Fading a bad offense from the AL

Updated on May 25, 2017 in MLB Betting Trends
11 on July 17, 2015

Nice Forum! Here’s my first post:

I am an old veteran gambler who has made more mistakes than days a lot of you have been alive! I don’t know this SDQL, but it sounds like it is a database which is something I have always kept and used; so I like the whole idea of this forum already. Using historical data is the mark of a disciplined gambler: using history to back up your decisions.

I’m going to share one of my more valuable systems I’ve used since the early 2000’s and hopefully someone can backtest it for me with sdql.

For years, I’ve looked at a simple logical angle; for whatever reason I’ve had large success with this in the AL rather than the NL. The public tends to go in a little too hard for betting for or against offenses looking at the most dumbed down stat: runs per game, but that is what I use anyways here. This is a more square betting system and that’s why I’m comfortable sharing it. By no means my best one.

Hitting well over 55% and up roughly 20-25% since the early 2000’s I look to bet against a home team scoring under 4.5 runs per game on the season. The spot I pick to do it is when they just came off of a blowout loss of 8 or more runs.

I have absolutely know idea how to use SDQL, but Tom told me that it is fine to post this here because there is an application of something I found in “any database.” Let’s see what you guys have got.

-curiousapple

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4 on July 17, 2015

Good situation, and here are the results over the last 12 years:

SU: 274-318 (-0.44, 46.3%)   avg line: -112.2 / 100.6   on / against: -$8,381 / +$5,415   ROI: -11.4% / +7.8

That is a 7.8% return.

Admin
on July 17, 2015

I got the same results, but here it is broken down by conference:
AL – 96-141 SU +49.2 units to fade since 2004
NL – 178-177 SU +4.95 units to fade since 2004

So you’re right; it does perform better in the AL. Any idea why?

Here is the SDQL: H and tA(runs) < 4.5 and p:margin < -7 and conference=AL
http://sportsdatabase.com/mlb/query?output=default&su=1&sdql=H+and+tA%28runs%29+%3C+4.5+and+p%3Amargin+%3C+-7+and+conference%3DAL&submit=++S+D+Q+L+%21++

Try using ‘grouping’ (check the other forum or the manual for a description) as such:
H and tA(runs) <=4.5,4.4,4.3,4.2,4.1,4 and p:margin < -7 and conference=AL

Looks pretty linear, and roi goes up to +29% at <=4 rpg average!

Author
on July 17, 2015

I have the reason why it does not perform in the NL. The reason is the DH. When you consider an AL team that averages less than 4.5 runs a game, that would be the NL equivalent of a team that averages 4.2 runs a game. (The DH is worth 0.3 runs per game to an AL team). So when you query for a conference specific result at 4.2 runs per game instead of 4.5 runs per game, it verifies the DH value in the AL:
H and Average(runs@team and season) < 4.2 and p:margin <= -8 and …

What you see is at 4.2 runs per game it negates the DH factor in the AL, while it compensates at the same rate of the value of the DH in the AL, and thus the results for the NL achieve a statistically acceptable similarity at 4.2rpg.

Author
on July 17, 2015

Actually, my mistake, it actually works better in the AL at 4.2 runs per game.

Author
on July 17, 2015

So what I thought to be the answer is not true, it did not verify.

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0 on July 17, 2015

Thanks curiousapple for the sharing of a system that has done you well…This is exactly the sort of thing I was hoping to see with the forum. This is give and take; the more knowledge you share, the more you’ll get back in return.

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0 on July 17, 2015

Great first post and welcome. A simple question. Do you track it from the beginning of the season or do you like to wait for a time span to go by?

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3 on July 17, 2015

Holy cow. Thanks everyone. I love that “grouping” – sort of hard to do anything like that in my excel database.

Cherry, I typically pass on the first month or so. Since this is a seasonal average stat being used, it is more meaningful as more games go by. In this case, I want it to be more meaningful. I have some other systems where I like to fade stats like this early in the season when they DON’T mean much.

Author
on July 18, 2015

here is one based on runs per game, and a few other features, not a lot of games, but powerful:

<tr bgcolor="#dddddd”>

line >= 100 and Average(runs@team and season) <= 3.8 and conference = NL and po:runs >= 8 and ppo:runs >= 8
SU: 41-23 (0.75, 64.1%)   avg line: 143.4 / -158.9   on / against: +$3,304 / -$3,874   ROI: +51.6% / -38.1%

basically says dogs +100 or more that average less than 3.8 runs a game in the NL, that are off consecutive games allowing 8 or more runs, that shows 51.6% ROI and 64.1% winning percentage to an average line of +143.4! Not many +143 dogs that win 64.1% of the time!

Admin
on July 19, 2015

Great find. Solid contrarian system; I think in this case, the opponent (as well as the public) isn’t taking the dog seriously considering the best results for this are in the last game of a series.

 

Subscriber
on May 25, 2017

“Here is the SDQL: H and tA(runs) < 4.5 and p:margin < -7 and conference=AL”

Filter this for games thru June, omitting games in July-Sep, and you get a much better ROI. Its a little flat after June.

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