[nash13]

200<=total<=209.5 and P:L and P:margin<=-10 and op:AW and op:margin>=10 and season >= 2009

[nash13]

College BB: 3>=line>=-3 and p:HL and p:margin>=-3 and month=1 and season >=2009

[Mako-SBR]

So for those who kept playing totals after that disastrous November start, how has it worked out for you? No off the cuff estimates please, what is your actual win/loss record since December 1?

I gave them up but am wondering if they rebounded for you guys and if they're still solid long-term.

[nash13]

So for those who kept playing totals after that disastrous November start, how has it worked out for you? No off the cuff estimates please, what is your actual win/loss record since December 1?

I gave them up but am wondering if they rebounded for you guys and if they're still solid long-term.

Only single plays when there are no contradictions for Totals starting 01.12.2014 up to 21.01.2015
104 Won - 89 Lost

[TheLineShifter]

Hello Everyone,

I am aware of the situation that query servers are responding a bit slow right now. Working on the tool to overcome this a little bit on our side to make queries a bit faster with the tool.

Best of luck tonight

[nash13]

A and p:L and p:margin<=-10 and p:line<=-6 and 51<=WP<=60 and o:WP>50

[nash13]

A and ou streak <=-2 and tA(points@season)>=102 and 98<=oA(points@season)<=102 and season >2009

[nash13]

total >200 and tA(FGA@season)>=82 and oA(FGA@season)>=82 and p:FGP>=50 and pp:FGP>=50 and season >2009

[nash13]

A and Sum(ou margin@team and season,N=5)<=-36 and 45<=WP<=55 and season >2009

[pip2]

OUCH! The last 282 active queries I have found went 106-171-5. It's tough to make money when you have a 38% win rate...

[Heart]

Yeah I'm hitting a disappointing 45% on my custom sdql plays in January (39-46). Not sure if this is just variance or if perhaps lines makers have caught on to some of the trends? Maybe some of the more long term users of sdql can weigh in on the bad month.

I'd think that when information that creates an edge (such as sdql) goes public it's not something a line maker worth his salt just ignores.

[nash13]

It all depends on the filters you use. The yield dropped a bit, but January was still in profit for me. But I use flexible stakes.

[Cutler'sThumb]

Huge day for anyone following all the active trends. Here are the biggest ones that don't have any conflicts. If anyone sees anything fishy, let me know.

OKC -9 (13,60, 110,173)
Rockets/Mavs Under 207 (18,29,86,116,238)
Mavs +4 (16, 33, 115)
Kings +6 (76, 104, 140, 183)
Nuggets +6.5 (63, 104, 206, 266)
Jazz +6.5 (237, 241, 248)

[pip2]

It all depends on the filters you use. The yield dropped a bit, but January was still in profit for me. But I use flexible stakes.

Nash, are you filtering these things out on the fly, as you search through active queries every day, so that if they improve over time they will eventually be allowed through your filters!

[nash13]

No quite a different concept. I take it season wise. At the start of the season I filter good trends and stick with them till the end of the season and then start again.

[pip2]

No quite a different concept. I take it season wise. At the start of the season I filter good trends and stick with them till the end of the season and then start again.

2 questions: What are you doing with all this new stuff that has been coming in since after the season started and
How hard would it be to automate the filtering process?

Thanks

[zxc]

Hi everyone. Is this possible to be converted to an SDQL Query?

"First game results of a road trip with at least 3 consecutive road games"

[nash13]

Hi everyone. Is this possible to be converted to an SDQL Query?

"First game results of a road trip with at least 3 consecutive road games"

A and p:H and n:A and nn:A
you should refine with rest or conference filters.

[nash13]

i like this one
A and p:H and n:A and nn:A and rest = 0 and 0

[nash13]

2 questions: What are you doing with all this new stuff that has been coming in since after the season started and
How hard would it be to automate the filtering process?

Thanks

I get them into the mix and evaluate them with the existing queries. Worked great so far.
But the hardest part is automating the filtering and measuring process of queries.
Scraping SDQL is automated right now, i have a program. now i am trying to get the developers make me a tool for filtering.
work in progress.

[zxc]

i like this one
A and p:H and n:A and nn:A and rest = 0 and 0

Thank you for this! But I think there is something missing on the last condition? It is not giving any results.

[JMon]

[QUOTE=nash13;23490985]i like this one
A and p:H and n:A and nn:A and rest = 0 and 0<o:rest<3[ quote]


</o:rest<3[>

[nash13]

that is it

[zxc]

that is it

Sorry. I am lost. So the query you like is " A and p:H and n:A and nn:A and rest = 0 and 0

[nash13]

add the part of the quote from JMon with "<...."

