6 research outputs found
The relations of motor, functional and metabolic abilities and competitive performance of elite soccer players measured by the method of motion analysis software system "tracking motion"
Π£ ΠΎΠ²ΠΎΠΌ ΠΈΡΡΡΠ°ΠΆΠΈΠ²Π°ΡΡ, Π½Π° ΠΎΡΠ½ΠΎΠ²Ρ ΠΏΡΠΈΠΌΠ°ΡΠ½ΠΎΠ³ ΡΠΈΡΠ° Π΄Π΅ΡΠΈΠ½ΠΈΡΠ°Π½Π΅ ΡΡ ΠΌΠΎΡΠΎΡΠΈΡΠΊΠ΅, ΡΡΠ½ΠΊΡΠΈΠΎΠ½Π°Π»Π½Π΅, ΠΌΠ΅ΡΠ°Π±ΠΎΠ»ΠΈΡΠΊΠ΅ ΠΈ ΡΠ°ΠΊΠΌΠΈΡΠ°ΡΡΠΊΠ΅ ΠΏΠ΅ΡΡΠΎΡΠΌΠ°Π½ΡΠ΅ Π²ΡΡ
ΡΠ½ΡΠΊΠΈΡ
ΡΡΠ΄Π±Π°Π»Π΅ΡΠ°. ΠΠ° ΠΎΡΠ½ΠΎΠ²Ρ ΡΠ΅ΠΊΡΠ½Π΄Π°ΡΠ½ΠΈΡ
ΡΠΈΡΠ΅Π²Π° ΡΡ ΡΡΠ²ΡΡΠ΅Π½Π΅ ΡΠ΅Π»Π°ΡΠΈΡΠ΅ ΠΌΠΎΡΠΎΡΠΈΡΠΊΠ΅, ΡΡΠ½ΠΊΡΠΈΠΎΠ½Π°Π»Π½Π΅ ΠΈ ΠΌΠ΅ΡΠ°Π±ΠΎΠ»ΠΈΡΠΊΠ΅ ΠΏΡΠΈΠΏΡΠ΅ΠΌΡΠ΅Π½ΠΎΡΡΠΈΠΈ ΡΠ° ΡΠ°ΠΊΠΌΠΈΡΠ°ΡΡΠΊΠΎΠΌ ΠΏΠ΅ΡΡΠΎΡΠΌΠ°Π½ΡΠΎΠΌ.
Π£ ΠΈΡΡΡΠ°ΠΆΠΈΠ²Π°ΡΡ ΡΠ΅ ΡΡΠ΅ΡΡΠ²ΠΎΠ²Π°Π»ΠΎ 70 ΠΈΡΠΏΠΈΡΠ°Π½ΠΈΠΊa ΠΈΠ· ΡΡΠ΄Π±Π°Π»ΡΠΊΠΈΡ
ΠΊΠ»ΡΠ±ΠΎΠ²Π°, ΡΠ»Π°Π½ΠΎΠ²Π° ΠΠ΅Π»Π΅Π½ Π‘ΡΠΏΠ΅Ρ ΠΠΈΠ³Π΅ Π‘ΡΠ±ΠΈΡΠ΅ ΠΈ Π½Π°ΡΠΈΠΎΠ½Π°Π»Π½Π΅ ΡΠ΅Π½ΠΈΠΎΡΡΠΊΠ΅ ΡΡΠ΄Π±Π°Π»ΡΠΊΠ΅ ΡΠ΅Π»Π΅ΠΊΡΠΈΡΠ΅.
ΠΠ΅ΡΠ½ΠΈ ΠΎΠΏΡΠ΅Π³ Π΄Π΅ΡΠΈΠ½ΠΈΡΠ°Π½ ΡΠ΅ Π½Π° ΠΎΡΠ½ΠΎΠ²Ρ 57 Π²Π°ΡΠΈΡΠ°Π±Π»ΠΈ, ΠΏΠΎΠ΄Π΅ΡΠ΅Π½ΠΈΡ
Ρ 5 Π΄ΠΈΠΌΠ΅Π½Π·ΠΈΡΠ° ΠΊΠΎΡΠ΅ ΡΠ΅ ΠΎΠ΄Π½ΠΎΡΠ΅ Π½Π° ΡΠ°Π·Π»ΠΈΡΠΈΡΠ΅ ΠΊΠ°ΡΠ°ΠΊΡΠ΅ΡΠΈΡΡΠΈΠΊΠ΅ ΠΈ ΡΠΏΠΎΡΠΎΠ±Π½ΠΎΡΡΠΈ ΡΡΠ΄Π±Π°Π»Π΅ΡΠ° ΠΈ ΡΠΎ: 1) ΠΌΠΎΡΡΠΎΠ»ΠΎΡΠΊΠ΅ ΠΊΠ°ΡΠ°ΠΊΡΠ΅ΡΠΈΡΡΠΈΠΊΠ΅; 2) ΠΌΠΎΡΠΎΡΠΈΡΠΊΠ΅ ΡΠΏΠΎΡΠΎΠ±Π½ΠΎΡΡΠΈ; 3) ΡΡΠ½ΠΊΡΠΈΠΎΠ½Π°Π»Π½Π΅ ΡΠΏΠΎΡΠΎΠ±Π½ΠΎΡΡΠΈ; 4) ΠΌΠ΅ΡΠ°Π±ΠΎΠ»ΠΈΡΠΊΠ΅ ΡΠΏΠΎΡΠΎΠ±Π½ΠΎΡΡΠΈ; 5) ΡΠ°ΠΊΠΌΠΈΡΠ°ΡΡΠΊΠ΅ ΠΏΠ΅ΡΡΠΎΡΠΌΠ°Π½ΡΠ΅; ΠΏΠΎΠΊΡΠΈΠ²Π°ΡΡΡΠΈ ΠΏΡΠΎΡΡΠΎΡ ΠΎΠΏΡΡΠΈΡ
, ΡΠΏΠ΅ΡΠΈΡΠΈΡΠ½ΠΈΡ
ΠΈ ΡΠΏΠ΅ΡΠΈΡΠ°Π»Π½ΠΈΡ
ΡΠΏΠΎΡΠΎΠ±Π½ΠΎΡΡΠΈ Π²ΡΡ
ΡΠ½ΡΠΊΠΈΡ
ΠΈΠ³ΡΠ°ΡΠ° ΡΡΠ΄Π±Π°Π»Π°.
