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Valentine should have yanked Lester after 3 runs in the first, as he obviously didn't have it .. again. Some management behavior should be criminal. |
Covers | 5 |
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But Orlando was my best play at 16-3, 84% win predicted! CHI was indeed a risk at 51-16, and DAL was my worst at 35-14. Of course, when I say "a risk" I mean under 80% win predicted .. and I never include any game that isn't 70% or better. Yes, leave it to ORL to cost me predictable money. |
simondjester | 4 |
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I rarely post here, but I ought to have my head examined for ever betting on Orlando! Today I had a straight-up parlay of ORL, DAL, and CHI. I have been winning with these close-to-even-money straight-up parlays, which I create based on my own derived algorithm applied to Killersports 17-years historic NBA data base using their SQL. But today it said Orlando had a 16-3 chance of beating WAS, even with Howard out, as Davis had been sufficiently adequate. But when it comes to being the rule's exception, no one excels at that better than Orlando! Orlando just has this way of letting teams get hot during a game and then being too often unable to put out the fire. Will I ever learn!? At least I've learned not to bet on spreads and totals any more. But that lesson took four and a half years to learn. Hopefully it won't take me that much time to learn to stay away from Orlando. |
simondjester | 4 |
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Quote Originally Posted by Air1: hey simon, i sent a friend request. i was hoping you can teach me how to use the killersports website. I learned their query by reading their teaching guide: https://killersports.com/NBA/PDF/query_manual.pdf . Just go to the link I provided in my previous post and use this guide and teach yourself. That's the best way, I would guess. |
Knoxpoker | 134 |
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Here are some more interesting results. Since 1995 when a team has a winning percentage of .600 or greater and they're playing at home against a team with a winning percentage of .500 or less and the day before the home team was blown out by 15.0 or more points on the road .. the home team roars back to go 30-1 SU but only 18-12-1 ATS. That's only happened once this year so far, with CHI taking it out on PHO both SU and ATS. Regarding teams with at least one win and one loss, it's been said that a good team (winning percentage of .600 or better) playing on the road has a tendency to look past a weaker team (winning percentage of .500 or less) if the very next day the good team has to play again and against another good team. But since 1995 the good team covers the spread against the weaker team in that scenario 97-66-5, 59.51 percent of the time. .. But, if instead of 0 days rest the good team has a couple days of rest to think about their next good opponent, they look past the weak team 16-27-1 ATS! Both are contrary to general expectations. Part of that, though, could be the fault of a very sharp sheduler. This year there will be 29 times when a team is playing its fifth game in six days. So far 16 of those situations have been played, and the talk was to bet against those teams ATS as they'd be really tired and the Books wouldn't sufficiently compensate. But just the opposite has occured so far, as the dead tired team has won ATS 12-4! Apparently the Books over-compensated! But who would have guess it?! Anyway, read through this publication: https://killersports.com/nbalog.pdf It contains the site's database analysis for this NBA season, which includes 10 perfect scenarios for each of the 30 teams. |
simondjester | 8 |
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Another interesting analysis is how teams do when a key player is missing. Again, the site is: https://killersports.com/nba.py/query?sid=guest&text=+&=1&submit=query We'll start with Steve Nash. Nash has been with the Suns since the 2004 season. So how have the Suns done ATS at home since then when Nash was in the lineup? The query is: season >= 2004 and site = home and team = Suns and Suns:Steve Nash:minutes>0.1 .. 157-158-7 with an avg line of -7.1 . Changing the home parm to away .. 170-135-10 with avg line of -0.6, over 55%, with Nash being a minor money-making difference away when he's present. But what if Steve's not in the lineup? Simply change the minutes parm to "<" .. .. So at home .. 5-6-0 with an avg line of -2.1, and away .. 5-14-0 with an avg line of 4.6. When the Suns are away without Nash, bet against them ATS, as it's a 73.68% back-tested chance of a win! How about the same regarding Superman. Howards been with Orlando since 2004, and during that time: in lineup at home: 168-153-11 -6.0, in lineup away: 166-149-10 0.7, out of lineup at home: 1-1-0 1.8, out of lineup away: 2-2-0 1.6. No wonder they call him Superman -- he hasn't missed many games. How about God when he was with Cleveland. Lebron was with Cleveland from 2003 thru 2009, and the results: in lineup at home: 165-139-3 -6.3, in lineup away: 159-147-5 0.7, out of lineup at home: 4-2-0 1.2, out of lineup away: 3-4-0 5.3. You can also check for points scored, so if you wanted to know how the Lakers did ATS in their next game after Kobe laid 40 or more on someone, the query is: Lakers:Kobe Bryant:p:points>=40 and the result: 28-24-1 1.5. Specs for constructing queries is found here: https://killersports.com/NBA/PDF/query_manual.pdf I'm interested to know if the rest of you come up with anything significant here.
