46zilzal
01-11-2010, 05:10 PM
When is enough TOO much?
The Follow UP vol 87 p. 57. The magazine of the Sartin Methodology
Done, of all people, by the CIA, it offers an experiment in betting.
Eight experienced handicappers were shown a list of 88 variables found on a typical past performance chart….Each handicapper was asked to identify what he considered to be the five MOST important items of information – those he would wish to use to handicap a race with…Each was the asked to select the 10, 20, and 40 most important variables he would use if limited to those levels of information.
At this point, the handicappers were give true data (sterilized so that horses and actual races could not be identified) for 40 past races and were asked to rank the top five horses in each race in order of expected finish. Each handicapper was given data in increments of 5, 10, 20 and 40 variables he judged to be the most useful. Thus, he predicted each race four times—once with each of the four levels of information. For each prediction, each handicapper assigned a value from 0 to 100 percent to indicate degree of confidence in the accuracy of his prediction.
When the handicapper’s predictions were compared with actual outcomes of these 40 races, it was clear that average accuracy of predictions remained THE SAME REGARDLESS OF HOW MUCH INFORMATION THE HANDICAPPERS HAD AVAILABLE. (My editing here) Three of the handicappers actually showed LESS accuracy as the amount of information increase, two improved their accuracy, and three were unchanged. All, however, expressed steadily increasing confidence in their judgments as more information was received.
The Follow UP vol 87 p. 57. The magazine of the Sartin Methodology
Done, of all people, by the CIA, it offers an experiment in betting.
Eight experienced handicappers were shown a list of 88 variables found on a typical past performance chart….Each handicapper was asked to identify what he considered to be the five MOST important items of information – those he would wish to use to handicap a race with…Each was the asked to select the 10, 20, and 40 most important variables he would use if limited to those levels of information.
At this point, the handicappers were give true data (sterilized so that horses and actual races could not be identified) for 40 past races and were asked to rank the top five horses in each race in order of expected finish. Each handicapper was given data in increments of 5, 10, 20 and 40 variables he judged to be the most useful. Thus, he predicted each race four times—once with each of the four levels of information. For each prediction, each handicapper assigned a value from 0 to 100 percent to indicate degree of confidence in the accuracy of his prediction.
When the handicapper’s predictions were compared with actual outcomes of these 40 races, it was clear that average accuracy of predictions remained THE SAME REGARDLESS OF HOW MUCH INFORMATION THE HANDICAPPERS HAD AVAILABLE. (My editing here) Three of the handicappers actually showed LESS accuracy as the amount of information increase, two improved their accuracy, and three were unchanged. All, however, expressed steadily increasing confidence in their judgments as more information was received.