Pace and Cap - Sartin Methodology & The Match Up - View Single Post

J2EEDeveloper · 12-08-2009, 10:38 AM

Ted,
I appreciate your detailed comments. There are three "gray areas" that I would like to clear up.

First, yes, I am a software developer. I have no intention, nor have I ever had any intention, or reverse-engineering or copying RDSS software. My interest in RDSS is exclusively in the area of personal use, in my own race analysis, for my own personal wagering. That is based on a very simple assumption; if RDSS can generate a consistent and meaningful profit, I can benefit far more from using it than I can from attempting to steal and market it. I am a professional bettor first, and a software developer second.

Second, zigging and zagging seems to be causing a bit of confusion. I was not referring to pace line selection, but rather to the approach to racing in general. When everyone else is focused on early speed on the rail (for example), that is "zagging." In that case, locating a decent wager on a deep closer that may benefit from a speed duel of early-speed types would be "zigging." In essence, looking for opportunities beyond the simplistic "horses that run fast tend to win more races than horses that run slow" approach used by many racing fans.

Third, the easiest way to understand Tversky and Kahnemann is the display of what is essentially a Brohamer Model at every roulette table in Las Vegas. If a passing bettor sees a table at which black has appeared a disproportionately high number of times in the most recent 20 or so coups, there is a strong tendency to believe that red is more likely to occur in the next few coups. It is called the Gambler's Fallacy. (The inverse would be to consider the wheel biased, and bet on black--both are equally foolish.) In essence, short range models don't mean much when considering long range results.

Do short range models work? No. If you happen to win, it is not because the short range model predicted you would win; it is because the result of your win was within the normal range of a larger scale of events. One of the most difficult things to accept in horse racing is that there is no such thing as "statistical pressure" in short runs. That is the reason for building long-term models.

I look forward to working with RDSS in the future, as time permits.

Best Regards

12-08-2009, 10:38 AM	#28
J2EEDeveloper AlwNW1X Join Date: Oct 2009 Posts: 16	Response Ted, I appreciate your detailed comments. There are three "gray areas" that I would like to clear up. First, yes, I am a software developer. I have no intention, nor have I ever had any intention, or reverse-engineering or copying RDSS software. My interest in RDSS is exclusively in the area of personal use, in my own race analysis, for my own personal wagering. That is based on a very simple assumption; if RDSS can generate a consistent and meaningful profit, I can benefit far more from using it than I can from attempting to steal and market it. I am a professional bettor first, and a software developer second. Second, zigging and zagging seems to be causing a bit of confusion. I was not referring to pace line selection, but rather to the approach to racing in general. When everyone else is focused on early speed on the rail (for example), that is "zagging." In that case, locating a decent wager on a deep closer that may benefit from a speed duel of early-speed types would be "zigging." In essence, looking for opportunities beyond the simplistic "horses that run fast tend to win more races than horses that run slow" approach used by many racing fans. Third, the easiest way to understand Tversky and Kahnemann is the display of what is essentially a Brohamer Model at every roulette table in Las Vegas. If a passing bettor sees a table at which black has appeared a disproportionately high number of times in the most recent 20 or so coups, there is a strong tendency to believe that red is more likely to occur in the next few coups. It is called the Gambler's Fallacy. (The inverse would be to consider the wheel biased, and bet on black--both are equally foolish.) In essence, short range models don't mean much when considering long range results. Do short range models work? No. If you happen to win, it is not because the short range model predicted you would win; it is because the result of your win was within the normal range of a larger scale of events. One of the most difficult things to accept in horse racing is that there is no such thing as "statistical pressure" in short runs. That is the reason for building long-term models. I look forward to working with RDSS in the future, as time permits. Best Regards