Equine Match Brings Thoroughbred AI Insights

We-Have-Seen-The-Future: The only certainties in the rapidly evolving world of Artificial Intelligence (AI) are uncertainty and a guaranteed disruption to all industries. That’s as, if not more, relevant to the thoroughbred sector due to its plethora of data. According to eirpresswire.com, Equine Match Ltd., based in Oxford, has launched a pioneering cloud-based software platform tailored for the global bloodstock industry, integrating advanced machine learning and AI. This innovation aims to revolutionise an industry historically reliant on human expertise for breeding and purchasing decisions. The platform delivers data-driven quantitative analysis, offering investors a proprietary predictive model alongside traditional qualitative assessments. Spencer Chapman, co-founder and an experienced owner-breeder, pointed out the platform's role in mitigating risks associated with traditional methods. By leveraging extensive proprietary data from over 60 countries spanning centuries, Equine Match generates predictive insights into performance, enhancing decision-making for breeders and buyers worldwide. Key products include the Sire Rating Index and Predictive Pedigree Rating, pioneering multi-variable predictors of racehorse career success by using advanced AI algorithms. Equine Match provides subscription-based access to its suite of tools, catering to global auction participants with options for stallion sponsorships and white-label services. Analysis by Equine Match reportedly found that “data from the Keeneland September Yearling Sale [1999-2022] reveals that top buyers consistently underperform relative to the sale average in terms of black-type performers, stakes winners and Graded winners per $1,000 spent. Surprisingly, the RNA [Reserve Not Attained] lots outperformed the sale average in all three categories, suggesting that horses that did not meet their reserve prices had a higher potential for success relative to their anticipated cost.” That is both provocative and revelatory. Watch this space.