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 and SportsDatabase.com run on Ubuntu - Linux servers. The databases and their query methods are all written in the open source scripting language Python. The databases are queried in-memory using Facebook’s Tornados web framework. David Beazley’s ply is used for the SDQL-to-Python compiler.

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)
  • powerful grouping (see Grouping)
  • custom averaging (see Summative)
  • parameter prefixes provide joins and self joins (see Parameter Prefix)
  • the SDQL is simple