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simondjester | 8 |
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Here's an example of what the query can do in the NBA using this database that I've pretty much confirmed goes from 1995 thru today. Supposing a team with a SU win percentage of from .650 thru .750, a really good team, plays a team with a winning percentage from .200 thru .400, a pretty bad team. What would be the ATS result. The query would be: WP>=65.00 and WP<=75.00 and o:WP>=20.00 and o:WP<=40.00 .. and the results are 704-713-29. The Books know what they're doing. However .. supposing the weak team's previous game was a blowout for them by 15 or more points, do the books adjust for that? This query would be: WP>=65.00 and WP<=75.00 and o:WP>=20.00 and o:WP<=40.00 and o:p:margin>=15.0 .. and the results are 146-169-6, so the Books adjust for the weaker team's little rise in self-confidence, but not significantly, either that or the stronger team compensates, as the the weaker team only wins ATS 53.65 percent of these games, barely enough to break even at -110. But what if the poor weaker team themselves got blown out by 15 or more points in its previous game? What affect does that have. The query for that is: WP>=65.00 and WP<=75.00 and o:WP>=20.00 and o:WP<=40.00 and o:p:margin<=-15.0 .. and the result is 53-21-3, a winning percentage ATS for the stronger team of 71.62%! Of course, that's over 17.5 seasons! But still it appears to illustrate that a weak team blowing someone out doesn't have as strong an affect on that team as getting blown out .. and that's one of the hypotheses that can be made from using this query. Interesting though, in 1995 this scenario that has a 71.62 winning percentage over 17.5 seasons was 1-5-1 .. so if someone had thought of it then and had only that season's worth of data to wok with, they might have discarded the hypothesis. To continue by year: 1996 8-1-1, 1997 6-1-0, 1998 0-0-0, 1999 3-1-0, 2000 2-1-0, 2001 4-1-0, 2002 3-0-0, 2003 5-2-0, 2004 2-0-0, 2005 2-0-0, 2006 0-1-0, 2007 6-2-0, 2008 4-0-0, 2009 3-2-0, 2010 3-2-0, and 2011 (this season to-date) 1-2-1. So, aside from 1995, this system was pretty good .. until 2009 when it's been 7-6-1 to-date. It all depends on the makeup of the teams in a given year and the luck of the schedule. Though this simply may reflect a bigger wave length in the quantum luck, it may also mean there's something to this. With a little more analysis using this query, one might be able to determine characteristics that caused 1995 and the most recent three years to be so comparatively anomalous, exclude them, and thus maybe achieve a win percentage greater than 80.00 percent. This is just one example. Someone with a sharper knowledge of NBA psychology than I possess might be able to develop some more workable hypotheses that consistently hit around 58 - 63 percent with about a hundred plays/year. That would be a great goal for consistent winning. Indeed, those professional handicappers who present picks for sale touting a particular pick as being based on a past scenario with a 75% winning percentage may simply have presented a ton of queries to this database and found a few that are truly predictive. By the way, this site has database info for the NFL and MLB too. |
simondjester | 8 |
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Quote Originally Posted by jv040:
I don't know if you can back test this or not. but I am back testing it using covers closing lines for nba on covers and it's a pain in the ass but the results look good so far.I only did five teams so far though. I'm back testing nba team wins 2 or more ats at home then breaks the streak wait one more game to see if it is a win or loss at home and if it's a w chase for a win up too three times or if its a loss chase a loss ats at home up to 3 times. I'm also testing losses at home 2 or more in a row the same way. so its like this if they win at home wwll then chase the loss if they w at home wwlw chase the win chase what ever is after the break in pattern ats. it doesn't matter if theres 6 wins at home or 10 losses at home in a row. hope you can back test this. I'm guessing from the back testing I did so far theres about 150 plays a year. I Interesting .. however, at the moment that degree of complexity appears to be beyond my knowledge of the query .. and it may be beyond the query itself except in little bits at a time. I'll take a look at it when I'm more adept at the query. |
simondjester | 8 |
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Quote Originally Posted by Riceboi:
is it free to use for anyone? Yes! |
simondjester | 8 |
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I have been learning the NBA SDQL at this link:https://killersports.com/nba.py/query?sid=guest&text=+&=1&submit=query And I could use some more practice. If anyone has a stats-based system they're wondering about, let me know and I'll see if I can back-test it. The data base here goes back at least to 1995 (from some of my test results) all the way to current, and the query is pretty powerful, able to look at previous-game(s) results and all, days rest, lots of stuff.
