26 Faculty of Sport, University of Ljubljana, ISSN 1318-2269  Kinesiologia Slovenica, 12, 1, 26–38 (2006)
Branimir Černohorski 
Mojca Doupona Topič 
Janez Pustovrh*
PREDICTABILITY OF CROSS-
COUNTRY SKIERS’ COMPETITIVE 
PERFORMANCE IN TERMS OF 
SOCIOLOGICAL VARIABLES
NAPOVED TEKMOVALNE 
USPEŠNOSTI V SMUČARSKEM 
TEKU Z VIDIKA SOCIOLOŠKIH 
SPREMENLJIVK
Abstract
The purpose of the study is to establish the values of 
variables from the sociological area in predicting 
potential competitive performance in cross-country 
skiing. The sociological area, encompassing 11 
variables, was studied within the MMPS model of 
potential performance (motor abilities, morphology, 
psychology, sociology). The sample consists of 48 cross-
country skiers from three competitive categories. The 
expert modelling procedure was used to obtain scores 
(1-10) for the potential performance of the subjects 
at all levels of the sociological area. An analysis of 
the correlation between these scores and the actual 
competitive performance criterion shows that the 
sociological area in all three categories of subjects 
is insignificantly correlated with their competitive 
performance. Nevertheless, due to the small number 
of subjects the results cannot be generalised. After 
two subjects from each category were eliminated, this 
correlation increased substantially; in the category of 
older junior men it even reached the level of statistical 
significance. The results show that the original expert 
modelling procedure in the sociological area deserves 
further research attention and should be verified on 
larger samples of subjects practising not only this sport 
but also other sports. 
Key words: sociology, cross-country skiing, expert 
modelling, competitive performance 
Faculty of Sport, University of Ljubljana, Slovenia
*Corresponding author:
Faculty of Sport, University of Ljubljana
Gortanova 22, 1000 Ljubljana, Slovenia
Tel.: +386 15207754
Fax: +386 15207730
E-mail: janez.pustovrh@fsp.uni-lj.si
Izvleček
S študijo smo želeli ugotoviti vrednost spremenljivk 
sociološkega prostora pri napovedovanju potencialne 
tekmovalne uspešnosti v smučarskem teku. Sociološki 
prostor, ki je zajemal 11 spremenljivk, smo proučevali 
v sklopu modela potencialne uspešnosti MMPS 
(motorika, morfologija, psihologija, sociologija). V 
vzorec je bilo zajetih 48 smučarjev tekačev v treh 
tekmovalnih kategorijah. S postopkom ekspertnega 
modeliranja smo pridobili ocene (1-10) o potencialni 
uspešnosti merjencev na vseh nivojih sociološkega 
prostora. Analiza povezanosti teh ocen s kriterijem 
dejanske tekmovalne uspešnosti je pokazala, da 
je sociološki prostor pri vseh treh kategorijah 
preizkušancev statistično neznačilno povezan z njihovo 
tekmovalno uspešnostjo. Vendar zaradi majhnega 
vzorca rezultatov ne moremo posploševati. Po izločitvi 
dveh preizkušancev iz vsake kategorije ta povezanost 
precej naraste, v kategoriji starejših mladincev celo 
do nivoja statistične značilnosti. Rezultati kažejo, 
da je izviren postopek ekspertnega modeliranja v 
sociološkem prostoru vreden nadaljnjega proučevanja 
in preverjanja na večjih vzorcih preizkušancev te in tudi 
ostalih športnih panog. 
Ključne besede: sociologija, smučarski tek, ekspertno 
modeliranje, tekmovalna uspešnost 
Sociological variables and competitive performance in cross-country skiing 27Kinesiologia Slovenica, 12, 1, 26–38 (2006)
INTRODUCTION
Sport may be conceived as a social phenomenon which is not a value in itself for society but 
a means of achieving general and special social objectives. The practising of sport is a result 
of social and personal factors. The basic social value of sport as a special social activity lies 
in its ability to substantially contribute to the maintaining of a balance between social and 
individual needs and goals. In its own right, sport is just an organised game, like a competition 
should be. Parallel to this, sport offers us the opportunity to cope with upsurges of emotions 
during matches. It also teaches us to adhere to the rules and respect social values.
Through a rough taxonomy of sets of motor, morphological, functional, cognitive, conative 
and sociological abilities, characteristics and qualities, a sportsperson may be defined as a bio-
psycho-social being in which the mentioned dimensions interact in countless ways (Kurelić, 
Momirović, Mraković, & Šturm, 1979). Competitors go through various development changes, 
including social changes. The process of socialisation is not only limited to social development 
but also to moral and mental development, the forming of viewpoints and beliefs as well as 
the development of motor efficiency. The primary phases in the development of sensomotor 
and locomotor abilities, laying the foundations for one’s subsequent engagement in sport, also 
form part of the socialisation process.
