NBA Stituational Bet, SDQL

Originally Posted by nash13

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

Originally Posted by 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

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

Originally Posted by nash13

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...

Originally Posted by hyahya

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.

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.

Am I the only one that has Totals plays giving much much better results than ATS plays the last month or so?

No for me it is just like yours, Totals are performing better than ATS in January so far

Originally Posted by 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.

I wonder if a query library got to be so big that every game every day had dozens of unique (and solid) queries active, if you would then have a really high win rate -- or if the queries would just cancel each other out all the time, or be wrong even when 2 dozen of them were in complete agreement...

Also, one other issue that keeps popping up for me is what constitutes a unique query?

AF and p:AL and p:ats margin<0 and playoffs = 0 and season>=2006
AF and p:AFL and 1 <= rest <= 2 and season>2007
AF and p:AFL and p:line >= -4 and season > 2007 and total>199
AF and p:AL and total >= 198
A and p:AFL and p:line >= -4 and season > 2007 and month!=11
A and p:AFL and 1 <= rest <= 2 and season >= 2005
A and F and p:A and p:L and total >= 198

If all these queries showed that phi, playing b2b, 5th game in 4 days, just returned from a 7-game road trip, is going to beat the Warriors, should you bet 7 units on it?

Originally Posted by pip2

I wonder if a query library got to be so big that every game every day had dozens of unique (and solid) queries active, if you would then have a really high win rate -- or if the queries would just cancel each other out all the time, or be wrong even when 2 dozen of them were in complete agreement...

that is the main concern i have about SDQL queries right now. I am at the point where i would like to take the best queries into consideration, but you'll never know. esp in the nba queries are very specific. NHL and MLB have more problems with Contradictions.

Originally Posted by pip2

Also, one other issue that keeps popping up for me is what constitutes a unique query?

AF and p:AL and p:ats margin<0 and playoffs = 0 and season>=2006
AF and p:AFL and 1 <= rest <= 2 and season>2007
AF and p:AFL and p:line >= -4 and season > 2007 and total>199
AF and p:AL and total >= 198
A and p:AFL and p:line >= -4 and season > 2007 and month!=11
A and p:AFL and 1 <= rest <= 2 and season >= 2005
A and F and p:A and p:L and total >= 198

If all these queries showed that phi, playing b2b, 5th game in 4 days, just returned from a 7-game road trip, is going to beat the Warriors, should you bet 7 units on it?

i had one game this year: 76ers vs Hawks on Jan. 13.
10 active queries for the Hawks and 1 active for the 76ers.
By my standards this is a no play for me, but it is free for discussion if a game like this with so much power on one side should be ignored.
The contradicting query for the 76ers was NBA255. It is a relativey strong query, one of the best. So if you stand by your standards this is a no play. Some would take Atlanta anyways.

The game ended Atlanta covering.

Originally Posted by nash13

i had one game this year: 76ers vs Hawks on Jan. 13.
10 active queries for the Hawks and 1 active for the 76ers.
By my standards this is a no play for me, but it is free for discussion if a game like this with so much power on one side should be ignored.
The contradicting query for the 76ers was NBA255. It is a relativey strong query, one of the best. So if you stand by your standards this is a no play. Some would take Atlanta anyways.

The game ended Atlanta covering.

So clearly, if a no-play is not a consideration in your example, determining a pick is more complicated than just going with the side supported by the query with the strongest WP/ROI/biggest sample size. Ideally, and what it appears Nash is successfully working towards, we would develop an algorithm that takes into account both rWP/ROI/sample size of an individual active query on a game, and ALSO the number of queries in support of one side vs the other of a particular game that a number of queries point to.

Originally Posted by pip2

I wonder if a query library got to be so big that every game every day had dozens of unique (and solid) queries active, if you would then have a really high win rate -- or if the queries would just cancel each other out all the time, or be wrong even when 2 dozen of them were in complete agreement...

I don't think it's a problem. If you have good queries that contradict each other - it's a good thing, since it will allow you to stay away from bad bets. That's why I always work with each query to see if it fits the situation for that night's game.
At least for me, so far, the problem is the opposite. On big cards of 10+ games, I have sometimes 8 - 9 bets and I would prefer to have no more than 5.

But if we will reach a point, where there are too much good queries that we can't sort... will be a problem - but we are very far from that imho.

I was personally very impressed with the back test Nash13 posted back around New Year (#2707). What he showed was a hit rate of 58.77% sample size of 832 plays. This was for one play on each non-conflicted trend. The he applied his quality filter and it went up to 61.03% over 308 plays. Also showed similarly effective numbers with large volume betting in hockey. I also saw this performance in my own hockey back test I did back in November, although that was only thru the first 30 or so trends.
I think this clearly supports a strategy of leveraging the trends into a large volume of plays. This allows the overall quality of the trends to grind along. There will be swings, as we have seen recently, but if we had been using the same strategy all season and had been 58-61% over 300-800 plays heading into January, a dip would have been more than acceptable.

Imho, it really boils down to two things:
1) Do you have the time or ability to analyze all the trends and actually handle the volume. It's still a daily project, but the software nash13 got developed has been the key for me.
2) What is your comfort level and risk tolerance. I personally don't mind if I have 1/3 of my BR in play on a given day, but cutting down to .5% of BR or .25% of BR solves that. Otherwise applying a level of filtering will pull the volume down. I also agree that we probably have a pretty good volume of trends (esp in NBA) and focusing in on eliminating redundancy and measuring quality is an important step.

To be honest, I'm not big believer in Nash's tests, unless Nash corrects me. All the queries we added during this season - we added since they work this season.
If I will add now a query that is 24 - 5 this season, looking back, it will boost the stats, but wouldn't have increased our profit during the season and there is no way to know if it will conitnue to work.