1

University of Ljubljana

Faculty of Sport

ANALYSIS OF LOAD AND EFFORT IN

SMALL-SIDED-HANDBALL GAMES

(Analiza obremenitve in napora rokometašev pri

prirejenih igrah glede na prostor in število igralcev)

Doctoral thesis

Promoter: Author:

Associate Professor Marko Šibila, Ph. D. Matteo Corvino

Co-promoter:

Associate Professor Antonio Tessitore, Ph. D.

Ljubljana, 2016

I declare that the scientific study entitled “Analysis of load and effort in small-sided-handball

games” is the result of my scientific research.

Matteo Corvino

Matteo Corvino

ANALYSIS OF LOAD AND EFFORT IN SMALL-SIDED-HANDBALL GAMES

University of Ljubljana, Faculty of Sport, Ljubljana, 2016

Pages 119, tabels: 25, figures: 22, references: 166

ANALIZA OBREMENITVE IN NAPORA ROKOMETAŠEV PRI PRIREJENIH IGRAH

GLEDE NA PROSTOR IN ŠTEVILO IGRALCEV

Univerza v Ljubljani, Fakulteta za šport, Ljubljana, 2016

Strani 119, tabele: 25, slike: 22, viri: 166

Keywords: handball; sport-specific training; video analysis; Global Positioning System

(GPS);

ANALYSIS OF LOAD AND EFFORT IN SMALL-SIDED-HANDBALL GAMES

Matteo Corvino

ABSTRACT

Objectives. The aim of this study was to investigate the effect of three different court

dimensions on the internal and external load during two types of small-sided handball games.

Methods. Eight male amateur handball players took part in this study and participated in

three different 8-min 3vs3 (plus goalkeepers) and three different 8-min 4vs4 (plus

goalkeepers) small-sided handball games (each repeated twice). The three court dimensions

for both drills, were 12×24m, 30×15m and 32×16m. Through Global Positioning System

devices (SPI pro elite 15 Hz, GPSports) and video analysis, the following parameters were

recorded: cyclic and acyclic movements (distance covered and number of technical actions

executed), heart rate, and rating of perceived exertion (RPE).

Results. – Total distance travelled increased with court dimensions in both the experimental

conditions. The analysis of distance covered in the four speed zones (0–1.4 m/s; 1.4–3.4 m/s;

3.4–5.2 m/s; >5.2 m/s) highlighted substantial differences: during 3vs3, playing with the

30×15m court in comparison to the 24×12m, the players covered less distance in the first

speed zone and more distance in the second and third speed zones (p<0.05; moderate ES).

Statistical differences were also found between the 3vs3 played on the 24×12m courts respect

to the 32×16m one: the players covered more distance in the second and third speed zones

with the 32×16m court in comparison to the 24×12m (p<0.05; moderate ES). Similar trend

was found during the 4vs4 drills. In these experimental conditions, the pitch dimensions

24×12m players achieved significantly higher value of distances in the first speed class and

significantly lower values in the third speed class compared with the matches played on the

courts of the other two dimensions (p<0.05; moderate ES). There was no significant effect of

court dimensions for both drills on the technical parameters (number of team actions, passes,

shoots, pistons movements toward goal and defensive activities), the number of specific

handball jumps and changes of direction, and the time spent in the different heart rate zones.

The rating of perceived exertion was significantly higher during the 3vs3 with the 32×16m

court compared with the 24×12m one (p<0.05; large ES). In matches with a greater number of

players (4vs4), court dimension had no significant effect on the assessment of perceived

exertion (RPE). With the comparison of the data obtained on the drills in the two

experimental conditions (3vs3 and 4vs4) in all three court dimensions, it is found that there is

no significant difference in the total distance travelled. Significant differences were shown in

the third speed class, where the higher value was achieved in the all court dimension of the

4vs4 drill (p<0.05; moderate ES). There was no significant difference in the frequency of

occurrence of the technical and tactical elements and specific handball jumps, changes of

direction; the effort assessment (heart rate and perceived exertion) did not underlined

statistical differences between the 3vs3 and 4vs4 small-sided handball games in all the

experimental conditions.

Conclusions. Our findings indicate that changing court dimensions during small-sided

handball games can be used to manipulate both external and internal loads on the players.

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CONTENT

1. INTRODUCTION..........................................................................................................8

1.1 Handball story.................................................................................................................8

1.2 Handball performance.....................................................................................................9

1.3 Male handball player’s characteristics..........................................................................12

1.4 Small-sided games in soccer.........................................................................................15

1.5 Small-sided games in rugby..........................................................................................17

1.6 Small-sided games in basketball...................................................................................18

1.7 Small-sided games in other team sports........................................................................20

1.8 Small-sided games vs. classic running drills.................................................................21

1.9 Small-sided games in handball......................................................................................23

2. TOPIC AND PROBLEM IDENTIFICATION...........................................................27

3. HYPOTHESIS..............................................................................................................27

4. METHODS...................................................................................................................29

4.1 Sample description........................................................................................................29

4.2 Parameters.....................................................................................................................29

4.3 Experimental procedures...............................................................................................32

4.4 Sample evaluation.........................................................................................................40

4.5 Statistical analysis.........................................................................................................44

5. RESULTS.....................................................................................................................46