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simondjester | 8 |
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Quote Originally Posted by mindtides:
Lets see if any team at least 2 games above .500 coming off of at least 2 losses, can cover or win their next 2 games. That's back-testable at https://killersports.com/nba.py/query?sid=guest&text=+&=1&submit=query With a query of: Sum(W@team and season) - Sum(L@team and season) >= 2 and p:margin<0 and pp:margin<0 The SU is 1306-909 and ATS 1094-1083-38, this is how a team does when it is at least 2 games above .500 at the present game and has just lost two previous games in a row. If that team lost the third game, how often did it win the fourth: SU 430-323 and ATS 367-369-17. And, if the team won the third, how often did it win the fourth: SU 853-597 and ATS 727-701-22. I couldn't find a way to insure that the team was at least 2 games above .500 after the third game. Regardless .. nothing here, and this data base goes back at least to 1995.
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mindtides | 13 |
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Depending on the type of system, it can be back-tested here: https://killersports.com/nba.py/query?sid=guest&text=+&=1&submit=query . I'm just learning how to use the query but so far it's debunked two stat-based systems in this forum. The Killersports data base goes way back, at least to 1995 in some of my tests. |
yankees4life08 | 2 |
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Quote Originally Posted by Knoxpoker:
Teams that are below 425 win percent , will rarely win more than 3 ATS in a row. Last yr you would have been up 27 units . I start the 2 game chase at 2 wins ATS I play 1 unit first game 2 units second game .. after that I take the 3 unit loss if it does not cover .. todays play .. (already started ) ATL -10.5 I just back-tested this at Killersports accessing their extensive NBA data base which goes back at least to 1995 from the results of some of my queries. The website I used is: https://killersports.com/nba.py/query?sid=guest&text=+&=1&submit=query The query I entered is: WP<42.50 and p:ats margin>0 and p:WP<42.50 and pp:ats margin>0 and pp:WP<42.50 and ppp:ats margin>0 and ppp:WP<42.50 The results: 520-525-16 ATS. That means roughly half the time a team with a SU WP of less than 42.50 (< .450) at the time of the fourth game won that fourth game ATS after winning ATS its last three in a row when at each of those three games the team had a WP less than 42.50. So .. of those 520 fourth game ATS wins, what was the result of the sub .450 team's fifth game ATS: 235-231-4. I don't believe this system works. If we only care about the team's WP during the fourth game only, the results ATS are: 536-549-18 .. and for the fifth game ATS: 242-241-6. Again, nothing. So how was this really for just last season (2010-2011)? To the first query add "and season = 2010" .. 26-39-1 ATS in the fourth game .. 12-12-0 in the fifth game. (Note that when the fifth game test results don't add up to the fourth game ATS wins, it's because that team also won SU and its WP exceeded .425.) The same for 2010 without considering the previous WP in the streak .. 27-41-1 ATS in the fourth game .. 12-12-0 in the fifth game. Again .. nothing. Back to the drawing board, I'm afraid.
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Knoxpoker | 134 |
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Quote Originally Posted by mindtides:
The core of the system will be based on any .500 + team coming off of at least 1 straight up loss playing a sub .500 team at home, it will be ATS and 1st halfs will be played in any sport that has halfs as well as the whole game. There are a few other factors involved in the plays that I will discuss should this do well.... plays to come soon. I just back-tested this system's NBA basic at Killer sports utilizing their extensive data base that goes back at least to 1995 that I've seen query results for. The web site I accessed is: https://killersports.com/nba.py/query?sid=guest&text=+&=1&submit=query The query I submitted is: site = home and WP>=50.00 and p:margin<0 and o:WP<50.00 The results ATS were 807-865-41. There appears to be nothing there. So I increased the home team's WP to 55.00 and dropped the away team's WP to 45.00 .. 454-483-26 ATS. At 60.00 and 40.00, 244-241-15 .. at 65.00 and 35.00, 128-105-6. At 70.00 and 30.00, 44-45-3. I'm thinking there's nothing there, though there are so many combinations to play with, the right one might yield desired results, but the quantity might end up being pretty small. |
mindtides | 273 |
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