The Science of a Horse Race

A horse race is a sport in which humans perched on their backs compel animals — usually geldings — to sprint at breakneck speeds. Behind this romanticized facade lies a world of drug abuse, injuries and, all too often, death. The sport is dangerous for spectators, too. Many come to the track to show off their fancy outfits and sip mint juleps, unaware that horses are running for their lives.

Spectators cheer for the horses, but in the end, it’s all about winning money. That’s why horse races have a long history of rigged rules, cronyism and corruption. And even after the Santa Anita Park disaster, despite dozens of new rules to make the sport safer, there’s still an element of crookedness in horse racing.

A century ago, the sport evolved from private bets to a pari-mutuel system in which those who place bets on horses that finish first, second and third share a pool of money minus a small percentage for the track management. It’s a system that makes the game more accessible to people without wealthy benefactors, but critics argue it also increases the incentive for horse owners to push their animals beyond their limits in the name of winning a prize money.

The sport was born in ancient Greece, where it was a common event at festivals and on holidays. Later, it spread to Rome and other ancient civilizations, as well as throughout Europe and the Americas.

It wasn’t until the 20th century, however, that it came to the United States and grew into the multibillion-dollar industry it is today. A number of factors contribute to this growth, including a proliferation of horse racing tracks and the invention of the pari-mutuel betting system. But perhaps the most significant factor is the development of the scientific method in horse racing.

Scientists have discovered that certain variables can predict how a horse will perform in a race. They call these variables “key factors.” These key factors include a horse’s physical condition (like its heart rate and the temperature of the track), its mental state (such as how nervous it is) and its genetic makeup (like the genes that determine whether it will be fast or slow).

A few years ago, Ben Benter, a computational scientist working at IBM, set out to develop a model that could detect a winning horse. He had to pay close attention to everything that happened on the course: a horse’s position in the pack, its energy levels and the way the track changed with the wind. To find out how to predict the winner, he needed all of this information. And he needed a lot of data, because only then would he be able to make the right adjustments to his algorithm. Eventually, his model was able to correctly predict the winners of more than 50 percent of all races. But the algorithm wasn’t foolproof.