tA(points)>=100 and oA(o: points)>=101 and WP>=60 and tS(L, N=5)>=4 and game number>=30
Total oriented trend, when a playoff team has a chance of getting getting back on the track against a poor defensive team.
I'm not much of a "team specific" user of sdql. However, I do review them and they also a great way to learn.Originally Posted by 19th Hole
Does anyone consider the the SDQL DAILY NBA TIPSHEET plays?
Agree, not much long term value with them for the most part as they're just too volatile.I'm not much of a "team specific" user of sdql. However, I do review them and they also a great way to learn.
They're actually a big part of the reason that the few SDQL-based pay touts out there have rarely exceeded 50% for long before crashing back to Earth over the course of a long season.
For a wide variety of reasons the majority of team/player trends break and expire at a much faster rate than the more generic league-wide trends...assuming the league-wide trend was based on logic and has a large number of games to analyze.
Excellent practice though within the db for sure, like that angle of the "daily" broadcasts.
That's not bad at all, good foundation to tweak and experiment off of.tA(points)>=100 and oA(o: points)>=101 and WP>=60 and tS(L, N=5)>=4 and game number>=30
Total oriented trend, when a playoff team has a chance of getting getting back on the track against a poor defensive team.
It's basically taking advantage of the books having to walk the total down with each loss as the playoff team runs through that negative streak, in order to keep the square bettor engaged and willing to keep throwing money at the over/fav.
Might possibly work the other way as well (to the Under) by reversing the scenario and playing the under whenever a strong playoff-headed team reels off 4 wins in 5 games and crushes the Over, will have to play with it.
Either way it's a good example of a base query/scenario that works which can then be expanded on, which everyone should be doing with each query we post just to get good at seeing the whole picture.
Ha, never knew that, nice T.There's a cleaner way to include that streak in this case:
o:streak = 4
Saves you the trouble of putting all those oppppppp entries.
Thanks.Ha, never knew that, nice T.If you need a losing streak, use an negative number. And of course > and < work with it too. I've been using "streak" and "ats streak" routinely to look for trends.
What about:
HD and p:ADW and season >= 2009 and conference = o:conference = po:conference = Eastern
The road faves in this trend are winning by over 6.5 points on average (and covering nearly 64% of the time). That would seem to bode well for tonight's matchup with a pretty low spread.
Thoughts?
I actually prefer teams based trends than general ones.Agree, not much long term value with them for the most part as they're just too volatile.
They're actually a big part of the reason that the few SDQL-based pay touts out there have rarely exceeded 50% for long before crashing back to Earth over the course of a long season.
For a wide variety of reasons the majority of team/player trends break and expire at a much faster rate than the more generic league-wide trends...assuming the league-wide trend was based on logic and has a large number of games to analyze.
Excellent practice though within the db for sure, like that angle of the "daily" broadcasts.
I'ts obvious that bookies (and public) react quicker to teams based trends, because they are easier to notice, but they are usually much more accurate.
Like Boston playing Under second game B2B few years ago. Or betting Over on Bucks games, when Bogut sat out. Playing Over in Thunder games, the first season with Perkins was easy money (still is btw).
Thunder off a loss angle and so on...
Such trends usually come with a good reason and not just statistical coincidence.
General trends are much harder to understand, are we looking at statistical abnormality that should correct itself or there is some logic behind it.
Nice one, especially since it's 4 - 11 last two seasons and 1 - 5 last six times.What about:
HD and p:ADW and season >= 2009 and conference = o:conference = po:conference = Eastern
The road faves in this trend are winning by over 6.5 points on average (and covering nearly 64% of the time). That would seem to bode well for tonight's matchup with a pretty low spread.
Thoughts?
like ittA(points)>=100 and oA(o: points)>=101 and WP>=60 and tS(L, N=5)>=4 and game number>=30
Total oriented trend, when a playoff team has a chance of getting getting back on the track against a poor defensive team.
the way I preferThere's a cleaner way to include that streak in this case:
o:streak = 4
Saves you the trouble of putting all those oppppppp entries.
op:W and op2:W and op3:W and op4:W
did you check out the total difference btwn conferences!Like this one quite a bit:
HD and season>2002 and p:AL and pp:A and ppp:A and pppp:A and ppppp:A and op:W
what about turning it into a small home dog and dropping the season filterHere's another:
HD and season>2009 and p: points<100 and pp: points<100 and tA(points)>100
Probably a little too general. Changing to:
HD and season>2009 and p: points<100 and pp: points<100 and tA(points)>100 and p:W
More descriptive of the actual situation but drops our sample size significantly and shows less consistency over time as it's 2-9 since 2009 but only 8-17 since 2002 (6-8 between 2002-2009)
1.5<=line<=3
I'm sure you do, the public eats these up as being 'real', which is why touts use them so frequently on their advertising blogs.I actually prefer teams based trends than general ones. I'ts obvious that bookies (and public) react quicker to teams based trends, but they are usually much more accurate.
And I can definitely see why they're appealing, no question. But the actual results from thousands of previous team/player-trend plays from dozens of logged handicappers over the past decade's worth of NBA seasons have proven them to be tough to win with the vast majority of the time.
The type that are like this example (not a real one, made up for the post) are nearly impossible to quantify as being anything other than a fluke, no matter how strong they may appear in the moment: "The Spurs are 14-2 when Tony Parker has a shooting % of 50% or higher in his previous game and 5+ assists".
Or something like: "The Spurs are 11-1 when coming off 2 days or more rest after winning on the road within their division if they're playing their 4th game in 7 nights".
I do like team trends in one way, which is as a tertiary piece of information when weighing other more important metrics/scenarios. But I won't make or cancel a bet I'm already leaning towards or against based on whether a team or player trend is pointing the opposite way.
But all of us are always open to new angles though, if you find some that offer more than 50+ game sample sizes we'd definitely like to look at them!
That's not bad either, I'd want to examine it a bit further but it looks like a solid one to build off and play with T. I hesitate to break out specific Divisions or Conferences (Eastern) but you never know, the data might point to some sort of hidden travel anomaly or circumstance that is present in a specific region that isn't in others.What about:
HD and p:ADW and season >= 2009 and conference = o:conference = po:conference = Eastern
The road faves in this trend are winning by over 6.5 points on average (and covering nearly 64% of the time). That would seem to bode well for tonight's matchup with a pretty low spread.
Thoughts?
Either way it's something to work on, like it.
Last edited by Mako-SBR; 03-18-14 at 05:23 PM.
Nothing for me tonight. Few leans, but nothing strong enough
GL fellas...and great contribution recently
