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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 SDB's sample su 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
3888 8.9 0.2 163 218 42.8 The Blue Jays are 163-218-14 AGAINST since Aug 12, 2013 at home
2283 24.0 -0.4 28 54 34.1 The Blue Jays are 28-54-3 AGAINST since Aug 12, 2013 as a home dog
180 39.6 -2.5 1 3 25.0 The Blue Jays are 1-3 AGAINST since Jun 12, 2018 on the road
165 25.0 -0.6 2 4 33.3 The Blue Jays are 2-4 AGAINST since Jun 07, 2018 as a favorite
165 24.4 -0.5 2 4 33.3 The Blue Jays are 2-4 AGAINST since May 18, 2018 as a home favorite
100 95.2 -6.0 0 1 0.0 The Blue Jays are 0-1 AGAINST since Jun 13, 2018 as a road favorite
100 83.3 -5.5 0 1 0.0 The Blue Jays are 0-1 AGAINST since Jun 22, 2018 as a dog
100 83.3 -5.5 0 1 0.0 The Blue Jays are 0-1 AGAINST since Jun 22, 2018 as a road dog
100 83.3 -5.5 0 1 0.0 The Blue Jays are 0-1 AGAINST since Jun 22, 2018
840 11.2 0.9 39 28 58.2 The Blue Jays are 39-28-2 ON since Apr 25, 2017 as a road dog
720 24.4 1.0 16 8 66.7 The Blue Jays are 16-8-3 ON since Apr 20, 2018 on the road

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).