A Set of Functions to Efficiently Scrape NFL Play by Play Data
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Updated
May 6, 2026 - R
A Set of Functions to Efficiently Scrape NFL Play by Play Data
python port of nflreadr package for loading nflverse data
A set of functions to visualize National Football League analysis in 'ggplot2'
Models for Fantasy Football Expected Points
Use publicly available data to track NFL betting trends.
Chat with NFL play-by-play data in plain English — an LLM translates questions to DuckDB SQL over nflverse parquet and answers back. FastAPI + React, runs local or hosted models.
NFL 4th-down decision audit. Win-probability model + coach scorecards with bootstrap confidence intervals.
Defensive blitz-rate predictability across 32 NFL defenses, 2022-2025
NFL play-by-play → BigQuery: idempotent nflverse ingestion + LLM-friendly docs + verification
AI pre-snap run/pass prediction & defensive tendency engine for football. LightGBM on nflverse data, time-split validated (69.7% acc, calibrated).
Predicts NFL 4th down decisions (punt/FG/go) with coach-aware ML + Streamlit explorer.
NFL in-game win probability model on 225k plays from six seasons of nflfastR. XGBoost, log loss 0.485 / AUC 0.841 on the held-out 2023 season. Python + DuckDB.
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