Winning picks from SDQL masters.
S p o r t s D a t a b a s e . c o m
agile access to sports data


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 ml against,SDB's sample ml on,SDB's sample ml against,SDB's sample ml on
$ ROI Margin wins losses % link
4185 7.0 -0.9 140 249 36.0 The Cubs are 140-249-1 AGAINST since May 22, 2011 as a road dog
938 18.0 -0.5 14 27 34.1 The Cubs are 14-27 AGAINST since Apr 25, 2018 as a dog
4298 4.3 1.2 386 215 64.2 The Cubs are 386-215-1 ON since Jun 03, 2014 as a favorite
3372 8.6 1.5 169 92 64.8 The Cubs are 169-92 ON since Jul 06, 2010 as a road favorite
1299 16.6 -0.4 42 36 53.8 The Cubs are 42-36 ON since Sep 25, 2013 as a home dog
635 33.5 2.5 11 5 68.8 The Cubs are 11-5 ON since Apr 06, 2019 on the road
562 19.6 1.2 14 6 70.0 The Cubs are 14-6 ON since Apr 21, 2019 at home
560 22.8 1.4 12 4 75.0 The Cubs are 12-4 ON since Apr 21, 2019 as a home 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).