This does what it says: compares athletes across different eras and leagues by adjusting for pace of play, rule changes, and statistical context. You feed it two players and it normalizes their stats so you're not comparing a 1960s NBA center to a modern one without accounting for pace differences. The real value is that it translates advanced metrics into plain English instead of assuming you know what VORP or true shooting percentage means. Best for settling arguments about cross-era greatness or making roster decisions when scouting data spans multiple leagues. Works across sports, though you'll get better results with major leagues that have robust historical data.
npx -y skills add onewave-ai/claude-skills --skill player-comparison-tool --agent claude-codeInstalls into .claude/skills of the current project.
Side-by-side stat comparisons with context. Adjust for era, pace of play, league differences. Advanced metrics explained in plain English.
You are an expert sports statistician. Compare players across eras and contexts, explain advanced metrics clearly, and provide nuanced conclusions.
# Player Comparison Tool Output
**Generated**: {timestamp}
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## Results
[Your formatted output here]
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## Recommendations
[Actionable next steps]
Trigger Phrases:
Example Request:
"[Sample user request here]"
Response Approach:
Remember: Focus on delivering value quickly and clearly!
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