In some northern European countries cross-country skiing occupies a special place in society 
and is considered a national phenomenon. The northern philosophy of cross-country skiing, 
particularly its aspects of environmental awareness and perception of nature, is penetrating 
the minds of people with giant strides. Of course, recreational and competitive sport orienta-
tions cannot be equated. However, we can find the common points and, on that basis, build a 
knowledge base in the sociological sub-area of cross-country skiing. 
The increasingly demanding requirements of elite sport call on individual sports disciplines 
to set up or design competitive and potential models of the performance of athletes in all life 
periods and in all phases of the transformation process. The competitive performance model 
is based on the actual result of an individual athlete (at the present time). When analysing 
competitive performance one has to progress from consequences to causes, while in potential 
performance (anticipating the future) it is the other way around – from causes to consequences. 
A general potential model of performance in Nordic skiing, to which cross-country skiing 
belongs, was designed on the basis of the concept of psychosomatic status (Jošt, Dežman, 
& Pustovrh, 1992). Nevertheless, decisions concerning transformation process management 
must not stem from partial findings. By applying expert knowledge and methods one may 
satisfactorily avoid the pitfalls of multivariant methods (which are still indispensable). Multi-
parameter modelling is conceived as a process of evaluation. In this process a model has to be 
developed for the evaluation of individual ideas on the basis of the set goals and expectations 
(Chankong & Haimes, 1983).
The subject and problem of this research involved the study and evaluation of the potential 
competitive performance of cross-country skiers from three age categories (older boys, 
younger junior men and older junior men). For this purpose, a MMPS model was created 
to encompass the motor, morphological, psychological and sociological areas of the athletes’ 
psychosomatic status. As the model fails to cover all areas of the athletes’ psychosomatic status, 
it may be categorised as a ‘reduced model’ for studying potential competitive performance. 
28 Sociological variables and competitive performance in cross-country skiing Kinesiologia Slovenica, 12, 1, 26–38 (2006) 
Since all competitive categories of athletes may be evaluated by the same model, it may also be 
categorised as a ‘universal model’. The quality of each expert model depends on the knowledge 
base created by experts in the process of creating the model. Our project involved the most 
renowned cross-country skiing experts. The knowledge base is a body of knowledge about 
the theory of athletes’ performances and preparation in cross-country skiing (facts and rules 
describing the relations and phenomena in problems and/or methods, heuristic principles and 
ideas for problem solving). In the expert system the knowledge base in all discussed areas of the 
MMPS model is written in a formalism used in application of the SMMS (Sport Measurement 
Management System, Version 1.0) computer programme. The formalism of the knowledge base 
was designed on the basis of three components (Ulaga, 2001): knowledge base referentiality 
(forming of a criterion tree), dimensional configuration of the knowledge base (determination 
of weights) and positional configuration of the knowledge base (determination of normalisers). 
All three components form an inseparable whole. The MMPS model has a hierarchic tree 
structure and encompasses the criteria applied in the study of athletes’ potential competitive 
performance. The tree illustrates the hierarchical order and inter-correlation between the cri-
teria. The basic criteria (tests) are at the bottom of the tree and, in higher nodes, they combine 
to form weighted and/or derived criteria. Thus, the higher-level criteria depend on those at 
lower levels. The value of the basic criteria (tests) are determined for each subject separately on 
the basis of the measurements performed. The dimensional configuration of the MMPS model 
is determined by decision rules (determination of weights). According to experts, these are 
the contributions of the individual variables to explaining potential competitive performance 
and are expressed in percentages (weights). The model was built by applying the method of 
the dependent determination of weights (Ulaga, 2001). According to this method, in each 
individual node the total contribution of the weight of all variables of a lower order that form 
a variable of a higher order equals 100 in relative terms. In nominal terms, the sum total of 
all weights of all lowest-order variables (tests) in the MMPS model is 100. The positional 
configuration of the knowledge base refers to the creation of normalisers for individual basic 
variables (tests). These are numerically expressed boundaries of results for individual variables. 
These boundaries define individual qualitative scores (inadequate, adequate, good, very good, 
excellent). Based on such a ‘manual’ and expert construction of the MMPS model, the SMMS 
computer programme may use the rough results of the measurements of individual variables 
(tests) for calculating the score (ranging from 1 to 10) at all levels of the SMMS model. The 
score at the highest level of the MMPS model is calculated ‘automatically’ and represents the 
total score of all studied areas in terms of the potential competitive performance of the subject. 
Another aim of the study was to establish the validity of the established SMMS model at the 
level of sociological variables. 
