Skills publicadas
Mostrando 4 de 28walk-forward-validation
The correct evaluation methodology for time-series sports prediction models. Use when user asks about model validation, cross-validation, train/test split, accuracy evaluation, overfitting detection, or statistical significance of sports model results. Refuses to run k-fold cross-validation on time-series data -- always redirects to walk-forward. Do not use for backtesting betting strategies with
team-analysis
Evaluates teams via standings, stats, division/conference rankings, season trends, and strength of schedule. Use when user asks how a team is doing, where they stand in the division, what their record is, how they compare to other teams, or wants to understand conference/playoff positioning. Do not use for individual player stats -- see player-scouting. Do not use for goalie performance -- see goa
ai-hockey-workflow
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
odds-explorer
Multi-book odds comparison, best price identification, vig calculation, line shopping, and line movement analysis for NHL. Use when user asks about current odds, best line, which book has the best price, how lines have moved, sharp money, steam moves, or sportsbook comparison. Do not use for devigging or implied probability math -- see odds-analysis. Do not use for comparing model output vs market