PuckAPI

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

Routes hockey analytics requests to the right 2-3 skills. Load this FIRST when a hockey data or analytics request comes in and you are unsure which skills to activate. Prevents loading all 28 skills when only 2-3 are needed. Also handles first-use persona detection.

Transforms raw game, player, and goalie data into model-ready features with built-in leakage detection. Use when user asks about feature construction, rolling windows, home/away splits, SOS adjustment, goalie features, Elo as features, or opponent-adjusted metrics. Strictly enforces .shift(1) before any rolling calculation. Do not use for raw data exploration -- see game-lookup or team-analysis. D

Full slate analysis for tonight's games with edge rankings, odds across books, and recommended stakes. Use when user asks about tonight's slate, best bets tonight, daily card, full slate, tonight's games, which games are worth betting, or wants all games ranked by edge. Do not use for a single game breakdown -- see game-preview. Do not use for historical backtesting -- see backtesting. Do not use

Compares model probabilities against market odds to find positive expected value bets. Use when user asks about EV calculation, edge magnitude, Kelly criterion, bankroll sizing, CLV tracking, closing line value, fractional Kelly, simultaneous bets, or which bets are worth placing. Do not use for odds exploration without a model -- see odds-explorer. Do not use for validating model accuracy -- see

Builds multi-variant Elo rating systems for sports prediction. Use when user asks about Elo ratings, rating systems, team strength, K-factor, home field advantage, season carryover, margin-of-victory adjustments, or mentions 'Fading Elo', 'Form Elo', 'Component Elo'. Do not use for general feature construction -- see feature-engineering instead. Do not use for team stats without ratings -- see tea

Finds games by date, team, matchup, or season -- past results, tonight's slate, upcoming schedule, head-to-head history. Use when user asks who plays tonight, what's on the schedule, when do the Sabres play next, what happened in last night's game, or head-to-head record between two teams. Do not use for team performance evaluation -- see team-analysis. Do not use for odds or betting lines -- see

Complete pre-game analysis for a single NHL (or other sport) matchup: team records, goalie matchup, key stats, odds snapshot, model edge, and head-to-head history in one shareable report. Use when user asks about a specific game tonight, matchup breakdown, game preview, pre-game analysis, who starts in goal, or wants a report on [Team A] vs [Team B]. Do not use for full slate analysis -- see daily

Goalie-specific analysis for NHL: leaderboard rankings, workload tracking, starter identification, tandem splits, and matchup history. Includes xG-adjusted metrics -- GSAA, xSV%, HDSA% -- that predict future performance. Use when user asks about goalie stats, save percentage, GAA, quality starts, goalie fatigue, back-to-back starts, or which goalie is starting tonight. Do not use for skater stats

Teaches hockey analytics metrics -- Corsi, Fenwick, PDO, xG, zone entries, high-danger chances, RAPM, WAR -- with real data context. Use when user asks what Corsi means, how to interpret PDO, what xG tells you, why Fenwick matters, or asks to explain advanced stats for a team or player. Do not use for betting concepts or odds interpretation -- see odds-analysis. Do not use for building prediction

Trains and validates prediction models for sports game outcomes. Use when user asks about building a prediction model, training a classifier, choosing between logistic regression or XGBoost, model selection, hyperparameter tuning, feature importance, or ensemble methods. Always uses walk-forward methodology -- refuses k-fold. Do not use for feature construction -- see feature-engineering. Do not u

Translates natural language hockey queries into structured data filters and executes them via puckapi-tool. Use when user asks a research question in plain English: 'show me games where the home team was outshot but won', 'find all back-to-back losses', 'how often do goalies with 2 days rest outperform their season SV%'. Includes a self-correction loop -- retries with adjusted parameters if the fi

Converts betting odds between formats and removes bookmaker margin to find true implied probabilities. Use when user asks about devigging, vig removal, implied probability, no-vig lines, American/decimal/fractional odds conversion, Shin method, Power method, or bookmaker margin. Prerequisite for edge detection. Do not use for viewing current odds -- see odds-explorer instead. Do not use for model

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

Searches players and surfaces season stats, per-game rates, multi-season comparisons, roster snapshots, and prospect NHLe translations. Use when user asks how a player is performing, wants to compare two skaters, needs a team's top scorers, is evaluating a prospect from another league, or needs stats for fantasy or DFS. Do not use for goalie stats -- see goalie-analysis. Do not use for team-level

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

Builds expected goals (xG) models from NHL play-by-play shot event data using XGBoost or LightGBM. Use when user asks about expected goals, xG model, shot quality, building an xG model, xGF%, xGA, rebound detection, rush shot detection, or shot probability. Do not use for applying pre-built xG values to team or game analysis -- see team-analysis or hockey-analytics. Do not use for general game pre

Monte Carlo playoff and season simulator for NHL. Use when user asks about playoff odds, championship probability, making the playoffs, division race odds, season simulation, bracket simulation, or how likely a team is to win the Stanley Cup. Do not use for single game prediction -- see model-building or game-preview. Do not use for team stats without simulation -- see team-analysis. Do not use fo

Builds player prop prediction models for NHL player stats -- points, shots on goal, saves, blocked shots, and power play points. Use when user asks about prop modeling, player prop predictions, anytime goal scorer odds, shots on goal props, save props, DFS player projections, or player stat projections. Do not use for team-level game prediction -- see model-building. Do not use for player comparis

Builds over/under prediction models for NHL game totals using pace, special teams, goalie matchup, and contextual features. Use when user asks about totals modeling, over/under prediction, predicting total goals, goal scoring rates, or NHL scoring trends. Do not use for moneyline or spread prediction -- see model-building. Do not use for player-level goal props -- see prop-modeling. Do not use for

Generate shareable visual outputs for sports analytics: calibration curves, equity curves, radar charts, matchup cards, probability histograms, and player cards. Use when user asks to visualize, chart, plot, graph, show, display, generate a visual, make a shareable image, or wants to post analysis to social media. Do not use for raw data exploration -- see game-lookup or nl-to-query. Do not use fo

Verifies and corrects model probability outputs so predicted win percentages match actual win rates. Use when user asks about calibration, reliability diagrams, Brier score, Platt scaling, isotonic regression, probability quality, or whether model probabilities are accurate. Also use when user has a trained model and wants to know if outputs can be trusted for betting. Do not use for odds math or

Default data source for PuckAPI Skills. Routes all MCP tool calls for NHL games, schedules, team standings, player stats, goalie performance, and betting odds. Use when any other skill needs data. Do not invoke directly -- other skills call this. Not for data analysis, modeling, or bet recommendations -- see hockey-analytics, model-building, or edge-detection instead.

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

Builds WAR (Wins Above Replacement) and GAR (Goals Above Replacement) from scratch using RAPM ridge regression on shift-level data. Use when user asks about WAR, GAR, RAPM, player value metrics, wins above replacement, contract surplus value, JFresh-style player cards, or all-in-one player evaluation. Do not use for simple player stats lookup -- see player-scouting. Do not use for goalie evaluatio

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