Eventing competitions in Great Britain (GB) comprise three disciplines, each split into four grades, yielding 12 discipline-grade traits. As there is a demand for tools to estimate (co)variance matrices with a large number of traits, the aim of this work was to investigate different methods to produce large (co)variance matrices using GB eventing data. Data from 1999 to 2008 were used and penalty points were converted to normal scores. A sire model was utilised to estimate fixed effects of gender, age and class, and random effects of sire, horse and rider. Three methods were used to estimate (co)variance matrices. Method 1 used a method based on Gibbs sampling and data augmentation and imputation. Methods 2a and 2b combined sub-matrices from bivariate analyses; one took samples from a multivariate Normal distribution defined by the covariance matrix from each bivariate analysis, then analysed these data in a 12-trait multivariate analysis; the other replaced negative eigenvalues in the matrix with positive values to obtain a positive definite (co)variance matrix. A formal comparison of models could not be conducted; however, estimates from all methods, particularly Methods 2a/2b, were in reasonable agreement. The computational requirements of Method 1 were much less compared with Methods 2a or 2b. Method 2a heritability estimates were as follows: for dressage 7.2% to 9.0%, for show jumping 8.9% to 16.2% and for cross-country 1.3% to 1.4%. Method 1 heritability estimates were higher for the advanced grades, particularly for dressage (17.1%) and show jumping (22.6%). Irrespective of the model, genetic correlations between grades, for dressage and show jumping, were positive, high and significant, ranging from 0.59 to 0.99 for Method 2a and 0.78 to 0.95 for Method 1. For cross-country, using Method 2a, genetic correlations were only significant between novice and pre-novice (0.75); however, using Method 1 estimates were all significant and low to moderate (0.36 to 0.70). Between-discipline correlations were all low and of mixed sign. All methods produced positive definite 12 × 12 (co)variance matrices, suitable for the prediction of breeding values. Method 1 benefits from much reduced computational requirements, and by performing a true multivariate analysis.

Few studies exist regarding the physiological responses of equestrian riders during actual or simulated competition. Interest has proliferated in recent years on the responses of riders, which is mainly due to the fatal tragedies that occurred in eventing in the late 1990s. More emphasis is also being placed on the importance of riders, fitness in order to improve athletic performance at the international level. The aim of the present study was to investigate the fitness and exercise capacity of female equestrian athletes, and to relate this to the metabolic requirements of dressage (DR), showjumping (SJ) and cross-country (XC) phases of the one-day event. Sixteen female collegiate riders (age = 24.5 ± 7.7 years; height = 166.6 ± 3.8 cm; weight = 60.4 ± 6.0 kg) competed in a simulated Horse Trials Pre-Novice competition riding either their own horse or one familiar to them. Anthropometric data were obtained for each rider (body mass index (BMI) = 21.7 ± 1.9; % body fat (BF) = 23.4 ± 5.3; lean body mass (LBM) = 48.5 ± 3.6). Each subject successfully completed all three phases of the event. There was a progressive increase in oxygen consumption (VO2) during the three phases (DR, SJ and XC) from a mean value of 20.4 ± 4.0 ml kg− 1 min− 1 (DR), 28.1 ± 4.2 ml kg− 1 min− 1 (SJ) to 31.2 ± 6.6 ml kg− 1 min− 1 (XC) (P < 0.001). Heart rate data showed a similar trend from a mean value of 157 ± 15 beats min− 1 (DR), 180 ± 11 beats min− 1 (SJ) to 184 ± 11 beats min− 1 (XC) (P < 0.001). Mean lactate concentration increased progressively from resting values: rest 2.5 ± 1.3 mmol, DR 4.8 ± 1.8 mmol, SJ 7.8 ± 2.4 mmol and XC 9.5 ± 2.7 mmol (P < 0.001). Urine osmolality was significantly (P < 0.001) increased from a pre-competition mean of 0.488 ± 0.270 mOsmol l− 1 to a post-competition mean of 0.684 ± 0.230 mOsmol l− 1. Mean hand grip strength was observed to decrease significantly (P < 0.01) from a pre-value of 32.3 ± 6.3 kg to a post-value of 29.8 ± 5.5 kg. Mean weight loss pre- to post-competition was 1.6 ± 1.1% body weight (P < 0.01). In conclusion, the study emphasises the variability in metabolic cost between riders performing in the same simulated competition but riding different horses, and highlights the difference in metabolic demand between the different phases.

