Note: This site will be discontinued as of September 1, 2021.
SDQL3 access will continue with user input data at http://s3.sportsdatabase.com.

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


name
password


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
6240 11.6 0.0 228 264 46.3 The Predators are 228-264-46 AGAINST since Nov 10, 2006 as a dog.
5710 12.9 0.0 186 221 45.7 The Predators are 186-221-37 AGAINST since Nov 10, 2006 as a road dog.
2210 14.3 -0.0 67 81 45.3 The Predators are 67-81-7 AGAINST since Mar 20, 2017 as a home favorite.
650 14.1 -0.2 21 25 45.7 The Predators are 21-25 AGAINST since Jan 12, 2020 on the road.
1150 16.4 0.2 35 27 56.5 The Predators are 35-27-8 ON since Nov 17, 2009 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
e-mail links:   Content@SportsDataBase.com    Support@SportsDataBase.com   
Content for this site is generated using the Sports Data Query Language (SDQL).