Benter wanted something more rigorous, so he went to the library at the University of Nevada at Las Vegas, which kept a special collection on gaming. Buried in stacks of periodicals and manuscripts, he found what he was looking for—an academic paper titled “Searching for Positive Returns at the Track: A Multinomial Logit Model for Handicapping Horse Races.” Benter sat down to read it, and when he was done he read it again.
The paper argued that a horse’s success or failure was the result of factors that could be quantified probabilistically. Take variables—straight-line speed, size, winning record, the skill of the jockey—weight them, and presto! Out comes a prediction of the horse’s chances. More variables, better variables, and finer weightings improve the predictions. The authors weren’t sure it was possible to make money using the strategy and, being mostly interested in statistical models, didn’t try hard to find out. “There appears to be room for some optimism,” they concluded.
Benter taught himself advanced statistics and learned to write software on an early PC with a green-and-black screen. Meanwhile, in the fall of 1984, Woods flew to Hong Kong and sent back a stack of yearbooks containing the results of thousands of races. Benter hired two women to key the results into a database by hand so he could spend more time studying regressions and developing code. It took nine months. In September 1985 he flew to Hong Kong with three bulky IBM computers in his checked luggage.
Benter still wins with his algorithm, but he is constantly tweaking it.
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