Bloomberg’s Kit Chellel wrote a fascinating profile of Bill Benter – a man who cracked the horse-racing code in the 1980s and made hundreds of millions of dollars.
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.