hockey-analytics

hockey-analytics is a skill for Claude Code from PuckAPI/claude-sports-analytics. It costs 107 tokens per session (2,474 once invoked), scanned A, original, MIT.

An explainer for hockey statistics such as Corsi, Fenwick, PDO, expected goals, zone entries, RAPM, and WAR. These are measures used to describe possession, shot quality, player impact, and team or player performance.

In plain words
What is it for?
Use it to learn what an advanced hockey metric means, interpret a team's or player's numbers, compare performance, or understand why a statistic changes over time.
Why use it?
It translates unfamiliar advanced statistics into ordinary language and explains how to interpret them in context. Live team, player, goalie, or metric data can be retrieved when the user asks for it.

Skill for Claude Code

Written for Claude Code: shipped in a Claude Code plugin.

Part of the puckapi-skills plugin — 28 skills shipped together

Good fit Use it to learn what an advanced hockey metric means, interpret a team's or player's numbers, compare performance, or understand why a statistic changes over time.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/puckapi/claude-sports-analytics/hockey-analytics
Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add PuckAPI/claude-sports-analytics --skill hockey-analytics
Clone the repo
git clone --depth 1 https://github.com/PuckAPI/claude-sports-analytics

Made for: Claude Code.

Or install puckapi-skills, the plugin that ships this one along with the rest of its 28 skills.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for hockey-analytics

README.md
[![agentmods](https://agentmods.dev/badge/skills/puckapi/claude-sports-analytics/hockey-analytics/github.svg)](https://agentmods.dev/skills/puckapi/claude-sports-analytics/hockey-analytics)
Your own site
<a href="https://agentmods.dev/skills/puckapi/claude-sports-analytics/hockey-analytics"><img src="https://agentmods.dev/badge/skills/puckapi/claude-sports-analytics/hockey-analytics/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for hockey-analytics

Your own site · 80×15
<a href="https://agentmods.dev/skills/puckapi/claude-sports-analytics/hockey-analytics"><img src="https://agentmods.dev/badge/skills/puckapi/claude-sports-analytics/hockey-analytics.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 107 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,474 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00107 $0.02474
Opus 5 $0.00053 $0.01237
Sonnet 5 $0.00021 $0.00495
Haiku 4.5 $0.00011 $0.00247

Measured 10d ago against content hash f463148a2418, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-10, from the pricing page.

Security

Grade A, and why

hockey-analytics scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 10d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

skills/hockey-analytics/SKILL.md · 195 lines

How it starts

The opening of the file, as written. The whole thing — 195 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Hockey Analytics

Default data tool: PuckAPI (puckapi-tool). Use get_team_stats for team-level advanced metrics (5 credits), get_player_stats for player bio data (5 credits), get_goalie_stats for goalie metrics (5 credits). For metric definitions and formulas without live data, no credits are consumed -- this skill answers from domain knowledge.

You are an expert hockey analyst. Your goal is to teach users what advanced hockey metrics mean, show them how to read the numbers in context, and connect metrics to real team/player data when asked.

This is the ON-RAMP. Users land here to understand metrics before they build models. Answer with the metric, then pull real numbers to make it concrete.

When to Use

  • "What is Corsi?" / "What does CF% mean?"
  • "Explain Fenwick to me"
  • "What does a PDO of 1.02 mean?"
  • "Is [team]'s xG rate good or bad this season?"
  • "What are high-danger chances?"
  • "What does RAPM measure?"
  • "How do I read zone entry data?"
  • "Explain advanced stats for the [team]"
  • "Why is PDO said to regress?"

When NOT to Use

  • Odds, line movement, vig, or betting concepts -- see odds-analysis
  • Building an xG model from scratch -- see xg-model-building
  • Feature engineering for a prediction model -- see feature-engineering
  • WAR decomposition and component breakdown -- see war-gar-decomposition

Commands Available

Command What It Does Credits
get_team_stats Team-level stats including shot attempt rates, PDO components 5
get_player_stats Player bio data (name, team, position); goalie stats for goalies 5
get_goalie_stats Save percentage, GAA, GSAA for goalies 5

Commands That Do NOT Exist

Not Available Use Instead
get_corsi Use get_team_stats and compute CF% from shot attempt columns
get_fenwick Use get_team_stats and subtract blocked shots from Corsi columns
get_xg xG is model-derived; pull shot data via get_team_stats and apply xG weights
get_zone_entries Not available via this tool; sourced from tracking data providers
get_rapm RAPM is model-derived; not a raw API field

Read the full file on GitHub · 195 lines

Files

What ships with it

1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 10d ago First seen · 195 lines · 107 tokens per session scan A f463148a2418

Subscribe to this mod's changes

hockey-analytics is a skill published in the GitHub repository PuckAPI/claude-sports-analytics (3 stars, last pushed 4mo ago), licensed MIT. It adds 107 tokens to every session and 2,474 once invoked, about $0.0005 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.

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