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 against
$ ROI Margin wins losses % link
1028 36.2 -1.7 7 18 28.0 The Mariners are 7-18-1 AGAINST since Jul 03, 2019 as a home dog.
1025 23.1 -1.0 13 25 34.2 The Mariners are 13-25-2 AGAINST since Aug 03, 2019 as a dog.
985 28.0 -0.9 10 21 32.3 The Mariners are 10-21-1 AGAINST since Aug 25, 2019.
985 23.8 -1.1 12 23 34.3 The Mariners are 12-23-3 AGAINST since Jul 03, 2019 at home.
325 20.9 -0.3 5 9 35.7 The Mariners are 5-9 AGAINST since Aug 29, 2019 as a road dog.
315 17.8 -0.3 6 10 37.5 The Mariners are 6-10 AGAINST since Aug 29, 2019 on the road.
300 69.3 -4.0 0 3 0.0 The Mariners are 0-3-1 AGAINST since May 22, 2019 as a road favorite.
270 22.8 -0.5 3 6 33.3 The Mariners are 3-6-2 AGAINST since Jul 26, 2019 as a 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).