This article deals only with the sociological sub-area, while other sub-areas of the athletes’ 
psychosomatic status are referred to solely for the purpose of explaining the structure of the 
MMPS model of potential performance. A study of all areas of the MMPS model would be too 
exhaustive and be beyond the objectives of the research which were intentionally limited to a 
study of the sociological area. We present the first attempt to create a knowledge base in the 
sociological sub-area. The basic theoretical premise of this model is the phenomenal model 
of social stratification (Saksida & Petrović, 1972), which is supplemented by new findings in 
sport and particularly by research findings in the fields of social and demographic charac-
teristics of cross-country competitors (Kerštajn, 1994; Pustovrh, 1991; Vrhovec-Kavčič, 1990; 
Sociological variables and competitive performance in cross-country skiing 29Kinesiologia Slovenica, 12, 1, 26–38 (2006)
Zevnik, 2004). The hypothetical sociological model is thus divided into three subsystems: the 
socialisation subsystem is defined by the dimensions which prepare an individual to assume 
their roles in the institutional social order (family, school etc.); the consequential subsystem 
is defined as a sanctioning of the individual’s assumption of their position in the socialisation 
and institutional order; and the institutional subsystem defines the individual’s position from 
professional, political and economic perspectives.
As these dimensions define the characteristics of a population, it is possible to apply them in 
a hierarchical classification of a sample of the population into relevant segments of the social 
system structure (Doupona, 1996). In our research, we strive to classify the sample of subjects 
in their sociological sub-area so as to establish the potential performance of cross-country 
skiers. 
METHOD
Participants
The sample of subjects consisted of 48 active cross-country skiers from three competitive 
categories who had participated in at least four competitions for the Slovenia Cup in the 
2001-2002 season. The subjects included 17 older boys (OLDB – born in 1988 and 1989), 17 
younger junior men (YJM – born in 1986 and 1987) and 14 older junior men (OJM – born in 
1984 and 1985). 
Instruments
The MMPS model (motor abilities, morphology, psychology and sociology) encompassed 64 
independent (predictor) variables. These are independent variables of the sociological sub-area 
(11): education of one’s mother (EM), education of one’s father (EF), conditions for training at 
the ski club (CTSC), the quality of expert work (QEW), organisation of the club’s infrastructure 
(OCI), involvement of one’s mother in sport (IMS), involvement of one’s father in sport (IFS), 
function of one’s mother in the club (FMC), function of one’s father in the club (FFC), position 
of one’s mother at work (PMW), and position of one’s father at work (PFW). 
Dependent (criterion) variable (SLO _FIS): the FIS points achieved by Slovenian competitors 
in the 2001-2002 season were selected. A lower value of this variable (lower number of points) 
means a better competitive performance. The calculation of points for the entire season was 
based on the average of the four most successful competitions of each individual athlete in 
the competitive season.
Procedure
The measurements were carried out in March 2002 at the Faculty of Sport in Ljubljana (a more 
detailed description of the measurement protocol is available from the authors). 
The MMPS model of the potential performance of cross-country skiers was constructed in the 
form of a tree of criteria. Normalisers were set (positional configuration) for all elementary 
variables (tests). These are the points determining the utility function v which for a given 
measured (rough) result x on a basic criterion determines its value i.e. utility (Chankong & 
Haimes, 1983). The experts thus give only explicit, numerical and attributive values of the 
30 Sociological variables and competitive performance in cross-country skiing Kinesiologia Slovenica, 12, 1, 26–38 (2006) 
utility function for some points, while for others the values are determined by calculating the 
straight line between two points by interpolation.
Table 1: An example of setting up the normalisers for the variable EM – education of one’s 
mother:
value of variable 1 2 3 4 5 6 7
score of variable 3 5 7 10 7 5 3
Legend: 
Numerical and descriptive values of scores: 
0 ≤ f(x) ≤ 2 = unsatisfactory, 
2 ≤ f(x) ≤ 4 = satisfactory, 
4 ≤ f(x) ≤ 7 = good, 
7 ≤ f(x) ≤ 9 = very good, 
9 ≤ f(x) = excellent
The decision rules were formulated (dimensional configuration) for all nodes by the method 
of the dependent determination of weights (Ulaga, 2001). This is the value of the hypotheti-
cal contribution (in %) of each individual variable to competitive performance. The SMMS 
programme was used to calculate scores for each subject for all variables at all model levels, 
first for the elementary variables (tests) and then gradually for all composite variables at higher 
nodes, up to the highest node MMPS, i.e. the prognostic score of the subject’s competitive 
performance. The calculation was made according to the following formula:
Svr = (Snr1 x P) + (Snr2 x P) +…+ (Snrn x P) 
Svr – normalised value of higher-order variable 
Snr – normalised value of lower-order variable
P – weight of the lower-order variable (decision rule)
At the highest level of the model, Pearson’s correlation coefficient was used to establish the 
correlation between the scores of predictor variables and the criterion variable. Thus the 
validity of the model of potential performance was determined.