5.1 Sample assessment........................................................................................................46

5.2 Analysis of load and effort in 3vs3 small sided games................................................48

5.3 Analysis of load and effort in 4vs4 small sided games................................................51

5.4 Analysis of load and effort in 3vs3 compared to 4vs4 small sided games...................53

6. DISCUSSION..............................................................................................................55

6.1 Sample analysis.............................................................................................................55

6.2 3vs3 small-sided handball games..................................................................................56

6.3 4vs4 small-sided handball games..................................................................................62

6.4 Comparison of the two type of small-sided handball games........................................67

7. CONCLUSION............................................................................................................72

7.1 Conclusions and practical implications.........................................................................72

7.2 New relevant findings...................................................................................................74

7.3 Proposals for further researches and views for the future............................................76

8. REFERENCES.............................................................................................................78

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9. OBSEŽEN POVZETEK V SLOVENŠČINI..............................................................105

9.1 Uvod.........................................................................................................................105

9.2 Cilji in hipoteze........……………………………………………………………….107

9.3 Metode dela..............................................................................................................108

9.4 Rezultati…………..………………………………………………………………..110

9.5 Razprava………….………………………………………………………………..117

9.6 Zaključek…………...………………………………………………………………118

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1. INTRODUCTION

1.1 Handball story

Handball is nowadays one of the most practiced sports in Europe. With a great geographic

differentiation, handball is becoming the second sport in Europe after football (soccer). The

great development of this sport has originated in Nordic countries (like Denmark, Sweden

and Germany), even if also countries as France, Hungary, Spain, Croatia, Romania, Slovenia

and Poland have professional championships since many years.

Parallel with the growth of handball in Europe, also the interest of sport science community

about this sport increased. From a scientific point of view, until the 90’s there was a lack of

specific knowledge concerning several aspects of handball. For instance, the training was

mainly based on coaches experiences (empirical level) with a conspicuous transfer of

information by similar team sports like soccer and basketball. In fact, handball coaches were

used to adopt the great number of scientific literature published on conditioning training

issues in soccer and basketball to build their drills, training sessions and long term planning.

On the other hand they were also frequently using information from the track and field

disciplines which were somehow connected to handball to develop explosive and elastic

strength (jump and throw power), sprint abilities, aerobic and anaerobic endurance.

Hence, scientific research on Handball start to appear in peer-reviewed journals during the

80s, with most of the studies focused on injury issues. In those years the only exception from

this trend of interest on prevention and treatment of injuries was the study of Delamarch,

Gratas, Beillot, Dassonville, Rochcongar and Lessard (1987), published on the International

Journal of Sports Medicine about the assessment of the anaerobic metabolism of handball

players and a first “physiological” analysis provided during a game. After years of research

focused only of traumatological aspects, in 1996 a new study on handball performance

investigated the heart rate of male players during matches (Loftin, Anderson, Lytton, Pittman

& Warren, 1996). Furthermore, this study showed also data about the maximal oxygen

consumption measured by means of an indirect method. In 1997, the first technical/tactical

study was published on a scientific journal: Apitzsch and Liu (1997) investigated the

correlation between field dependence-independence and handball shooting by Swedish

national male handball players. The authors analyzed all the Sweden male national team

matches at the ’94 European Handball Championship; in particular, field-goal shooting

attempts and shooting efficiency of each players were calculated. The results of this study

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were not statistically significant and the experimental approach had limitations in the sample

dimension and homogeneity. The study of Apitzsch and Liu of 1997 was followed along the

years by other studies focused on the analysis of handball performance by a tactical point of

view: in particular the influence of the attack tactics on the match result (Rogulj, Shroj V. &

Shroj, L., 2004; Srhoj, Rogulj, Padovan & Katic, 2001), the strategies of the goalkeeper

(Gutierrez-Davila, Rojas, Ortega, Campos & Parraga, 2011), the handball players trajectories

(Barros, Menezes, Russomanno, Misuta, Brandão, Figueroa, Leite & Goldenstein, 2011), the

handball penalty shot (Bourne, Bennett, Haye & Williams, 2011), the offensive efficiency

(Moncef, Dagbaji, Abdallah & Mohamed, 2011), the effects of game location, period and

quality of opposition (Olivera, Gómez & Sampaio, 2012), the home advantages (Gutiérrez

Aguilar, Saavedra García & Fernández Romero, 2012) and the defensive system (Debanne &

Lafaye, 2014) were analyzed. Furthermore, in 2012, the first study with a complete

technical/tactical match analysis in handball, was published on a scientific journal (Bilge,

2012): average number of attacks, attack efficiency, shot efficiency, average fast break goals

per game, fast break efficiency, goalkeeper efficiency, average goalkeeper saves per game,

average number of exposures to foul per game, and differences in the ratios of position throws

(wing, pivot, back court, break-through, fast break, and 7-meter) to all goals were examined.

