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35

CORRELATION BETWEEN DIFFERENT MOTOR ABILITIES 
AND SCORE POINTS IN THE RAUCH CUP

Špela BOGATAJ¹, Blaž LEŠNIK¹

¹University of Ljubljana, Faculty of Sport, Slovenia

Corresponding author: 
Špela BOGATAJ 

University of Ljubljana, Faculty of Sport, Slovenia 
Phone: +386 40 415 766 

e-mail: sspelabogataj@gmail.com

ABSTRACT

In alpine skiing, like in other sports, achieving good results depends on a vari-
ety of factors and the quality of planning and conducting the process of training. The 
purpose of the research was to determine whether there is a correlation between the 
selected motor tests and the number of points achieved in Rauch Cup. The research 
was conducted on a sample of 41 male competitors from different ski clubs across Slo-
venia. The following tests were conducted on our selected group of 13- to 14-year old 
males: taping with a dominant leg, test of stability, run from a flying start (maximum 
speed), ten jumps on both legs, 400-metre run, running nines, counter-movement jump 
and reaction time to a visual impulse (squat jump). The linear regression analysis was 
used to determine the relationship between the selected motor tests and performance in 
alpine skiing (Rauch Cup points). Correlation was found between each individual mo-
tor test and criterion variable (Rauch Cup points) except test of stability and reaction 
time test (squat jump). Multiple linear regression (MLR) showed us that the selected 
model, assembled of four tests that gave the highest MLR was significant (R = .727; p 
< .001). According to the findings, we can conclude that motor skills represent 53 % of 
the competitive performance variance of the alpine skier.

Keywords: alpine skiing, competition, motor functions, performance.

Original scientific article      UDC: 796.926:796.012.1
received: 2018-04-26



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POVEZAVA RAZLIČNIH MOTORIČNIH SPOSOBNOSTI Z 
DOSEŽENIMI TOČKAMI V RAUCH POKALU

IZVLEČEK

Pri alpskem smučanju je doseganje dobrih rezultatov, enako kot tudi pri drugih 
športnih disciplinah, odvisno od različnih dejavnikov in kakovosti načrtovanja ter iz-
vajanja trenažnega procesa. Namen naše raziskave je ugotoviti, ali obstaja korelacija 
med rezultati v izbranih motoričnih testih in številom doseženih točk v Rauch pokalu. 
V raziskavo smo vključili 41 moških tekmovalcev, starih od 13 do 14 let, iz različnih 
slovenskih smučarskih klubov. Izvedli smo sledeče teste: taping z dominantno nogo, test 
stabilnosti, tek z letečim štartom (maksimalna hitrost), deseteroskok sonožno, tek na 
400 metrov, osmice med devetimi keglji, skok z nasprotnim gibanjem in reakcijski čas 
na vizualni impulz (skok iz polčepa). S Pearsonovim koeficientom smo določili linearno 
razmerje med motoričnimi testi in kriterijsko spremenljivko (dosežene točke v Rauch 
pokalu). Regresijska analiza je bila uporabljena za določitev hipotetičnega vpliva celo-
tnega spektra izbranih motoričnih sposobnosti na uspešnost pri alpskem smučanju. Ko-
relacijska analiza med posameznimi testi in kriterijsko spremenljivko je pokazala, da 
vsi testi razen testa stabilnosti in reakcijskega časa na vizualni impulz, medsebojno ko-
relirajo. Multipla regresija nam je pokazala, da je regresijski model, sestavljen iz štirih 
izbranih spremenljivk, značilen (R = .727; p < .001). Glede na ugotovitve lahko trdimo, 
da motorične sposobnosti predstavljajo velik delež tekmovalne uspešnosti v alpskem 
smučanju, zato bi morali redno testiranje vključiti v program treninga in evalvacije. 

Ključne besede: alpsko smučanje, tekmovanje, motorika, tekmovalna uspešnost

INTRODUCTION

Good psychophysical preparation is one of the basic conditions for achieving good 
results at competitions. That is why this part requires extra attention in younger as 
well as in older categories of competitors. The potential of the psychosomatic status of 
an alpine skiing competitor depends on the development of their motor skills, which 
also represents a basic guideline for designing a training process with content that is 
as closely as possible related to the quality of movement in alpine skiing. Depending 
on this, we need to define a method to help us monitoring positive or negative changes 
which result from both the content and intensity of the training process (Šturm, 2012). 
Coaches should perform regular tests of their athletes aiming to obtain valid results for 
efficient and healthy athlete’s development and health (Ušaj, 2003). 

