A crowd-sourced stats provider.
S p o r t s D a t a b a s e . c o m
agile access to sports data


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
732 43.1 -0.9 3 11 21.4 The Lightning are 3-11 AGAINST since Nov 29, 2013 as a home dog
690 172.5 -2.8 0 4 0.0 The Lightning are 0-4 AGAINST since Apr 10, 2019 as a favorite
690 172.5 -2.8 0 4 0.0 The Lightning are 0-4 AGAINST since Apr 10, 2019
605 201.7 -2.7 0 3 0.0 The Lightning are 0-3 AGAINST since Mar 30, 2019 at home
605 201.7 -2.7 0 3 0.0 The Lightning are 0-3 AGAINST since Mar 30, 2019 as a home favorite
3169 23.2 0.7 69 34 67.0 The Lightning are 69-34 ON since Feb 11, 2017 on the road
3051 20.6 0.8 72 31 69.9 The Lightning are 72-31 ON since Apr 23, 2015 as a road favorite
1066 36.7 0.6 18 11 62.1 The Lightning are 18-11 ON since Mar 13, 2017 as a road dog
964 30.0 0.6 19 13 59.4 The Lightning are 19-13 ON since Mar 09, 2017 as a 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).