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NBA Trends SDB Home    NBA Trends    NBA Query
Include trends from SDB's sample ats SDB's sample ou SDB's sample su guest's web all active on filter on
Trends from SDB's sample su,SDB's sample su
p val wins losses % link
0.000000 63 261 19.4 The Grizzlies are 63-261 ATS (-9.00 ppg) since Nov 11, 1995 as a dog off a home game off a loss
0.000000 42 202 17.2 The Grizzlies are 42-202 ATS (-9.00 ppg) since Nov 11, 1995 as a dog after playing as a home dog off a loss
0.000000 25 95 20.8 The Grizzlies are 25-95 ATS (-8.00 ppg) since Feb 05, 1996 as a home dog off a home game off a loss
0.000000 19 78 19.6 The Grizzlies are 19-78 ATS (-8.00 ppg) since Feb 05, 1996 as a home dog after playing as a home dog off a loss
0.000000 48 7 87.3 The Grizzlies are 48-7 ATS (8.00 ppg) since Jan 21, 2011 as a home favorite off a game as a dog off a loss
0.000000 50 11 82.0 The Grizzlies are 50-11 ATS (6.00 ppg) since Jan 21, 2011 as a home favorite off a road game off a loss
0.000000 39 6 86.7 The Grizzlies are 39-6 ATS (9.00 ppg) since Jan 21, 2011 as a home favorite after playing as a road dog off a loss
0.000078 22 3 88.0 The Grizzlies are 22-3 ATS (6.00 ppg) since Dec 22, 2009 as a favorite after playing as a home dog
0.000111 19 2 90.5 The Grizzlies are 19-2 ATS (8.00 ppg) since Jan 02, 2013 as a road favorite off a loss
0.000137 16 1 94.1 The Grizzlies are 16-1 ATS (7.00 ppg) since Dec 22, 2009 as a home favorite after playing as a home dog
0.000259 15 1 93.8 The Grizzlies are 15-1 ATS (6.00 ppg) since Feb 24, 2010 as a favorite after playing as a home dog off a loss

Trend Parameters: active, english, invested, losses, margin, pushes, pval, 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
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Content for this site is generated using the Sports Data Query Language (SDQL).