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 32.8 -1.4 5 12 29.4 The Brewers are 5-12-1 AGAINST since Aug 19, 2018 as a dog
580 40.9 -1.9 3 9 25.0 The Brewers are 3-9-1 AGAINST since Aug 19, 2018 as a road dog
570 46.3 -1.9 2 8 20.0 The Brewers are 2-8-1 AGAINST since Oct 01, 2018
500 76.1 -3.4 0 5 0.0 The Brewers are 0-5-1 AGAINST since Sep 26, 2018 on the road
355 31.6 -1.6 3 7 30.0 The Brewers are 3-7 AGAINST since Sep 15, 2018 as a home favorite
325 20.4 -1.0 5 9 35.7 The Brewers are 5-9 AGAINST since Sep 15, 2018 at home
235 16.3 -0.5 5 8 38.5 The Brewers are 5-8 AGAINST since Sep 15, 2018 as a favorite
100 83.3 -1.5 0 1 0.0 The Brewers are 0-1 AGAINST since Oct 20, 2018 as a home dog
2233 12.1 0.8 94 66 58.8 The Brewers are 94-66-9 ON since May 18, 2011 as a road favorite
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).