Alpine skiing is a complex sport discipline which requires basic muscular power, 
aerobic and anaerobic abilities as well as a wide movement program of specific motor 



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Špela BOGATAJ, Blaž LEŠNIK: CORRELATION BETWEEN DIFFERENT MOTOR ABILITIES AND SCORE POINTS ...,  35–44

abilities. The contribution level of each factor depends on the competition demands in 
which the athlete takes part. Some sports, like swimming or track, are performed in a 
controlled environment and there the demands of competition can be quantified quite 
easily. On the other hand, sports like alpine skiing or football are exposed to various 
external influences and an athlete must often adapt to them in the middle of their per-
formance (Heikkinen, 2003).

If we want to develop an appropriate battery of tests for alpine skiers, we need to 
understand which muscles are used during a competition and in what way (the type 
of contraction). During these tests, the athletes need to stimulate those muscles in the 
same way as they do at the competition. Hintermeister et al. (1995) conducted research 
involving elite skiers and found out that their lower body and torso musculature was 
heavily activated during the alpine skiing movements. Throughout a turn, adductors 
and some other muscles were working almost continuously at over 100 % of maximum 
voluntary rate of contraction. Brown and Wilkinson (1983) state that alpine skiers have, 
in comparison with untrained general population, lower body fat and that their body 
composition is similar to weight lifters’ and swimmers’. A study conducted by Haymes 
& Dickinson (1980) documented that alpine skiers have high ranking of isokinetic leg 
strength. The conclusion from these results suggests that lower body strength is an 
important predictor of a successful alpine ski competitor. This can help us conduct a 
proper battery of tests for alpine skiers. 

There is not a lot of research done with younger populations in alpine skiing corre-
lating competition performance and field or laboratory tests. Mladenović et al. (2015) 
investigated the correlation between results in ten motor ability tests and achieved 
level of ski knowledge during six-day alpine ski school in children aged between 7 
and 8. They found that successful children have better developed agility, coordination, 
strength and frequency of movement. Bandalo and Lešnik (2011) studied a correlation, 
based on a model of potential and competitive performance, on a sample of 30 older 
boys aged from 13 to 14 who participated in the Argeta Cup 2009 / 2010 and showed 
4 correlations of anthropometric dimensions and 13 correlations of motor dimensions. 
Dolenec and Lešnik also found an important correlation between competition success 
and morphology and motor abilities in young female (Dolenec, 1996) and young male 
competitors (Lešnik, 1996) in alpine skiing. Based on the results they concluded that it 
would be reasonable to reduce the number of variables from battery of tests.

According to these findings, we have put together a potentially successful battery of 
tests that measure those motor skills that are most associated with competitive perfor-
mance. As Dolenec (1996), Bandalo and Lešnik (2011) and Lešnik (1996) suggested, 
we have reduced the number of motor variables from eighteen to eight variables. We set 
the following research questions: i.) is there a correlation between selected motor tests 
and points achieved in Rauch Cup in male U14 age class and ii) does the selected model 
of four variables has a correlation with points achieved in the Rauch Cup. 



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METHODS

Participants

The sample consisted of 41 boys who were competing in Rauch Cup (slalom, giant 
slalom and super-G) in season 2016 / 17 in U14 age class. They came from different 
ski clubs across Slovenia. The Ethical Board of the Faculty of Sport, University of Lju-
bljana, approved the research experiment. All participants were informed of the study 
purpose and voluntarily participated in all tests. Parental written agreement was also 
obtained for each participant. 

Procedure

Measurements were assessed in autumn, before the competition season started. The 
whole procedure and tests were explained prior to the start of measurements. Tests were 
conducted at the Faculty of Sport in Ljubljana. The athletes were properly warmed-up 
before the start. First we assessed basic anthropometric measurements, body height and 
body weight. Then we used the following motor tests:

Taping with a dominant leg (TAP)

This represents the rate of movements test and is performed by shifting one’s foot as 
quickly as possible over a 15-cm-high bar within 15 sec. The athlete sits on a chair with 
arms along his torso. One full cycle consists of moving the foot over the bar, touching 
the ground and returning the foot to its original position. The device counts only fully 
completed cycles and our research consisted of each athlete having two attempts, with 
the better of the two taken into account. 

