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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
4819 5.1 0.2 370 455 44.8 The Orioles are 370-455-30 AGAINST since Jun 02, 2013
2694 7.2 0.1 144 185 43.8 The Orioles are 144-185-10 AGAINST since Jul 21, 2014 as a dog
1257 23.3 -0.4 16 30 34.8 The Orioles are 16-30-3 AGAINST since Mar 29, 2018 at home
1125 37.9 -1.7 7 19 26.9 The Orioles are 7-19-1 AGAINST since Mar 31, 2018 as a home dog
300 45.8 -2.4 1 4 20.0 The Orioles are 1-4-1 AGAINST since May 29, 2018 as a home favorite
300 45.8 -2.4 1 4 20.0 The Orioles are 1-4-1 AGAINST since May 29, 2018 as a favorite
200 31.5 -0.9 2 4 33.3 The Orioles are 2-4 AGAINST since Jul 03, 2018 as a road dog
200 31.5 -0.9 2 4 33.3 The Orioles are 2-4 AGAINST since Jul 03, 2018 on the road
585 54.2 3.0 8 2 80.0 The Orioles are 8-2 ON since Aug 12, 2017 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).