Winning picks from SDQL masters. 		S p o r t s D a t a b a s e . c o m
tools for the objective handicapper


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MLB Trends SDB Home    MLB Trends    MLB Query
Include trends from SDB's sample ml against SDB's sample ml on SDB's sample ou against SDB's sample ou on guest's web all active on filter on
Trends from SDB's sample ou against,SDB's sample ou on,SDB's sample ou against,SDB's sample ou on
$ ROI Margin wins losses % link
650 25.0 -0.1 8 15 34.8 The Blue Jays are 8-15 AGAINST since Aug 10, 2018 at home
515 20.7 -0.8 8 14 36.4 The Blue Jays are 8-14 AGAINST since May 18, 2018 as a home favorite
410 13.3 -0.0 10 15 40.0 The Blue Jays are 10-15-2 AGAINST since Sep 02, 2018
400 87.0 -2.0 0 4 0.0 The Blue Jays are 0-4 AGAINST since Sep 22, 2018 as a home dog
380 52.8 -2.6 1 5 16.7 The Blue Jays are 1-5 AGAINST since Sep 02, 2018 as a favorite
200 25.6 0.4 2 4 33.3 The Blue Jays are 2-4-1 AGAINST since Sep 22, 2018 as a dog
180 37.5 -2.8 1 3 25.0 The Blue Jays are 1-3 AGAINST since Sep 02, 2018 as a road favorite
1548 14.3 1.0 57 38 60.0 The Blue Jays are 57-38-4 ON since Apr 25, 2017 as a road dog
Trend Parameters: active, english, invested, losses, margin, profit, pushes, sdql, start, team, wins

How To Use the Trends Page:
Use the Pythonic Query Language to explore a database of trends. The full PyQL format is: parameters @ conditions. More typical use just specifies the condition and takes a default output.

To see all trends with an average margin of at least 2 use the PyQL condition: margin > 2.

To see all perfect trends use the PyQL: wins * losses = 0
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Content for this site is generated using the Sports Data Query Language (SDQL).