PhD N.Y. Palchikova¹
Dr.Hab., Professor S.S. Dobrovolsky¹
PhD E.A. Gonchar^1
1Far Eastern State Academy of Physical Culture, Khabarovsk

Keywords: model, modelling, training, bandy, junior players, psychophysical performance rates.

Background. Training process in bandy may be efficient conditional on large volumes of data being collected to rate different aspects of athlete's fitness; with the data being processed and analysed on a systemic basis to find logics in a “successful” bandy player training process; build up staged individual athletic training models; apply the models for the categorical athletic fitness forecasts; identify the individually most efficient training tools etc. [3].

It is a common knowledge that the individual psychophysical statuses of the players may be of serious effect on the team competitive performance, and this is the reason why today a high priority is given to the efforts to find the best qualitative correlations of individual physical, technical, mental and emotional performance rates most effective for competitive teamwork and apply them for the training process design and management [2].

Athletic training models for different skill levels may be efficiently designed using neural networks. Such networks are efficient in forecasting variations in the subject process or system [3], with the forecasts designed based on regressive correlations of the expected result (deliverable) versus a variety of athlete's fitness rates (input data), with traditional methods including analysis and synthesis, deduction and induction, monitoring, tests, systemisation, classification, intuitive foresight, hypothesis, analogies, extrapolation etc. being applied. Intuitive foresight, for instance, is commonly acknowledged as pivotal for any expert valuation.

Athletic training process in bandy may be described as a complex staged system with the athlete’s actions and mental and emotional statuses being not always measurable and correctable enough [2]. Therefore, the training system needs to be made customisable for the provisionally “successful” and “less successful” junior players with the relevant training process management models designed to offer the best progress paths for the players’ motor skills being efficiently mastered and excelled at every stage of the training system, with the currently most efficient training tools and methods being applied.

Objective of the study was to assess benefits of the new training model in application to “successful” junior bandy players to improve the athletic training system efficiency.

Methods and structure of the study. The study data were processed by Neuro Pro and Deduktor software toolkits, with 12 mental and emotional performance parameters (aggression, stress, anxiety, balance, energy, self-control, inhibition rates etc.) tested and supported by the test data generated by Vibramed express-test system. [1]. In addition, the following methods were applied: vibration image analysing Vibramed method that gives the means to profile, on a non-interference basis, the individual mental and emotional statuses in a training process, with the head micro-movements and vestibular-emotional reflexes being fixed and statistically analysed [3, 4]; mental status test method using Omega C computerised system to rate a variety of abilities by the following: adaptation to physical load rate; integral physical fitness rate; stress rate; autonomic system index; energy supply rate etc.; and expert valuation method to rate the athletes’ competitive performance.

Subject to the study were 22 athletes of 15-16 years of age from the Khabarovsk Territorial Bandy Development Centre, the two-times winners of the Russian Wicker Ball Club Cup Competitions; Russian Champions; Russian Bandy Federation Cup winners; International Reebok Cup winners; and World Cup winners. Based on the prior performance test data, the junior players were split up into provisionally “successful” and “less successful” groups, followed by the players’ mental and physical statuses tested in the competitive periods.

Study results and discussion. The prior performance tests found statistically insignificant intergroup differences in the athletes' fitness rates. The special physical qualities and technical fitness rating (30m and 60m skating skills) tests showed the “successful” group being 2.5% and 2.9% faster (Р≤0.05) than the “less successful” group.  The “successful” group was also 5.2% and 3.8% (Р≤0.05) better in the difficult technique performance (pole dribbling with the right and left hands with throws on goal) tests versus the “less successful” group. Furthermore, the “successful” group was also 7.8% (Р≤0.05) better in the agility (6x9m shuttle skating) test; and 3.5% better in the special endurance (10x200m figure-of-eight skating) test; with the intergroup differences being statistically significant.

Generally, the “successful” group speed qualities, skating and stick and ball handling techniques are so high and stable that they do not need to focus on them in competitive trainings for success, since the excellent skills are natural and mandatory for the players of this qualification. The highest priority in this group is normally given to the special endurance and speed-strength qualities in association with due tactical training of the players, plus some critical mental and emotional status control abilities. The “less successful” players are typically less skilled in the skating and stick handling aspects and, therefore, still in need of special technical and tactical training.