[nash13]

o:rest and so on

[nash13]

2 questions: What are you doing with all this new stuff that has been coming in since after the season started and
How hard would it be to automate the filtering process?

Thanks

For NHL example:
As mentioned in the sheet, the date of contribution is important for me. From that point forward I evaluate if the trend holds up. The Queries 03-09 are left out, because they are very flawed with the special time frame looking on. Taking the rest into account starting form their date of contribution and with contradictions and anything else: NHL is up 51+ Units

[nash13]

In the last couple of weeks and since starting the sheet, there are a some people in the sheet who have never said anything or contributed at all. I would kindly ask the regular posters about their opinion what to do about that?

4 or 5 who never showed up again were deleted, if there was mistakenly one of the regular posters around here, please PM me. i think it is a sign of respect to the regular posters and contributors if the one's who are only watching are left out again.

[hyahya]

I sorted the spreadsheet based on the Z-scores listed from highest to lowest and grouped them by 10s while removing duplicates and took a look at results for this season. Got through the 1st 40 so far (removing 114, 255 and 19 being they're duplicates):

1-10: 44-32
11-20: 41-20
21-30: 63-37
31-40: 48-25

Total: 196-114

So even though the spreadsheet has had a rough go of it over the last few weeks, overall still looking good on the season (at least the top 40). Basically, if you'd flat bet every query (include conflicting and duplicates), you'd be up about 70 units on the year.

[birdsfan]

I am still trying to get all this stuff so please any help is greatly appreciated.

I am looking for something simple NCAABB single digit Home favorites with same season revenge.

HF and P:AL and P:season = season and line >= -9.5

[emceeaye]

For NHL example:
As mentioned in the sheet, the date of contribution is important for me. From that point forward I evaluate if the trend holds up. The Queries 03-09 are left out, because they are very flawed with the special time frame looking on. Taking the rest into account starting form their date of contribution and with contradictions and anything else: NHL is up 51+ Units

Nash, thank you for the very useful information on NHL. Can you clarify what you mean by queries 03 - 09? Are you referring to NHL queries numbers 3 through 9?

Thanks

[perryhs]

I am still trying to get all this stuff so please any help is greatly appreciated.

I am looking for something simple NCAABB single digit Home favorites with same season revenge.

HF and P:AL and P:season = season and line >= -9.5

HF and P:AL and P:season = season and line >= -9.5 and p:O and op:O

[pip2]

For NHL example:
As mentioned in the sheet, the date of contribution is important for me. From that point forward I evaluate if the trend holds up. The Queries 03-09 are left out, because they are very flawed with the special time frame looking on. Taking the rest into account starting form their date of contribution and with contradictions and anything else: NHL is up 51+ Units

Yeah I just recently came to that realization the hard way. A lot of my pimped-out queries had results looked like this on the first day I created them: WWWWWWLWWWWWW. Then after they had been around for a month or so, the results looked more like like this: WWWWWWLWWWWWWLLWLLLLWLLL...

The problem for me is that I am like a mother with an ugly child when it comes these queries, and to me they always seem good-looking because I made them. But they alone would probably account for the 7% difference between me and Heart. After that there are a few other stinkers that other people wrote that probably account for another 10%...

Thanks to hyahya I am going back to see how many rotten ones I can get rid of based on z-score...

[dmitean]

So even though the spreadsheet has had a rough go of it over the last few weeks, overall still looking good on the season (at least the top 40). Basically, if you'd flat bet every query (include conflicting and duplicates), you'd be up about 70 units on the year.

I don't think it had rough go the last couple of weeks, not for me anyways.
I'm currently not looking to add queries, but to find best ways to work with existing ones and last week I hit around 40% - 45%, but three weeks before that, 68% success.

I think that if you try to check if query works for a specific game and find two queries that work (F/D A/H. month, season and so on) and no contradicting ones - it has pretty high success rate - at least till recent week.

[nash13]

it is not working everyday but on averrage better than most of the other methods i tried before.
and when there are certain circumstances a query can not reflect, i will not play it. these are just helpful hints and decision advices.

Last 2 days 21 units profit NBA, NHL and NCAA combined. The hardest thing is the volume of plays, so you have to adjust to your bankroll.
On averrage 57 queries were active. ist you only use 0.25% as 1 unit, that's still 15% of your bankroll in play. A bit too much, but that's the risk in it.