Preliminary Examination of the Biological and Industry Constraints on the Structure and Pattern of Thoroughbred Racing in New Zealand over Thirteen Seasons: 2005/06–2017/18

• Published in: Animals (Basel) Vol. 11; no. 10; p. 2807
• Main Authors: Legg, Kylie A., Gee, Erica K., Cochrane, Darryl J., Rogers, Chris W.
• Format: Journal Article
• Language: English
• Published: Basel MDPI AG 27.09.2021; MDPI
• Subjects: Age; Aging; Careers; Ecological models; Health risks; horse; Horse racing; Horses; injury; Injury prevention; Jurisdiction; Modelling; Racehorses; Races; racing; Risk analysis; Risk factors; Seasons; System dynamics; Thoroughbred; New Zealand
• DOI: 10.3390/ani11102807
• ISSN: 2076-2615

This study aimed to examine thirteen seasons of flat racing starts (n = 388,964) in the context of an ecological system and identify metrics that describe the inherent characteristics and constraints of the New Zealand Thoroughbred racing industry. During the thirteen years examined, there was a 2–3% per year reduction in the number of races, starts and number of horses. There was a significant shift in the racing population with a greater number of fillies (aged 2–4 years) having a race start, and subsequent longer racing careers due to the inclusion of one more racing preparation post 2008 (p < 0.05). Additionally, there was an increasingly ageing population of racehorses. These changes resulted in more race starts in a career, but possibly because of biological constraints, there was no change in the number of race starts per season, starts per preparation, or days spelling between preparations (p < 0.05). There was no change in the proportion of horses having just one race start (14% of new entrants), indicating that the screening for suitability for a racing career remained consistent. These data identify key industry parameters which provide a basis for future modelling of intervention strategies to improve economic performance and reduce horse injury. Consideration of the racing industry as a bio-economic or ecological model provides framework to test how the industry may respond to intervention strategies and signal where changes in system dynamics may alter existing risk factors for injury.