Information you need to win
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 SDB's sample su guest's web all active on filter on
Trends from SDB's sample ou against,SDB's sample ou against
$ ROI Margin wins losses % link
2642 16.1 -0.4 56 86 39.4 The Giants are 56-86-8 AGAINST since Aug 09, 2015 as a road dog
1720 7.9 -0.1 81 104 43.8 The Giants are 81-104-13 AGAINST since May 12, 2016 on the road
760 14.2 -0.6 19 28 40.4 The Giants are 19-28-2 AGAINST since May 23, 2018
655 45.4 -2.0 3 10 23.1 The Giants are 3-10 AGAINST since Jun 10, 2018 as a dog
490 42.1 -0.6 3 8 27.3 The Giants are 3-8 AGAINST since Jun 24, 2018 as a favorite
390 36.6 -0.3 3 7 30.0 The Giants are 3-7 AGAINST since Jun 24, 2018 as a home favorite
365 24.3 -0.1 5 9 35.7 The Giants are 5-9 AGAINST since Jun 24, 2018 at home
100 100.0 -3.5 0 1 0.0 The Giants are 0-1 AGAINST since Jul 02, 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).