At the end of 90s, following the trend of other team sports researches, studies on handball

training analysis starts to develop. In 1997, Jensen, Jacobsen, Hetland and Tveit investigated

for the first time the effect of combined strength and sprint training on maximal oxygen

uptake, isometric strength and sprint performance in female elite handball players during a

season. After the study of Jensen et al. (1997), many others researchers focused on several

aspects of handball training, as strength (Carvalho, Mourão & Abade, 2014; Chelly,

Hermassi, Aouadi & Shephard, 2014; Cherif, Said, Chaatani, Nejlaoui, Gomri & Abdallah,

2012; Gorostiaga, Izquierdo, Iturralde, Ruesta & Ibáñez, 1999; Hermassi, Chelly, Fathloun

& Shephard, 2010; Hermassi, Chelly, Tabka, Shephard & Chamari, 2011; Hermassi, van den

Tillaar, Khlifa, Chelly & Chamari, 2015; Ignjatovic, Markovic & Radovanovic, 2012; Jansen,

Schmidtbleicher & Cabri, 2007; Luteberget, Raastad, Seynnes & Spencer, 2015; Marques

& González-Badillo, 2006; Saeterbakken, van den Tillaar & Seiler, 2011; Tyrdal & Pettersen,

1998; Wagner & Müller, 2008), endurance (Bucheit, Laursen, Kuhnle, Ruch, Renaud

& Ahmaidi, 2009a; Bucheit, Lepretre, Behaegel, Millet, Cuvelier & Ahmaidi, 2009b; Bucheit,

Mendez-Villanueva, Quod, Quesnel & Ahmaidi, 2010; Iacono, Eliakim & Meckel, 2015) and

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stretching (Zakas, A., Vergou, Grammatikopoulou, Zakas, N., Sentelidis & Vamvakoudis,

2003) ones.

The development of always new technology for performance analysis in sport, has determined

an increase of the number of studies focused on notational and time motion analyses in

handball (and sports in general). These new technology allowed not only the classical

physiological analysis of the match (i.e. Heart Rate and Lactate) but also including aspects

related to the different movements and distances covered by players. It was 2002 when

appeared the first study on match analysis in handball (Pers, Bon, Kovacic, Šibila & Dezman,

2002) with an analysis of movements speed and distance covered. The authors found that

players covered on average a distance of 4800 m during the analyzed matches; sprints (speed

>5.2 m/s) amounted to 7% of the playing time, 25% of playing time was spent in fast running

(speed 5.2<3.0 m/s), 31% in slow running (speed 3.0<1.4) and 37% in walking or standing

still (speed <1.4m/s). After this study, a lot of researchers investigated the tactical, technical,

and physical aspects of handball by means of video-match-analysis (Bilge, 2012; Gutiérrez

Aguilar et al., 2012; Gutiérrez & Ruiz, 2013; Karcher & Buchheit, 2014;

Krüger, Pilat, Uckert, Frech & Mooren, 2014; Manchado, Tortosa-Martínez, Vila, Ferragut

& Platen, 2013; Michalsik & Aagaard, 2014; Michalsik, Madsen, & Aagaard, 2014a;

Michalsik, Madsen & Aagaard, 2014b; Michalsik & Aagaard, 2015; Michalsik, Madsen &

Aagaard 2015a; Michalsik, Aagaard & Madsen, 2015b; Moncef, Dagbaji, Abdallah

& Mohamed, 2011; Oliveira, Gómez & Sampaio, 2012; Póvoas,

Seabra, Ascensão, Magalhães, Soares & Rebelo, 2012; Póvoas, Ascensão, Magalhães,

Seabra, Krustrup, Soares & Rebelo, 2014a; Póvoas, Ascensão, Magalhães,

Seabra, Krustrup, Soares & Rebelo, 2014b; Wagner, Finkenzeller, Würth & von Duvillard,

2014).

In the last 10 years, a lot of studies have focused their attention also on the physiological and

anthropometric characteristics of handball players (Bayios, Anastasopoulou, Sioudris

& Boudolos, 2001; Chaouachi, Brughelli, Levin, Boudhina, Cronin & Chamari, 2009; Chelly,

Hermassi & Shephard, 2010; Garcia-Tabar, Llodio, Sánchez-Medina, Ruesta, Ibañez

& Gorostiaga, 2015; Ghobadi, Rajabi, Farzad, Bayati & Jeffreys, 2013; González-Ravé,

Juárez, Rubio-Arias, Clemente-Suarez, Martinez-Valencia & Abian-Vicen, 2014; Gorostiaga,

Granados, Ibáñez & Izquierdo, 2005; Granados, Izquierdo, Ibañez, Bonnabau & Gorostiaga,

2007; Hasan, Reilly, Cable & Ramadan, 2007; Haugen, Tønnessen & Seiler, 2014; Krüger et

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al., 2014; Massuça, Fragoso & Teles, 2014; Massuça, Branco, Miarka & Fragoso, 2015;

Michalsik et al., 2014a; Michalsik et al., 2014b; Milanese, Piscitelli, Lampis & Zancanaro,

2011; Nikolaidis & Ingebrigtsen, 2013; Nikolaidis, Ingebrigtsen, Póvoas, Moss & Torres-

Luque, 2015; Rannou, Prioux, Zouhal, Gratas-Delamarche & Delamarche, 2001; Rogulj,

Srhoj, V., Nazor, Srhoj, L. & Cavala, 2005; Sibila & Pori, 2009; Sporis, Vuleta, D., Vuleta, D.

