Sports box scores provide numerical information about a sporting event: SportsDatabase.com makes box score data researchable. A list of available parameters is give on each query page and you can see the temporal extent of each database using the SDQL: season.

Once you have created an account you can enter and share other data fields (such as city population and offensive coordinator). Members can also save and share trends and SDQL short cuts.

KillerSports.com is sharing their handy short cuts and you can use the Manage link (when logged in) to follow these under their user name KS.

Membership is free and you only need to enter a user name and password in the upper right to create an account. We use cookies to keep you logged in and you can logout using the Sign Out link in the upper right.

Open Source Tools

Ubuntu is the operating system and philosophy. NginX is the http server. Facebook's Tornado serves as the web framework and holds the PyQL databases in RAM. The Python Programming Language is happily used throughout.

Use the Sports Data Query Language (SDQL) to research databases made up mostly of historic box scores and including upcoming schedules and other user input data such as temperature, playing surface, coaches and betting lines.

Query Links: CFL, MLB, NBA, NCAABB, NCAAFB, NFL, NHL, WNBA

Use the Pythonic Query Language (PyQL) to explore a database made up of sports trends.

Trend Links: CFL, MLB, NBA, NCAABB, NCAAFB, NFL, NHL, WNBA

Need anything? Write us at support@SportsDatabase.com

Have a nice day.

The Sports Data Query Language Manual

The Sports Data Visualization Blog

KillerSports.com publishes NFL, NBA and MLB sports data query language (SDQL) content from SportsDataBase.com.

Master Cappers at http://KillerCappers.com use the SDQL to research their picks.

Share and grow your knowledge of the SDQL at the discussion group.

Help maintain the databases at the data group.

Tweets by @sdql