Haralabos Voulgaris Building a stack in stages
Haralabos „Bob“ Voulgaris ist ein kanadisch-griechischer Pokerspieler und professioneller Sportwetter. Haralabos „Bob“ Voulgaris (* 7. April in Winnipeg, Manitoba) ist ein kanadisch-griechischer Pokerspieler und professioneller Sportwetter. Haralabos Voulgaris (* ), kanadisch-griechischer Pokerspieler; Pantelis Voulgaris (* ), griechischer Filmregisseur; Petros Voulgaris (–). Abonnenten, folgen, Beiträge - Sieh dir Instagram-Fotos und -Videos von Haralabos Voulgaris (@haralabob) an. Haralabos Voulgaris has won 0 bracelets and 0 rings for total earnings of $ See all events where they placed in-the-money.
Haralabos Voulgaris Video
Bill Simmons, Zach Lowe, and Haralabos Voulgaris Preview the 2014-15 NBA Season - B.S. Report
i don't think this qualifies as a black swan. Black swan is something that changes what you think is possible (examples: automation, cars, pc, the internet, 9/11). searching for positives here but I take some comfort in the fact that the one country getting the most credit for being aggressive in testing, South Korea, seems to. Veteran sports bettor and poker player Haralobos Voulgaris has crossed over with an NBA front office job. Is this the start of a trend? Haralabos Voulgaris Poker Spieler Profil. Die aktuellsten Informationen, Gewinne und Galerie. Uhr aufstehen, Zähne putzen, anziehen; Arbeit; Spiele des Tages. Marvel Puzzle Quest ☑ – “Big Enchilada” # mit Gamora (Guardians of the Galaxy). Pro gespieltem Diener gibt es einen Zauberspruch der normalerweise das gleiche Mana kostet wie der Diener aber in diesem Fall Manakosten von Null hat. Visit Review. The Hong Kong based entrepreneur wins the third largest first-place prize in poker history. Eric Raskin Eric is a veteran click here, editor, and podcaster in the sports and gaming link. There will be skeptics, of course, https://gutterfunk.co/casino-online-schweiz/das-grggte-stadion-in-deutschland.php as there were in Philadelphia when GM Sam Hinkie intentionally bottomed out to give the 76ers a chance to later rise to the top. But if it works, it will surely become a trend in the NBA, not a one-off. For more than forty https://gutterfunk.co/online-casino-list-top-10-online-casinos/chapta.php, the World Series of Poker has been the most trusted name in the game. Their algorithms are proprietary. And with each passing year, their sophistication mounts. Their goal is nothing less than a sustainable edge.
It is a paradoxical quest. The history of sports betting is littered with the corpses of gamblers who have enjoyed spectacular runs only to flame out just as quickly when their edges die.
When they see a gambler winning big, bookmakers correct their mistakes. Rival gamblers spot the same edges -- or copy them -- and bet the line back to plumb.
Indeed, while the wide availability of information in the Internet age and exponential increase in computer processing power have given rise to the sports gambling quant, those very same factors have made the pursuit of a sustainable edge that much more quixotic.
The marketplace evolves. The betting public, square though it may be, is better informed than ever before: Reams of team and player statistics reside in the cloud, awaiting download.
The bookmakers, meanwhile, have joined the quantitative battle. Some who formulate the opening lines only a few still do so; all the others simply copycat have engineered their own sophisticated models.
Cantor Fitzgerald, the Wall Street trading firm, started a division called Cantor Gaming in to operate a sportsbook business in Las Vegas, then acquired the consulting firm that had been the oddsmaker of record for the gambling world.
Andrew Garrood, a former high-finance quant whose previous experience included developing pricing models for interest rate derivatives at a London bank, designed it.
A slim six-footer with dark hair and dark eyes, Voulgaris talks fast. His eyes flit. He has the canny, quick-minded air of a merchant in a bazaar in the Eastern Mediterranean.
Since birth, he seems never to have lacked for self-confidence. He likes to say that he had no mentors when it comes to his gambling career, but in reality, he did.
When Voulgaris was 18, he took a gap year between high school and college. First he traveled to Greece, visiting the hardscrabble villages -- Argos, Tripoli -- where his parents were born and raised before they immigrated, in their 20s, to Canada.
Then he and his father made a trip to Las Vegas, where they lived for most of the next two months at Caesars Palace. The elder Voulgaris had risen from poverty to become a successful Winnipeg entrepreneur.
He developed commercial real estate; he owned and operated a Greek restaurant called Hermes -- the patron god of among other things games, sports and sudden enrichment.
His net worth grew into the millions; he also happened to be an avid gambler. He was also, his son now suggests, the consummate square.
There was no rhyme or reason to it. He was very, very superstitious. He would have dreams, with, like, numbers and colors in them, and that would influence him.
Nevertheless, Voulgaris remembers those Vegas days fondly. So he spent most of his time in the Caesars sportsbook. Because it was basketball season, he watched a lot of NBA, but with a purpose.
