The Cleveland Browns of the National Football League recently caused a media stir by hiring sports analytics guru Paul DePodesta as chief strategy officer. DePodesta first gained notice in the early 2000s when he helped Major League Baseball’s Oakland A’s build a contending team on a relatively meager budget for player salaries; Jonah Hill’s character in the movie Moneyball was based on him. DePodesta subsequently used analytics to put together the New York Mets club that played in the 2015 World Series.
Analytics in sports generally refers to the application of inferential statistics to data in order to make sounder decisions about such critical matters as player acquisition and in-game tactics. It’s called sabermetrics in baseball and has been used for about 20 years. The Moneyball movie and media reports about it tend to leave the erroneous impression that sports analytics was pioneered in Major League Baseball.
On the contrary, analytics emerged long before in American horse racing. Andrew Beyer was one of the innovators some 45 years ago with his Beyer Speed Figures, and “Beyers” in 1992 became a staple of the past performances published in the Daily Racing Form.
In the early 1970s, the late Richard Broadbent founded Bloodstock Research Information Services to craft software for broodmare owners to employ in identifying the most promising stallion alternatives. The venture eventually branched out into the handicapping analytics business known as Brisnet.
Horse racing, like baseball, was a natural for analytics because of the meticulously documented and mammoth statistical history of the sport.
The increased affordability of personal computers for the masses in the 1980s and 1990s led to the development of sophisticated but inexpensive software programs for handicapping. Today, for instance, well-known proprietary software offerings by Equibase and the Daily Racing Form enable handicappers to experiment with personalized analytic models. Thoro-Graph, another analytics-based handicapping tool, has also been employed successfully by some racehorse owners and trainers to pinpoint horses to buy.
Biometric techniques for selecting unraced Thoroughbreds are yet another type of analytics. Techniques, for example, that measure cardio efficiency and assess motion flow fall into this genre.
While analytics are pervasive in a growing number of sports, they are widely misunderstood, perhaps because analytics may seem to the public like the product of a black box wherein unsystematic data are inputted and profound insights are said to materialize.
Properly used, analytics reveal statistically recurring relationships that can be capitalized on by decision makers. However, they are not meant to substitute for human judgment, whether it concerns what pitcher to trade for, what play to call on third and goal at the 2-yard line, or which horse to bet on, breed to, or buy.
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