Quote Originally Posted by Scrivero:
As you already know, I have never run SDQL queries, but I am eager to learn. So, I tried the query you used for this but with a little tweak:
Your query was: Query: AF and total>=8 and 50<=WP<=55 and 41<=o:WP<=51And the results I got with that, which were very close to yours:
RL:
| 442-435 (-0.11, 50.4%) | avg line: 123.6 / -136.4 | on / against: +$10,822 / -$16,098 | ROI: +11.9% / -13.2% |
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I made a tweak and made this query: AF and total=8 and 50<=WP<=55 and 41<=o:WP<=51And the results were:
RL: | 106-87 (0.01, 54.9%) | avg line: 125.2 / -136.9 | on / against: +$4,397 / -$5,594 | ROI: +22.4% / -21.0% |
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So apparently, if I havent gotten this all wrong,
betting on games that have an O/U line of exactly 8 brings a ROI of +22,4 % compared to the over or exactly 8 that brings a ROI of +12 %.
Of course the amount of games goes down a lot so its not as trustworthy as with the >=8. Maybe the variance is less though. I dont have the skills to check that.
Please correct me if I got it all wrong. If its right though, should we try to use it and tweak the system more? Should I try to make it into my first MLB system ever without knowing anything about the game or about betting it :D
Could you possibly check that exactly 8 O/U by seasons? I dont know how to do it. I could just take the results to excel but there seems to be a faster/easier way.
You are absolutely correct about the query with total=8, and it looks like a good one to track. I usually just use an inequality to include multiple
totals, and take a hit on ROI to lower the variance a bit. A
nice increase in ROI for a specific value is usually caused by one or two
seasons being better than normal, but in this case, it's spread
very well across seasons.
If you want to group by season, just add the word "season" to the query with no values associated with it ...
Query: AF and total=8 and 50<=WP<=55 and 41<=o:WP<=51 and season
I removed some columns from the result, but here it is:
games RL Avg Run Line $ RL On
14 12-2 (1.93, 85.7%) 111.1 +$1,295 season = 2007
17 8-9 (-1.44, 47.1%) 121.2 +$70 season = 2008
16 6-10 (-1.12, 37.5%) 116.2 -$390 season = 2009
10 7-3 (0.50, 70.0%) 124.8 +$590 season = 2010
20 10-10 (0.30, 50.0%) 133.8 +$349 season = 2011
22 12-10 (0.68, 54.5%) 121.8 +$427 season = 2012
18 10-8 (0.22, 55.6%) 125.9 +$404 season = 2013
31 16-15 (-0.76, 51.6%) 125.4 +$420 season = 2014
27 16-11 (0.24, 59.3%) 131.5 +$996 season = 2015
18 9-9 (0.28, 50.0%) 132.3 +$236 season = 2016
You can see that only one season (2009) finished negative. Nice!
For my system, I just found the best range of totals and filtered the winning percentages based on that range. Ideally, we would look at each total individually and tweak the winning percentage for each one to get a much higher ROI. Then, basically, combine the best of each Total into one system.
My goal for now is to see how this system plays out independent of the lines and data in the SDQL database, but please feel free to track your research here. I'm curious how high you can get the ROI by filtering at each specific Total value.