Robotic 'Footbot' training simulator system applicable for footballers' fitness rating, control and improvement

Фотографии: 

ˑ: 

V.Yu. Komkov1
PhD, Associate Professor V.A. Blinov2
Dr.Biol., Professor Y.V. Koryagina3
1LLC «Sport Automatics", Omsk
2Siberian State University of Physical Culture and Sports, Omsk
3North-Caucasian Federal Research and Clinical Center of the Federal Biomedical Agency, Yessentuki

Keywords: competitive performance, technical skills building in football, training simulators.

Background. Football is ranked among the most popular sport disciplines and lately has shown great progress in the game on the whole and its every element in particular including technical mastery; game design and tactical control skills; physical capacities; and determination and volitional qualities of the players, with the game elements being closely interrelated [2, 3].

Modern football development trends may be analyzed based on the competitive performance data of the leading football teams and individual players. Thus, the competitive performance data and analysis of the 2014 FIFA World Championship made it possible to summarize the accomplishments and progress data of the leading football teams, rate physical qualities and technical mastery of the players and analyze the modern game design models and tactics. The sport progress data of the World Championship were discussed at the global forum of football coaches hosted by Saint Petersburg city. The football analysts noted that the game speed and pace have never been so high, with the team success determined by high individual technical mastery, mobility and ball passing skills, particularly short-distance ones [3]. Most of the football analysts, however, recognized that the Russian footballers still lag behind the best foreign players in the game control skills, and this is true both for national elite and youth football sport. Some of the leading Russian sport analysts, having analyzed the national team performance in the 2013 FIFA U-17 World Cup games (for the players under 17 years of age) noted as particularly striking the inadequate technical skills, with too many blunders in passing, receiving and other ball control techniques [4]. The 2015 FIFA U-19 World Cup data and analyses showed once again that a special emphasis in the training process shall be made on the individual technical progress with the training systems designed to develop fast individual responses and teamwork in the rapidly changing game situations, with the skills building component being ranked among the top priorities of the modern youth football [1].

It may be pertinent to mention that the top-ranking global events, as far as the historical progress in the football theory and practice is concerned, have always given a boost to modern football due to the stepwise changes triggered by the innovative training technologies and game concepts.

Objective of the study was to design a football simulator system to secure progress of football players in a variety of aspects including: technical skills, complex responses, action accuracy, positioning skills, response speed, and physical fitness.

Methods and structure of the study. Sport Automatics Company incorporated in the Techno Park business-incubator of the Novosibirsk ‘Academ Park’ has developed the Ball Games Simulator (Model Patent #164165) that is applicable for football skills building purposes to address the above-discussed training issues.

Study results and discussion. The proposed robotic ‘FootBot’ simulator may be described as the training cage equipped with the ball shooting cannons in the center of each of the four walls, with the ball shooting process controllable by the intensity, speed and trajectory. The trainee’s task is to receive, handle and shoot the ball on a colored target as soon as possible. It is common knowledge that the ball control skills are critical for success in football and make it different from many other sport disciplines [1]. The individual tactical and technical performance in every match may be classified as follows (see Figure 1):

Figure 1. Individual tactical and technical performance analysis, %

Figure 2. Technical skills trained using the FootBot simulator

The training simulator makes it possible to train the ball receiving, passing and handling skills on a time-efficient basis, with the player trained to effectively handle the ball as the situation requires; to ensure individual progress in a variety of aspects including ball handling speed, accuracy, response efficiency, positioning skills and game situation analysis; with the special benefits for attention focusing, switchover and control abilities. The training simulator assisted trainings were found beneficial both for the game perception and motor skills and qualities which are always critical for competitive success.

We have also developed an application software to run the tests, rate progress and make recommendations. The simulator-assisted trainings and tests help detect weaknesses in the individual performance that need to be addressed by corrections to the individual training systems. The versatile training process design and management toolkit offered by the software helps make adjustments to the training systems and combine training tools as required by the training process goals and individual training agendas – for instance, competitive performance may be adjusted for individual game roles. The statistical data, reports and analyzes generated by the system are stored in each player’s passport and always available for the coach’s reference online in the selection or post-injury rehabilitation processes.

The ‘FootBot’ training simulator was applied to test the technical performance of the 16-17 year-old (n=19 born in 1999) players trained in one of the leading national football academies, with the test system set as follows: ball cannoning rate of 40km/h; low shooting trajectory; no spin (0o) on the ball; 4 cannons shooting from 4 walls; cannon shooting rate timed to the shots on target (successful or missing); 48 balls were shot in each test, with every ball shot on target after 2-3 handling touches.

It was the shooting pace and accuracy that dominated in the individual performance ratings, with the total technical performance scored by points. Given in Table 1 hereunder are the individual technical performance rates and final ratings of the players.

