Hartpury University Repository

Clark, C. C. T.

Barnes, Claire M.

Swindell, Nils J.

Holton, Mark D.

Bingham, Daniel D.

Collings, Paul J.

Barber, Sally E.

Summers, Huw D.

Mackintosh, Kelly A.

Stratton, Gareth

English

Profiling Movement and Gait Quality Characteristics in Pre-School Children

Smith, Laura J.

Tabor, Gillian

Williams, Jane

A retrospective case control study to investigate race level risk factors associated with horse falls in Irish Point to Point races

Marlin, David

1 
 
EQUINE ENDURANCE RACE PACING STRATEGY AND PERFORMANCE IN 1 
120km SINGLE-DAY RACES 2 
 3 
David Marlin*, Cambridge, UK dm@davidmarlin.co.uk 4 
Jane Williams, University Centre Hartpury, Hartpury, Gloucestershire, UK 5 
 6 
 7 
 Corresponding author.  8 
2 
 
Abstract 9 
Race pace strategy has been extensively studied in human sports such as running, cycling and 10 
swimming. In contrast, pacing strategy appears to have been virtually ignored in equestrian sport 11 
despite its potential to contribute to performance optimisation. Previously we have demonstrated that 12 
there are significant differences in pacing strategy between finishers and non-finishers in 120km 13 
single day endurance races [1]. The aim of the present study was to further analyse the same dataset of 14 
electronically-timed FEI 120km (single day) CEI** endurance races that took place in Europe and the 15 
Middle East in 2016 and 2017. The competition records of 218 horses that finished (average 16 
completion rate 56%) in 24 races, each consisting of 4 loops (laps) were evaluated.  Final loop speed 17 
was significantly increased for horses placed in the top three who recorded 12% faster mean speed 18 
(P=0.011) compared to horses that finished outside of the top 3. Top 3 finishing horses also 19 
significantly increase the speed they complete loop 3 (p= 0.040; 3% increase in percentage of loop 1 20 
speed) and the final loop (p=0.008; 8% increase in percentage of loop 1 speed) of races compared to 21 
horses who achieve lower placings and completed loop 1 at a 3% lower percentage of their average 22 
race speed (p=0.008) compared to those who finished 4th or higher.  These results suggest that horses 23 
that are placed in the top 3 are ridden more consistently.  24 
 25 
Word Count:  26 
Keywords: competition; equestrian; completion; failure  27 
3 
 
Introduction 28 
On a global basis, equine endurance racing is the second largest Federation Equestre Internationale 29 
(FEI) discipline behind show-jumping [2]. The main distances at which high level competition takes 30 
place are 120km and 160km. Horses and riders compete at these distances in a single day. The races 31 
are broken down into 4-6 loops or laps, with mandatory veterinary inspections for fitness to continue 32 
and hold times ranging from 30-40 min between each loop.  33 
Pacing strategy has been extensively studied in a number of sports, including marathon running, 34 
cycling and long distance swimming and a number of pacing-related factors associated with 35 
performance have been identified [e.g. 3 to 12]. The contribution of pacing strategy in equestrian 36 
sport has received virtually no attention other the study by Spence et al. [13] who found that better 37 
performing horses exhibited “race length-dependent pacing strategies” which were “correlated with 38 
the fastest racing times”.  39 
We [1] recently reported that in horses racing over 120km in a single day: those horses that 40 
successfully finished recorded 7% slower average speeds; horses withdrawn at the first veterinary 41 
check for “gait” recorded a 36% faster average speed than those withdrawn at the finish; horses 42 
withdrawn for “metabolic” reasons between loops 2 and 3 reduced their speed by an average of 17% 43 
on the final loop. Overall, horses that failed to finish races appeared to be ridden with a more 44 
aggressive race strategy than those which completed. In contrast, horses that finished had a slower 45 
loop 1 pace but went on to complete subsequent loops at a higher percentage of their loop 1 speed.  46 
The aim of the present study was to re-examine the data from the horses that completed (n=218, 56% 47 
of starters) with a view to trying to understand if pacing strategy influenced finishing position.  48 
 49 
Materials and Methods 50 
Retrospective competition records for 24, 120km FEI CEI** level single-day global endurance races 51 
that took place in the 2016 and 2017 seasons were collated to compare speed related variables 52 
between horses that achieved a placing of 1st, 2nd or 3rd in races. All races operated a fully automated 53 
electronic timing and had a results service provided by Endurance Team Styria (Hahnhofweg 30, 54 
8075 Graz, Austria); an FEI approved timing and results service provider. Races took place in Europe 55 
(n=15) or the Middle East (n=9). For each 120km race listed in the online archive, the data were 56 
downloaded as a PDF file and converted into a Microsoft Excel spreadsheet. For each horse that 57 
started and completed the race, average speed per loop (lap, km/h) and average speed for the entirety 58 
of the race were recorded. This enabled individual horses’ racing strategy to be calculated.  A strategy 59 
marker was calculated by dividing the average speed for sequential loops of the course by the average 60 
speed of the horse during loop 1, and multiplying this by 100% to give a percentage marker for each 61 
4 
 