Jr. & Milanović, 2010; Srhoj, Marinovic & Rogulj, 2002; Vila,

Manchado, Rodriguez, Abraldes, Alcaraz & Ferragut, 2012). In particular some authors

investigated also the differences between players, determined by their playing positions.

These studies have been very important for the development of the concept of specific

training and individualization of load in handball.

1.2 Handball performance

Handball is one of the fastest team sports, characterized by repeated jumps, sprints, changes

in direction, body contact at high speed, and specific technical movement patterns occurring

in response to the varying tactical situations of the game (Karcher & Buchheit, 2014). Being

handball a sport composed by high-intensity actions in alternation with periods of lower

activity, the players’ performance is strongly influenced by the anaerobic glycolytic and

aerobic systems.

The anaerobic glycolytic demands of an handball match has been investigated in some studies

since 2000. Unfortunately, the only way that researchers had to understand the contribution to

the performance of the players’ energetic system, was the measurements of blood lactate,

which has notoriously a lot of limitations, and the different results emerged from the studies

were probably explained by these difficulties. The study of Póvoas (2009) on Portuguese elite

teams, reported mean values of blood lactate of 4.2 ± 2 (range 1.6– 8.6) mmol.l-1

and 3.1 ± 1.8

(1.3–8.4) mmol.l-1

during the first and second halves, respectively. Other studies that were

focused on the measurement of blood lactate at the end of the match, found values of 4.8 ±

1.9 mmol.l-1

in Danish male elite players (Michalsik et al., 2014b) and 8.3 ± 0.9 mmol.l-1

in

adolescent Tunisian players (Chelly, Hermassi, Aouadi, Khalifa, Van den Tillaar, Chamari

& Shephard, 2011). The great limitation of the analysis of blood lactate data is that these are

largely influenced by the activity that players have performed during the last 3-5 minutes

before the sampling. For instance, the occurrence of a great number of high intensity activity

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in this period could modify the results of the test, overestimating the real value. Furthermore,

players with different roles (wings, pivot and backcourt) could probably report different blood

lactate values due to their different demands of the match.

Regarding the aerobic demands of handball performance, there is a general difficulty to

analyse this aspect. Indeed, the best way to analyse the contribution of aerobic system to the

performance of any sports, is the analysis of the oxygen consumption by means of a

metabolimeter, and the use of this tools during official handball match is not allowed (where

it could be during friendly ones). In the majority of the studies published on this aspects, the

aerobic demands were estimated from heart rate (HR) recordings and the associated HR/VO2

relationship established previously during an incremental test (Karcher & Buchheit, 2014).

The estimated average VO2 reached during a game ranged between 70.9 ± 6% (Michalsik et

al., 2014b), 71 ± 6% (Srhoj et al., 2002) and 74 ± 10% (45–92%) (Póvoas, 2009) % of

VO2max.

Analysing directly the HR data, the study of Póvoas, Seabra, Ascensão, Magalhães, Soares

and Rebelo (2012), showed that during handball matches, the players effective mean HR

(considering only the effective time spent by the players on the field) is around 82 ± 9.3 % of

HRmax. Differently, when the authors of this study considered the total mean HR (with also the

time spent by the players on the bench), the values are 72 ± 16.7 %. The successive study of

Kruger et al., (2013), analyzed the HR of handball players during an entire match, dividing

the results in the different roles. Findings of this study underlined the significant different

relative HR during the match for wings and back position (respectively 85.2 ± 5.8 % and 86.4

± 1.8 % of HRmax) respect to the pivot position (83.4 ± 1.0 % of HRmax).

Taken together with the similar blood lactate levels, the lower HR values observed in

handball compared with basketball or soccer suggest that handball may put a relatively

greater emphasis on anaerobic glycolytic energy (Karcher & Buchheit, 2014).

1.3 Male handball player’s characteristics.

Starting from the first study in 2001 of Rannou et al., the physical and physiological

characteristics of handball players were study in various researches. In the majority of this

studies, the first measures investigated were the anthropometric characteristics: height, body

mass, Body Mass Index (BMI) (Ghobadi et al., 2013; Haugen et al. 2014; Kruger et al. 2013;

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Massuça et al., 2015; Michalsik et al., 2014; Srhoj et al., 2002) and percentage of body fat

(Chaouachi et al., 2009; Chelly et al. 2010; Gorostiaga et al., 2005; Massuça et al., 2014;

Nikolaidis & Ingebrigtsen, 2013; Nikolaidis et al., 2015; Sibila and Pori, 2009; Sporis et al.,

2010) were deeply analyzed. An interesting study in 2013 (Ghobadi et al.), analyzed the

height, weight and BMI of all the players involved in the 2013 Men’s Handball World

Championship (409 handball players in 24 handball teams). The authors found the following

mean values: height of 190.1 ± 6.8 Cm, body mass of 92.4 ± 9.8 Kg and BMI of 25.5 ± 2.1.

