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I'd rather know 1,000 positive indicators and have a general notion of how strong each was than to have 3 positive indicators that I knew to be exactly a very strong indicator but with no knowledge of the stratification of those indicators.
Many people try to look at data in an arbitrarily exact way. Most data is very stratified. Do you look at the totals or do you break it out by each combination of field size, number of horses in the race matching the criteria, type of race, age of the horses, distance, surface, track or circuit (including the quality of racing there), etc., etc., etc.
What about negatives? What is a "showstopper"? What is the relationship between showstoppers and positive factors?
What about combinations of positive factors? Are there ever combinations of positive factors that are negative?
The truth of the matter is that computers aren't really telling us much when we examine isolated factors such as horses carrying over 114 pounds. Many people who do not use computers assume that computers are incapable of making determinations beyond such a simple level. Generally, computer handicapping is probably still in its infancy, but has already come a long way from 20 years ago.
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Ranch West
Equine Performance Analyst, Quick Grid Software
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