Analysis of horse performance at the Snaffle Bit Futurity

Abstract

The cow horse industry has experienced an increasing growth in both numbers and prize money over the years. This raises several questions related to industry trends to the center of attention of horse owners and other industry stakeholders. There is a growing interest in examining the trends to understand what trainers are continually at the top, what sires are producing quality offspring, and what breeders have an impact on the horse making it to the top. The breeders are interested to learn whether there are optimal breeding techniques and particular lines that can optimize the chance of winning and maximize the return on investment. Some observable trends include million-dollar riders repeatably making it to the finals, million-dollar sires producing offspring who continually score high, and a trend in the gender of horses that make it to the finals. The objective of this thesis is to generate insights into the potential effect of factors such as trainers, sires, gender, and linebreeding may have on producing a constant top performer through the analysis of trends in the Snaffle Bit Futurity Finalists data set. The literature uncovered that there are trends in other industries with linebreeding to produce certain qualities and traits. There are remaining questions such as what else might influence a high performing horse besides genetics. The data that was used in this study consisted of 570 horses who have made the Snaffle Bit Futurity Finals from 1970 – present. The data that was captured consisted of riders, owners, breeders, year shown, score, linebreeding, and gender. A regression analysis was used to estimate the significance of these factors on the overall population. The results of this study uncovered that although the descriptive statistics show trends there are no statistically significant effects detected in the results of regression analysis. The top descriptive results showed that linebreeding is heavily used within this industry when looking at the first four generations. Additionally, over the years certain million-dollar riders and stallions repeatably make it to the finals. Lastly, there was also a common trend on the owners who made it to the finals. While the trends that were found in the descriptive statistics indicated potential relationships, the results of regression analysis did not indicate statistically significant relationships. Given the limited scope of the data and the analysis, this study was unable to identify and uncover specific factors that can have a significant effect on a horse becoming a top scoring finalist. One important limiting factor is the inability to capture the extent to which genetic factors and line breeding may affect the chances of success. Further studies should investigate how the percent of linebreeding affects the overall score of the finalist.