ΠΠ° ΠΏΡΠΎΡΠ΅Π½Ρ ΠΌΠΎΡΡΠΎΠ»ΠΎΡΠΊΠΈΡ
, ΠΌΠΎΡΠΎΡΠΈΡΠΊΠΈΡ
, ΡΡΠ½ΠΊΡΠΈΠΎΠ½Π°Π»Π½ΠΈΡ
ΠΈ ΠΌΠ΅ΡΠ°Π±ΠΎΠ»ΠΈΡΠΊΠΈΡ
ΠΊΠ°ΡΠ°ΠΊΡΠ΅ΡΠΈΡΡΠΈΠΊΠ° ΠΈ ΡΠΏΠΎΡΠΎΠ±Π½ΠΎΡΡΠΈ, ΠΊΠΎΡΠΈΡΡΠ΅Π½Π° ΡΠ΅ ΡΡΠ°Π½Π΄Π°ΡΠ΄ΠΈΠ·ΠΎΠ²Π°Π½Π° ΠΎΠΏΡΠ΅ΠΌΠ° Ρ Π»Π°Π±ΠΎΡΠ°ΡΠΎΡΠΈΡΡΠΊΠΈΠΌ ΠΈ ΡΠ΅ΡΠ΅Π½ΡΠΊΠΈΠΌ ΡΡΠ»ΠΎΠ²ΠΈΠΌΠ°.
ΠΠ° ΠΏΡΠΎΡΠ΅Π½Ρ ΡΠ°ΠΊΠΌΠΈΡΠ°ΡΡΠΊΠ΅ ΠΏΠ΅ΡΡΠΎΡΠΌΠ°Π½ΡΠ΅, ΠΊΠΎΡΠΈΡΡΠ΅Π½ ΡΠ΅ ΡΠΎΡΡΠ²Π΅ΡΡΠΊΠΈ ΡΠΈΡΡΠ΅ΠΌ Π·Π° ΠΏΡΠ°ΡΠ΅ΡΠ΅ ΠΊΡΠ΅ΡΠ°ΡΠ° ΠΠΠΠΠ Π¦, ΡΠΎΠΏΡΡΠ²Π΅Π½Π΅ ΠΏΡΠΎΠΈΠ·Π²ΠΎΠ΄ΡΠ΅ (Tracking Motion Software System by BioIRC, Kragujevac).
ΠΠ° ΠΎΡΠ½ΠΎΠ²Ρ Π΄ΠΎΠ±ΠΈΡΠ΅Π½ΠΈΡ
ΠΌΠ°ΡΠ΅ΠΌΠ°ΡΠΈΡΠΊΠΈΡ
ΠΌΠΎΠ΄Π΅Π»Π°, Π³Π΄Π΅ ΡΡ ΠΎΠΏΠΈΡΠ°Π½Π΅ Π·Π°Π²ΠΈΡΠ½ΠΎΡΡΠΈ ΠΏΠ΅ΡΡΠ΅Π½ΡΠΈΠ»Π½Π΅ Π΄ΠΈΡΡΡΠΈΠ±ΡΡΠΈΡe ΠΈ Π΄Π΅ΡΠΊΡΠΈΠΏΡΠΈΠ²Π½ΠΈΡ
Π²ΡΠ΅Π΄Π½ΠΎΡΡΠΈ Π·Π° ΡΠ°Π·Π»ΠΈΡΠΈΡΠ΅ ΠΏΠΎΠΊΠ°Π·Π°ΡΠ΅ΡΠ΅ ΠΏΡΠΈΠΏΡΠ΅ΠΌΡΠ΅Π½ΠΎΡΡΠΈ, Π΄Π΅ΡΠΈΠ½ΠΈΡΠ°Π½ ΡΠ΅ Π±Π°Π·ΠΈΡΠ½ΠΈ, ΡΠΏΠ΅ΡΠΈΡΠΈΡΠ½ΠΈ ΠΈ ΡΠΏΠ΅ΡΠΈΡΠ°Π»Π½ΠΈ Π½ΠΈΠ²ΠΎ ΡΠ°Π·Π²ΠΈΡΠ΅Π½ΠΎΡΡΠΈ Π΄Π°ΡΠ΅ ΡΠΏΠΎΡΠΎΠ±Π½ΠΎΡΡΠΈ, ΡΠ° Π°ΡΠΏΠ΅ΠΊΡΠ° ΡΠ΅Π»Π°ΡΠΈΠ²Π½ΠΈΡ
ΠΈ Π°ΠΏΡΠΎΠ»ΡΡΠ½ΠΈΡ
Π²ΡΠ΅Π΄Π½ΠΎΡΡΠΈ ΡΠΏΠΎΡΠΎΠ±Π½ΠΎΡΡΠΈ Π²ΡΡ
ΡΠ½ΡΠΊΠΈΡ
ΡΠΏΠΎΡΡΠΈΡΡΠ°.
