Annotation

The article provides the algorithm of individualization of the general physical fitness of professional ice hockey players in accordance with the team’s physical fitness model, which consists of the creation of a physical preparedness model on a testing results basis and individual profiles of athletes’ general physical preparedness, their comparison, and individualization of loads by correction of volume, taking into account peculiarities of professional hockey players’ motor abilities manifestation.

Introduction

The effectiveness of competitive activity in most sports largely depends on the level of general physical fitness of athletes. The training loads of modern sports have reached their maximum values, which makes the problem of their rational dosing extremely urgent. In these conditions, the individualization of the training process is recognized by expertsas a promising area of professional athletes’ preparation (Zh.L. Kozina et al.).

Effective management of the training process is possible only on the basis of feedback – the objective information about the level of development of the basic motor abilities of athletes. The main tool for obtaining this information in sports is the testing (M.A. Godik, R.W. Earle).

The results of a survey of 101 ice hockey practitioners [2, 7] allow us to conclude that the majority of coaches underestimate the testing of general physical fitness as a training process management tool. In most Russian and Belorussian clubs, there is no unified off-ice testing program, and there is no consistency in its application. In professional ice hockey, it is common for coaches not to test the players at all. The training loads are subjectively regulated by the coaches. This approach significantly reduces the effectiveness of the training process and does not contribute to the realization of the players’ potential.

In this regard, an important task is the systematization of testing methods and means, the development of criteria for assessing the level of general physical fitness, the creation of a team’s physical fitness model, as well as the development of an algorithm of the training process individualization.

Methods

Experimental approach to the problem

In the process of the literature analysis, no objective test was found to assess aerobic endurance, which would not require maximum effort and the results of which would not depend on the level of motivation of the subjects. Most of the tests used in sports to evaluate this component are maximal, and therefore the results highly depend on the degree of motivation of the subjects or are inconvenient for simultaneous testing of a large number of athletes (any ice hockey team), or are laboratory and therefore are not practical. As a result of theoretical analysis and research, the test 3.000 meters run at HR 160 bpm was chosen [3, 5, 7]. The basis of the test is the assumption (V.P. Karpman) that the anaerobic threshold (AT) is more informative than VO_2max due to the higher correlation of the former with athletic performance (N.D. Altukhov, V.N. Seluyanov). With identical HR, an athlete with a higher VO_2max will show superior performance in the aerobic zone. HR 160 bpm corresponds to the average value of ice hockey players’ AT. It was determined in the research with the participation of 64 professional KHL players [3, 5, 7]. The graphoanalytic method was also used to determine the correspondence of AT, VO_2max, and the test 3.000 meters run at HR 160 bpm execution time [2]. Afterwards, the RAMP test on a cycle ergometer was performed, where individual AT and VO_2max was determined. The data obtained were processed statistically and approximated in Microsoft Excel. The levels of AT and VO_2max were determined as reference points, and a 2nd-order polynomial was used as an approximating function. The approximation was carried out by the Gauss–Newton optimization method.

As a result, formulas for prediction AT (1) and VO_2max (2) based on the running time were obtained.

AT = -516.55x² + 756.15x - 108.65, (1)

where х – 3.000 meter at HR 160 bpm running time

VO_2max = -175.51x² + 190.94x + 0.3689 (2)

The use of this test allows to:

- exclude the influence of athletes’ motivation on the test result, thereby objectively assessing their aerobic endurance;

- reduce the load during the test and systematically retest the subjects without overloading them;

- compare the players’ performance;

- track changes in the athletes’ aerobic endurance levels throughout the competition period. The test 3.000 meters run at HR 160 bpm meets such test requirements as reliability and validity and can be used in professional sports [3, 5].

While designing a training program for experimentation, the question of the effectiveness of players’ speed, strength, and speed-strength abilities transfer from off-ice to on-ice performance arose (A.S. Pavlov, V.P. Savin). In order to find the answer, a study on the interconnection of speed, strength, and speed-strength abilities of professional hockey players on-ice and off-ice was conducted [10]. A very strong correlation was found between off-ice speed in the test 30 meters sprint and on-ice speed in the test 27.5 meters sprint skating forward (R= 0.91). A strong correlation was found between speed-strength (the broad jump test) and speed abilities off-ice (R= - 0.84) and on-ice (R= - 0.77). A moderate correlation was revealed between maximal isometric strength (isometric mid-thigh pull test) and speed abilities of ice hockey players off-ice (R= - 0.54) and on-ice (R= - 0.64). The revealed relationships between 11 indicators of speed, speed-strength, and strength abilities supplement the ideas of transference of physical abilities from off-ice to on-ice, and allowed us to shift to the experiment.