Test of stability (STAB)

The athlete had two attempts for this test, which was used to assess the overall 
dynamic stability and was performed in laboratory with Biodex Balance SD. The result 
is presented in the form of stability index. The athlete was positioned with both legs 
on the device’s platform and attempted to maintain the stable position for as long as 
possible.



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Run from the flying start – maximum speed (MAXSP)

The athletes had two attempts and were asked to start in the ski stance position. On 
starting mark athlete must in 30m develop maximum speed. The results are measured in 
m / s by a laser device, maximum speed achieved during running was recorded.

Ten jumps on both legs (MSKOK10)

This test measured driving power of the legs, with each athlete having two attempts 
and the longest of the two was taken into analysis. The test involved the measurement 
of the distance achieved by 10 consecutive jumps with no interruption between repeti-
tions. 

400m run (MT400)

Speed endurance was assessed by 400 meters run test. Athletes performed this test 
only once.

Running nines (SKI9)

The task here was to run as quickly as possible around nine pins (in the form of an 
eight) and represents a test of agility. This test was performed only once. 

Counter movement jump (CMJ)

In this test, the athletes had to jump as high as possible using countermovement 
jumping technique (CMJ). They had three trial jumps followed by two recorded at-
tempts. There was a 2-minute rest between each jump, with jumps being performed on 
a ground-force plate. The height was calculated based on the flight time. The highest 
jump was taken into account. 

Reaction time to a visual impulse (squat jump) (SJREAC)

Reaction time to a visual impulse triggered by computer screen was measured us-
ing Optojump device. On a visual signal, the athlete had to jump as quickly as possible 
from a squat position. They had three trial jumps followed by two recorded attempts.



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ANNALES KINESIOLOGIAE • 9 • 2018 • 1

Criterion variable (points in Rauch Cup)

The criterion variable represents the actual performance of all measured competi-
tors on Rauch Cup in the 2016 / 2017 season. This was expressed by the total number 
of points, achieved in each individual competition for Rauch Cup.

Statistical Analysis

Collected data was analysed using SPSS (IBM, version 22, USA) 
and Microsoft Excel 2013 and we summarized data with descripti-
ve statistics. With Pearson’s correlation coefficient we determined the line-
ar correlation of each individual variable with competitive performance (Ra-
uch Cup points). The multiple linear regression (MLR) analysis was used to 
determine how multiple independent variables are related to one dependent variable, 
in our case to competitive performance. With Enter method we inserted four variables 
that gave the highest MLR, with that we predicted the level of effect of this model and 
each variable on criterion variable. The criterion variable was represented by the total 
number of points, achieved in the Rauch Cup. Statistical significance was accepted at 
p < .05.

RESULTS

Participant’s basic anthropometric data are presented in Table 1. 

Table 1: Basic anthropometric data.

AM ± SD

N 41

Body height (cm) 158.2 ± 9.3

Body mass (kg) 49.5 ± 11.7

In Table 2 we determined for each variable minimum value, maximum value, range 
of values and arithmetic mean ± standard deviation.



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Špela BOGATAJ, Blaž LEŠNIK: CORRELATION BETWEEN DIFFERENT MOTOR ABILITIES AND SCORE POINTS ...,  35–44

Table 2: Descriptive statistics for each variable.

RANGE MIN MAX AM ± SD

Taping with the dominant leg 9.0 17.0 26.0 22.0 ± 2.3

Test of stability 6.6 1.3 7.9 3.9 ± 1.8

Maximum speed 2.47 5.39 7.87 6.64 ± .55

Ten jumps on both legs 11.1 15.2 26.3 19.6 ± 2.4

400m run 41.7 62.1 103.8 79.8 ± 9.6

Running nines 11.6 28.1 39.7 33.0 ± 2.8

Counter-movement jump 22.5 18.6 41.1 27.6 ± 4.8

Reaction time to a visual impulse .23 .39 .62 0.47 ± .06

Note: Range - the range between minimum and maximum value, MIN – minimum value, 
MAX - maximum value, AM±SD – arithmetic mean with standard deviation.

Table 3: Pearson correlation coefficient values between motor variables and perfor-
mance (points) in the Rauch Cup.

TEST POINTS

Taping with the dominant leg
r .320*
p .041

Test of stability
r .111
p .488

Maximum speed
r .712**
p <.001

Ten jumps on both legs
r .678**
p <.001

400m run
r -.583**
p <.001

Running nines
r -.563**
p .001

Counter-movement jump
r .576**
p .001

Reaction time to a visual impulse
r -.293
p .063

Note: ** - Correlation is significant at the 0.01 level (2-tailed), * - Correlation is significant at 
the 0.05 level (2-tailed), r – Pearson’s coefficient.