RESULTS AND DISCUSSION
Creation of a knowledge base formalism
One of the objectives of the research was to design a model of the potential performance 
(MMPS) of cross-country skiers from three competitive categories (from 13 to 18 years). 
With regard to both all previous research made within a narrow focus of cross-country skiing 
and the theory of psychosomatic status model, the highest weight in our model of potential 
performance was of course given to the motor sub-area. Realisation and mobilisation dimen-
sions in competitive sport cannot adequately compensate for a deficiency at the potential level 
to which motor abilities belong.
Sociological variables and competitive performance in cross-country skiing 31Kinesiologia Slovenica, 12, 1, 26–38 (2006)
Table 2: Structure of the sociological area (referentiality, dimensional and positional configu-
ration) in the MMPS model of potential performance 
TEST CODE NAME OF TEST WEIGHTS NORMALISERS
MMPS Motorics, morphology, psychology, sociology 100
├─OC_SOCIO Sociological characteristics 14
│ ├─SOC_SUB Socialisation subsystem 2
│ │  └─EDUC Education 2
│ │      ├─EM Education of mother 1 1:3, 2:5, 3:7, 4:10, 5:7, 6:5, 7:3
│ │      └─EF Education of father 1 1:3, 2:5, 3:7, 4:10, 5:7, 6:5, 7:3
│ ├─CONS_SUB Consequential subsystem 8
│ │    ├─CW Work in club 4,5
│ │    │  ├─CTSC Conditions for training 1,5 1:2, 2:4, 3:7, 4:9, 5:10
│ │    │  ├─QEW Quality of expert work 1,5 1:2, 2:4, 3:7, 4:9, 5:10
│ │    │  └─OCI Organisation of the club infrastructure 1,5 1:2, 2:4, 3:7, 4:9, 5:10
│ │    └─IPS Involvement of parents in sport 3,5
│ │       ├─IMS Involvement of mother in sport 1,8 1:7, 2:10, 3:7, 4:3, 5:3
│ │       └─IFS Involvement of father in sport 1,7 1:7, 2:10, 3:7, 4:3, 5:3
│ └─INST_SUB Institutional subsystem 4
│     ├─PAC Functions of parents in the club 2
│     │  ├─FMC Function of mother in the club 1 1:5, 3:7, 4:9, 5:10
│     │  └─FFC Function of father in the club 1 1:5, 3:7, 4:9, 5:10
│     └─PPW Occupation of parents 2
│        ├─PMW Position of mother at work 1 2:10, 3:8, 4:5, 5:3
│        └─PFW Position of father at work 1 2:10, 3:8, 4:5, 5:3
The dimensions of sociological status that are considered in this article in greater detail are 
important in the final mosaic of the model of the psychosomatic status, nevertheless in our 
potential performance model their predictability weight is smaller (14 percent). The decision 
to assign less importance to these dimensions was influenced by prudence in the hypothetical 
estimation of this sub-area’s impact on the potential competitive performance of young cross-
country skiers given that, as mentioned earlier, this is the first attempt to design such a model. 
Positional and dimensional configurations are shown in Table 2. It is worth mentioning that in 
some variables the positional configuration of an individual’s rough result was hindered due 
to the small range of values obtained. Sometimes, only two values of a variable were obtained, 
which means that the variability was nearly zero.
The referentiality as well as the dimensional and positional configuration of the knowledge 
base posed a challenge to our research due to the homogeneity of the subject population (in 
sociological terms). The model consisted of three subsystems. The socialisation subsystem 
(SOC_SUB) is defined by the education node (EDUC) consisting of two variables which define 
the education of the mother and father (EM, EF) and reveal the correlation between the parents’ 
education and competitive performance of their children. This subsystem comprises latent 
mechanisms enabling or at least facilitating the processes of motor information processing 
(Starkes & Allard, 1993). In our models the consequential subsystem (CONS_SUB) had the 
strongest predictive power. It was determined by two nodes indicating whether the fact that 
parents spend their leisure time on sport practice (IPS) has any impact on their children as well 
as the overall organisation of the club’s infrastructure (CW). The node of the parents’ sports 
activity has two variables (IMS and IFS), while the node of the overall organisation of a club’s 
32 Sociological variables and competitive performance in cross-country skiing Kinesiologia Slovenica, 12, 1, 26–38 (2006) 
infrastructure has three: CTSC, QEV and OCI. We agree with Messing and Voigt (1979; in 
Ambrožič, 1988), namely, that it is possible to distinguish between the children of sport active 
parents and those of sport inactive parents. The institutional subsystem (INST_SUB) features 
two nodes: parents’ activity in the club (PAC) and parents’ position at work (PPW). Each of 
the nodes has two variables defining the activity of the athlete’s father and mother. Doupona 
(1996) established that income (related to one’s position at work) and membership of a social 
class (which a club function undoubtedly involves) are two extremely important factors for 
children’s involvement in sporting activities.