The studies focused on the anthropometric characteristics of handball players, that detected

also the percentage of body fat, found values from 10.5 ± 5.5% (Massuça et al. 2014) to 18.1

± 3.8% Nikolaidis et al., 2015). Furthermore, some researchers divided their results into the

different playing positions, underlined greater values for height and body mass for back

players and pivot respect to the wings (Haugen et al. 2014; Kruger et al. 2013; Massuça et al.,

2015; Michalsik et al., 2014; Nikolaidis et al., 2015; Sibila & Pori, 2009; Sporis et al., 2010;

Srhoj et al., 2002). After the anthropometric characteristics of height, body mass, BMI and

percentage of body fat, some authors analyzed also the physiological characteristics of

handball players. The most investigated physiological characteristics of handball players were

VO2max (Chaouachi et al., 2009; Michalsik et al., 2014; Rannou et al., 2001; Sporis et al.,

2010), HRmax (Kruger et al., 2013; Sporis et al., 2010) and maximal anaerobic power (Chelly

et al. 2010; Nikolaidis & Ingebrigtsen, 2013; Nikolaidis et al., 2015; Rannou et al., 2001).

From the findings of these studies, emerges the following physiological profile of handball

player: the VO2max ranges from 52.8 ± 5.5 ml*kg*min-1

(Chaouachi et al. 2009) to 58.7 ± 0.9

ml*kg*min-1

(Rannou et al., 2001); the HRmax reached during exhaustive incremental

endurance test ranges from 191 ± 8 bpm (Sporis et al. 2010) to 194 ± 5 bpm (Kruger et al.

2013); the maximal anaerobic power reached during test ranges from 898 ± 220 Watt (Chelly

et al. 2010) to 1172 ± 47 Watt (Rannou et al., 2001). Some authors, in addition to analyze the

anthropometric and physiological characteristics of handball players, focused their researches

on some performance parameters like speed, upper and lower limb strength, jump ability and

flexibility of handball players. In the great part of these studies, the speed of handball players

was assessed by the administration of a 30m maximal sprint test (Chaouachi et al., 2009;

Kruger et al., 2013; Massuça et al. 2014; Massuça et al., 2015; Michalsik et al., 2014): the

handball players mean time during this test varies from 4.22 ± 0.1 sec. (Kruger et al. 2013) to

4.48 ± 0.3 sec. (Massuça et al., 2015). Other than speed of handball players, some authors

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were also interested in analyzing the strength of handball players. Different methods to

assesses this characteristic of handball players were applied: the measurement of handgrip

strength (Massuça et al. 2014; Massuça et al., 2015; Nikolaidis et al., 2015), the one maximal

repetition (1RM) bench press and squat exercises (Chaouachi et al., 2009; Chelly et al. 2010;

Gorostiaga et al., 2005; Haugen et al. 2014), isokinetic tests (Bayios et al., 2001; González-

Ravé et al., 2014) and the indirect method of throwing velocity measurement (Chaouachi et

al., 2009; Chelly et al. 2010; Haugen et al. 2014; Kruger et al., 2013; Michalsik et al., 2014).

The results of the previous mentioned studies on the strength characteristics of the handball

players are resume in the Table 1.

Table 1

Main Strength Characteristics of Handball Players

Characteristic Values (range) Authors

Handgrip 52.6 ± 8.3 - 116.1 ± 14.8 kg Massuça et al. 2015;

Nikolaidis et al., 2015;

Bench press (1RM) 88.5 ± 10.5 - 106.9 ± 11.6 kg Chelly et al. 2010;

Gorostiaga et al., 2005;

Squat (1RM) 131 ± 22 - 177.7 ± 27.5 kg Haugen et al. 2014;

Chaouachi et al., 2009;

Throwing velocity 23.0 ± 1.8 - 28.0 ± 1.5 m/s Chelly et al. 2010;

Haugen et al. 2014;

Another indirect method to assess the strength of the lower limb is the jump ability

evaluation. A lot of researchers measured the height of three types of jumps in handball

players: Squat Jump (SJ), Counter-Movement Jump (CMJ) and CMJ with free arms

movements (Haugen et al. 2014; Kruger et al., 2013; Massuça et al. 2014; Massuça et al.,

2015; Michalsik et al., 2014; Nikolaidis & Ingebrigtsen, 2013; Nikolaidis et al., 2015). The

jump’s height values found by these studies ranges from 33.9 ± 4.8 to 36.6 ± 5.0 cm for the SJ

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(Nikolaidis et al., 2015 - Massuça et al. 2014), from 35.9 ± 5.3 to 43.9 ± 6.0 cm for the CMJ

(Nikolaidis et al., 2015 - Michalsik et al., 2014) and from 43.6 ± 5.6 to 47.1 ± 5.1 cm for the

CMJ with free arms movement (Nikolaidis et al., 2015 - Kruger et al., 2013).

The last handball players characteristic investigated by researchers was the flexibility, by the

administration of the sit and reach test (Nikolaidis & Ingebrigtsen, 2013; Nikolaidis et al.,

2015). The values found by these two study were 21.8 ± 8.7 cm and 23.1 ± 9.1 cm in the sit

and reach test.

1.4 Small-sided games in soccer

In team sports as soccer and rugby, with the aim of developing a specific capacity of players

to perform endurance training related to the game demands, training methods that use the ball

(i.e. small sided games and skill-based conditioning games) have been extensively studied. In

particular, the team sport with a larger number of studies focused on small-sided games

(SSG’s) is soccer. In this sport, one of the first studies on the use of SSG’s was that of Platt,

Maxwell, Horn, Williams and Reilly, (2001) about physiological and technical analysis of

3vs3 and 5vs5 during youth matches.