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Table 3 presents Pearson’s correlation coefficients for the motor tests in relation 
to skiing performance. We found positive correlation between criterion variable and 
variables TAP, MSKOK10, MAXSP and CMJ, while negative for MT400 and SKI9. In 
the case of SJREAC and STAB, the correlation coefficient calculation did not show a 
significant correlation.

Multiple linear regression (MLR) analysis was performed with Enter method. We 
included 4 predictors that gave the highest MLR for our sample of 41 participants. 
These were MAXSP, MSKOK10, MT400 and CMJ. Results showed that the linear 
relationship, between four motor tests and skiing performance is high (R = .727; P < 
.001) and explained 53 % of skiing performance variance (Table 4).

Table 4: Model.

R R2 P

.727 .53 < .001

Note: R – coefficient of multiple correlation; R²- coefficient of determination. Predictors: 
(Constant), MAXSP - run from the flying start (max. speed), MSKOK10 – ten jumps on both 
legs, MT400 - 400m run, CMJ – counter-movement jump.

Table 5: The multiple linear regression (MLR) analysis.

B Beta Partial R P

Constant -1773.776 .033

Maximum speed 199.497 .613 .342 .036

Ten jumps on both legs 24.375 .325 .178 .284

400m run 2.917 .156 .113 .498

Counter-movement jump -2.373 -.063 -.046 .784

Note: dependent variable: Pokal; predictors: (Constant), MAXSP - run from the flying start (max. 
speed), MSKOK10 – ten jumps on both legs, MT400 - 400m run, CMJ – counter-movement 
jump.

In Table 5 we can see that when we add four variables into MLR analysis, some of 
them are not significant anymore. In our case, the variable MAXSP is the most impor-
tant contributor (p = .036).



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DISCUSSION

This study was focused on the correlation between the selected motor abilities and 
competitive performance in U14 age group of alpine skiers. We found a correlation be-
tween competitive performance and results in six out of eight motor tests. Positive cor-
relation was found between Rauch points and variables TAP, MSKOK10, MAXSP and 
CMJ, while negative for MT400 and SKI9. The same as Bandalo and Lešnik (2011), 
we also did not find a significant correlation between balance (variable STAB) and 
criterion variable. This is interesting because the postural control in alpine skiing, in 
particular the management of the balance, is widely considered as one of the limiting 
factors of performance. For future research, we suggest that researchers use different 
balance tests and find out which test is best correlated with performance. In multiple 
linear regression, we included 4 predictors that gave the highest MLR: MAXSP, CMJ, 
MSKOK10 and MT400. Simple linear regression showed us that each predictor vari-
able had a significant p-value. But from the multiple regression model output, CMJ, 
MSKOK10 and MT400 no longer displayed a significant p-value. We think this is an 
example of collinearity of the predictors. But overall, the model is still significant. In 
our case, the variable MAXSP, which represents maximum speed, had a strongest cor-
relation with the criterion. With our research we addressed the dilemma with using a 
greater or smaller battery of test. As Lešnik (1996) and Dolenec (1996) suggested, we 
used a smaller battery, which can be performed at once. Based on the test results we can 
plan and conduct the training process, which later leads to efficient effort overcoming at 
training and at competitions. In future, it will be necessary to monitor the development 
of young athletes even more systematically. This is a sensitive period and that is why 
it is even more important that the battery of tests is effective and tells us those things 
about the athlete, which professionals needs in order to guide them in the training pro-
cess. Nowadays, the differences between individuals’ performance are getting smaller, 
that is why we need to focus on raising the level of motor and functional skills to the 
highest level possible. In this part, testing motor abilities plays an important role. Altho-
ugh highly developed motor abilities are crucial for good competitive performance, we 
must not ignore the role of biological age, motivation and concentration for this age 
group. 

CONCLUSION

Our findings show the suitability of selected motor tests in determining the potential 
success of young alpine skiers. We will continue with deployment of state-of-the-art 
measurement methods and try to connect them with the measurements of older age 
categories of competitors in alpine skiing. In conclusion, the test concepts presented in 
this study can help ski schools, clubs and skiing federations in the guidance and evalua-
tion of young talents. In the future, we suggest that in addition to motor test, researches 
also include several anthropometric measures and examine cognitive and behavioural 
measures of motivation.



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