A crowd-sourced stats provider. 		S p o r t s D a t a b a s e . c o m
tools for the objective handicapper


name
password

MLB Trends SDB Home    MLB Trends    MLB Query
Include trends from SDB's sample ml against SDB's sample ml on SDB's sample ou against SDB's sample ou on guest's web all 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
890 59.1 -1.8 2 11 15.4 The Pirates are 2-11-1 AGAINST since Sep 03, 2020 as a home dog.
890 59.1 -1.8 2 11 15.4 The Pirates are 2-11-1 AGAINST since Sep 03, 2020 at home.
770 27.8 -0.9 8 16 33.3 The Pirates are 8-16-2 AGAINST since Sep 03, 2020 as a dog.
770 27.8 -0.9 8 16 33.3 The Pirates are 8-16-2 AGAINST since Sep 03, 2020.
375 24.3 -1.1 4 8 33.3 The Pirates are 4-8-2 AGAINST since Jul 19, 2019 as a home favorite.
100 15.9 -0.8 2 3 40.0 The Pirates are 2-3-1 AGAINST since Sep 15, 2020 on the road.
100 15.9 -0.8 2 3 40.0 The Pirates are 2-3-1 AGAINST since Sep 15, 2020 as a road dog.
100 100.0 -5.5 0 1 0.0 The Pirates are 0-1 AGAINST since Aug 09, 2020 as a favorite.
535 24.5 1.1 13 7 65.0 The Pirates are 13-7 ON since Mar 30, 2018 as a road favorite.
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).