He paid attention to adjustments, the ebb and flow of the pace of play. He took notes on what he saw. He eavesdropped on his fellow gamblers.
At times they wagered together. His two months in Vegas -- and, really, the whole of his childhood -- were an education by counterexample.
The first computer model put into the service of sports gambling dates to the late s, when Michael Kent, a former nuclear submarine engineer for a Pentagon contractor, wrote a program that predicted NFL, college football and college basketball scores.
At the time, though, he was going up against green-eyeshade bookmakers armed with nothing more than adding machines and intuition.
It was hardly a fair fight. Kent eventually moved to Las Vegas, where a betting syndicate -- the legendary Computer Group -- formed around his work, winning untold millions for its members well into the s.
Kent continued to develop models and bet on sports up until seven years ago. He is now retired, according to his lawyer, his whereabouts closely guarded.
Billy Walters, a core member of the Computer Group, has, however, stayed in the game; he now has a staff of consulting mathematicians who have built advanced predictive models to project scores.
Walters, Kent and their syndicates stood basically alone until the late s, when PCs became powerful enough to do the computation work required by predictive models, and more data became available to feed them.
Voulgaris was well aware of these predecessors. As a purely subjective bettor, Voulgaris had been placing perhaps individual wagers each season.
But after the disastrous end to the season, with his edge gone, he decided that he should increase his betting frequency by an order of magnitude but decrease the sums he was putting at risk on each wager.
It only made probabilistic sense. If his return on investment ROI fell from 20 percent to, say, 5 percent, that was okay.
This new approach would require an enormous amount of research and analysis. It would require projecting a score for each and every game in an NBA regular season -- all 1, A single human mind would be overwhelmed by the workload; only a computer program could handle it.
Voulgaris chose the right moment to start building a predictive model for NBA games. Four years earlier, in the season, the league had for the first time made play-by-play information available to the public, whereas before only box scores were published.
This trove of fresh information had no immediate practical value, except perhaps to assuage fan curiosity.
But by , a large enough sample of data had accumulated to employ it with scientific rigor. To help him build his model, Voulgaris required a specialist in the field, a mind trained in the codes of statistics, mathematics and computer science.
He started the search in It took him two years and six individual tryouts -- most of those interviewees were found online, Voulgaris says, and two of them landed in NBA front offices -- to find the right person.
The right person was a literal math prodigy. As a preteen, he had won national math contests; he had been the subject of awestruck articles in major newspapers.
He had scored a perfect on the math portion of the SAT when he was in seventh grade. At the time of his interview with Voulgaris, he had just quit a high-paying job designing algorithms for an East Coast hedge fund with a roster of Nobel-grade quant talent.
The relationship got off to a rocky start. To do so, they would have to break the game down into its basic unit, the possession.
Each simulation would therefore be a series of mini-simulations. First, the program would have to predict the number of possessions each matchup would likely produce.
Then it would need to judge the likeliest outcome of each possession: Score or no score; one point, two points or three; micro-forecasts ascertained from historical performance data.
It would also have to take into account a vast number of potential occurrences, each missed shot or successful rebound creating the possibility of still other occurrences -- a garden of explosively forking paths, as if in parallel universes.
The program would run tens of thousands of simulations for each matchup, discarding the most outlandish or improbable results. It would be a black box -- prophecy as output.
Between the statistical analysis, the algorithms and the programming, it took two years to create their first model, version 1.
Voulgaris continued to bet subjectively, marking time until the model was ready. When they finished, they called it Ewing.
At some point in the process of breaking the game down into its component parts, they realized that Ewing would also require a kind of feeder model, one that could forecast the lineups a team would most likely use each game and the minutes each player was likely to see on the court.
They called that model Van Gundy. Van Gundy, in turn, required its own feeder tool, one that would track the overall roster patterns for each team, the trades, the draft picks, the midseason player-acquisition tendencies.
Sources: Mavs hire ex-pro gambler Voulgaris. Dallas Mavericks. What people in the NBA are saying about the Orlando restart. Source: Lakers assistant Hollins to stay behind.
Los Angeles Lakers. Pacers' Oladipo to sit out restart of NBA season. Indiana Pacers. Pels' Bzdelik won't join team; no word on Gentry.
New Orleans Pelicans. Source: NBA, union agree to jersey messages. Utah Jazz. Source: Heat close facility after 2nd positive test.
Pacers' Oladipo to sit out restart of NBA season. Indiana Pacers. Pels' Bzdelik won't join team; no word on Gentry. New Orleans Pelicans.
Source: NBA, union agree to jersey messages. Utah Jazz. Source: Heat close facility after 2nd positive test.
Miami Heat. During this time Bob began to learn his future craft , sitting in the sportsbook watching NBA games while his father played blackjack.
A few years later and right out of college, Bob was poring over the preseason odds of winning the NBA Championship.
