Before the invention of electronic brains (computers), handicappers were relying on their own trends, stats, and good sense to survive. The idea was to create a model that could analyze each situation and predict the probabilities. Eliminate the human factor taking Emotion and prejudice out of every decision.
Before 1980, computers were only a gimmick of Science Fiction, where blinking lights and crazy display monitors were serviced by Geeks in white lab coats. The idea of beating the Bookmakers, started with a small group of programmers. It was headed up by a 25 year old mathemetician, who had spent 11-years helping develop water sanitizers for fortune 500 company CH2m-HILL.
Finding such work boring he relocated to Las Vegas to bet on Football games. For the last seven years he had been saving his money, to wager on football and basketball games. The job of betting sports fulltime was a little harder than he had imagined. He would wake up early, update his information from the morning newspapers.
Access the Control Data computer on which he was renting time, and establish a belting line for each game. Then he and a friend would spend the rest of the day and night visiting sports books and private bookmakers, seeking out the most favorable opportunity. According to his records, he lost $20.000 that football season. His bad luck continued two months into the basketball season. I was getting killed," he says. "I was at the point where I was debating what my future was going to be.
Betting the games was an awesome responsibility. It was not an easy thing to settle up with a bookmaker after each round of bets, carrying huge bundles of cash in and out of public places. Whenever he had a lot of money on him, he feared he was being followed. If he happened to notice two men walking behind him on the sidewalk, he would run as fast as he could into the nearest casino, and stand near a security guard for a while.
So that's the story I heard. I good one, but it is the past. Things aren't so simple as they once were. You can see our new state-of-the-art systems available at this website and even be part of the action now. Visit: The Best Sports Prediction Network on the Web Hope to see you join us!
I was asked a question that I figured I'd answer with Football Season fast approaching. The question was, do you generalize a formula for all sports you run? The answer is a big NO. They're all different animals. MLB is perhaps the most complicated as it is a "different animal" from month to month. Let me give you a couple of very basic, and fundamental differences between the three.
You've hopefully come to realize that the perhaps the best place to look for value in sports betting is in games after the team lost. This holds true in just about all of them, but some more than others. The main point I want to make in this email is that MLB, NFL, and NCAAF are all momentum driven sports; however, the way you should look to capitalize varies with each:
Here's some proof:
-In MLB: teams win 51.0% of the time after a WIN (55.0% at home and 46.6% percent on the road). -In MLB: teams win 48.9% of the time after a LOSS (53.8% at home and 44.6% percent on the road).
Don't get excited though about tailing teams off wins and fading losses. It is of course all covered by the house. The real question is…
Where would you have lost the most amount of money, and where the least?
Last 7 Years:
-In MLB: betting a team after a WIN would lose you -426.31 units (-203.40 at home and -222.91 on the road).-In MLB: betting a team after a LOSS would lose you -560.02 units (-128.72 at home and -431.30 on the road).
See how a contrarian look at things will reveal an instant loophole?
======An MLB trick **In baseball, consider the classic get-away loss situation. If a team lost every game of a series, it would be logical to say that they are wanting the win here especially at home in front of their fans....
Read more: For more technical information on our propriatary modeling and sports prediction methods check out: The Bottom Line (nfl-mlb-cfb)
Ultimate Sports Prediction Algorithms for over 10 Years
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