PhD, Associate Professor A.Yu. Titlov¹
Dr.Hab., Professor E.A. Shirkovets^2
1State University of Humanities and Social Studies, Kolomna, Moscow Region
²Federal Scientific Center of Physical Education and Sports, Moscow

Keywords: skating sports, skaters of different specializations, functionality test rates

Introduction. Long-term training of skaters affect the development of those functional systems that determine their special working capacity depending on the chosen specialization [1-5]. This article compares the performance indicators of skaters of different specializations obtained during testing in standard laboratory conditions [4, 1]. The system of athletic training based on the analysis of a complex of ergometric and biological indicators makes the process of training management objective and targeted [2].

Objective of the study was to identify differences in the main components of special working capacity of elite speed sprint and all-round skaters.

Methods and structure of the study. To determine the functional indicators of the athletes under study, we used a standard stepped test. The test time was determined by the actual functionality rates of the athletes, but the work performed was always submaximal. The tests included analyses of the exhale and blood lactate at every stage of the tests to estimate the maximal power and aerobic/ anaerobic thresholds. The speed-strength qualities were rated by a strain gauge platform, with the maximal leg extension strength and one/ two leg jump time fixed in the tests

Sampled for the study were 24 elite athletes qualified Masters of Sports to World Class Masters of Sports, and having the close track records, including 12 sprinters and 12 skaters specializing in the classical all-round events. The subgroups did not have any statistically significant differences neither in the athletes’ qualifications nor in their experience.

Results and discussion. Table 1 presents the results of the comparative analysis of ergometric indicators obtained during the stepped test.

Table 1. Ergometric indicators in skaters of different specializations

Note. The table presents working time, maximum power in absolute and relative values, power of anaerobic threshold and its share of maximum power in chain order.

The performance time limit differed statistically significantly at the high level (p<0.01) in both groups. The maximum power values in the all-round skaters were significantly higher than in the speed sprint skater group. In the all-rounder group, the power of anaerobic threshold was on average equal to 1912±278 kgm/min, and in the sprinter group – 1756±278 kgm/min. These differences were significant at p<0.05. In general, according to most ergometric performance criteria, the all-rounders demonstrated significantly higher rates, since their sports performance was to more provided by such physical quality as endurance.

Table 2 contains the data on the power capabilities of the skaters tested on the strain gauge platform. It illustrates the differences in their power characteristics. The analysis of these data proved the advantage of the sprinters in terms of the speed-strength abilities as opposed to the all-rounders.

Table 2. Power capabilities of skaters tested on strain gauge platform

Note. The table represents the data on the jumping power and speed, one/ two leg jump time.

The jumping test performed with maximum effort on the strain gauge platform showed that the jumping speed in the speed sprint skaters was higher as opposed to that in the all-round ones, but the differences were insignificant. The time taken to take off the strain gauge platform when jumping from one leg and two legs was significantly (p<0.05) higher in the sprinters than in the all-rounders.

Table 3 shows the differences in a number of morphological indicators of the speed sprint and all-around skaters.

Table 3. Comparison of morphological parameters of elite skaters of different specializations

The body length in the group of all-rounders was 185.7±6.8 cm and 184.3±7.9 cm in the group of all-rounders and sprinters respectively, the differences being significant at p<0.05. The athletes’ body weight was 82.3±4.9 and 83.1±6.2 kg, respectively; the differences were insignificant. The proportion of muscle mass was 56.2±2.3% and 56.1±1.5% in the speed sprint skaters and all-round skaters respectively. Such data are characteristic of the athletes involved in the speed-strength trainings. The relative fat mass in the sprinters and all-rounders was 8.6±1.9% and 8.7±1.7%, respectively; the differences were statistically insignificant.

The above tables compare the differences between the individual indicators. It should be emphasized that the multi-factorial group test data analysis found some significant intergroup differences between the athletes with different specializations in generalized blocks. As a result of the factor analysis conducted by the method of principal components, we obtained interpretable load matrices, which revealed the specific factors reflecting a certain physical quality.