Π£ΡΠ²ΡΡΠΈΠ²Π°ΡΠ΅ Π½ΠΈΠ²ΠΎΠ° ΠΈ ΡΠΌΠ΅ΡΠ° ΡΠ΅Π»Π°ΡΠΈΡΠ° ΠΈΠ·ΠΌΠ΅ΡΡ ΠΊΡΠΈΡΠ΅ΡΠΈΡΡΠΊΠΈΡ
Π·Π°Π²ΠΈΡΠ½ΠΈΡ
ΠΈ Π½Π΅Π·Π°Π²ΠΈΡΠ½ΠΈΡ
Π²Π°ΡΠΈΡΠ°Π±Π»ΠΈ, ΡΠΏΡΠΎΠ²Π΅Π΄Π΅Π½ΠΎ ΡΠ΅ ΡΠ΅Π΄Π½ΠΎΠ΄ΠΈΠΌΠ΅Π½Π·ΠΈΠΎΠ½Π°Π»Π½ΠΈΠΌ ΠΈ Π²ΠΈΡΠ΅Π΄ΠΈΠΌΠ΅Π½Π·ΠΈΠΎΠ½Π°Π»Π½ΠΈΠΌ ΠΊΠΎΡΠ΅Π»Π°ΡΠΈΡΠ°ΠΌΠ°- Π»ΠΈΠ½Π΅Π°ΡΠ½ΠΎΠΌ ΠΈ ΠΡΠ»ΡΠΈΠΏΠ»Π° ΡΠ΅Π³ΡΠ΅ΡΠΈΠ²Π½ΠΎΠΌ Π°Π½Π°Π»ΠΈΠ·ΠΎΠΌ. ΠΠ΅Π½Π΅ΡΠ°Π»Π½ΠΈ Π½ΠΈΠ²ΠΎ ΠΊΠΎΡΠ΅Π»Π°ΡΠΈΡΠ΅ ΠΈΠ·ΠΌΠ΅ΡΡ ΠΏΠΎΡΠΌΠ°ΡΡΠ°Π½ΠΈΡ
ΠΏΡΠΎΡΡΠΎΡΠ° ΡΠΏΠΎΡΡΡΠΊΠ΅ ΠΏΠ΅ΡΡΠΎΡΠΌΠ°Π½ΡΠ΅, ΠΌΠΎΡΠΎΡΠΈΡΠΊΠ΅, ΡΡΠ½ΠΊΡΠΈΠΎΠ½Π°Π»Π½Π΅ ΠΈ ΠΌΠ΅ΡΠ°Π±ΠΎΠ»ΠΈΡΠΊΠ΅ ΠΏΡΠΈΠΏΡΠ΅ΠΌΡΠ΅Π½ΠΎΡΡΠΈ ΡΡΠ΄Π±Π°Π»Π΅ΡΠ°, ΡΠ° ΡΠ°ΠΊΠΌΠΈΡΠ°ΡΡΠΊΠΎΠΌ ΠΏΠ΅ΡΡΠΎΡΠΌΠ°Π½ΡΠΎΠΌ ΡΠ΅ Π΄Π΅ΡΠΈΠ½ΠΈΡΠ°Π½ ΠΌΠ΅ΡΠΎΠ΄ΠΎΠΌ Π»ΠΈΠ½Π΅Π°ΡΠ½Π΅ ΡΠ΅Π³ΡΠ΅ΡΠΈΡΠ΅. ΠΠ΅ΡΠΈΠ½Π° ΠΈΠ·ΡΠ°ΡΡΠ½Π°ΡΠΈΡ
ΠΌΠΎΠ΄Π΅Π»Π° ΠΈΠΌΠ° Π²ΠΈΡΠΎΠΊ ΠΏΡΠ΅Π΄ΠΈΠΊΡΠΈΠ²Π½ΠΈ Π½ΠΈΠ²ΠΎ ΠΎΠ΄ ΠΏΡΠ΅ΠΊΠΎ 80% ΠΈ Π²ΠΈΡΠΎΠΊΠΎ ΡΡ ΡΡΠ°ΡΠΈΡΡΠΈΡΠΊΠΈ Π·Π½Π°ΡΠ°ΡΠ½ΠΎ ΠΎΠΏΠΈΡΠ°Π»ΠΈ ΠΌΠ΅ΡΠ΅Π½Π΅ Π²Π°ΡΠΈΡΠ°Π±Π»Π΅, ΠΎΠ΄Π½ΠΎΡΠ½ΠΎ ΠΌΠ΅ΡΠ΅Π½ΠΈ ΠΏΡΠΎΡΡΠΎΡ. ΠΠ° ΡΠ°Ρ Π½Π°ΡΠΈΠ½ ΡΠ΅ ΠΈΠ·Π²ΡΡΠ΅Π½ΠΎ Π΄ΠΈΡΠ°Π³Π½ΠΎΡΡΠΈΡΠΈΠΊΠΎΠ²Π°ΡΠ΅ ΠΈ Π½ΠΎΡΠΌΠΈΡΠ°ΡΠ΅ Π°ΠΊΡΡΠ΅Π»Π½ΠΎΠ³ ΡΡΠ°ΡΠ° Π΄Π°ΡΠΎΠ³ ΠΏΡΠΎΡΡΠΎΡΠ° ΠΌΠ΅ΡΠ΅ΡΠ° Π·Π° ΠΈΡΠΏΠΈΡΠΈΠ²Π°Π½Ρ ΠΏΠΎΠΏΡΠ»Π°ΡΠΈΡΡ. Π Π΅Π·ΡΠ»ΡΠ°ΡΠΈ ΠΎΠ²ΠΎΠ³ ΠΈΡΡΡΠ°ΠΆΠΈΠ²Π°ΡΠ° ΡΠ° Π°ΡΠΏΠ΅ΠΊΡΠ° Π΄Π΅ΡΠΈΠ½ΠΈΡΠ°Π½ΠΈΡ
ΠΏΠ΅ΡΡΠΎΡΠΌΠ°Π½ΡΠΈ, ΡΡΠ²ΡΡΠ΅Π½ΠΈΡ
ΡΠ΅Π»Π°ΡΠΈΡΠ° Ρ ΡΠ°ΠΊΡΠΎΡΡΠΊΠΎΡ ΡΡΡΡΠΊΡΡΡΠΈ, Π½ΠΈΠ²ΠΎΠ° ΡΠ°Π·Π²ΠΈΡΠ΅Π½ΠΎΡΡΠΈ, ΡΡΠΈΡΠ°ΡΠ° ΠΈ ΠΏΠΎΠ²Π΅Π·Π°Π½ΠΎΡΡΠΈ ΠΈΠ½Π΄ΠΈΠΊΠ°ΡΠΎΡΠ° Π·Π° ΠΏΡΠΎΡΠ΅Π½Ρ Π½ΠΈΠ²ΠΎΠ° ΠΈ Π²ΡΡΡΠ° ΠΏΡΠΈΠΏΡΠ΅ΠΌΡΠ΅Π½ΠΎΡΡΠΈ, Ρ ΠΎΠ΄Π½ΠΎΡΡ Π½Π° ΡΠ°Π·Π»ΠΈΡΠΈΡΠ΅ Π³ΡΡΠΏΠ΅ ΠΈΠ³ΡΠ°ΡΠ°, ΡΠΎΡ Π²ΠΈΡΠ΅ Π½Π°Π³Π»Π°ΡΠ°Π²Π°ΡΡ ΡΡΠΈΡΠ°Ρ Π°Π΄Π°ΠΏΡΠ°ΡΠΈΡΠ΅ Π·Π° ΡΠ°Π·Π»ΠΈΡΠΈΡΠΎ ΠΈΡΠΏΠΎΡΠ°Π²Π°ΡΠ΅ ΠΏΡΠΈΠΏΡΠ΅ΠΌΡΠ΅Π½ΠΎΡΡΠΈ ΠΈΠ³ΡΠ°ΡΠ°, Π°Π»ΠΈ ΠΈ ΠΏΠΎΠ²Π΅Π·Π°Π½ΠΎΡΡΠΈ ΡΠΏΠΎΡΡΡΠΊΠ΅ Π³ΡΠ°Π½Π΅ ΠΈ ΠΏΡΠΎΠ΄ΡΠΊΡΠΈΡΠ΅ ΡΠ°Π·Π»ΠΈΡΠΈΡΠΈΡ
Π²ΠΈΠ΄ΠΎΠ²Π° ΠΏΡΠΈΠΏΡΠ΅ΠΌΠ΅...The primary aim of this research defines motor, functional, metabolic and competitorβs performances of elite soccer players. On the basis of the secondary aims, relations of motor, functional and metabolic preparedness and competitorβs performance are determined.
The research was conducted on 70 examinees from soccer clubs, the members of Jelen Super League Serbia and senior national soccer team.
Measurement range was defined on the basis of 57 variable divided into 5 dimensions which referred to different soccer playerβs performances: 1) morphological characteristics; 2) motor performances (abilities); 3) functional performances (abilities); 4) metabolic performances; 5) competitorβs performances; covering the area of general, specific and special performances of elite soccer players.
