Terms of Service & Data Attribution
Effective Date: 2026 Season
01. Intellectual Property & Data Usage
DynastyDash processes raw NFL data to generate proprietary, advanced metrics including, but not limited to, Leverage Adjusted Opportunity (LAO), Consistency Floor Deviation (CFD), First Read Share (FR%), Checkdown Rate (CHK%), and Designed Screen Share (DES%). The algorithmic formulas, machine learning models, and valuation curves utilized to produce these metrics remain the exclusive intellectual property of DynastyDash.
Safeguard Clause: You are granted a limited, personal license to view and utilize these insights for the management of your individual fantasy football leagues. Automated scraping, bulk downloading, reverse-engineering of our 10,000-point curve, or commercial redistribution of DynastyDash "Alpha" metrics is strictly prohibited without explicit written consent.
02. Open Source & API Attribution
DynastyDash functions as a highly specialized data orchestrator. Our backend Python pipelines heavily rely on the incredible work of the open-source sports analytics community. We proudly acknowledge and attribute the following providers:
NFLverse
We utilize NFLverse repositories to source our raw, play-by-play `.parquet` data, which serves as the foundational building block for our proprietary efficiency calculations.
FTN Data
Advanced charting components, such as designed screen tracking and explicit checkdown flagging, are made possible through structural data formats pioneered by FTN.
Sleeper API
DynastyDash is an independent application and is not affiliated with Sleeper. We utilize their public REST API to securely fetch user rosters, transactions, and league metadata.
Next Gen Stats (NFL)
Metrics utilizing advanced player tracking data, specifically Rushing Yards Over Expected (RYOE), are processed using official Next Gen Stats frameworks.
03. Limitation of Financial Liability
Fantasy football inherently involves variance, injuries, unpredictable human elements, and often, monetary stakes. DynastyDash is an analytical tool designed to provide data-driven probabilities, not absolute guarantees.