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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 against
$ ROI Margin wins losses % link
2568 26.3 -0.8 28 56 33.3 The Tigers are 28-56-4 AGAINST since Aug 01, 2017 on the road
2480 27.9 -0.8 25 52 32.5 The Tigers are 25-52-3 AGAINST since Aug 01, 2017 as a road dog
2206 16.1 -0.4 46 72 39.0 The Tigers are 46-72-6 AGAINST since Sep 28, 2017
2058 23.4 -0.8 27 50 35.1 The Tigers are 27-50-2 AGAINST since Apr 26, 2018 as a dog
768 36.3 -1.7 5 13 27.8 The Tigers are 5-13-1 AGAINST since Jun 04, 2018 as a home dog
625 22.0 -1.3 9 16 36.0 The Tigers are 9-16-1 AGAINST since Sep 06, 2016 as a road favorite
570 31.1 -1.6 4 10 28.6 The Tigers are 4-10-3 AGAINST since Apr 01, 2018 as a favorite
370 24.6 -1.5 4 8 33.3 The Tigers are 4-8-2 AGAINST since Apr 01, 2018 as a home favorite
200 39.2 -0.0 1 3 25.0 The Tigers are 1-3-1 AGAINST since Aug 10, 2018 at home

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).