In order to estimate morphological, motor, functional and metabolic performances, standardized equipment was used, in laboratory and conditions in the field, i.e. standard measuring and test, sophisticated devices.
In order to estimate competitorsβ performances, an in-house motion tracking software system BioIRC was used.
On the basis of the acquired mathematical models, which describe dependencies of percentile distribution and descriptive values for different preparedness indicators, we defined basic, specific and special level of development of the given ability from the aspect of relative and absolute values of performances (abilities) of elite soccer players.
Determination of level and direction of relations between criterion dependent and independent variables was conducted with one-dimensional and multi-dimensional correlations β Thompsonβs and Multiple regression analysis. General level of correlation among the observed spaces of sport performances, motor, functional and metabolic preparedness of soccer players, with competitorΒ΄s performance was defined with linear regression method. Most calculated models had high predicative level of over 80% and in statistically meaningful manner described measured variables; that is, measured space.
In that way, diagnosis and standardization of the actual state of the given measured space was conducted for the examined population. From the aspect of defined performances, relations determined in the factor structure, level of development, the influence and connection of indicators for estimation of the level and type of preparedness in relation to different groups of players, the results of this research further emphasize the influence of adaptation for different manifestation of playersβ preparedness, but also the connection of sport and production of different types of preparation.
On a general level, and in relation to the primary aim of this study, by defining the level of different performances and types of preparedness of elite soccer players, it is possible to establish a system for diagnostic purposes, for training recommendations and prognostics..