The 6. After winning another big sum when the Lakers won their second consecutive title, Voulgaris started to make around NBA wagers a season.
Often these bets were on first and second half totals, which he started hammering after realizing sportsbooks were calculating them by just dividing their projected game total in half which would not factor in the foul-heavy, stop-start nature of NBA fourth quarters.
Eventually the books caught on and Voulgaris needed a new way to regain his edge. This time, he enlisted help by hiring a literal math prodigy away from an analytical hedge fund job in Together, they began to build a predictive model that could simulate the likely outcome of every NBA matchup thousands of times.
At the time, though, he was going up against green-eyeshade bookmakers armed with nothing more than adding machines and intuition.
It was hardly a fair fight. Kent eventually moved to Las Vegas, where a betting syndicate -- the legendary Computer Group -- formed around his work, winning untold millions for its members well into the s.
Kent continued to develop models and bet on sports up until seven years ago. He is now retired, according to his lawyer, his whereabouts closely guarded.
Billy Walters, a core member of the Computer Group, has, however, stayed in the game; he now has a staff of consulting mathematicians who have built advanced predictive models to project scores.
Walters, Kent and their syndicates stood basically alone until the late s, when PCs became powerful enough to do the computation work required by predictive models, and more data became available to feed them.
Voulgaris was well aware of these predecessors. As a purely subjective bettor, Voulgaris had been placing perhaps individual wagers each season.
But after the disastrous end to the season, with his edge gone, he decided that he should increase his betting frequency by an order of magnitude but decrease the sums he was putting at risk on each wager.
It only made probabilistic sense. If his return on investment ROI fell from 20 percent to, say, 5 percent, that was okay.
This new approach would require an enormous amount of research and analysis. It would require projecting a score for each and every game in an NBA regular season -- all 1, A single human mind would be overwhelmed by the workload; only a computer program could handle it.
Voulgaris chose the right moment to start building a predictive model for NBA games. Four years earlier, in the season, the league had for the first time made play-by-play information available to the public, whereas before only box scores were published.
This trove of fresh information had no immediate practical value, except perhaps to assuage fan curiosity.
But by , a large enough sample of data had accumulated to employ it with scientific rigor. To help him build his model, Voulgaris required a specialist in the field, a mind trained in the codes of statistics, mathematics and computer science.
He started the search in It took him two years and six individual tryouts -- most of those interviewees were found online, Voulgaris says, and two of them landed in NBA front offices -- to find the right person.
The right person was a literal math prodigy. As a preteen, he had won national math contests; he had been the subject of awestruck articles in major newspapers.
He had scored a perfect on the math portion of the SAT when he was in seventh grade. At the time of his interview with Voulgaris, he had just quit a high-paying job designing algorithms for an East Coast hedge fund with a roster of Nobel-grade quant talent.
The relationship got off to a rocky start. To do so, they would have to break the game down into its basic unit, the possession. Each simulation would therefore be a series of mini-simulations.
First, the program would have to predict the number of possessions each matchup would likely produce. Then it would need to judge the likeliest outcome of each possession: Score or no score; one point, two points or three; micro-forecasts ascertained from historical performance data.
It would also have to take into account a vast number of potential occurrences, each missed shot or successful rebound creating the possibility of still other occurrences -- a garden of explosively forking paths, as if in parallel universes.
The program would run tens of thousands of simulations for each matchup, discarding the most outlandish or improbable results.
It would be a black box -- prophecy as output. Between the statistical analysis, the algorithms and the programming, it took two years to create their first model, version 1.
Voulgaris continued to bet subjectively, marking time until the model was ready. When they finished, they called it Ewing. At some point in the process of breaking the game down into its component parts, they realized that Ewing would also require a kind of feeder model, one that could forecast the lineups a team would most likely use each game and the minutes each player was likely to see on the court.
They called that model Van Gundy. Van Gundy, in turn, required its own feeder tool, one that would track the overall roster patterns for each team, the trades, the draft picks, the midseason player-acquisition tendencies.
That database, less intricate than the other two, they at times jokingly referred to as Morey, as in Daryl Morey, the quant-minded GM of the Rockets.
Ewing, Van Gundy, Morey. Player, coach, GM. The names of each corresponding, of course, to the job of each tool. Every score the model spit out was higher than the average lines produced by the bookmakers -- the standard by which they would be judging themselves.
The model, in other words, was recommending that Voulgaris bet the over in every single game. After weeks spent poring through code, Voulgaris finally caught the flaw.
In more advanced versions of Ewing, they would jettison this primitive free throw method. The key is to find those scraps that are more predictive than others.
Each player has two values -- on offense and as a defender -- and those values are constantly changing.
So Voulgaris and the Whiz created, for Ewing, an aging component. Further number-crunching revealed that different types of players, based on position and size, will reach their zeniths at different ages and on trajectories that are possible to predict.
Haralabos Voulgaris Better than the book
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