The pedagogical experiment was conducted in the period from December 14, 2015, to February 8, 2016, with the participation of players of the hockey club Vitebsk according to the algorithm of individualization of the general physical fitness of professional ice hockey players in accordance with the team’s physical fitness model (Figure 1). 

Figure 1.The algorithm of individualization of the general physical fitness of professional ice hockey players in accordance with the team’s physical fitness model

The first step was to create a testing battery for professional hockey players. According to the results of factor analyses of hockey players’ general fitness (M.V. Pankov, V.V. Filatov, S.C. Nightingale), the most significant physical abilities are: coordination, strength, speed, speed-strength, and both aerobic and anaerobic endurance. Based on this information and on the literature review (M.A. Godik, L.P. Matveev, V.N. Platonov, B. Epley, et al.), an optimal testing program for professional hockey players from the point of view of the author of this work was developed (Table 1). It contains one test for each physical ability except coordination. Each component of coordination abilities requires a separate test [4, 6-9], therefore, according to the recommendations of specialists (R. Lalibert, P. Twist, A.W. Sharp), two components were selected. Obtained testing results of a large sample of professional KHL hockey players allowed us to develop assessment scales for each test. The variation values were determined as follows (M.A. Godik):

x ± 0.5 = average,

x + 2𝛔 very high,

x – 2𝛔 very low.

Subjects

30 professional ice hockey players 16–20 years old: 18 forwards and 12 defensemen. Based on the pretest results, an experimental (EG) and control group (CG) of 15 participants each were formed with no significant difference between the groups (P≥0.05). As a result of the theoretical analysis of the experiment strategy, it was decided to focus on improving physical abilities that don’t meet the team’s model. It was assumed that this approach allows to balance intra-team interactions (A.K. Lukashevsky). In accordance with the chosen strategy, the team's physical fitness model was formed as the mean value of each test (Table 1). According to the literature review (C.A. Geithner, H-S. Song, J.D. Vescovi) and the opinion of a reputable ice hockey coach (R. Krueger), in modern ice hockey there is no significant difference in the level of physical abilities development between defenders and forwards. Hence, the participants weren’t separated by their playing position.

Table 1. The testing battery and the team’s physical fitness model

Physical abilities	Test	Team’s model
		EG	CG
Coordination	1. The BalanceBoard balance maintenance 30 seconds 2. 4×9 meters shuttle run	21 floor touch 9.21 sec	21 floor touch  9.28 sec
Strength	3. Isometric mid-thigh pull	212 kg	219 kg
Speed	4. 30 meters sprint 4А. 5 meters sprint 4B. Flying 10 meters sprint (20 meters build-up)	4.37 sec 1.12 sec 1.21 sec	4.37 sec 1.11 sec 1.22 sec
Speed-strength	5. Broad jump	245 cm	246 cm
Aerobic endurance	6. 3.000 meters run at HR 160 bpm	15:38 min:sec	15:42 min:sec
Anaerobic endurance	7. 4×50 meters shuttle run	33.23 sec	33.13 sec

Based on the team’s model, individual physical fitness profiles of EG participants were created (Figure 2). 

1 – isometric mid-thigh pull, 2 – broad jump, 3 – 30 meters sprint, 4 – 5 meters sprint, 5 – flying 10 meters sprint (20 meters build-up), 6 – 3.000 meters run at HR 160 bpm, 7 – 4×50 meters shuttle run, 8 – 4×9 meters shuttle run, 9 – the BalanceBoard balance maintenance 30 sec, red color – the team’s physical fitness model, blue color – the pretest results (December 14, 2015)

Figure 2. The pretest individual physical fitness profiles of the EG participants

Table 2. Training volume (min)

Participant	Balance	Agility	Speed	Speed-Strength	Strength	Endurance	Total
1. К-й М.	352	152	152	108	210	240	1214
2. С-о С.	352	152	152	108	420	400	1584
3. П-в А.	160	152	152	108	210	400	1182
4. Е-в М.	160	344	152	108	210	400	1374
5. Б-в Н.	352	152	152	180	420	240	1496
6. С-о В.	160	152	344	108	420	240	1424
7. И-н К.	160	152	152	108	210	400	1182
8. Д-ч В.	160	344	152	180	420	400	1656
9. К-в А.	160	344	344	108	420	240	1616
10. Б-в А.	352	152	344	180	210	240	1478
11. Ш-о И.	160	152	344	180	210	240	1286
12. Д-в И.	352	344	344	108	420	400	1968
13. Д-в Е.	352	152	344	180	420	240	1688
14. К-ч Н.	160	344	344	180	210	240	1478
15. О-й Л.	352	344	344	180	420	400	2040
EG participants, x̅	250	229	254	142	322	315	1511
CG participants, ȳ	256	240	240	168	336	400	1640

