Benter has identified
130 variables (e.g. past runs, speed etc) that influence the result of a
race. He and his team review past runs to assign values for each horse against
each of these variables. It is understood that these variables reflect both
the horse's form and how the race will be run.
The variable information
is fed into a computer that simulates potential outcomes of the race. The
results from these simulations allow Benter and his team to assign probabilities
to each runner, representing their percentage chance of winning the race.
Benter then compares
the horse's probability of winning against its market price and identifies
cases where the market price for a horse is significantly higher than the
computer simulated chance of winning - referred to as value opportunities.
Value theory suggests taking 'true odds', where the horse's odds (market
price) are equal to its chance of winning, will result in you breaking even
over time. Therefore if you always take horses that are over the odds, that
is where their odds are greater than their chance of winning, then well
tested probability theory warrants your success over time.
When Benter started
applying his method he used only 16 variables for his form analysis. The
increase in variables to 130 highlights the learning nature of Benter's
method. The growth of these variables can be attributed to the tireless
quest of understanding how poor results occur. In many cases it is likely
that poor results are due to a lack of information used to assess the race
and its runners. The answer? Understand what other factors may have influenced
the outcome of the race and add them to the pool of variables to be assessed
for future races.