hockey-analytics

Name: hockey-analytics
Availability: InStock
Author: PuckAPI

Explain advanced hockey analytics metrics like Corsi, Fenwick, PDO, xG, and RAPM.

2|1|Updated May 1, 2026

Search Tags:#performance #analytics #metrics #team #player #hockey #advanced stats

Ready to run

npx skills add https://github.com/PuckAPI/claude-sports-analytics --skill hockey-analytics

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: hockey-analytics
Source: https://github.com/PuckAPI/claude-sports-analytics/tree/main/skills/hockey-analytics
Command: npx skills add https://github.com/PuckAPI/claude-sports-analytics --skill hockey-analytics

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

This Skill helps users learn and interpret advanced hockey analytics metrics, bridging the gap between raw data and meaningful understanding.

Core Features & Use Cases

Metric Explanation: Clarifies the meaning and significance of metrics like Corsi, Fenwick, PDO, xG, and RAPM.
Data Retrieval: Provides real data examples from teams and players to illustrate metric concepts.
Use Case: For instance, explain Buffalo's CF% this season by fetching team data and contextualizing the number in league standings.
Operational Support: Assists users in understanding how to apply metrics in team analysis, player scouting, or model building.

Quick Start

Ask the AI to explain a hockey metric like CF% or interpret a team's advanced stats using real data.

Frequently Asked Questions about hockey-analytics

High-intent search queries and answers about installing and using this skill.

FAQPage Schema

What do advanced hockey analytics metrics like Corsi and Fenwick actually measure?▼

Advanced hockey analytics metrics like Corsi and Fenwick measure puck possession by tracking shot attempts. Corsi includes all shots on goal, missed shots, and blocked shots, while Fenwick excludes blocked shots, providing insights into a team's offensive and defensive performance trends.

How do I interpret a hockey team's PDO and xG metrics using real data?▼

To interpret hockey metrics like PDO and xG using real data, you analyze shooting plus save percentages for PDO, and expected goals for xG. Fetching team data provides context to evaluate if a team's performance is sustainable or subject to regression.

Can I use this Skill to explain specific player performance stats such as RAPM?▼

Yes, you can use this Skill to explain specific player performance stats such as RAPM. It retrieves real player data to demonstrate how Regularized Adjusted Plus-Minus isolates a player's even-strength impact by controlling for teammates and opponents.

How does this Skill retrieve real team and player data for hockey metrics?▼

This Skill retrieves real team and player data for hockey metrics by using data retrieval APIs. It fetches relevant team and player metrics, such as a team's CF% this season, to provide concrete examples and contextualize the numbers within league standings.

What is the best way to apply advanced stats like xG in hockey team analysis?▼

The best way to apply advanced stats like xG in hockey team analysis is to compare expected goals against actual goals to identify scoring efficiency. This Skill provides data retrieval and context to assist in evaluating strategic performance and building models.

Do I need prior knowledge of advanced hockey stats to understand the metric explanations?▼

No, you do not need prior knowledge of advanced hockey stats. The Skill clarifies the meaning and significance of metrics like Corsi, Fenwick, PDO, xG, and RAPM from the ground up, bridging raw data with meaningful understanding for team analysis.