.. _short-anchor: Short Cuts ================== SDQL short cuts save on typing and make queries more readable. single letter ------------- The SDQL provides single letter short cuts for common parameters. * **H** the team is at home * **A** the team is away * **W** the team won * **L** the team lost * **F** the team is favored to win * **D** the team is the underdog * **O** the game went over the projected total * **U** the game went under the projected total * **C** the team and opponent are in the same conference. Single letter short cuts can be strung together: *H and W and F* is the same as *HWF*. To see the Average margin for home dogs after winning as an away dog, use the SDQL: `A(points-o:points) @ HD and p:WAD `_ summative --------- Summative short cuts are also addressed in :ref:`summative-anchor`. * **tA** the team's season to date average * **tS** the team's season to date sum * **oA** the opponent's season to date average * **oS** the opponent's season to date sum * **tpA** the team's average last season * **tpS** the team's sum last season * **opA** the opponent's average last season * **opS** the opponent's sum last season * **tp2A** the team's average two seasons back * **tp2S** the team's sum two seasons back * **op2A** the opponent's average two seasons back * **op2S** the opponent's sum two seasons back The pattern continues so that summative stats from any past season can be accessed. For baseball, the corresponding shortcuts for starters are: **sA, sS, spA, spS**, and so on. To see how NFL teams have done in week 1 when their average points had increased over the past three seasons, use the SDQL: `tp3A(points)`_ Python automatically casts Booleans as integers inside of summatives. To see the against-the-spread record of each NBA team for the 2016 season, use the SDQL: `tS(points+line>o:points) as 'ATSW',tS(points+line`_