A Comparison of the Performance of Horses from the International WBFSH Rankings in Dressage, Jumping and Eventing Based on Their Sex, Age, Proportion of Thoroughbred Genes and Affiliation to the Studbook.

Research Overview

• This study evaluates how factors such as sex, age, thoroughbred gene proportion, and studbook affiliation affect the performance of elite horses in dressage, jumping, and eventing disciplines.
• The research uses data from the World Breeding Federation for Sport Horses (WBFSH) Studbook Rankings from 2019 to 2024 to identify statistical patterns and influences on horse performance.

Research Objectives and Data Source

• Objective: To determine how sex, age, thoroughbred genetics, and studbook affiliation influence horse performance in three equestrian sports: dressage, jumping, and eventing.
• Data Source: WBFSH Studbook Rankings from 2019 to 2024, which rank top sport horses internationally based on competition results.

Key Factors Examined

• Studbook Affiliation: The breed registry or studbook to which the horse belongs.
• Sex of the Horse: Mare (female), gelding (castrated male), or stallion (intact male).
• Age of the Horse: The horse’s age at the time of competition.
• Proportion of Thoroughbred Genes: The percentage of thoroughbred ancestry present in the horse’s pedigree.

Findings on Studbook Affiliation

• Studbook affiliation emerged as the most influential factor across all three disciplines (dressage, jumping, eventing).
• Specifically, horses from the following studbooks consistently ranked among the best: Belgian Warmblood, German Sport Horse, Hanoverian, Royal Dutch Sport Horse, Oldenburg, and Westphalian.
• This indicates that certain breed registries maintain breeding programs or selection criteria highly effective for performance in multiple equestrian sports.

Findings on Sex of the Horse

• In jumping, geldings were statistically proven to outperform mares and stallions, suggesting they have competitive advantages for this discipline.
• In eventing, both geldings and stallions showed significantly better performance than mares, which could relate to behavioral, physical, or management factors related to sex.
• No specific sex-related performance outcomes were highlighted for dressage in the abstract.

Findings on Age

• Optimal performance age varies by discipline: 11 years old was the peak performance age in jumping competitions.
• In eventing, horses achieve their highest performance at 15 years old, indicating a later peak compared to jumping.
• This supports the idea that physiological and experience-related maturational effects differ between equestrian sports.

Findings on Thoroughbred Gene Proportion

• In dressage, horse performance was significantly influenced by the percentage of thoroughbred genes.
• Specifically, dressage horses with 20% to 50% thoroughbred genetics achieved better results, indicating a balanced mix of thoroughbred and warmblood traits may optimize dressage abilities.
• This finding reflects the importance of genetic composition tailored to the demands of specific disciplines.

Implications for Breeding and Selection

• The study confirms that selecting sport horses for elite competitions should be based on specialized performance criteria distinct for each equestrian discipline.
• Different breeding programs are necessary to optimize success in dressage, jumping, and eventing due to varying ideal traits such as age peaks and genetic makeup.
• Recognizing the effect of studbook affiliation highlights the importance of registry-specific breeding strategies and genetic resources in equine sports performance.
• Sex and age differences in performance emphasize that management and training programs should be tailored accordingly.

Summary

• This research provides statistically supported insights into how genetic background, physical characteristics, and management (through studbook influence) impact elite equine performance.
• By demonstrating distinct patterns for each discipline, the study aids breeders, trainers, and sport horse evaluators in making data-driven decisions to maximize athletic potential.