The scientific literature published during the last fifteen years has reported a high impact of

the SSG’s through the analysis of HR, Rate of Perceived Exertion (RPE) and blood lactate

accumulation. The findings of these studies showed that during a bout of SSG’s, soccer

players were exposed to average heart rates from 82 to 91% of heart rate max (Abrantes,

Nunes, Maçãs, Leite & Sampaio, 2012; Ade, Harley & Bradley, 2014; Aguiar, Botelho, Lago,

Maças & Sampaio 2012; Aguiar, Botelho, Gonçalves & Sampaio, 2013; Aroso, Rebelo &

Gomes-Pereira, 2004; Brandes, Heitmann & Müller, 2012; Campos-Vazquez, Mendez-

Villanueva, Gonzalez-Jurado, León-Prados, Santalla & Suarez-Arrones, 2014; Casamichana,

Suarez-Arrones, Castellano & San Román-Quintana, 2014; Clemente, Wong del P., Martins

& Mendes, 2014; Coutts, Rampinini, Marcora, Castagna & Impellizzeri, 2009; Da Silva,

Impellizzeri, Natali, De Lima, Bara-Filho, Silami-Garçia & Marins, 2011; Dellal, Chamari,

Pintus, Girard, Cotte & Keller, 2008; Dellal, Hill-Haas, Lago-Penas & Chamari, 2011;

Dellal, Varliette, Owen, Chirico & Pialoux, 2012; Fanchini, Azzalin, Castagna, Schena,

Mccall & Impellizzeri, 2011; Halouani, Chtourou, Dellal, Chaouachi & Chamari, 2014;

Harrison, Kilding, Gill & Kinugasa, 2014; Hill-Haas, Dawson, Impellizzeri & Coutts 2011;

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Hoff, Wisløff, Engen, Kemi & Helgerud, 2002; Hoffman, Reed, Leiting, Chiang & Stone,

2014; Jones & Drust, 2007; Katis & Kellis, 2009; Kelly & Drust, 2009; Köklü,

Aşçi, Koçak, Alemdaroğlu & Dündar, 2011; Köklü, 2012; Köklü, Ersöz, Alemdaroğlu, Aşç

& Ozkan, 2012; Köklü, Alemdaroğlu, Dellal & Wong, 2015; Köklü, Sert, Alemdaroğlu

& Arslan, 2015a; Little & Williams, 2006; Little & Williams, 2007; Mallo & Navarro, 2008;

Platt et al., 2001; Rampinini, Impellizzeri, Castagna, Abt, Chamari, Sassi & Marcora, 2007;

Tessitore, Meeusen, Piacentini, Demarie & Capranica, 2006; Tsuda, Shinozaki, Goto &

Takamatsu, 2007; Williams & Owen, 2007). The great part of the studies previous mentioned

reported the HR data also divided in different classes of percentage respect to the HRmax.

Showing data in this way, the researchers found that during the SSG’s the players are exposed

for a big time to a heart rate greater than 90% of HRmax; this data is comparable with the

official match one.

To better analyse the physiological demands of the SSGs in soccer, many studies investigated

also the blood lactate accumulation (Aroso et al., 2004; Brandes et al., 2012; Coutts et al.,

2009; Dellal et al., 2011; Dellal et al., 2012; Fanchini et al., 2011; Harrison et al., 2014; Hill-

Haas et al. 2011; Hoff et al., 2002; Köklü et al., 2011; Köklü et al., 2012; Köklü et al., 2015a;

Köklü, 2012; Platt et al., 2001; Rampinini et al., 2007; Tessitore et al., 2006; Tsuda et al.,

2007). The results of this type of studies showed blood lactate accumulation at the end of

SSG’s ranging from 3 to 8 mmol*l-1

. The variability of this data is probably due to the great

difference of setting of this type of drills, such as bouts duration, number of players, pitch

dimensions, the presence of the goalkeepers and coach’s encouragement.

Another important tool to assess the effort of players consequent to the small sided games, is

the administration of the Rate of Perceived Exertion by means of Borg scales (Borg, 1982).

Among the body of literature that focused on the use of this tool to evaluate the physiological

response of SSG’s (Abrantes et al., 2012; Ade et al., 2014; Aguiar et al., 2013; Campos-

Vazquez et al., 2014; Dellal et al., 2011; Dellal et al., 2012; Halouani et al., 2014; Harrison et

al., 2014; Hill-Haas et al. 2011; Köklü et al., 2015; Köklü et al., 2015a) one particular

research had demonstrate the reliability of RPE on specific SSGs. The study of Coutts et al.

(2009) investigated the correlation of heart rate and blood lactate values with RPE ones

during small-sided soccer games, demonstrating that RPE correlates well with traditional

markers of exercise intensity during soccer-specific SSG’s training. Thus, player’s ratings of

17

perceived exertion may be used within a soccer training session to monitor global exercise

intensity, and help the coach in the control of the training stimulus.