The relations of motor, functional and metabolic abilities and competitive performance of elite soccer players measured by the method of motion analysis software system "tracking motion"
Π£ ΠΎΠ²ΠΎΠΌ ΠΈΡΡΡΠ°ΠΆΠΈΠ²Π°ΡΡ, Π½Π° ΠΎΡΠ½ΠΎΠ²Ρ ΠΏΡΠΈΠΌΠ°ΡΠ½ΠΎΠ³ ΡΠΈΡΠ° Π΄Π΅ΡΠΈΠ½ΠΈΡΠ°Π½Π΅ ΡΡ ΠΌΠΎΡΠΎΡΠΈΡΠΊΠ΅, ΡΡΠ½ΠΊΡΠΈΠΎΠ½Π°Π»Π½Π΅, ΠΌΠ΅ΡΠ°Π±ΠΎΠ»ΠΈΡΠΊΠ΅ ΠΈ ΡΠ°ΠΊΠΌΠΈΡΠ°ΡΡΠΊΠ΅ ΠΏΠ΅ΡΡΠΎΡΠΌΠ°Π½ΡΠ΅ Π²ΡΡ
ΡΠ½ΡΠΊΠΈΡ
ΡΡΠ΄Π±Π°Π»Π΅ΡΠ°. ΠΠ° ΠΎΡΠ½ΠΎΠ²Ρ ΡΠ΅ΠΊΡΠ½Π΄Π°ΡΠ½ΠΈΡ
ΡΠΈΡΠ΅Π²Π° ΡΡ ΡΡΠ²ΡΡΠ΅Π½Π΅ ΡΠ΅Π»Π°ΡΠΈΡΠ΅ ΠΌΠΎΡΠΎΡΠΈΡΠΊΠ΅, ΡΡΠ½ΠΊΡΠΈΠΎΠ½Π°Π»Π½Π΅ ΠΈ ΠΌΠ΅ΡΠ°Π±ΠΎΠ»ΠΈΡΠΊΠ΅ ΠΏΡΠΈΠΏΡΠ΅ΠΌΡΠ΅Π½ΠΎΡΡΠΈΠΈ ΡΠ° ΡΠ°ΠΊΠΌΠΈΡΠ°ΡΡΠΊΠΎΠΌ ΠΏΠ΅ΡΡΠΎΡΠΌΠ°Π½ΡΠΎΠΌ.
Π£ ΠΈΡΡΡΠ°ΠΆΠΈΠ²Π°ΡΡ ΡΠ΅ ΡΡΠ΅ΡΡΠ²ΠΎΠ²Π°Π»ΠΎ 70 ΠΈΡΠΏΠΈΡΠ°Π½ΠΈΠΊa ΠΈΠ· ΡΡΠ΄Π±Π°Π»ΡΠΊΠΈΡ
ΠΊΠ»ΡΠ±ΠΎΠ²Π°, ΡΠ»Π°Π½ΠΎΠ²Π° ΠΠ΅Π»Π΅Π½ Π‘ΡΠΏΠ΅Ρ ΠΠΈΠ³Π΅ Π‘ΡΠ±ΠΈΡΠ΅ ΠΈ Π½Π°ΡΠΈΠΎΠ½Π°Π»Π½Π΅ ΡΠ΅Π½ΠΈΠΎΡΡΠΊΠ΅ ΡΡΠ΄Π±Π°Π»ΡΠΊΠ΅ ΡΠ΅Π»Π΅ΠΊΡΠΈΡΠ΅.
ΠΠ΅ΡΠ½ΠΈ ΠΎΠΏΡΠ΅Π³ Π΄Π΅ΡΠΈΠ½ΠΈΡΠ°Π½ ΡΠ΅ Π½Π° ΠΎΡΠ½ΠΎΠ²Ρ 57 Π²Π°ΡΠΈΡΠ°Π±Π»ΠΈ, ΠΏΠΎΠ΄Π΅ΡΠ΅Π½ΠΈΡ
Ρ 5 Π΄ΠΈΠΌΠ΅Π½Π·ΠΈΡΠ° ΠΊΠΎΡΠ΅ ΡΠ΅ ΠΎΠ΄Π½ΠΎΡΠ΅ Π½Π° ΡΠ°Π·Π»ΠΈΡΠΈΡΠ΅ ΠΊΠ°ΡΠ°ΠΊΡΠ΅ΡΠΈΡΡΠΈΠΊΠ΅ ΠΈ ΡΠΏΠΎΡΠΎΠ±Π½ΠΎΡΡΠΈ ΡΡΠ΄Π±Π°Π»Π΅ΡΠ° ΠΈ ΡΠΎ: 1) ΠΌΠΎΡΡΠΎΠ»ΠΎΡΠΊΠ΅ ΠΊΠ°ΡΠ°ΠΊΡΠ΅ΡΠΈΡΡΠΈΠΊΠ΅; 2) ΠΌΠΎΡΠΎΡΠΈΡΠΊΠ΅ ΡΠΏΠΎΡΠΎΠ±Π½ΠΎΡΡΠΈ; 3) ΡΡΠ½ΠΊΡΠΈΠΎΠ½Π°Π»Π½Π΅ ΡΠΏΠΎΡΠΎΠ±Π½ΠΎΡΡΠΈ; 4) ΠΌΠ΅ΡΠ°Π±ΠΎΠ»ΠΈΡΠΊΠ΅ ΡΠΏΠΎΡΠΎΠ±Π½ΠΎΡΡΠΈ; 5) ΡΠ°ΠΊΠΌΠΈΡΠ°ΡΡΠΊΠ΅ ΠΏΠ΅ΡΡΠΎΡΠΌΠ°Π½ΡΠ΅; ΠΏΠΎΠΊΡΠΈΠ²Π°ΡΡΡΠΈ ΠΏΡΠΎΡΡΠΎΡ ΠΎΠΏΡΡΠΈΡ
, ΡΠΏΠ΅ΡΠΈΡΠΈΡΠ½ΠΈΡ
ΠΈ ΡΠΏΠ΅ΡΠΈΡΠ°Π»Π½ΠΈΡ
ΡΠΏΠΎΡΠΎΠ±Π½ΠΎΡΡΠΈ Π²ΡΡ
ΡΠ½ΡΠΊΠΈΡ
ΠΈΠ³ΡΠ°ΡΠ° ΡΡΠ΄Π±Π°Π»Π°.
