For as long as there have been racehorses, trainers have leaned on pedigree to guide the big decisions. Bloodlines, sire records, the achievements of a dam’s earlier progeny, this is the language the industry has spoken for generations, and for good reason. But it has always described a horse’s potential rather than its reality. It tells you the family a horse comes from, not necessarily the athlete standing in front of you.
Today, genomics is beginning to fill that gap, adding a new layer of understanding that reveals what’s happening beneath the surface of each individual horse.
At the centre of this shift is the Zinto Labs Equinome genomics test, helping some of the sport’s leading racing teams understand how each horse is genuinely built to perform. Rather than replacing the trainer’s eye, it sharpens it, putting hard data behind instincts that were previously a matter of experience and feel.
The insights span the things trainers care about most: how a horse’s muscle is likely to develop, the race distances it’s naturally suited to, and the rate at which it’s likely to progress and mature. Taken together, that picture helps teams make smarter, better-timed decisions about training and placement, knowing when to push, when to wait, and where a horse is most likely to be competitive.
It’s the difference between managing a horse on assumption and managing it on evidence.
For renowned trainer Ciaron Maher, that evidence has become part of the everyday routine rather than a one-off curiosity. “It’s a test we refer to quite often,” he explains, describing how it “supports decisions throughout a horse’s training.” In an environment where small margins separate a place from a win, having an extra, objective reference point is something his team returns to again and again, not just early in a horse’s career, but as it develops and its programme evolves.
That confidence is echoed on the data side of the operation. Josh Kadlec-Cavanagh, Head of Data & Performance at Ciaron Maher Racing, is responsible for turning information into a competitive edge and he doesn’t hedge on the value of the genomic insight. “The results are undeniable for us on the track,” he says.
For a modern racing operation that treats performance as a discipline in its own right, that’s a meaningful endorsement. It reflects a wider change in how the best teams work: decisions increasingly grounded in measurable data, layered on top of the horsemanship that has always defined the sport.
The value of genomic data isn’t limited to a single stage of a horse’s life. Whether it’s identifying raw sprint power or mapping out a genuine endurance profile, the same underlying insight informs choices from the yearling paddock through to race day.
For breeders, that means the ability to make more confident matings and selections, understanding not just which horses come from fast families, but which individuals carry the traits that actually drive performance. For trainers, it means placing horses in the races that suit them and building programmes around how each animal is likely to mature. And for owners, it means decisions backed by something more solid than hope.
None of this displaces the craft at the heart of racing. Genomics doesn’t train a horse, and it doesn’t win a race. What it does is turn long-held assumptions into evidence, giving the people who make the decisions a clearer view of the athlete they’re working with.