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  • Why Timescale
    Overview Cost efficient Built on PostgreSQL Optimized for performance Easy for developers Free production support Secure and compliant Industries that rely on us Energy and environment AI and machine learning Crypto and finance Transportation and logistics AI and machine learning

    We’re in your corner even during the trial phase. Contact us to discuss your use case with a Timescale technical expert.

    Request a demo
  • Customer Stories
  • Developers
    Timescale Docs Docs Timescale TutorialsTutorials Timescale GuidesGuides Timescale SupportSupport Timescale Developers' newsletterDevelopers' newsletter

    Support

    Community Github Slack Forum

    Contribute

    Contribute to code or Docs
    Learn

    Time-Series Database Basics

    Do you have time-series data? What is data compression and how does it work? Database partitioning: what it is and why it matters Building a scalable database

    Timescale & PostgreSQL

    Exploring PostgreSQL extensions A guide to PostgreSQL views What is PostgreSQL and where did it come from A summary on SQL joins Understanding PostgreSQL functions

    Building Blocks

    PostgreSQL materialized views and where to find them PostgreSQL join type theory

    Timescale Benchmarks

    vs RDS vs Amazon Timestream vs Influx vs Cassandra vs MongoDB vs ClickHouse
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General

Hacking NFL data with PostgreSQL, TimescaleDB, and SQL

27 Jul 2021 15 min read

Learn how to use time-series data provided by the NFL to uncover valuable insights into many player performance metrics – and ways to apply the same methods to improve your fantasy league team, or your knowledge of the game - all with PostgreSQL, SQL, and freely available extensions.

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Hacking NFL data with PostgreSQL, TimescaleDB, and SQL
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