ΠΠ° ΠΏΡΠΎΡΠ΅Π½Ρ ΠΌΠΎΡΡΠΎΠ»ΠΎΡΠΊΠΈΡ
, ΠΌΠΎΡΠΎΡΠΈΡΠΊΠΈΡ
, ΡΡΠ½ΠΊΡΠΈΠΎΠ½Π°Π»Π½ΠΈΡ
ΠΈ ΠΌΠ΅ΡΠ°Π±ΠΎΠ»ΠΈΡΠΊΠΈΡ
ΠΊΠ°ΡΠ°ΠΊΡΠ΅ΡΠΈΡΡΠΈΠΊΠ° ΠΈ ΡΠΏΠΎΡΠΎΠ±Π½ΠΎΡΡΠΈ, ΠΊΠΎΡΠΈΡΡΠ΅Π½Π° ΡΠ΅ ΡΡΠ°Π½Π΄Π°ΡΠ΄ΠΈΠ·ΠΎΠ²Π°Π½Π° ΠΎΠΏΡΠ΅ΠΌΠ° Ρ Π»Π°Π±ΠΎΡΠ°ΡΠΎΡΠΈΡΡΠΊΠΈΠΌ ΠΈ ΡΠ΅ΡΠ΅Π½ΡΠΊΠΈΠΌ ΡΡΠ»ΠΎΠ²ΠΈΠΌΠ°.
ΠΠ° ΠΏΡΠΎΡΠ΅Π½Ρ ΡΠ°ΠΊΠΌΠΈΡΠ°ΡΡΠΊΠ΅ ΠΏΠ΅ΡΡΠΎΡΠΌΠ°Π½ΡΠ΅, ΠΊΠΎΡΠΈΡΡΠ΅Π½ ΡΠ΅ ΡΠΎΡΡΠ²Π΅ΡΡΠΊΠΈ ΡΠΈΡΡΠ΅ΠΌ Π·Π° ΠΏΡΠ°ΡΠ΅ΡΠ΅ ΠΊΡΠ΅ΡΠ°ΡΠ° ΠΠΠΠΠ Π¦, ΡΠΎΠΏΡΡΠ²Π΅Π½Π΅ ΠΏΡΠΎΠΈΠ·Π²ΠΎΠ΄ΡΠ΅ (Tracking Motion Software System by BioIRC, Kragujevac).
ΠΠ° ΠΎΡΠ½ΠΎΠ²Ρ Π΄ΠΎΠ±ΠΈΡΠ΅Π½ΠΈΡ
ΠΌΠ°ΡΠ΅ΠΌΠ°ΡΠΈΡΠΊΠΈΡ
ΠΌΠΎΠ΄Π΅Π»Π°, Π³Π΄Π΅ ΡΡ ΠΎΠΏΠΈΡΠ°Π½Π΅ Π·Π°Π²ΠΈΡΠ½ΠΎΡΡΠΈ ΠΏΠ΅ΡΡΠ΅Π½ΡΠΈΠ»Π½Π΅ Π΄ΠΈΡΡΡΠΈΠ±ΡΡΠΈΡe ΠΈ Π΄Π΅ΡΠΊΡΠΈΠΏΡΠΈΠ²Π½ΠΈΡ
Π²ΡΠ΅Π΄Π½ΠΎΡΡΠΈ Π·Π° ΡΠ°Π·Π»ΠΈΡΠΈΡΠ΅ ΠΏΠΎΠΊΠ°Π·Π°ΡΠ΅ΡΠ΅ ΠΏΡΠΈΠΏΡΠ΅ΠΌΡΠ΅Π½ΠΎΡΡΠΈ, Π΄Π΅ΡΠΈΠ½ΠΈΡΠ°Π½ ΡΠ΅ Π±Π°Π·ΠΈΡΠ½ΠΈ, ΡΠΏΠ΅ΡΠΈΡΠΈΡΠ½ΠΈ ΠΈ ΡΠΏΠ΅ΡΠΈΡΠ°Π»Π½ΠΈ Π½ΠΈΠ²ΠΎ ΡΠ°Π·Π²ΠΈΡΠ΅Π½ΠΎΡΡΠΈ Π΄Π°ΡΠ΅ ΡΠΏΠΎΡΠΎΠ±Π½ΠΎΡΡΠΈ, ΡΠ° Π°ΡΠΏΠ΅ΠΊΡΠ° ΡΠ΅Π»Π°ΡΠΈΠ²Π½ΠΈΡ
ΠΈ Π°ΠΏΡΠΎΠ»ΡΡΠ½ΠΈΡ
Π²ΡΠ΅Π΄Π½ΠΎΡΡΠΈ ΡΠΏΠΎΡΠΎΠ±Π½ΠΎΡΡΠΈ Π²ΡΡ
ΡΠ½ΡΠΊΠΈΡ
ΡΠΏΠΎΡΡΠΈΡΡΠ°.