Table 1. Individual technical performance rates and final ratings

Names

Sessions

Balls shot

Accuracy, %

Pace, s

Total points

Rating

Player 1

3

48

93,75

3,24

56,09

1

Player 2

3

48

90,63

3,1

55,28

2

Player 3

3

48

89,58

3,09

54,88

3

Player 4

3

48

87,5

3,2

53,45

4

Player 5

3

48

84,09

3,09

52,4

5

Player 6

3

48

86,36

3,34

52,35

6

Player 7

3

48

83,33

3,14

51,83

7

Player 8

3

48

85,42

3,37

51,8

8

Player 9

3

48

83,33

3,22

51,5

9

Player 10

3

48

81,82

3,13

51,2

10

Player 11

3

48

77,08

3,09

49,28

11

Player 12

3

48

79,55

3,37

49,16

12

Player 13

3

48

77,08

3,15

48,97

13

Player 14

3

48

73,77

3,03

48,07

14

Player 15

3

48

78,13

3,56

47,8

15

Player 16

3

48

73,44

3,4

46,31

16

Player 17

3

48

71,43

3,23

46,08

17

Player 18

3

48

68,75

3,09

45,5

18

Player 19

3

48

68,75

3,49

43,83

19

Player 20

3

48

66,67

3,4

43,23

20

Player 21

3

48

65,63

3,45

42,57

21

Player 22

3

48

62,5

3,4

41,38

22

Given in Tables 2 and 3 is the detailed individual performance rating test data.

Table 2. Player 19: individual technical performance rating test data

Session

Time, s

Setting

Balls

Accuracy, %

Pace, s

1) Training exercise

80

4 cannons, 360 ̊, low balls

16

62,5

3,46

2) Training exercise

70

4 cannons, 360 ̊, low balls

16

75

3,32

3) Training exercise

70

4 cannons, 360 ̊, low balls

16

87,5

3,29

4) Tests

65

 

U-17 test

16

62,5

2,97

5) Tests

70

 

U-17 test

16

68,75

3,46

6) Tests

70

U-17 test

16

56,25

3,78

Figure 3. Player 19: test data analysis

Note: 1, 2, 3 – training session number; r, l – right and left side, respectively; (6) number of balls shot

Based on the Player 19 test data, the individual technical performance may be rated as follows: of the eight technical skills, only the 180o turn to the left was performed 100% perfect; the 90o+ turns, particularly to the left were the most difficult for the player. The player’s game role is the right forward that means that he has to show the tested technical skills seldom (with 90o+ turns). However, he still has to resort to the skill when the game situation requires and, if untrained, will act either imperfect or unsuccessful and may even lose the ball control. The performance rating test data provided by the FootBot training simulator system may hence be effectively applied to correct deficiencies in the individual technical skills and competitive performance.

Conclusion. Presently in the national science a growing priority is being given to the technical performance of the leading Russian footballers as verified by the above mentioned study reports and analytical findings. The newly designed ‘Footbot’ training simulator was found beneficial as verified by the footballers’ progress in the ball control, receiving and passing skills, shooting speed and accuracy, with the system providing an efficient test toolkit for the real-time fitness and progress rating tests. 

References

  1. Vlasov A.E., Dresvyannikov D.O., Leksakov A.V. et al Yunosheskiy futbol: sostoyanie i trendy. Tekhnicheskiy otchet po rezultatam Chempionata Evropy U-19 v Gretsii I elitnogo otborochnogo raunda v Shvetsii 2015 godu dlya komand igrokov ne starshe 19 let [Youth football: status and trends. Technical report on the results of the European Championship U-19 in Greece and the elite qualifying round in Sweden in 2015 for teams under 19]. Moscow, 2015, pp. 3-15. Available at: http://www.rfs.ru/main/interactive/blogs/blogs_arhive/tx483/8.html
  2. Guba V.P., Leksakov A.V. Teoriya i metodika futbola [Theory and methodology of football]. Moscow: Sovetskiy sport publ., 2013, 536 p.
  3. Ordzhonikidze Z.G., Pavlov V.I. Fiziologiya futbola [Physiology of football]. Moscow: Chelovek, Olimpiya publ., 2008, 240 p.
  4. Sovremenny futbol: sostoyaniei trendy (poitogamChempionatamira FIFA – 2014) [Modern football: state and trends (by the results of FIFA World Cup 2014)]. Available at: http://www.rfs.ru/main/interactive/blogs/blogs_arhive/tx388/8.html
  5. Ekspertny analiz igr na Chempionate mira (igrokikomand ne starshe 18 let /U-17/) [Expert analysis of games of the World Championships (teams under 18 (U-17)], 2013, UAE. Available at: http://www.rfs.ru/res/docs/metod_posob_u17.pdf

Corresponding author: koru@yandex.ru

Abstract

Objective of the study was to design a football simulator to secure progress of football players in a variety of aspects including: technical skills, complex responses, action accuracy, positioning skills, response speed, and physical fitness. Benefits of a robotic ‘Footbot’ training system applied in the technical fitness building component of the Russian footballers’ training systems are discussed and supported by the progress test rates of the 16-17 year-old footballers trained in one of the leading Russian academies. Of special promise and benefits are the ‘Footbot’ training system assisted individualized training options designed to bridge the tested gaps in the individual fitness, rate progress of each player and generate current ratings of the footballers.