Computer Based Horse Race Handicapping And Wagering Systems Pdf - easysiteilikeHorse Racing Forum - PaceAdvantage. By way of encouragement to those who are currently experiencing protracted losing runs, I suggest you download and listen to the William Benter Hong Kong syndicate fame presentation entitled What are my odds? I particularly like the way he nonchalantly refers to horse-racing as being 'near to his heart' and, later in the presentation, shows a graph of which he is 'particularly proud' master of understatement. Best wishes, John. This looks like a good way to spend friday afternoon thanks Joe M.
Probability & Statistics (24 of 62) Calculating the Odds and Horse Racing
Adapting support vector machine methods for horserace odds prediction
Close to a billion dollars later, he tells his story for the first time. No, he told this story decades ago, and published papers detailing his algorithms, e. Benter, W. Hausch and Ziemba eds. The only mention of it I could find just said it was suspected he had won the unclaimed prize. NetOpWibby on May 3,
Annals of Operations Research. April , Cite as. The methodology of Support Vector Machine Methods is adapted in a straightforward manner to enable the analysis of stratified outcomes such as horseracing results. As the strength of the Support Vector Machine approach lies in its apparent ability to produce generalisable models when the dimensionality of the inputs is large relative to the the number of observations, such a methodology would appear to be particularly appropriate in the horseracing context, where often the number of input variables deemed as being potentially relevant can be difficult to reconcile with the scarcity of relevant race results. The methods are applied to a relatively small races in-sample sample of Australian racing data and tested on races out-of-sample with promising results, especially considering the relatively large number 12 of input variables used. Skip to main content.
As the access to this document is restricted, you may want to search for a different version of it. You can help correct errors and omissions. See general information about how to correct material in RePEc. For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Tai Tone Lim. If you have authored this item and are not yet registered with RePEc, we encourage you to do it here.
Benter, W. In, Hausch, Donald B. San Diego, USA. Academic Press. Downloads from ePrints over the past year.
Skip to search form Skip to main content. Benter Published DOI: Data requirements, handicapping model development, wagering strategy, and feasibility are addressed. A logit-based technique and a corresponding heuristic measure of improvement are described for combining a fundamental handicapping model with the public's implied probability estimates. View PDF.