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 against
$ ROI Margin wins losses % link
9650 8.7 0.1 470 515 47.7 The Canucks are 470-515-120 AGAINST since Oct 05, 2006.
5870 10.3 0.1 235 267 46.8 The Canucks are 235-267-66 AGAINST since Oct 20, 2006 as a favorite.
5220 9.5 0.1 236 262 47.4 The Canucks are 236-262-53 AGAINST since Oct 05, 2006 on the road.
5010 18.0 0.0 105 141 42.7 The Canucks are 105-141-33 AGAINST since Oct 17, 2009 as a home favorite.
4230 11.2 0.1 159 183 46.5 The Canucks are 159-183-34 AGAINST since Oct 05, 2006 as a road dog.
3530 6.7 0.1 232 243 48.8 The Canucks are 232-243-53 AGAINST since Oct 05, 2006 as a dog.
1300 12.4 -0.0 42 50 45.7 The Canucks are 42-50-13 AGAINST since Dec 12, 2010 as a road favorite.
910 65.0 -0.0 3 11 21.4 The Canucks are 3-11 AGAINST since Feb 21, 2019 at home.
560 80.0 -0.7 1 6 14.3 The Canucks are 1-6 AGAINST since Feb 23, 2019 as a home dog.
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).