subsequent loop completed relative to loop 1. The significance of the pacing strategy deployed by 62 
horses for loop 1 was also evaluated by dividing the average speed for loop 1 by the average speed for 63 
the duration of the race, and multiplying this by 100%. This information was used to evaluate how 64 
riders used speed strategically throughout the course of a race. 65 
A series of Mann Whitney U analyses identified if significant differences existed between loop speeds 66 
and average speed, and the strategy deployed within horses that placed in the top three compared to 67 
horses that completed outside of the top three ranks.  Subsequent Kruskal-Wallis tests investigated if 68 
differences in speed and the strategic approach applied in the race occurred between horses placed 69 
first, second and third in FEI CC** single-day 120km races. Significance was set at P<0.05.  70 
 71 
Results 72 
Competition records for 218 horses (56%) that successfully completed the 24 races surveyed were 73 
evaluated; the remaining 44% (n=171) were eliminated.  Thirty-three percent (n=72) of horses 74 
finished races with a top three placing (1st, 2nd or 3rd), with the remaining 67% (n=146) successfully 75 
completing the races outside of these ranks (range: 4th to 21st place).  76 
 77 
Race speed  78 
Loop speed decreased sequentially throughout races from loop 1> loop 2> loop 3 but then increased 79 
for the final loop (Figure 1). Horses that went on to achieve a top three ranking completed all loops at 80 
a higher average speed than those that finished in the lower rankings, recording a 5% faster average 81 
speed across the entire race (Table 1). Despite this, no significant differences in speed were found for 82 
loops 1, 2 or 3 (P>0.05), although final loop speed was significantly increased for horses placed in the 83 
top three who recorded 12% faster mean speed (P=0.011) compared to the other finishers.  Variation 84 
in speed on each loop (%CV, Table 1) was always lower in top 3 placed horses, with the exception of 85 
loop 3. In both groups the greatest variation in speed was on the final loop (Top 3 31%; Other 86 
placings 41%).  87 
5 
 
 88 
Figure 1: Differences in speed profiles (mean±sd) between endurance horses which successfully 89 
completed races with a top three finish and horses which completed outside of the top three places; 90 
km/h: kilometres per hour; sd: standard deviation. 91 
 92 
Table 1: Race speed profiles for horses that placed in the top three positions and those that completed 93 
but outside of the top three placings to 2 decimal places; km/h: kilometres per hour; sd: standard 94 
deviation; IQR: interquartile range; %CV: coefficient of variation.   95 
 
Loop1  
km/h (%CV) 
Loop 2  
km/h (%CV) 
Loop 3  
km/h (%CV) 
Final Loop 
km/h (%CV) 
Average 
whole 
course 
km/h (%CV) 
Horses 
with a top 
3 placing 
mean±sd 
 
19.9±4.4 
(22%) 
 
19.4±3.8 
(20%) 
 
19.0±4.4 
(23%) 
 
20.7±6.5 
(31%) 
 