1.5 Small sided games in rugby

The utilization of the small-sided game was not only investigated in soccer but also in other

team sports like rugby, where a lot of studies were focused on this topic. The first study was

that of Gabbett (2002). The findings of this research were that the majority of injuries during

a rugby season were sustained in traditional conditioning activities that involved no skill

components (i.e. running without the ball), while in contrast the incidence of injuries

registered during skill-based conditioning games was lower. Thus the results of Gabbett

(2002) suggest that skill-based conditioning games offer a safe and effective method of

conditioning for rugby league players. Another study focused on the application of small-

sided game in rugby was presented by Gamble (2004). The author investigated the changes in

endurance fitness level of elite rugby union players, undertaking skill-based conditioning

games for a 9-week preseason training period. The findings of this study showed a general

decreasing of heart rate recovery after the end of the test and an increasing of the percentage

of heart rate max at the end of the test. Both HR recovery and % HRmax results are indicative

of advances in training status.

Two years after the study of Gamble (2004) another research of Gabbett (2006) investigated

the skill-based conditioning games in rugby. The aim of this study was to understand if skill-

based conditioning games could be a valid alternative to the traditional conditioning for rugby

players. The researcher found similar changes in agility and VO2max and greater

improvements in speed and muscular power in athletes participating in skill-based

conditioning games in comparison to those participating in traditional conditioning activities.

(Gabbet, 2006). These results demonstrate that skill-based conditioning games offer an

effective method of conditioning for rugby league players.

The study of Foster, Twist, Lamb and Nicholas (2010) was the first small-sided games rugby

study similar to the previous soccer ones: authors focused their attention on the analysis of

SSGs in rugby, in order to investigate the influence of number of players involved and

playing area size on players’ heart rate responses. During this study, rugby players were

involved in 2 repeated trials of six 4-minute conditioned SSG’s over a 2-week period; the

18

SSG’s varied by playing area size (15x25 m, 20x30 m, 25x35 m) and players number (4vs4

and 6vs6). Differently from results published on soccer studies, the results of those focused on

rugby revealed a non significant effect of playing area size on players’ heart rates, while

significant effects were found for the number of players involved with higher heart rate values

in 4vs4 SSGs condition compared to the 6vs6 one (90.6% vs. 86.2% of HRmax). Thus the

findings of the study of Foster et al. (2010) demonstrate that SSGs in rugby generate

physiological responses suitable for aerobic conditioning which, although unaffected by the

size of the playing area are sensitive to the number of players involved. From 2010 until now,

a lot of rugby studies investigated the main characteristics of small-sided games in this sport

(Gabbet, Jenkins & Abernethy, 2010; Gabbet, Abernethy & Jenkins, 2012; Gabbet, Jenkins

& Abernethy, 2012; Johnston, Gabbett & Jenkins, 2014; Johnston, Gabbett, Seibold & Jenkins

2014a; Kennet, Kempton & Coutts, 2012; Sampson, Fullagar & Gabbett, 2015): physiological

and skill demands and the factors affecting exercise intensity (wrestling, bout duration, field

size and physical contact).

1.6 Small-Sided games in Basketball

Another team sports interested by the study of SSGs is basketball. The first study about this

topic was that of Sampaio, Abrantes and Leite (2009): the authors investigated the power,

heart rate and perceived exertion players’ responses during two SSGs conditions in

basketball: 3vs3 and 4vs4. The results of this study emphasized once again the high impact of

SSGs in team sports, with an average HR values greater than 80% of HRmax, which has a

similar trend to that of match. Furthermore analyzing the difference between the two types of

drills investigated in this study, the authors found that the increase in the field dimensions

corresponded to a decrease in physiological demands of the drill. Indeed the 3vs3 analyzed by

Sampaio et al. (2009) was played with a smaller playing area for player respect to the 4vs4

and as a consequence the players involved in the first drill had a greater metabolic demands

express by a greater percentage of HRmax. Following this first study, others authors analyzed

the small-sided games in basketball: in particular Klusemann, Pyne, Foster and Drinkwater

(2012), Atli, Köklü, Alemdaroğlu and Koçak (2013) and Delextrat and Martinez (2014)

investigated the characteristics of small-sided games and the consequences of the

administration of these type of drills on basketball players’. The aim of the first research of

Klusemann et al. (2012), was to understand the influence of number of players (2v2/4v4),

19

court size (half/full court) and work-to-rest ratios (4x2.5 min/2x5 min) on the demands

of small-sided games in basketball. The results of this study confirmed the previous research

of Sampaio et al. (2009), about the high intensity of these type of drills in basketball: authors

found that HR and RPE were moderately higher in 2vs2 respect to the 4vs4 (86±4% vs.

83±5% of HRmax; 8±2 vs. 6±2 RPE values). In 2013, Atli et al., investigated the effect of 2

pitch sizes (full court vs. half court) on HR in basketball players during 3-aside games; the

findings of this study underlined a 9.3% higher HR values on the large pitch size (28x15)

compared with the small pitch size (14x15). The authors of this research, made also a

technical analysis of the small-sided games: significant differences between the two

experimental conditions in the parameters of shots, rebounds, and passes, were found. Thus,

this paper confirmed the majority of the previous findings of small-sided games in team

sports: when the relative court size per player is decreased, the number of technical actions in

the game increase but HR responses decreased.