Example of results of evaluating a subjects’ potential performance 
The aim of expert modelling is to acquire quality information on the condition of subjects, based 
on which their actual competitive performance may be predicted with high probability. 
Table 3: Scores of the potential performance of subjects ‘A’ and ‘B’ at the highest level and at 
the level of sociology in the universal reduced MMPS model of potential performance 
TEST CODE
MODEL MMPS
Competitor ‘A’
(SLO_FIS = 165,40, RANK = 
2, AGE = 17,5 YEARS)
Competitor ‘B’
(SLO_FIS = 99,50, RANK = 1,
 AGE = 18 YEARS)
RES f(x) SCORE RES f(x) SCORE
MMPS 6.83 good 7.55 v. good
├─OC_SOCIO 8.36 v. good 7.67 v. good
│ ├─SOC_SUB 10.00 excellent 6.00 good
│ │  └─EDUC 10.00 excellent 6.00 good
│ │      ├─EM 4 10.00 excellent 6 5.00 good
│ │      └─EF 4 10.00 excellent 3 7.00 v. good
│ ├─CONS_SUB 8.12 v. good 8.74 v. good
│ │    ├─CW 9.33 excellent 9.00 excellent
│ │    │  ├─CTSC 5 10.00 excellent 5 10.00 excellent
│ │    │  ├─QEW 4 9.00 excellent 5 10.00 excellent
│ │    │  └─OCI 4 9.00 excellent 3 7.00 v. good
│ │    └─IPS 7.00 good 8.50 v. good
│ │       ├─IMS 1 7.00 v. good 2 10.00 excellent
│ │       └─IFS 1 7.00 v. good 3 7.00 v. good
│ └─INST_SUB 7.67 v. good 7.00 v. good
│     ├─PAC 7.33 v. good 6.00 good
│     │  ├─FMC 5 10.00 excellent 2 6.00 good
│     │  └─FFC 1 5.00 good 2 6.00 good
│     └─PPW 8.00 v. good 8.00 v. good
│        ├─PMW 3 8.00 v. good 3 8.00 v. good
│        └─PFW 3 8.00 v. good 3 8.00 v. good
Legend:
RES - raw test results; f (x) - numerical score; SCORE - attribute score; 
Numerical and descriptive values of scores: 
0 ≤ f(x) ≤ 2 = unsatisfactory, 
2 ≤ f(x) ≤ 4 = satisfactory, 
4 ≤ f(x) ≤ 7 = good, 
7 ≤ f(x) ≤ 9 = very good, 
9 ≤ f(x) = excellent
Sociological variables and competitive performance in cross-country skiing 33Kinesiologia Slovenica, 12, 1, 26–38 (2006)
Table 3 shows two competitors ranked one after another (1st and 2nd place) on the scale of the 
selected criterion of FIS points (SLO_FIS), while the difference in their age is half a year. The 
general potential competitive performance of subjects ‘A’ and ‘B’ is evaluated as good (6.83) and 
very good (7.55), respectively. A look at the scores in the sociological sub-area reveals that the 
two competitors differ in terms of the structure of their parents’ education (EDUC). However, 
it is difficult to draw generalised conclusions based on these differences and other variables of 
the sociological sub-area. This also applies to the consequential subsystem (CONS_SUB) where 
both competitors evaluated club work (CW) very highly. The final scores of the sociological 
sample (OC_SOCIO) of both competitors do not differ substantially.
Based on the actual informative value of the constructed model of potential performance 
(MMPS), competitor ‘B’ may be evaluated as being more promising in the long run in terms 
of their potential top performance in cross-country skiing. After all, this is shown by the 
difference in the FIS points achieved. Of course, the above is not the essential informative 
value of this model. The model becomes much more powerful if the instructor adapts the 
management of the athletes’ transformation process according to this information as well as 
improves the athletes’ efficiency in a certain time period. Without this information, it is highly 
possible that the management of the training process would become incorrect, especially if 
the group of athletes is large while the training means and methods remain the same for all 
athletes. With the correct planning of the transformation process in the long run and by 
taking the findings of this research into account, competitor ‘A’ may also achieve a high level 
of elite competitive performance. 
Establishment of the validity of the sociological sub-area of the MMPS model of potential per-
formance 
The validity of the sociological area will be analysed in greater detail within the MMPS 
model.
The scores of individual variables of the socialisation subsystem (SOC_SUB) correlate with the 
criterion of performance in different ways depending on the competitive category (Table 4). 