Π£ΡΠ²ΡΡΠΈΠ²Π°ΡΠ΅ Π½ΠΈΠ²ΠΎΠ° ΠΈ ΡΠΌΠ΅ΡΠ° ΡΠ΅Π»Π°ΡΠΈΡΠ° ΠΈΠ·ΠΌΠ΅ΡΡ ΠΊΡΠΈΡΠ΅ΡΠΈΡΡΠΊΠΈΡ
Π·Π°Π²ΠΈΡΠ½ΠΈΡ
ΠΈ Π½Π΅Π·Π°Π²ΠΈΡΠ½ΠΈΡ
Π²Π°ΡΠΈΡΠ°Π±Π»ΠΈ, ΡΠΏΡΠΎΠ²Π΅Π΄Π΅Π½ΠΎ ΡΠ΅ ΡΠ΅Π΄Π½ΠΎΠ΄ΠΈΠΌΠ΅Π½Π·ΠΈΠΎΠ½Π°Π»Π½ΠΈΠΌ ΠΈ Π²ΠΈΡΠ΅Π΄ΠΈΠΌΠ΅Π½Π·ΠΈΠΎΠ½Π°Π»Π½ΠΈΠΌ ΠΊΠΎΡΠ΅Π»Π°ΡΠΈΡΠ°ΠΌΠ°- Π»ΠΈΠ½Π΅Π°ΡΠ½ΠΎΠΌ ΠΈ ΠΡΠ»ΡΠΈΠΏΠ»Π° ΡΠ΅Π³ΡΠ΅ΡΠΈΠ²Π½ΠΎΠΌ Π°Π½Π°Π»ΠΈΠ·ΠΎΠΌ. ΠΠ΅Π½Π΅ΡΠ°Π»Π½ΠΈ Π½ΠΈΠ²ΠΎ ΠΊΠΎΡΠ΅Π»Π°ΡΠΈΡΠ΅ ΠΈΠ·ΠΌΠ΅ΡΡ ΠΏΠΎΡΠΌΠ°ΡΡΠ°Π½ΠΈΡ
ΠΏΡΠΎΡΡΠΎΡΠ° ΡΠΏΠΎΡΡΡΠΊΠ΅ ΠΏΠ΅ΡΡΠΎΡΠΌΠ°Π½ΡΠ΅, ΠΌΠΎΡΠΎΡΠΈΡΠΊΠ΅, ΡΡΠ½ΠΊΡΠΈΠΎΠ½Π°Π»Π½Π΅ ΠΈ ΠΌΠ΅ΡΠ°Π±ΠΎΠ»ΠΈΡΠΊΠ΅ ΠΏΡΠΈΠΏΡΠ΅ΠΌΡΠ΅Π½ΠΎΡΡΠΈ ΡΡΠ΄Π±Π°Π»Π΅ΡΠ°, ΡΠ° ΡΠ°ΠΊΠΌΠΈΡΠ°ΡΡΠΊΠΎΠΌ ΠΏΠ΅ΡΡΠΎΡΠΌΠ°Π½ΡΠΎΠΌ ΡΠ΅ Π΄Π΅ΡΠΈΠ½ΠΈΡΠ°Π½ ΠΌΠ΅ΡΠΎΠ΄ΠΎΠΌ Π»ΠΈΠ½Π΅Π°ΡΠ½Π΅ ΡΠ΅Π³ΡΠ΅ΡΠΈΡΠ΅. ΠΠ΅ΡΠΈΠ½Π° ΠΈΠ·ΡΠ°ΡΡΠ½Π°ΡΠΈΡ
ΠΌΠΎΠ΄Π΅Π»Π° ΠΈΠΌΠ° Π²ΠΈΡΠΎΠΊ ΠΏΡΠ΅Π΄ΠΈΠΊΡΠΈΠ²Π½ΠΈ Π½ΠΈΠ²ΠΎ ΠΎΠ΄ ΠΏΡΠ΅ΠΊΠΎ 80% ΠΈ Π²ΠΈΡΠΎΠΊΠΎ ΡΡ ΡΡΠ°ΡΠΈΡΡΠΈΡΠΊΠΈ Π·Π½Π°ΡΠ°ΡΠ½ΠΎ ΠΎΠΏΠΈΡΠ°Π»ΠΈ ΠΌΠ΅ΡΠ΅Π½Π΅ Π²Π°ΡΠΈΡΠ°Π±Π»Π΅, ΠΎΠ΄Π½ΠΎΡΠ½ΠΎ ΠΌΠ΅ΡΠ΅Π½ΠΈ ΠΏΡΠΎΡΡΠΎΡ. ΠΠ° ΡΠ°Ρ Π½Π°ΡΠΈΠ½ ΡΠ΅ ΠΈΠ·Π²ΡΡΠ΅Π½ΠΎ Π΄ΠΈΡΠ°Π³Π½ΠΎΡΡΠΈΡΠΈΠΊΠΎΠ²Π°ΡΠ΅ ΠΈ Π½ΠΎΡΠΌΠΈΡΠ°ΡΠ΅ Π°ΠΊΡΡΠ΅Π»Π½ΠΎΠ³ ΡΡΠ°ΡΠ° Π΄Π°ΡΠΎΠ³ ΠΏΡΠΎΡΡΠΎΡΠ° ΠΌΠ΅ΡΠ΅ΡΠ° Π·Π° ΠΈΡΠΏΠΈΡΠΈΠ²Π°Π½Ρ ΠΏΠΎΠΏΡΠ»Π°ΡΠΈΡΡ. Π Π΅Π·ΡΠ»ΡΠ°ΡΠΈ ΠΎΠ²ΠΎΠ³ ΠΈΡΡΡΠ°ΠΆΠΈΠ²Π°ΡΠ° ΡΠ° Π°ΡΠΏΠ΅ΠΊΡΠ° Π΄Π΅ΡΠΈΠ½ΠΈΡΠ°Π½ΠΈΡ
ΠΏΠ΅ΡΡΠΎΡΠΌΠ°Π½ΡΠΈ, ΡΡΠ²ΡΡΠ΅Π½ΠΈΡ
ΡΠ΅Π»Π°ΡΠΈΡΠ° Ρ ΡΠ°ΠΊΡΠΎΡΡΠΊΠΎΡ ΡΡΡΡΠΊΡΡΡΠΈ, Π½ΠΈΠ²ΠΎΠ° ΡΠ°Π·Π²ΠΈΡΠ΅Π½ΠΎΡΡΠΈ, ΡΡΠΈΡΠ°ΡΠ° ΠΈ ΠΏΠΎΠ²Π΅Π·Π°Π½ΠΎΡΡΠΈ ΠΈΠ½Π΄ΠΈΠΊΠ°ΡΠΎΡΠ° Π·Π° ΠΏΡΠΎΡΠ΅Π½Ρ Π½ΠΈΠ²ΠΎΠ° ΠΈ Π²ΡΡΡΠ° ΠΏΡΠΈΠΏΡΠ΅ΠΌΡΠ΅Π½ΠΎΡΡΠΈ, Ρ ΠΎΠ΄Π½ΠΎΡΡ Π½Π° ΡΠ°Π·Π»ΠΈΡΠΈΡΠ΅ Π³ΡΡΠΏΠ΅ ΠΈΠ³ΡΠ°ΡΠ°, ΡΠΎΡ Π²ΠΈΡΠ΅ Π½Π°Π³Π»Π°ΡΠ°Π²Π°ΡΡ ΡΡΠΈΡΠ°Ρ Π°Π΄Π°ΠΏΡΠ°ΡΠΈΡΠ΅ Π·Π° ΡΠ°Π·Π»ΠΈΡΠΈΡΠΎ ΠΈΡΠΏΠΎΡΠ°Π²Π°ΡΠ΅ ΠΏΡΠΈΠΏΡΠ΅ΠΌΡΠ΅Π½ΠΎΡΡΠΈ ΠΈΠ³ΡΠ°ΡΠ°, Π°Π»ΠΈ ΠΈ ΠΏΠΎΠ²Π΅Π·Π°Π½ΠΎΡΡΠΈ ΡΠΏΠΎΡΡΡΠΊΠ΅ Π³ΡΠ°Π½Π΅ ΠΈ ΠΏΡΠΎΠ΄ΡΠΊΡΠΈΡΠ΅ ΡΠ°Π·Π»ΠΈΡΠΈΡΠΈΡ
Π²ΠΈΠ΄ΠΎΠ²Π° ΠΏΡΠΈΠΏΡΠ΅ΠΌΠ΅...The primary aim of this research defines motor, functional, metabolic and competitorβs performances of elite soccer players. On the basis of the secondary aims, relations of motor, functional and metabolic preparedness and competitorβs performance are determined.
The research was conducted on 70 examinees from soccer clubs, the members of Jelen Super League Serbia and senior national soccer team.
Measurement range was defined on the basis of 57 variable divided into 5 dimensions which referred to different soccer playerβs performances: 1) morphological characteristics; 2) motor performances (abilities); 3) functional performances (abilities); 4) metabolic performances; 5) competitorβs performances; covering the area of general, specific and special performances of elite soccer players.
In order to estimate morphological, motor, functional and metabolic performances, standardized equipment was used, in laboratory and conditions in the field, i.e. standard measuring and test, sophisticated devices.
In order to estimate competitorsβ performances, an in-house motion tracking software system BioIRC was used.
On the basis of the acquired mathematical models, which describe dependencies of percentile distribution and descriptive values for different preparedness indicators, we defined basic, specific and special level of development of the given ability from the aspect of relative and absolute values of performances (abilities) of elite soccer players.
Determination of level and direction of relations between criterion dependent and independent variables was conducted with one-dimensional and multi-dimensional correlations β Thompsonβs and Multiple regression analysis. General level of correlation among the observed spaces of sport performances, motor, functional and metabolic preparedness of soccer players, with competitorΒ΄s performance was defined with linear regression method. Most calculated models had high predicative level of over 80% and in statistically meaningful manner described measured variables; that is, measured space.
