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 ml against,SDB's sample ml on,SDB's sample ml against,SDB's sample ml on
$ ROI Margin wins losses % link
1289 12.7 0.1 46 47 49.5 The Knights are 46-47 AGAINST since May 30, 2018.
1245 44.3 -1.8 3 17 15.0 The Knights are 3-17 AGAINST since Jun 02, 2018 as a road dog.
1230 40.6 -1.5 4 18 18.2 The Knights are 4-18 AGAINST since Jun 02, 2018 as a dog.
960 32.9 0.3 14 15 48.3 The Knights are 14-15 AGAINST since Jan 21, 2019 as a favorite.
624 64.7 -1.5 1 7 12.5 The Knights are 1-7 AGAINST since Mar 25, 2019 on the road.
565 80.7 0.6 3 4 42.9 The Knights are 3-4 AGAINST since Mar 23, 2019 as a home favorite.
565 80.7 0.6 3 4 42.9 The Knights are 3-4 AGAINST since Mar 23, 2019 at home.
1038 93.3 1.5 10 1 90.9 The Knights are 10-1 ON since Oct 15, 2017 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).