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Old 01-12-2021, 02:20 PM   #57
Nitro
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Join Date: Feb 2009
Location: NY
Posts: 18,945
Quote:
Originally Posted by dnlgfnk View Post
I couldn't play your way. Wouldn't enjoy it You couldn't play mine.

I create my own odds line/pct. based upon previous trips. Emulating Benter however primitively, I use the public odds as a separate factor, incorporating all the data crunching of the best handicapper race in, race out to merge with my own, waiting as long as possible to fashion my "true odds".

Playing in a casual manner since last August with a small betting unit, I'm showing a 17% profit after roughly 365 wagers. I could screen shot if necessary, and if instructed how. I plan to ramp up this spring, for better or worse.
Well, to each his own.
I enjoy my method of play because I came to the realization that this game is not about the horses. Its about those who control every aspect of a horse’s racing career and their personal financial goals. All the data crunching, statistical analysis and subjective interpretations of a horse's information pales by comparison to the objective realities of the monies being wagered on those horses at any given time.

How do I know this? Because I did play your way for 30 odd years with some respectable success. But not enough success to justify the long hours and sweat equity I would pour into this game. I now simply review all aspects of the market through a highly sophisticated tote analysis during any typical betting cycle that may interest me. It takes all of about 10 to 12 minutes of my time to determine if there’s a viable and lucrative play or not.

Since you mentioned Bill Benter (a player I highly respect) I suggest that you consider some of his thoughts:
Quote:
Excerpts from:
Computer Based Horse Race Handicapping and Wagering Systems:”
A Report by William Benter


The complexity of predicting horse performance makes the specification of an elegant handicapping model quite difficult. Ideally, each independent variable would capture a unique aspect of the influences effecting horse performance. In the author's experience, the trial and error method of adding independent variables to increase the model's goodness-of-fit, results in the model tending to become a hodgepodge of highly correlated variables whose individual significance's are difficult to determine and often counter-intuitive.

Additionally, there will always be a significant amount of 'inside information' in horse racing that cannot be readily included in a statistical model. Trainer's and jockey's intentions, secret workouts, whether the horse ate its breakfast, and the like, will be available to certain parties who will no doubt take advantage of it. Their betting will be reflected in the odds. This presents an obstacle to the model developer with access to published information only. For a statistical model to compete in this environment, it must make full use of the advantages of computer modeling, namely, the ability to make complex calculations on large data sets.

The odds set by the public betting yield a sophisticated estimate of the horses' win probabilities.

It can be presumed that valid fundamental information exists which can not be systematically or practically incorporated into a statistical model. Therefore, any statistical model, however well developed, will always be incomplete. An extremely important step in model development, and one that the author believes has been generally overlooked in the literature, is the estimation of the relation of the model's probability estimates to the public's estimates, and the adjustment of the model's estimates to incorporate whatever information can be gleaned from the public's estimates. The public's implied probability estimates generally correspond well with the actual frequencies of winning.
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