Nhl Data logo

Nhl Data

Organization
machina-sports
nhl-data

NHL data via ESPN public endpoints and the official NHL API — scores, standings, rosters, schedules, game summaries, injuries, futures, leaders, and news, plus an analytics backend: play-by-play with on-ice coordinates, cross-league career rows, skater/goalie leaders, and history to 1917. Zero config, no API keys. Use when: user asks about NHL scores, standings, team rosters, schedules, game stats, box scores, play-by-play, injuries, transactions, betting futures, team/player statistics, NHL news, shot locations, career stats, skater/goalie leaders, or historical NHL seasons. Don't use when: user asks about other hockey leagues (AHL, KHL, college hockey). For other sports use: nfl-data (NFL), nba-data (NBA), wnba-data (WNBA), mlb-data (MLB), football-data (soccer), tennis-data (tennis), golf-data (golf), cricket-data (cricket), cfb-data (college football), cbb-data (college basketball), fastf1 (F1). For betting odds use polymarket or kalshi. For news use sports-news.

Overview

Publishermachina-sports
Repositorysports-skills
Skill namenhl-data
Stars
255
Forks
38
Bundled files
3
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 3 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by machina-sports on GitHub. Read the source before you install it.

Installation

Install the Nhl Data AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/machina-sports/sports-skills/tree/main/skills/nhl-data
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/machina-sports/sports-skills.git /tmp/sports-skills
mkdir -p .claude/skills
cp -r /tmp/sports-skills/skills/nhl-data .claude/skills/nhl-data
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Nhl Data in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Nhl Data on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Nhl Data is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

NHL 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:

bash
which sports-skills || pip install sports-skills

If pip install fails with a Python version error, the package requires Python 3.10+. Find a compatible Python:

bash
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:

bash
sports-skills nhl get_scoreboard
sports-skills nhl get_standings --season=2025
sports-skills nhl get_teams

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: 2026-02-18 → 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 NHL season runs October–June. If the current month is October–December, the active season year matches the current year. If January–June, the active season started the previous calendar year (use that year as the season).
  • Example: Current date is February 2026 → active season started October 2025 → use season 2025.

Commands

CommandDescription
get_scoreboardLive/recent NHL scores
get_standingsStandings by conference and division
get_teamsAll NHL teams
get_team_rosterFull roster for a team
get_team_scheduleSchedule for a specific team
get_game_summaryDetailed box score and scoring plays
get_leadersNHL statistical leaders
get_newsNHL news articles
get_play_by_playFull play-by-play for a game
get_scheduleGames on a specific date (no season filter; see get_team_schedule)
get_injuriesInjury reports across all teams
get_transactionsRecent transactions
get_futuresFutures/odds markets
get_team_statsTeam statistical profile
get_player_statsPlayer statistical profile
find_nhl_playerSearch the NHL's player registry by name
get_nhlstats_scheduleGames via the NHL API — team seasons to the Original Six era, NHL game ids
get_nhlstats_player_statsCareer season-by-season across leagues via NHL API
get_nhlstats_player_game_logOne player's games in a season (opponent, home/away, result, stat line) via NHL API
get_nhlstats_play_by_playPlay-by-play with on-ice x/y coordinates, zone, shot type
get_nhlstats_boxscoreFull box score (skaters + goalies) via NHL API
get_nhlstats_standingsStandings, current or any historical date (back to 1917)
get_nhlstats_leadersSkater and goalie leaders by category

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

Using ESPN and the NHL API Together

The get_nhlstats_* commands read api-web.nhle.com — the NHL's current API. (The retired statsapi.web.nhl.com, which most community docs still describe, no longer resolves.) It carries the analytics layer ESPN does not: on-ice shot coordinates, cross-league career rows, goalie leaders, and history to the Original Six era. The two sources use unrelated id systems:

  • Game ids. NHL ids are 10 digits encoding season/type/game (2023030417); ESPN uses 9-digit event ids (401559593). No shared column — join on the game date plus teams.
  • Team abbreviations. Five teams differ: ESPN LA/NJ/SJ/TB/UTAH vs NHL LAK/NJD/SJS/TBL/UTA. Every get_nhlstats_* team filter accepts either spelling, and rows carry both (team_abbreviation, team_abbreviation_espn).
  • Player ids. NHL player ids (8478402) and ESPN athlete ids are unrelated. Resolve names with find_nhl_player; ASCII spellings match accented names ("stutzle" finds "Tim Stützle").
  • Career rows span leagues. get_nhlstats_player_stats returns every league a player appeared in, each row labelled with league and is_nhl — filter to is_nhl before summing career numbers. A player traded mid-season has one NHL row per team plus a team: "TOTAL" row (is_total: true, counting stats summed, rate stats omitted); skip is_total rows when summing.
  • Seasons. Pass the starting year (season=2024 means 2024-25). The NHL form ("20242025") is also accepted.
  • How a final was decided. status is the NHL's game state (OFF/FINAL for any final). decided_by on schedule rows and box scores is REG, OT or SO (null until final). Shootout scores follow the official result: the winner is credited one goal (a 1-1 game won in the shootout is 2-1).
  • Blocked shots. In get_nhlstats_play_by_play, team_id and player on a blocked-shot row are the shooter's (the NHL's event owner); the box score's blockedShots credits the defender, given as blocking_player and blocking_team_id. Count blocks by blocking_team_id.

Examples

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

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

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

  1. Derive season year from currentDate
  2. Call get_standings(season=<derived_year>)
  3. Filter results for Eastern Conference Result: Eastern Conference standings with W-L-OTL, points, regulation wins

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

  1. Call get_team_roster(team_id="21") Result: Full Maple Leafs roster with name, position, jersey number, shoots/catches

Example 4: Game box score User says: "Show me the full box score for last night's Bruins game" Actions:

  1. Call get_scoreboard(date="<yesterday>") to find the event_id
  2. Call get_game_summary(event_id=<id>) for full box score Result: Complete box score with per-player stats and scoring plays

Example 5: Stanley Cup odds User says: "What are the Stanley Cup odds?" Actions:

  1. Call get_futures(limit=10) Result: Top Stanley Cup contenders with odds values

Example 6: Player statistics User says: "Show me Connor McDavid's stats" Actions:

  1. Derive season year from currentDate
  2. Call get_player_stats(player_id="3895074", season_year=<derived_year>) Result: Season stats by category with value, rank, and per-game averages

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

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 NHL teams with their IDs (expansion teams like the Seattle Kraken and Utah Mammoth have non-sequential 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: Offseason — scoreboard returns 0 events Cause: No games scheduled during the offseason (July–September) Solution: Use get_standings or get_news instead; use get_schedule to find when the season resumes

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Nhl Data AI skill do?

NHL data via ESPN public endpoints and the official NHL API — scores, standings, rosters, schedules, game summaries, injuries, futures, leaders, and news, plus an analytics backend: play-by-play with on-ice coordinates, cross-league career rows, skater/goalie leaders, and history to 1917. Zero config, no API keys. Use when: user asks about NHL scores, standings, team rosters, schedules, game stats, box scores, play-by-play, injuries, transactions, betting futures, team/player statistics, NHL news, shot locations, career stats, skater/goalie leaders, or historical NHL seasons. Don't use when...

Why use Nhl Data on TypingMind?

Because you install it once and use it with any model. Nhl Data is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Nhl Data in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/machina-sports/sports-skills/tree/main/skills/nhl-data. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Nhl Data?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Nhl Data?

As many as you like. As long as a model supports skills, you can use Nhl Data with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Nhl Data AI skill free?

Yes. It is published on GitHub by machina-sports under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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