In that way, diagnosis and standardization of the actual state of the given measured space was conducted for the examined population. From the aspect of defined performances, relations determined in the factor structure, level of development, the influence and connection of indicators for estimation of the level and type of preparedness in relation to different groups of players, the results of this research further emphasize the influence of adaptation for different manifestation of playersβ preparedness, but also the connection of sport and production of different types of preparation.
On a general level, and in relation to the primary aim of this study, by defining the level of different performances and types of preparedness of elite soccer players, it is possible to establish a system for diagnostic purposes, for training recommendations and prognostics..
Noninvasive determination of knee cartilage deformation during jumping
The purpose of this investigation was to use a combination of image processing, force measurements and finite element modeling to calculate deformation of the knee cartilage during jumping. Professional athletes performed jumps analyzed using a force plate and high-speed video camera system. Image processing was performed on each frame of video using a color recognition algorithm. A simplified mass-spring-damper model was utilized for determination of global force and moment on the knee. Custom software for fitting the coupling characteristics was created. Simulated results were used as input data for the finite element calculation of cartilage deformation in the athlete's knee. Computer simulation data was compared with the average experimental ground reaction forces. The results show the three-dimensional mechanical deformation distribution inside the cartilage volume. A combination of the image recognition technology, force plate measurements and the finite element cartilage deformation in the knee may be used in the future as an effective noninvasive tool for prediction of injury during jumping
Noninvasive determination of knee cartilage deformation during jumping
The purpose of this investigation was to use a combination of image processing, force measurements and finite element modeling to calculate deformation of the knee cartilage during jumping. Professional athletes performed jumps analyzed using a force plate and high-speed video camera system. Image processing was performed on each frame of video using a color recognition algorithm. A simplified mass-spring-damper model was utilized for determination of global force and moment on the knee. Custom software for fitting the coupling characteristics was created. Simulated results were used as input data for the finite element calculation of cartilage deformation in the athlete's knee. Computer simulation data was compared with the average experimental ground reaction forces. The results show the three-dimensional mechanical deformation distribution inside the cartilage volume. A combination of the image recognition technology, force plate measurements and the finite element cartilage deformation in the knee may be used in the future as an effective noninvasive tool for prediction of injury during jumping