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
2732 16.0 0.0 76 82 48.1 The Knights are 76-82 AGAINST since May 29, 2018.
2138 46.1 -1.9 5 29 14.7 The Knights are 5-29 AGAINST since May 31, 2018 as a road dog.
2023 42.5 -1.6 6 29 17.1 The Knights are 6-29 AGAINST since May 31, 2018 as a dog.
1620 22.5 0.3 37 35 51.4 The Knights are 37-35 AGAINST since Jan 21, 2019 as a favorite.
1468 16.2 -0.5 32 46 41.0 The Knights are 32-46 AGAINST since May 31, 2018 on the road.
552 184.0 -2.3 0 3 0.0 The Knights are 0-3 AGAINST since Jan 07, 2020 as a home favorite.
552 184.0 -2.3 0 3 0.0 The Knights are 0-3 AGAINST since Jan 07, 2020 at home.
1139 112.5 2.0 10 0 100.0 The Knights are 10-0 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).