batter_percentile_ranks
Analyze MLB hitter performance using Statcast percentile ranks for metrics like exit velocity and barrel rate. Compare players against league averages to evaluate their elite status in specific statistical categories.
Instructions
Statcast percentile ranks for hitters vs the league (exit velo, barrel%, xwOBA, etc.).
Each metric is 0–100 where higher is better for that stat. Use to answer "How elite is this hitter on Statcast?" or compare league-wide.
Args: year: Season year (e.g. 2024). player_name: Optional. If set, returns only that player's row (e.g. "Aaron Judge").
Qualifying batters: ~2.1 PA per team game (Statcast default).
Input Schema
TableJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
| year | Yes | ||
| player_name | No |
Output Schema
TableJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
| result | Yes |
Implementation Reference
- src/statcast_mcp/server.py:1190-1219 (handler)Implementation of the batter_percentile_ranks MCP tool, which fetches data from pybaseball and formats it.
@mcp.tool() def batter_percentile_ranks(year: int, player_name: str | None = None) -> str: """Statcast percentile ranks for hitters vs the league (exit velo, barrel%, xwOBA, etc.). Each metric is 0–100 where higher is better for that stat. Use to answer "How elite is this hitter on Statcast?" or compare league-wide. Args: year: Season year (e.g. 2024). player_name: Optional. If set, returns only that player's row (e.g. "Aaron Judge"). Qualifying batters: ~2.1 PA per team game (Statcast default). """ from pybaseball import statcast_batter_percentile_ranks as _fn try: data = _fn(year) except Exception as e: return f"Error fetching batter percentile ranks: {e}" if player_name: try: data = _filter_player_rows(data, player_name) except ValueError as e: return str(e) if data.empty: return f"No percentile data found for {player_name} in {year}." return _fmt(data, max_rows=50)