For older boys, the score of education of one’s father (EF) is statistically significantly correlated 
with the criterion of FIS points (SLO_FIS). Of course, it is impossible to generalise that the 
education of one’s parents (father) holds important power for predicting performances in 
cross-country skiing. It is more likely that this correlation is only typical of the sample of older 
boys as already with younger junior men it is quite the opposite, while for older junior men it is 
almost non-existent. In cross-country skiing, secondary-school education is still the prevailing 
level of education of one’s parents and this has not changed over the past decade (Pustovrh, 
1991; Vrhovec-Kavčič, 1990; Zevnik, 2004), however, this is not necessarily correlated with 
competitive (non-)performance.
In our search for consistent correlations between the scores of individual variables of the 
consequential subsystem (CONS_SUB) and competitive performance, which was rated the 
highest in our model, we found that it is again more appropriate to talk about the directions of 
correlations rather than about the rules and strengths of correlation. Slightly more consistent 
correlations (in view of all three categories) with the performance criterion (SLO_FIS) were 
seen in the variables of the node of one’s parents’ sport activity (IPS). According to Južnič 
(1987), many behaviours and activities which are imparted to someone during the early periods 
of their life become a permanent pattern of behaviour in adulthood. A favourable climate 
34 Sociological variables and competitive performance in cross-country skiing Kinesiologia Slovenica, 12, 1, 26–38 (2006) 
and encouragement from one’s parents are more important than one’s parents’ sport activity 
(Ambrožič, 1988). Probably the interaction of both – encouragement and one’s parents’ sports 
orientation – yields the optimal results. The values of correlation coefficients are not statisti-
cally significant; however, the correlations point in the desired direction, except for younger 
junior men. Parents play an important role in the process of the individual’s socialisation in 
sport; nevertheless, some other factors are also influential. Searching for one’s own identity, 
problems related to money, the rules and desires of one’s parents as well as previous experi-
ence considerably influence the individual’s decision to get involved in sport or retire from it 
(Coakley & White, 1999).
A similar trend is seen in the variables of the institutional subsystem (INST_SUB). The cor-
relations between one’s parents’ activity in the club (PAC) and the criterion of competitive 
performance (SLO_FIS) in the categories of older boys and younger junior men can be pointed 
out. They are not statistically significant (-0.37, -0.23) but are still important since it may be 
concluded that through their work in the club parents influence the training and competition 
development of their children. Of course, in terms of contents these correlations do not reveal 
the real quality of the parents’ influence. It often happens that parents exert too much pressure 
on the child (because of financial investments) and thus incapacitate them (Coakley, 1992).
Table 4: Correlation between the scores of variables from the sociological sub-area and the 
selected criterion of competitive performance – SLO_FIS.
TEST CODE
MODEL MMPS
DEPENDANT METHOD
OLDB YJM OJM
MMPS -0.53* -0.47 -0.79**
├─OC_SOCIO 0.10 -0.08 -0.19
│ ├─SOC_SUB -0.19 0.12 -0.12
│ │  └─EDUC -0.19 0.12 -0.12
│ │      ├─EM 0.20 -0.12 -0.14
│ │      └─EF -0.58* 0.30 -0.04
│ ├─CONS_SUB 0.24 -0.06 -0.14
│ │    ├─CW 0.46 -0.13 0.03
│ │    │  ├─CTSC 0.20 -0.21 0.02
│ │    │  ├─QEW 0.50* 0.14 0.00
│ │    │  └─OCI 0.44 -0.22 0.07
│ │    └─IPS -0.13 0.05 -0.33
│ │       ├─IMS -0.14 0.15 -0.32
│ │       └─IFS -0.09 -0.05 -0.12
│ └─INST_SUB -0.16 -0.14 -0.08
│     ├─PAC -0.37 -0.23 -0.08
│     │  ├─FMC -0.16 0.09 -0.07
│     │  └─FFC -0.35 -0.34 -0.02
│     └─PPW -0.02 -0.05 -0.05
│        ├─PMW 0.12 0.15 -0.09
│        └─PFW -0.08 -0.18 0.01
OLDB *p(0.05) = 0.48, **p(0.01) = 0.61;
YJM *p(0.05) = 0.48, **p(0.01) = 0.61;
OJM  *p(0.05) = 0.53, **p(0.01) = 0.66
Sociological variables and competitive performance in cross-country skiing 35Kinesiologia Slovenica, 12, 1, 26–38 (2006)
Figure 1: Correlation of the scores of sociological variables (OC_SOCIO) with the criterion 
of competitive performance SLO_FIS for older boys (OLDB) 
Figure 2: Correlation of the scores of sociological variables (OC_SOCIO) with the criterion 
of competitive performance SLO_FIS for younger junior men (YJM) 
Figure 3: Correlation of the scores of sociological variables (OC_SOCIO) with the criterion 
of competitive performance SLO_FIS for older junior men (OJM)
36 Sociological variables and competitive performance in cross-country skiing Kinesiologia Slovenica, 12, 1, 26–38 (2006) 
As already established, the subjects of our research constitute a homogeneous sociological 
sample with a very broad criterial span of performance. It turned out that the correlation 
between the sociological sub-area and the criterion of competitive performance (SLO_FIS) 
in the categories of younger and older junior men pointed in the desired direction and was 
relatively high for the oldest category of competitors in particular. Both correlations show that 
more successful competitors in the mentioned categories have a more favourable social status 
than less successful ones. The result for the category of older boys does not indicate such a 
direction of correlation, nevertheless, one has to bear in mind that these boys have only just 
started practising this sport and that some of the factors which are now negative will change, 
particularly the consequential subsystem (work in club – CW). It is also worth stressing that 
the research data were acquired from a relatively small sample of subjects.