During the study, we restricted ourselves to isolating and analyzing two main factors having high factor loads regarding some variables and low factor loads regarding the others. Such a model is referred to as a simple structure of the phenomenon under study. It helps evaluate the ratio of the identified factors and their contribution to the overall result. In Table 4, the statistically significant indicators of factor loads are highlighted in bold for the purpose of inclusion in the component analysis.

Table 4. Factor loads regarding special working capacity indices in speed sprint and all-round skaters

In Factor I, determining 35% of the total sample variance, the greatest factor load in the group of speed sprint skaters was detected in a complex of morphological and functional indicators. This factor associates the body dimensions with the ability to perform muscular work of the highest intensity in a short time. In Factor II (27% of the total sample variance), the greatest factor load was observed in a set of parameters that associate specific characteristics (that is, referred to a body mass unit). This includes the power and cost-effectiveness of intensive work, as well as the fat component, but with a negative sign. Thus, Factor II can be defined as a specific power factor in terms of the optimal morphological state of the sprinters.

A different picture of the factor load distribution regarding working capacity indices was observed in the all-around skaters group. In Factor I, determining 31% of the total sample variance, the greatest load during testing was exerted by the power indicators, as well as a set of bioenergy parameters that ensure continuous performance of submaximal loads. This factor can be defined as integral working capacity when performing specific skating activities with its adequate energy supply. In Factor II (24% of the total sample variance), it is the morphological indicators and strength abilities in jumping exercises that have the largest factor weight rate. This included the body length and weight, as well as the muscle component of the body weight, total jumping power, and one/ two leg jump time.

Conclusion. The factor analysis (with both of the groups virtually identical in the age structure and sports qualification, though having different qualifications) found significant intergroup differences in the special physical working capacity indices. The speed sprint skaters were characterized by a set of parameters, where the overall dimensions, anaerobic performance and speed-strength qualities prevailed. For the all-round skaters with a focus on long-distance running in both training and competitive activities, of great importance were the components associated with the ability to perform strenuous work for a long time. The nature of energy supply and morphological characteristics of the athletes conform to such conditions.

References

1. Kubatkin V.P. Dinamika pokazateley rabotosposobnosti pri dolgovremennoy adaptatsii konkobezhtsev k trenirovochnyim nagruzkam [Dynamics of performance indicators under long-term adaptation of speed skaters to training loads]. Teoriya i praktika fiz. kultury. 2006. no. 11. pp. 26-31.
2. Shirkovets E.A., Titlov A.Yu., Lunkov S.M. Kriterii i mekhanizmy upravleniya podgotovkoy sportsmenov v tsiklicheskikh vidakh sporta [Criteria and mechanisms for cyclical athletes training management]. Vestnik sportivnoy nauki. 2013. no. 5.pp. 67-70.
3. Asmussen E., Klausen K. Lactate production and anaerobic work capacity after prolonged exercise. Acta physiol. scand., 1994, 90, N  4. pp.731-742.
4. Komi V., Rusco H. Anaerobic performance capacity in athletes. Acta physiol. scand.,-1998, 100, N 1.pp. 107-114.
5. Stromme S., Ingjer F., Meen H. Assessment of maximal aerobic power specifically trained athletes. J. Appl. Physiol, 1997,42, N6.pp.833- 837.      

Corresponding author: titlov.161059@yandex.ru

Abstract

The article analyzes the skaters’ working capacity rates obtained in standard laboratory conditions. The physical fitness of the athletes was rated by stepped tests till refusal, with the test time determined by the actual functionality rates of the athletes. The tests included analyses of the exhale and blood lactate at every stage of the tests to estimate the maximal power and aerobic/ anaerobic thresholds. The speed-strength qualities were rated by a strain gauge platform, with the maximal leg extension strength and one/ two leg jump time fixed in the tests. Sampled for the study were 24 elite skaters qualified MS to WCMS and having the close track records, including 12 sprinters and 12 skaters specializing in the classical all-round events. The tests found significant differences in the sample anthropometric characteristics, strength and functionality test indices. The multi-factorial group test data analysis (with both of the groups virtually identical in the sport specialization, age structure and qualifications) found significant intergroup differences in the special physical working capacity indices.