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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NHL Trends SDB Home    NHL Trends    NHL Query
Include trends from SDB's sample ml against SDB's sample ml on SDB's sample ou against SDB's sample ou on 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
1080 38.6 -0.6 9 18 33.3 The Sharks are 9-18-1 AGAINST since Nov 21, 2019.
940 21.9 -0.4 17 24 41.5 The Sharks are 17-24-2 AGAINST since Feb 05, 2019 as a dog.
840 18.7 -0.4 18 24 42.9 The Sharks are 18-24-3 AGAINST since Feb 21, 2019 on the road.
800 22.2 -0.3 14 20 41.2 The Sharks are 14-20-2 AGAINST since Feb 05, 2019 as a road dog.
560 70.0 -0.8 1 6 14.3 The Sharks are 1-6-1 AGAINST since Nov 27, 2019 as a favorite.
550 20.4 -0.2 11 15 42.3 The Sharks are 11-15-1 AGAINST since May 18, 2019 at home.
500 31.2 -0.7 6 10 37.5 The Sharks are 6-10 AGAINST since Oct 09, 2010 as a home dog.
1140 28.5 0.6 24 15 61.5 The Sharks are 24-15-1 ON since Nov 24, 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).