Table 3. The pretest and posttest results

Test	Dec 14, 2015		Feb 08, 2016		Significance level, Р
	EG(n=15)	CG(n=15)	EG(n=15)	CG(n=15)
	x̅1 ± Sx̅	ȳ1 ± Sȳ	x̅2 ± Sx̅	ȳ2± Sȳ	x̅1 – ȳ1	x̅2 – ȳ2	x̅1 – x̅2	ȳ1 – ȳ2
The BalanceBoard balance maintenance 30 seconds, floor touches	21.27 ±1.30	21.67 ±1.20	5.13 ±1.03	5.67 ±1.05	≥0.05	≥0.05	≤0.05	≤0.05
4×9 meters shuttle run, sec	9.18 ±0.08	9.28 ±0.08	8.90 ±0.08	9.29 ±0.07	≥0.05	≤0.05	≤0.05	≥0.05
Isometric mid-thigh pull, kg	211.93 ±9.12	218.60 ±10.53	226.60 ±8.77	229.67 ±10.47	≥0.05	≥0.05	≤0.05	≤0.05
30 meters sprint, sec	4.37 ±0.04	4.37 ±0.03	4.32 ±0.04	4.60 ±0.04	≥0.05	≤0.05	≤0.05	≤0.05
5 meters sprint, sec	1.12 ±0.01	1.11 ±0.01	1.08 ±0.01	1.26 ±0.01	≥0.05	≤0.05	≤0.05	≤0.05
Flying 10 meters sprint, sec	1.21 ±0.01	1.22 ±0.01	1.21 ±0.02	1.27 ±0.02	≥0.05	≤0.05	≥0.05	≤0.05
Broad jump, cm	244.67 ±3.47	246.40 ±2.69	250.60 ±2.99	234.60 ±3.21	≥0.05	≤0.05	≤0.05	≤0.05
3.000 meters run at HR 160 bpm, min:sec	15:38 ±0:20	15:42 ±0:18	15:22 ±0:24	15:19 ±0:17	≥0.05	≥0.05	≥0.05	≤0.05
4×50 meters shuttle run, sec	33.23 ±0,35	33.13 ±0.28	32.95 ±0.34	35.53 ±0.46	≥0.05	≤0.05	≥0.05	≤0.05

Discussion
The performed training load had a different effect on the physical fitness of EG and CG participants. In the tests 4×9 meters shuttle run, 30 meters sprint, 5 meters sprint, flying 10 meters sprint, broad jump, and 4×50 meters shuttle run, the results of CG on average decreased, while participants of EG showed improvements (Figure 3). In these tests, EG players demonstrated significantly superior results (P≤0.05).

Figure 3. The pretest to posttest results changes

The positive dynamics from the pretest to the posttest was registered in the test the BalanceBoard balance maintenance, isometric mid-thigh pull, 3.000 meters run at HR 160 bpm in both groups. However, no significant differences were revealed between the groups (P≥0.05).

Based on the posttest results, the individual fitness profiles of the EG participants were created (Figure 4). They allow to visually assess the degree of change in indicators under the influence of the training load.

1 – isometric mid-thigh pull, 2 – broad jump, 3 – 30 meters sprint, 4 – 5 meters sprint, 5 – flying 10 meters sprint (20 meters build-up), 6 – 3.000 meters run at HR 160 bpm, 7 – 4×50 meters shuttle run, 8 – 4×9 meters shuttle run, 9 – the BalanceBoard balance maintenance 30 sec, red color – the team’s physical fitness model, blue color – the pretest results (December 14, 2015), green color – the posttest results (February 08, 2016)

Figure 4. The pretest and posttest individual physical fitness profiles of the EG participants

A significant difference in the individual profiles of EG participants before applying the algorithm of individualization of the general physical fitness of professional ice hockey players in accordance with the team’s physical fitness model can be seen in Figure 5. Its application contributed not only to a significant improvement of agility, speed, speed-strength abilities, and anaerobic-glycolytic endurance but also allowed to level the physical fitness of professional hockey players of the team to increase the effectiveness of intra-team interactions (A.K. Lukashevsky).

1 – isometric mid-thigh pull, 2 – broad jump, 3 – 30 meters sprint, 4 – 5 meters sprint, 5 – flying 10 meters sprint (20 meters build-up), 6 – 3.000 meters run at HR 160 bpm, 7 – 4×50 meters shuttle run, 8 – 4×9 meters shuttle run, 9 – the BalanceBoard balance maintenance 30 sec

Figure 5. Comparison of the pretest (left image) and posttest (right image) individual physical fitness profiles of the EG participants