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 ou against,SDB's sample ou on,SDB's sample ou against,SDB's sample ou on
$ ROI Margin wins losses % link
190 42.2 -3.0 1 3 25.0 The Mariners are 1-3 AGAINST since May 21, 2019 on the road
190 42.2 -3.0 1 3 25.0 The Mariners are 1-3 AGAINST since May 21, 2019
100 90.9 -8.5 0 1 0.0 The Mariners are 0-1 AGAINST since May 22, 2019 as a road favorite
100 90.9 -8.5 0 1 0.0 The Mariners are 0-1 AGAINST since May 22, 2019 as a favorite
2270 32.7 1.9 43 19 69.4 The Mariners are 43-19-2 ON since Sep 19, 2018
1813 13.5 0.9 71 49 59.2 The Mariners are 71-49-3 ON since Sep 27, 2017 as a dog
1631 13.0 0.8 66 46 58.9 The Mariners are 66-46-3 ON since Sep 26, 2017 on the road
1416 15.1 0.8 51 34 60.0 The Mariners are 51-34-1 ON since Aug 27, 2017 as a road dog
1165 21.3 1.5 31 18 63.3 The Mariners are 31-18-1 ON since Aug 01, 2018 at home
890 68.6 2.8 10 1 90.9 The Mariners are 10-1-1 ON since Apr 05, 2019 as a favorite
500 93.5 3.6 5 0 100.0 The Mariners are 5-0 ON since Apr 25, 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).