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 ml against,SDB's sample ml on,SDB's sample ml against,SDB's sample ml on
$ ROI wins losses % link
3296 10.0 75 144 34.2 The Athletics are 75-144 AGAINST since Oct 08, 2013 as a road dog
1715 20.7 44 30 59.5 The Athletics are 44-30 ON since Apr 18, 2017 at home
1406 55.3 17 7 70.8 The Athletics are 17-7 ON since Sep 06, 2017
1331 22.7 32 15 68.1 The Athletics are 32-15 ON since Jul 26, 2016 as a favorite
1223 44.6 18 5 78.3 The Athletics are 18-5 ON since May 24, 2015 as a road favorite
1215 28.7 24 18 57.1 The Athletics are 24-18 ON since Apr 18, 2017 as a home dog
811 50.6 10 6 62.5 The Athletics are 10-6 ON since Sep 06, 2017 as a dog
658 39.2 10 3 76.9 The Athletics are 10-3 ON since Jul 04, 2017 as a home favorite
527 41.0 8 4 66.7 The Athletics are 8-4 ON since Sep 13, 2017 on the road

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).