The study undertook comparative analysis of horse gender and eventing performance. Limited previous research has investigated the impact horse gender may have on performance. However, many competitors have a preference for one gender over another (normally geldings). The study sampled five levels of the sport (intro, pre-novice, novice, intermediate and advanced) and investigated dependent variable penalty scores within the dressage, show jumping and cross-country phases; additionally, final penalty score, rank in competition and lifetime score were analysed. Results indicated the effect of gender to be limited. Issues relating to sample size, data structure and scoring mechanisms are discussed further.

Eventing is a three-phased discipline with a stratified progressive performance structure. Sample data (10%) were analysed from all horses competing within the UK (n = 53 890) during 2003 at all five levels of competition (intro, pre-novice, novice, intermediate, advanced). Five performance penalty score contributors were examined (dressage score, show jumping time faults, show jumping jump faults, cross-country jumping faults and cross-country time faults – independent variables) with regard to their effect on final ranking in competition (dependent variable). Percentage accruement of penalty points showed dressage to be the largest contributor (69%) at the intro level, falling to 53% at the advanced level. The show jumping phase was the smallest percentage contributor (greatest influence seen at the novice level, 9%). The influence of cross-country increased as the level of competition became more difficult (greatest at the advanced level, 42%). Linear regression analysis was undertaken with the use of a standardized linear model. The models accounted for between 75 and 83% of all variance dependent on level. Accession of data to the model was almost identical from novice level upwards, with cross-country time and dressage faults exerting the greatest influence. At the lower levels of competition a more complex picture of accession was observed. The use of regression analysis supported the stated sporting aims of eventings governing bodies.

Subjective bias by judges within the dressage phase of eventing competition is problematic if correct evaluation of horse and rider performance is to be undertaken. The present study examines dressage penalty scoring (penalty scores are awarded for completion of a pre-set series of dressage movements) within a population of novice event horses (n = 2471). Between May and June 2003, 22 novice events within the UK were analysed, and at each event up to six competitions or sections (at the same competitive level) were run. The whole population data structure was normal in distribution, Pearson's skewness 0.314 (Kolmogorov–Smirnov Z = 1.855, P>0.05 from zero) and kurtosis at 0.425. The mean score recorded for the whole population was 37.82 penalty points (standard deviation = 5.65 and standard error = 0.11). A number of effects were observed within the population. Between-events effects were observed in three of the 22 events studied (P<0.01). Of those events running three or more sections (n = 16), within-event effects were observed for 10 events as differences (P<0.01) in mean scoring patterns between sections. All events running two sections (n = 4) were observed to exhibit differences (P<0.02) in mean scores. Differences (P>0.01) between the dressage test used at events were determined using post hoc Bonferroni tests. However, these differences were not found to have a confounding effect on the between-event observations. The study indicates that additional methodologies need to be implemented to ensure that accurate and impartial evaluation of event horses is conducted.

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.

The objective of this experiment was to compare the physiological changes that occurred in horses competing in the cross-country portion of Training, Preliminary and Intermediate horse trials. The hypothesis was that temperature (T), heart rate (HR), respiratory rate (RR), and on-site acid–base and electrolyte monitoring would allow differentiation between difficulty levels in horse trials. Sixteen client-owned horses competing at the Trojan-Horse Spring Horse Trials in Cave Creek, Arizona, USA, were studied. T, HR, RR and anaerobic lithium-heparinized jugular venous samples were obtained before, and 1–2 min after, cross-country exercise. Samples were analysed for blood gases (body temperature-corrected) and concentrations of sodium ([Na+]), potassium ([K+]), chloride ([Cl−]), ionized calcium ([Ca2+]i), blood urea nitrogen ([BUN]) and glucose ([GLC]) using a point-of-care analyser. Results were compared using analysis of variance with the level of significance set at P<0.05. In all groups, exercise increased T, HR, RR, packed cell volume and haemoglobin concentration, and decreased partial pressure of CO2 (PCO2), [total CO2 concentration], bicarbonate concentration ([HCO3−]) and [Ca2+]i (P<0.05). Post-exercise RR was higher, and pH, PCO2, [tCO2], [HCO3−] and base excess were lower, in Intermediate and sometimes Preliminary horses compared with Training horses (P<0.05). It was concluded that horse trials caused milder, but otherwise similar, physical, blood gas and electrolyte changes to those observed in complete three-day events. Physical and point-of-care plasma acid–base and electrolyte monitoring allowed differentiation between horses competing at various levels of difficulty in a horse trial.