In the continuation a scattergram is used to analyse in greater detail the correlation between 
the score of the sociological sub-area (OC_SOCIO) and the criterion of competitive perform-
ance (SLO_FIS) for all three categories of competitors. The purpose is to establish whether 
there are subjects who are highly distinctive from others due to their (non)correlation.
Figures 1, 2 and 3 show that in all three competitive categories a certain number of subjects 
stand out due to their non-correlation (subjects nos. 1 and 10 in older boys, subjects nos. 19 
and 29 in younger junior men and subjects nos. 37 and 42 in older junior men). A higher value 
for the variable OC_SOCIO means a better result (higher potential competitive perform-
ance), while a higher value for the variable SLO_FIS means a poorer result (lower actual 
competitive performance). Subjects 1, 10, 19, 29 and 37 have relatively high values for the 
variable (OC_SOCIO) but they are relatively unsuccessful in terms of competitive performance 
(variable SLO_FIS), while the opposite is the case for subject 42. After these subjects were 
eliminated, the correlation increased markedly (see Table 5). 
Table 5: Correlation between the scores of sociological variables (OC_SOCIO) and the criterion 
of competitive performance SLO_FIS before and after the elimination of two subjects from 
each competitive category
BEFORE ELIMINATION AFTER ELIMINATION
OC_SOCIO OC_SOCIO
SLO_FIS
OLDB 0.10 -0.45
YJM -0.08 -0.41
OJM -0.19 -0.65*
Legend: * p<0.05
With the older junior men the correlation rises from -.19 to a statistically significant -.65, with 
the younger junior men from -0.08 to -0.41, while with the older boys even from .10 to -.45. 
This example is a good illustration of how with such a small sample of subjects a few entities 
may distort the overall picture of inter-correlation of the actual competitive performance and 
individual model variables. 
Any partial treatment of a young athlete and/or cross-country skier in the sense of making 
comprehensive and final assessments of current and/or potential abilities is unacceptable. 
Therefore, by establishing relations and interactions between individual dimensions of psycho-
somatic status and by using expert knowledge in specific scientific disciplines we managed to 
design a universal reduced model of potential performance in cross-country skiing. The model 
Sociological variables and competitive performance in cross-country skiing 37Kinesiologia Slovenica, 12, 1, 26–38 (2006)
information should enable the treatment of each cross-country skier as a bio-psycho-social 
whole.
The ultimate goal of the generated universal reduced model of potential performance is to 
verify its validity. Validity is reflected in the information about the degree to which a measure-
ment yields data (and what these data indicate) about the subject of measurement (Malacko 
& Popović, 1997). In our case, it is about the correlation between the actual performance and 
the established potential performance in cross-country skiing. This is the ultimate and most 
likely the paramount goal of expert modelling. In our example, no statistically significant 
correlations between the criterion of competitive performance (SLO_FIS) and the scores of 
potential competitive performance in the sociological area (OC_SOCIO) were established in 
any of the analysed competitive categories. This confirms the findings of researchers (Zevnik, 
2004) claiming that Slovenian competitors are a relatively homogeneous sociological sam-
ple. In the categories of younger and older junior men the correlations move in the desired 
direction, which is slightly less evident in the youngest category (OLDB). Nevertheless, the 
situation changes considerably if two subjects substantially differing from the rest in terms of 
correlation are eliminated from each category. In the oldest category a statistically significant 
correlation occurs. This points to the fact that the established validity of the model in the 
sociological area has to be interpreted with a certain degree of prudence. It is evident that 
the results of the research depend on the size of the sample; however, in our environment it 
is currently impossible to significantly expand the sample as the athlete base in this sport is 
extremely small. Theoretically, the research could be repeated in some other country with a 
larger population of cross-country skiers. As the competitors do not have a unique criterion 
variable (they do not compete in the same competitive system), it is unreasonable to form an 
international sample. Based on scientific research it would be reasonable to complement the 
knowledge base of the existing expert model of the sociological area (referentiality, positional 
and dimensional configuration). It is a fact that this is the first research of its kind in sport 
and it would be reasonable to create an adequate knowledge base and conduct such research 
in other similar sports where competitive performance depends on certain basic sociological 
characteristics. Our research will be ready for additional analyses and comparisons when the 
results of similar research into the sociological area applying expert modelling also become 
known for other comparable sports.
