Explorar skills

Track predictions vs actuals in production: log bets, compute CLV, monitor ROI, detect edge decay, and run significance tests. Use when user asks about tracking bets, bet logging, closing line value, CLV, ROI tracking, win rate, drawdown monitoring, or whether their model has an edge right now. Do not use for finding today's bets -- see daily-card or edge-detection. Do not use for historical backt

Builds automated sports analytics pipelines -- daily data pulls, scheduled prediction generation, model versioning, prediction tracking, and drift alerting. Use when user asks how to automate their model, how to run predictions every morning, how to set up a cron job for sports data, how to track model performance over time, or how to version their model. Do not use for one-time data pulls -- use

Teaches how to use Claude and MCP tools effectively for hockey analytics -- exploratory analysis, hypothesis testing, model iteration, and report generation. Use when user asks how to analyze hockey data with AI, how to structure an analysis session, how to test a hypothesis about team or player performance, how to improve a model systematically, or how to generate a performance report. Do not use

Walk-forward historical testing of betting strategies to determine whether a model's edge is real. Use when user asks about backtesting, historical simulation, ROI over a season, whether a strategy works, bootstrap confidence intervals, edge compression, or model audit over time. Refuses in-sample testing -- walk-forward only. Do not use for live bet tracking -- see bet-tracker. Do not use for fin