In the mental and emotional status control rates, we found the following statistically significant differences: the “successful” group was 4.3% better in the self-control and 4.7% in the vitality rates; 5.4% better in the energy supply rates; 5.8% better in the adaptation to physical load rates (Р≤0.05); 6.2% higher in the inhibition rates; and 11% better in the stress rate (Р≤0.05) versus the “less successful” group. A set of the post-match tests showed speed-strength endurance, agility, complex technique performance skills, vitality, self-control, inhibition and energy supply rates in the “successful” group being more stable versus the “less successful” group.

Furthermore, we applied the neuro-networking software tools to develop a successful player staged training model customisable for a specific competitive training process. The model was used to generate a set of the key psychophysical qualities to be improved in the athletes for the desired competitive success. Most important for the specific competitive training stage were the following qualities of the junior athletes: excellent skating and stick handling skills; agility and special endurance; adaptability to physical load; energy supply; high self-control; optimal vitality; and low stress rates. Therefore, the model yielded the practical qualities and skills of the junior athletes of special variable importance for the competitive successes at the long-term training process stages. The progress forecasting capacity of the new model was tested by the actual rates being analysed versus the forecast rates generated by the model.

In the model piloting experiment, we applied the Deduktor software in the “what if” format to profile and forecast progress paths of the “less successful” athletes to attain the “success” rates in the most important game performance aspects. The model piloting experiment in the “what if” format generated the key data for the junior athletes’ training systems and the data were used to individualise the systems to attain the model characteristics of successful athletes. The forecast data were tested in practice by the training model applied to excel the junior athletes’ training process.

The contributions of different factors to the competitive success, as profiled by the neuro-networking method in application to the junior athletes having close track records, made it possible to identify deficiencies in the traditional bandy education and training systems and take necessary corrective actions to design infividual progress paths for the sport excellence process and competitive success.

Conclusion. The new model piloting experiment made it possible to offer the individual sport excellence plans for young athletes to form a team of evenly “successful” players. It was found that the innovative training tools, when applied on a timely and efficient basis, make it possible to step up the training process efficiency and respond, on an integrated basis, to variations in the physical fitness and mental and emotional statuses of the athletes to attain the highest possible competitive team success.

References

1. Minkin V.A., Nikolaenko N.N. Primenenie tekhnologii i sistemy vibroizobrazheniya dlya analiza dvigatelnoy aktivnosti i issledovaniya funktsionalnogo sostoyaniya organizma [Vibroimage technology and system to analyze motor activity and functional state of the body]. Meditsinskaya tekhnika, 2008, no. 4, pp. 30-34.
2. Fateeva O.A. Metodika povysheniya effektivnosti tekhniki bega na konkakh khokkeistov s myachom 12-15 let. Dis. kand. ped. nauk [Methods to increase efficiency of running technique of bandy players aged 12-15 years. PhD diss.]. Khabarovsk, 2007, 159 p.
3. Shustin B.N. Modelirovanie v sporte (Teoreticheskie osnovyi i prakticheskaya realizatsiya). Avtoref. dis. dokt. ped. nauk [Modelling in sports (Theoretical foundations and practical implementation). Doct. diss. abstract. Moscow, 1995, 82 p.

Corresponding author: dobrovolsky@list.ru

Abstract        

Modelling process is known to provide efficient tools for the training process design and control. The study addresses the base logics in the junior players’ ways to success and offers a training model to help attain the required physical, technical, mental and emotional progress and control abilities. Subject to the study were 22 athletes of 15-16 years of age split up into provisionally “successful” and “less successful” groups. The individual performance profiling data were processed by Neuro Pro and Deduktor software toolkits, with 12 mental and emotional performance rates obtained and analysed; with the test data being processed by the vibration image analysing Vibramed method; plus the mental status test method using Omega C computerised system; and the expert valuation method were applied in the study. The test data and analyses demonstrated benefits of the new model as verified by the training process efficiency improvements found by the combined tests and trainees’ physical, mental and emotional performance controls, with the individual and team progress confirmed by the practical competitive accomplishments. The training model piloting experiment made it possible to offer the individual sport excellence plans for the young athletes to attain the highest possible competitive team success.