Big data and the processing of predictive analytics has been used for more than 20 years in sports. The first notable instance of the two being used was when Billy Beane, then the general manager of the MLB’s Oakland A’s, used them to show how getting on base was more important than getting a home run or even what a particular player’s batting average was. That has, in part, led to the development of analytics becoming a major part of most sports, including horse races. The aggregation and assimilation of large amounts of data on jockeys, horses, tracks and more creates a more complete picture of a particular event and, in turn, helps sports gamblers make more intelligent decisions. Gaming industry executive and horseracing expert Adam Bjorn knows the importance of big data and analytics, and expects even greater reliance on them in horseracing moving forward.
In horseracing, one of the most popular data analysis platforms is Equibase, which was developed before Beane showed the power of mass data analytics. The Jockey Club collaborated with several thoroughbred racing associations to create the platform in 1990 and it now holds data on around 1.7 million races, as well as more than 14 million starts. In total, Equibase provides access to more than one billion separate elements that can, at some point, be accessed to make smarter bets.
Among the choices available to gamblers there is the success of the jockey, the diet of the horse, the weather during the race (as well as how the weather has affected horses at particular tracks in the past), the length of the track, the racing pattern of the horse and much more. It can also be used to interpret the diet of the horse and its mood, which will also impact how the horse runs on a particular day.
Equibase paved the way for other solutions to be offered, such as Trakus. This system uses a series of sensors and GPS trackers that are installed on the horse’s saddle, allowing for real-time updates on the horse and the track. Trakus includes a 3D graphical representation of the data produced, which makes it easier for the gambler to interpret all the data points for placing their wagers.
In addition, this information can also be used to provide updates to jockeys and trainers, allowing them to adjust their approach to the day’s conditioning and races.
Bjorn states, “With AI and machine learning starting to infiltrate the sports-betting and horse racing industry from the professional bettor’s aspect, the bookmakers are needing to begin investing much further into this, to compete and improve their overall offerings. On the horse racing side of the business this has been used for many years in finding value among the world totes as well as running race simulations to try and have as close as possible to the actual finishing order based on thousands and thousands of running the races and coming up with what each likely outcome is valued or predicted as. From the bookmaker’s side, it’s about using consumer patterns and their history of bets to combat this from the other side and have their odds moving dynamically in the right direction automatically as each bet is placed.”
Big data is also providing another, much-needed solution. The compiling of massive amounts of data and its subsequent interpretation leads to predictive modeling. Through this, trainers, owners and jockeys can understand their horses better and are more capable of determining when one of them might suffer an injury. While there will always be injuries in horse racing, just like there are in all sports, this capability should greatly reduce the number of injuries seen.
Horserace tracks are giving visitors new forms of engagement through big data, as well. As they interpret the data, the tracks are then able to provide instant specials or other promotional offerings based on previous behaviors. This increases the entertainment value of the race, as well as a larger percentage of sports gamblers looking for some additional excitement.