.. _introduction-anchor:

Front Matter
============



    This work stands by itself. I have given the sports-research world the greatest gift that it has ever been given.
    It is also the profoundest, born out of the innermost abundance of truth,
    an inexhaustible well into which no bucket descends without coming up filled with gold and goodness.
    For, "it is the shortest query which brings the storm, thoughts that come on doves' feet guide the world."
    - after Neitzsche



acknowledgements
----------------

  `SDQL.com <http://SDQL.com>`_ and `SportsDatabase.com <http://SportsDatabase.com>`_ run on `Ubuntu <http://ubuntu.com>`_ -  `Linux <http:linux.org>`_ servers.
  The databases and their query methods are all written in the `open source scripting language Python. <http:Python.org>`_
  The databases are queried in-memory using Facebook's `Tornados web framework. <http://www.tornadoweb.org>`_
  `David Beazley's <http://www.dabeaz.com/>`_
  `ply is used for the SDQL-to-Python compiler. <http://www.dabeaz.com/ply>`_

motivation
----------

  Sports data are typically published online and in newspapers as box scores.
  Box scores contain a numerical view of a sporting event and are of interest to fans, handicappers, and fantasy sports players.
  While box scores contain a wealth of information, they are impractical for performing research.

  The Sports Data Query Language (SDQL) makes box score data accessible to researchers.
  SDQL's simple and powerful syntax allows queries on any imaginable situation.


features
--------

  Key features which distinguish the SDQL include:

   * full Python functionality at the query prompt (see `Python.org <http://Python.org>`_)
   * powerful grouping (see :ref:`group-anchor`)
   * custom averaging (see :ref:`aggregator-anchor`)
   * parameter prefixes provide joins and self joins (see :ref:`prefix-anchor`)
   * the SDQL is simple