Format basketball statistics with the StatsFormatter class for percentages, averages, and totals.
npx skills add https://github.com/a-jay85/IBL5 --skill basketball-stats
Please help me install this Agent Skill. Skill: basketball-stats Source: https://github.com/a-jay85/IBL5/tree/main/.claude/skills/basketball-stats Command: npx skills add https://github.com/a-jay85/IBL5 --skill basketball-stats
This Skill standardizes the formatting of various basketball statistics, ensuring consistency and readability across different contexts.
Use the basketball-stats skill to format the player's field goal percentage using their made and attempted field goals.
High-intent search queries and answers about installing and using this skill.
To format basketball statistics, apply specific formatting rules to percentages, averages, and totals to ensure numerical consistency and readability across sports data applications. This standardizes player and team metrics for professional presentation.
Calculate per-game and per-36-minute basketball averages by processing counting stats through a dedicated formatting class. This computes the performance metrics and applies appropriate formatting rules for consistent numerical display.
Handle zero-division for shooting percentages by applying custom formatting rules during the calculation of field goal, three-point, and free throw metrics. This ensures accurate numerical display even when a player has zero attempts.
You can apply custom decimal places to different basketball stat types using specific formatting rules. This allows precise control over how percentages, averages, and totals are presented for player or team statistics.
Format counting stats with appropriate comma separators by processing the raw totals through the statistics formatter. This presents numerical basketball data cleanly and improves readability for career stat lines.
The basketball statistics formatter applies to displaying both player and team statistics. It calculates performance metrics and ensures numerical consistency across different sports data contexts and applications.
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