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Scoring analysis of completing pre-novice event horses at six selected events

Published online by Cambridge University Press:  09 March 2007

TC Whitaker ,
J Hill  and
JP Shearman
TC Whitaker*
Affiliation:
Faculty of Applied Science and Technology, Writtle College, Chelmsford CM1 3RR, UK
J Hill
Affiliation:
Faculty of Applied Science and Technology, Writtle College, Chelmsford CM1 3RR, UK
JP Shearman
Affiliation:
Department of Biological Sciences, University of Essex, Colchester, UK
*
*tcw@writtle.ac.uk
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Abstract

This study examined how horse age and gender, rider gender and individual event affected the performance of horses competing at six selected pre-novice events. Dressage accounted for 63% of penalties accumulated whilst 27.9% of penalties were from the cross-country phase and 9.1% from the show jumping phase. The data highlighted differences in the distribution of penalties between events. Male riders scored 4.5 penalties (P<0.001) less than female riders for cross-country jumping. Mares and geldings showed a very small variation (0.8 penalties) in final mean score for competition; however, stallions' mean score was 12.2 points (P<0.01) lower than mares' and 11.4 points (P<0.001) lower than geldings'. Seven-year-olds scored the fewest mean final penalty points when compared with all other age groups (P<0.001). The strongest correlations were between dressage penalty score and final placing at event, r=0.911 (P<0.01), whilst the weakest was observed between cross-country penalties and final penalty score, r=0.091 (P<0.01). It can be concluded that environmental factors exert a significant influence upon scoring at the pre-novice eventing level, both within phases of competition and over the whole competition.

Keywords

pre-noviceeventingperformance analysisenvironment
Type
Research Article
Information
Equine and Comparative Exercise Physiology , Volume 1 , Issue 3 , August 2004 , pp. 185 - 192
Copyright
Copyright © Cambridge University Press 2004

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References

1Deuel, NR and Russek-Cohen, E (1995). Scoring analysis of three World Championship three-day events. Journal of Equine Veterinary Science 15, 11.CrossRefGoogle Scholar
2British Eventing, (2001). 2001 British Eventing Rules Stoneleigh, UK: British Eventing.Google Scholar
3British Eventing, (2001). British Eventing Bulletin & Omnibus Schedule Autumn 2001. Stoneleigh, UK: British Eventing.Google Scholar
4 Burghley Direct Web Page (2001). Event Results [online]. Available at http://www.bdwp.co.uk (accessed 4 August 2001).Google Scholar
5Gardiner, WP (1997). Statistics for the Biosciences. Hemel Hempstead, UK: Prentice Hall Europe.Google Scholar
6Zar, JH (1999). Biostatistical Analysis, New Jersey, Prentice Hall, Inc.Google Scholar
7Pearson, K (1920). Historical notes on the history of correlations. Biometrika 13, 25–45.CrossRefGoogle Scholar
8Langlois, B (1975). Analyse statisique des gains des pur sang de trios ans dans les courses plates françaises. Annales de Génétique et de Sélection Animale 7, 387–408.CrossRefGoogle Scholar
9Arnason, T, Darenius, A and Philipsson, J (1982). Genetic selection indices for Swedish trotter broodmares. Livestock Production Science 8, 557–565.CrossRefGoogle Scholar
10Silvestrelli, M, Pieramati, C, Cavalucci, C, and Bonanzinga, M (1995). The current breeding plans for the saddle horse, trotter and thoroughbred in Italy. Paper presented at the 46th Annual Meeting of the European Association for Animal Production,Prague, Czech Republic,4–7 September.Google Scholar
11Bartlett, MS (1947). The use of transformations. Biometric 3, 39–52.CrossRefGoogle ScholarPubMed
12Thöni, H (1967). Transformation of Variables Used in the Analysis of Experimental and Observational Data. A Review. Technical Report No. 7, Ames, IA: Statistical Laboratory, Iowa State University.Google Scholar
13Little, RJA and Rubin, DB (1987). Statistical Analysis with Missing Data. New York: Wiley.Google Scholar
14Bruns, E, Schober, M, and Fredricson, I (2001). Interstallion – a cross-country evaluation of testing methods and data availability/suitability. Paper presented at the 52nd Annual Meeting of the European Association for Animal ProductionBudapest, Hungary,26–29 August.Google Scholar
15Birrell, S and Theberge, N (1989). Ideological control of women in sport. In: Birrell, S & Cole, CL (eds), Women, Sports and Culture. Champaign, IL: Human Kinetics, pp. 241–359.Google Scholar
16Bennett, RS, Whitaker, KG, Wooley Smith, NJ and Sablove, A (1987). Changing the rules of the game: reflections toward a feminist analysis of sport. Women Studies International Forum 10, 369–379.CrossRefGoogle Scholar
17Aldridge, LI, Kelleher, DL, Reilly, M and Brophy, PO (2000). Estimation of the genetic correlation between performances at different levels of show jumping competitions in Ireland. Journal of Animal Breeding and Genetics 117, 65–72.CrossRefGoogle Scholar
18 British Horse Trials Association/Federation Equestre Internationale (2000). The International Eventing Safety Committee Report, April 2000 [online]. Available at http:// www.horsesport.org (accessed 18 October 2001).Google Scholar