19.5±4.4 
(23%) 
median±IQR 
 
18.7±7.4 
 
18.8±5.7 
 
17.9±7.2 
 
20.2±11.0 
 
18.0±7.6 
Horses 
placed 
outside the 
top 3 
mean±sd 
 
19.4±3.9 
(35%) 
 
18.7±3.4 
(30%) 
 
18.0±3.6 
(20%) 
 
18.3±4.7 
(41%) 
 
18.5±3.5 
(35%) 
median±IQR 
 
19.3±6.7 
 
18.6±5.5 
 
17.7±5.1 
 
17.7±7.3 
 
18.1±6.3 
      
      
 96 
 97 
10
12
14
16
18
20
22
24
26
28
Loop 1 Loop 2 Loop 3 Final Loop
Sp
ee
d
 k
m
/h
Average speed (km/h)
Top 3 ranked horses Horses ranked outside of the top three placings
6 
 
Race strategy 98 
Horses that successfully finished 120km CEI ** races appeared to adopt a similar pacing strategy, 99 
however those that go on to attain a top three finishing position maintain a faster average racing speed 100 
(as a % of their Loop 1 speed) throughout the duration of the race (Figure 2; Table 2). These better 101 
performing horses also complete loop 3 faster (p= 0.040; 3% increase in percentage of loop 1 speed) 102 
and the final loop faster (p=0.008; 8% increase in percentage of loop 1 speed) compared with horses 103 
who achieve lower placings.  Additional differences in pacing strategies were also apparent in the 104 
earlier stages of races. Top 3 finishing horses reduced the speed they completed loops 2 and 3 (1.4% 105 
and 3% reduction in percentage of loop 1 speed, respectively) approximately 50% less on the first 106 
loop and 25% less on loops 2 and 3, than their less successful competitors (3% and 4% reduction in 107 
percentage of loop 1 speed, respectively). On the final loop, 57% of top 3 placed horses completed 108 
faster than their loop 1 speed compared with 47% of lower placed horses. In comparison, on the final 109 
loop only 9% of top 3 placed horses completed at <75% of their loop 1 speed compared with 18% of 110 
lower placed horses. The greatest variation in speed as a % of loop 1 speed was seen in both groups 111 
on the final loop.  112 
     
The significance of the pacing strategy deployed for loop 1 was also investigated; horses which 113 
achieved a top 3 rank completed loop 1 at a 3% lower percentage of their average race speed 114 
(p=0.008) compared to those who finished 4th or higher, suggesting consistency is a more successful 115 
strategy to enhance performance in CEI** endurance races.  116 
 117 
 118 
 119 
Figure 2: Differences in strategic profiles between endurance horses which finished in the top 3 and 120 
horses finished outside the top 3; %: percentage of loop 1 mean speed selected loop completed at; L1: 121 
Loop 1; L2; Loop 2; L3: Loop 3: Finish: final loop. 122 
70
80
90
100
110
120
130
Loop 1 Loop 2 Loop 3 Final Loop
P
er
ce
n
ta
ge
 o
f 
lo
o
p
 1
 s
p
ee
d
Strategy per loop
Top 3 ranked horses Horses ranked outside of the top three placings
7 
 
 123 
Table 2: Race strategy profiles (mean±sd) for horses that finished in the top three compared to those 124 
completing outside of the top three places; %: percentage of loop 1 speed selected loop completed at.   125 
 126 
 127 
 
Loop1  
% 
Loop 2  
% 
Loop 3  
% 
Final Loop 
% 
Average 
whole course 
% 
Horses 
with a top 
3 placing 
mean±sd 
 
