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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
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
300 88.2 -2.8 0 3 0.0 The Orioles are 0-3 AGAINST since Aug 11, 2018
300 88.2 -2.8 0 3 0.0 The Orioles are 0-3 AGAINST since Aug 11, 2018 as a dog
300 88.2 -2.8 0 3 0.0 The Orioles are 0-3 AGAINST since Aug 11, 2018 at home
300 88.2 -2.8 0 3 0.0 The Orioles are 0-3 AGAINST since Aug 11, 2018 as a home dog
690 43.9 1.8 10 3 76.9 The Orioles are 10-3-1 ON since Jul 07, 2018 as a road dog
690 43.9 1.8 10 3 76.9 The Orioles are 10-3-1 ON since Jul 07, 2018 on the road
643 19.4 2.1 18 11 62.1 The Orioles are 18-11-1 ON since Jul 07, 2018 as a dog
585 54.2 3.0 8 2 80.0 The Orioles are 8-2 ON since Aug 12, 2017 as a road favorite
550 21.6 2.7 14 8 63.6 The Orioles are 14-8-1 ON since Jul 15, 2018

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).