sports-data-hq
Official@sports-data-hq
Provides predictive NHL modeling, betting edge detection, and advanced hockey performance metrics for sports data analysis and wagering strategy.
Agent Skills by sports-data-hq
Showing 28 vetted skills indexed across 1 GitHub repositories.
sports-data-hqvisualization
Generates hockey analytics charts from precomputed metrics using Python or ASCII.
sports-data-hqprop-modeling
Project NHL player prop outcomes for skaters and goalies.
sports-data-hqteam-analysis
Analyze NHL team standings, records, and playoff positions from PuckAPI or CSV data.
sports-data-hqbacktesting
Simulate historical betting performance with walk-forward tests and report ROI and drawdown.
sports-data-hqgoalie-analysis
Compute workload-adjusted and xG-adjusted NHL goalie metrics from game logs.
sports-data-hqhockey-analytics
Explain hockey analytics metrics like Corsi, xG, and WAR with league context.
sports-data-hqpuckapi-tool
Route NHL data retrieval across PuckAPI endpoints for games, standings, and odds.
sports-data-hqdispatch
Routes hockey analytics requests to the most relevant 2-3 supporting skills.
sports-data-hqfeature-engineering
Transforms raw hockey data into leak-free model features for predictive modeling.
sports-data-hqbet-tracker
Resolve open hockey wagers and compute ROI, win rate, and drawdown metrics.
sports-data-hqprobability-calibration
Verify model probability outputs and calibration error with reliability diagrams and Brier score analysis.
sports-data-hqelo-engineering
Build and tune multi-variant Elo ratings for hockey team-strength prediction.
sports-data-hqwar-gar-decomposition
Estimate hockey player WAR and GAR from shift-level data using ridge regression.
sports-data-hqdaily-card
Rank NHL nightly slates into betting edges with quarter-Kelly stake recommendations.
sports-data-hqnl-to-query
Translate natural language hockey questions into structured query filters and PuckAPI operations.
sports-data-hqai-hockey-workflow
Structure hockey analytics sessions for exploration, hypothesis testing, model iteration, and reporting.
sports-data-hqxg-model-building
Build expected goals models from NHL play-by-play shot events.
sports-data-hqdata-pipeline
Automate scheduled NHL data pipelines for predictions, storage, and drift alerts.
sports-data-hqedge-detection
Compare calibrated model probabilities with market odds to detect positive expected value bets.
sports-data-hqodds-explorer
Compare NHL betting odds across sportsbooks for moneyline, puck line, and totals.
sports-data-hqwalk-forward-validation
Evaluate time-series sports prediction models with walk-forward validation.
sports-data-hqplayoff-simulation
Simulate NHL season outcomes to estimate playoff and championship probabilities.
sports-data-hqtotals-modeling
Build calibrated NHL totals prediction models for game goal distributions and over/under probabilities.
sports-data-hqgame-preview
Generate a complete pre-game report for a single NHL matchup.
Frequently Asked Questions About sports-data-hq
FAQPage SchemaWhat specific tasks can I perform with these sports data capabilities?▼
You can execute end-to-end NHL analysis, including building expected goals models, calculating player WAR/GAR metrics, performing walk-forward model validation, and identifying betting edges by comparing calibrated probabilities against market odds.
Who is the target persona for these sports analytics functions?▼
These functions are designed for sports data scientists, quantitative analysts, and professional bettors who require structured NHL play-by-play data processing, predictive model building, and rigorous backtesting of wagering strategies.
What are the primary data dependencies for these models?▼
The system relies on structured NHL play-by-play event data, game logs, and real-time betting odds retrieved via PuckAPI endpoints to populate feature engineering pipelines and probability calibration diagrams.