100±0.0 
 
98.6±7.5 
 
96.1±9.6 
 
103.9±22.2 
 
102.2±8.0 
median±IQR 
 
100±0.0 
 
98.3±9.5 
 
98.4±10.4 
 
104.9±26.9 
 
100.2±8.4 
Horses 
placed 
outside the 
top 3 
mean±sd 
 
100±0.0 
 
97.1±7.4 
 
93.3±10.5 
 
94.8±18.7 
 
105.0±8.5 
median±IQR 
 
100±0.0 
 
97.2±9.0 
 
95.3±11.9 
 
98.5±23.7 
 
102.9±8.3 
 128 
Discussion and conclusions 129 
Within endurance races, riders must continuously adapt and maintain the horse’s gait and speed to 130 
optimise performance [14]; in effect applying a pacing strategy.  We have previously reported that 131 
competitors in FEI CEI** 120km single day races who applied consistent pacing strategies delivering 132 
sustainable speeds were less likely to be eliminated [1]. Analysis of race finishers further suggests that 133 
pacing strategy influences competitive success. Similar patterns in race completion were observed for 134 
both groups of finishers investigated, with a sequential decrease in speed from loop 1 through to loop 135 
3, followed by an increase in speed for the final loop. The average speed of the horses who recorded a 136 
top three rank in races was consistently higher than the other combinations who completed the races. 137 
Differences in race pacing strategy also occurred between the groups; top three horses completed 138 
loops 1 to 3 at a more consistent pace (5% variation from loop 1 speed) compared to horses placed 139 
fourth and above (7% variation from loop 1 speed). Interestingly, although both groups increased their 140 
speed during the final loop, the top three ranked horses recorded speeds which were higher than what 141 
they had used for loop 1(>100%) whilst the lower ranked horses did not attain their loop 1 speed 142 
(95%). The pacing strategy adopted for loop 3 and the final loop appear to be significant in predicting 143 
which horses are more likely to achieve success, with superior performers able to complete these at a 144 
higher percentage of loop 1 speed than their peers.  145 
8 
 
Our results suggest that combinations who adopt a higher average speed throughout races but manage 146 
this through a more consistent pacing strategy are more likely to achieve a top 3 rank in FEI CEI** 147 
120km single day races. The association between performance and higher average race speed 148 
identified here reinforces the importance of appropriate preparation and training to ensure endurance 149 
horses possess suitable fitness levels to meet the demands of competition. The use of appropriate 150 
pacing strategies during racing is also key to maintain optimal performance during racing. Consistent 151 
pacing strategies for loops of the track are associated with superior performance in human athletes 152 
competing in endurance running [7 -9]. Our results suggest adopting a similar approach could 153 
optimise the performance of combinations in endurance racing. Endurance trainers and riders should 154 
also consider how the training regimens implemented are preparing horses for races. Regular 155 
monitoring of fitness parameters, such as heart rate, evaluation of speed and pacing work are 156 
recommended to ensure horses are suitably prepared for races and to support the application of pacing 157 
strategies during competition [1]. Furthermore, it appears that for many horses that fail to complete, 158 
this may be due to riding too fast on the first loop for the horses ability and level of fitness. Use of 159 
heart rate monitors in training to establish the heart rate and velocity relationship or use in races could 160 
reduce eliminations and help identify optimal race strategy. Further studies investigating how pacing 161 
strategies are used across different levels of competition and to identify optimal pacing strategies to 162 
enhance performance in endurance racing are warranted.  163 
 164 
Conflicts of interest: none 165 
Funding: This research did not receive any specific grant from funding agencies in the public, 166 
commercial, or not-for-profit sectors.  167 
9 
 
References 168 
[1] Marlin, D., Williams, J.M. Equine endurance race pacing strategy differs between finishers and 169 
non-finishers in 120km single-day races. Comp Exerc Physio 2017; in press. 170 
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[2] Fédération Equeste Internationale (FEI) Annual Report, 2015. Available from: 172 
http://inside.fei.org/fei/about-fei/publications/fei-annual-report/2015/  173 
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[3] Abbiss, C.R., Laursen, P.B., Models to explain fatigue during prolonged endurance cycling. Sports 175 
Med 2005; 35(10): 865-898. 176 
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[4] Hanley. B. Pacing profiles and pack running at the IAAF World Half Marathon Championships. J 178 
Sports Sci 2015; 33(11):1189-95. 179 
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[5] Santos-Lozano, A., Collado, P.S., Foster, C., Lucia, A., Garatachea, N. Influence of sex and level 181 
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