-by-play, injuries, transactions, betting futures, depth charts, team/player statistics, NFL news, or which players are trending in fantasy adds/drops. Don't use when: user asks about football/soccer (use football-data), college football (use cfb-data), or other sports.

How do I install nfl-data?

Run npx skills add https://github.com/machina-sports/sports-skills --skill nfl-data in your project. The skills CLI detects the agents you use and copies the skill into the right folder. For Claude Code you can also place the skill folder at ~/.claude/skills/nfl-data/ (personal) or .claude/skills/nfl-data/ (project).

Which AI agents can use nfl-data?

Any agent that supports the open Agent Skills format (a folder with a SKILL.md file), including Claude Code, Codex, Cursor, GitHub Copilot, Gemini CLI, Windsurf, Cline, OpenCode and more.

Is nfl-data safe to install?

No partner security audit is available yet. Skills can run commands and scripts, so read the SKILL.md and any bundled files before installing.

Who maintains nfl-data?

It is published by machina-sports in machina-sports/sports-skills. It has 753 recorded installs.

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