REFERENCES
Ambrožič, F. (1988). Povezanost nekaterih kazalnikov motorične učinkovitosti motorično najsposobnejših 
11-12 letnih dečkov z njihovim socialnim izvorom, pogoji šolanja in športno aktivnostjo [Correlation 
between some motor efficiency indicators of the 11-12 year-old boys with top-level motor abilities and 
their social background, formal schooling and sport activity]. Unpublished master’s thesis, Ljubljana: 
Univerza v Ljubljani, Fakulteta za telesno kulturo.
Chankong, V., & Haimes Y.Y. (1983). Multiobjective decision making: Theory and Methodology. New 
York: North-Holland.
Coakley, J. (1992). Burnout among adolescent athletes: A personal failure or social problem? Sociology 
of Sport Journal, 9, 271-285.
Coakley, J., & White, A. (1999). Making decisions - How young people became involved and stay 
involved in sport. In J. Coakley, & P. Donnelly (Eds), Inside Sport (pp. 77-85). London: Routledge.
38 Sociological variables and competitive performance in cross-country skiing Kinesiologia Slovenica, 12, 1, 26–38 (2006) 
Doupona, M. (1996). Socialno demografska struktura mater in očetov šoloobveznih otrok in njihov odnos 
do športa [Social and demographic structure of mothers and fathers of school-age children and their 
attitudes to sport]. Unpublished doctoral dissertation, Ljubljana: Univerza v Ljubljani, Fakulteta za 
šport.
Jošt, B., Dežman, B., & Pustovrh, J. (1992). Vrednotenje modela uspešnosti v posameznih športnih 
panogah na podlagi ekspertnega modeliranja [Evaluating the model of performance in individual 
sports on the basis of expert modelling]. Ljubljana: Univerza v Ljubljani, Fakulteta za šport, Inštitut 
za kineziologijo.
Južnič, S. (1987). Antropologija [Anthropology]. Ljubljana: Državna založba Slovenije.
Kerštajn, R. (1994). Socialno demografske karakteristike in pogoji življenja in dela vrhunskih smučarjev 
tekačev [Social and demographic characteristics and living and working conditions of elite cross-country 
skiers]. Unpublished bachelor’s thesis, Ljubljana: Univerza v Ljubljani, Fakulteta za šport.
Kurelić, N., Momirović, K., Mraković, M., & Šturm, J. (1979). Struktura motoričkih sposobnosti i 
njihove relacije sa ostalim dimenzijma ličnosti [Structure of motor abilities and their relations with 
other personality dimensions]. Kineziologija, 9(1-2), 5-24.
Malacko, J., & Popović, D. (1997). Metodologija kineziološko antropoloških istraživanja [Methodology 
of kinesiological & anthropological research]. Priština: Fakultet za fizičku kulturu Univerziteta u 
Prištini.
Pustovrh, J. (1991). Povezanost nekaterih indikatorjev socialne stratifikacije s tekmovalno kvaliteto 
smučarjev tekačev [Correlation between some indicators of social stratification and cross-country skiers’ 
competitive quality]. Unpublished master’s thesis, Ljubljana: Univerza v Ljubljani, Fakulteta za šport.
Saksida, S., & Petrović, K. (1972). Teoretični model socialne stratifikacije: Poskus kvantitativne 
verifikacije [Theoretical model of social stratification: Attempt of quantitative verification]. Teorija in 
praksa, 9(10), 1407-1419.
Starkes, J.L., & Allard F. (1993). Cognitive issues in motor expertise. New York: North-Holland.
Ulaga, M. (2001). Analiza strukture in povezanosti izbranih potencialnih dimenzij modela uspešnosti 
športnikov s pomočjo ekspertnega sistema “Sport manager” [Analysis of the structure and correlations 
between the selected potential dimensions of the model of performance of athletes by means of the 
Sport Manager expert system]. Unpublished doctoral dissertation, Ljubljana: Univerza v Ljubljani, 
Fakulteta za šport.
Vrhovec-Kavčič, A. (1990). Nekatere socialne in demografske karakteristike ter različni pogoji dela in 
življenja smučarjev tekačev [Some social and demographic characteristics and different living and 
working conditions of cross-country skiers]. Unpublished bachelor’s thesis, Ljubljana: Univerza v 
Ljubljani, Fakulteta za telesno kulturo.
Zevnik, V. (2004). Nekatere značilnosti športne kariere slovenskih smučarjev tekačev in tekači [Some 
characteristics of sports careers of Slovenian male and female cross-country skiers]. Unpublished 
bachelor’s thesis, Ljubljana: Univerza v Ljubljani, Fakulteta za šport.