The study of Delextrat and Martinez (2014) on small-sided games in basketball, compared the

effects of 2 training interventions based on small-sided games (SGG) and high-intensity

interval training (HIT) on physical and technical performance of male

junior basketball players. Before the experimental sessions, players aerobic fitness, repeated

sprint ability (RSA), defensive and offensive agility, upper and lower body power, shooting

and passing skills, were assessed. The main results of this study were that both interventions

resulted in similar improvements in aerobic capacity but RSA was unchanged after both

interventions. Furthermore, compared to HIT, SSG resulted in greater improvements in

defensive agility, shooting skills and upper body power.

The last study on small-sided games in basketball was the research of Conte, Favero,

Niederhausen, Capranica anf Tessitore (2015) about differences in load and effort of 2vs2 in

respect to 4vs4 small-sided games in basketball. The researchers, investigated also any

differences in these two types of drills using continuous or intermittent regimes. The findings

of this study were the higher effort of players during the 2vs2 compared with the 4vs4 (higher

HR and RPE values), and the greater HR values for the continuous protocol in respect of the

intermittent one.

20

1.7 Small-sided games in other team sports

In the wide field of team sports also cricket and volleyball demonstrated interest for the small-

sided games or game-like drills. The study of Vickery, Dascombe, Duffield, Kellett

and Portus (2013) analyzed the influence of field size, player number and rule changes on the

physiological responses and movement demands of small-sided games for cricket training.

The drill analyzed by the authors was a typical cricket SSG (Battlezone). Thanks to the GPS

units, Heart rate and movement demands were continuously recorded during different

scenarios of “Battlezone”. The results showed that batsmen covered the greatest distance

(1.147±175 m) and the majority of time (i.e., 65– 86%) was spent with a HR ranging between

51 and 85% of HRmax. The findings of this research suggested that the greater changes in

training intensity were due to different playing rules. Changes in filed size had minimal effect

on training intensity.

The interest in small-sided games in volleyball was testified by the studies of Lehnert,

Stejskal, Háp and Vavák (2008) and Gabbett (2008). By the findings of this two studies

emerge (like in others team sports studies) the efficiency of training with SSG’s in volleyball.

Indeed the results of Lehnert et al. (2008) about the comparison of a normal match 6vs6 with

a modified rules 6vs6 one, underlined the greater intensity of the games with modified rules,

in particular for specific roles. Since this drill implies many consecutive attacks from the

same team, the players that cover attack roles will have a greater metabolic demands respect

to the defensive players.

The aim of a much complex study of Gabbett (2008) on SSGs in volleyball was to compare

the effects on youth players of two types of training stimuli: 1) one group trained with a skill-

based conditioning game (SSG’s), 2) one group trained with an instructional training focused

on technical gestures. The first results of this study showed a close similarity of the

physiological demands of the SSGs with those of the match. In this study was assessed also

the fitness and technical level of the two experimental groups after the experimental period.

Using some physical and technical tests, researchers found that the skill-base conditioning

games group had a greater increase of physical fitness level but a lower increase in technical

skill. Thus by the findings of this study emerges that the better training process for youth

volleyball players was composed by both the training methods: a skill-based conditioning

games method to improve the physical fitness capacity and an instructional training to

improve the players’ technical skill.

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1.8 Small-sided games vs. classic running drills

With the increased interest on the SSGs, and their physiological and technical-tactical

characteristics, some studies pass to a successive research hypothesis: could be possible

substitute the classic intermittent running training methods with the SSGs?

For example one of the first of this type of study was that of Sassi, Reilly and Impellizzeri

(2004), which was focused on the physiological response of soccer players during generic

versus specific aerobic training. The findings of this study highlighted the higher intensity of

small-sided games (4vs4 and 8vs8) respect to the repetitive interval running training

(4x1000m). In the study of Sassi et al. (2004), the highest intensity emerged during 4vs4

small-sided games, where players averaged 91% of HRmax. Similar values of HR were

observed during 8vs8, while during interval running training the average HR values detected

was 85% of HRmax.

After two years, Impellizzeri, Marcora, Castagna, Reilly, Sassi, Iaia and Rampinini (2006)

analyzed the physiological and performance effects of generic versus specific aerobic training

in soccer players. In particular, the authors investigated whether 12 weeks of SSGs training

could give the same improvement in aerobic fitness to the players. The assessment was made

by the analysis of the maximum oxygen uptake, lactate threshold, running economy and a

soccer-specific endurance test. Furthermore, an assessment provided during the performance

was focused on the total distance covered and time spent standing, walking, and at low-and

high-intensity running speed by players. The results of this study showed significant

improvements in aerobic fitness and match performance in both groups of soccer players

(SSG’s vs. intermittent running exercise). However , no significant differences between

specific and generic aerobic interval training were found in any of the measured variables

including soccer specific test.

In the successive comparative study of Dellal, Chamari, Pintus, Girard, Cotte and Keller

(2008), the heart rate responses during SSGs and short intermittent running training in elite

soccer players were investigated. The drills investigated by the authors were 6 types of small-

sided games (1vs1, 2vs2, 4vs4 with goalkeeper, 8vs8, 8vs8 with goalkeeper, 10vs10with

goalkeeper), and 5 types of intermittent running training (the high intensity part ranged from

100% to 120% of VO2max and from 30’’ to 5’’, with passive or active recovery). The findings

of this study underlined the incidence of the presence of the goalkeeper during small-sided

games in soccer; indeed, only during 2vs2 and 8vs8 with GK, similar heart rate response with

22

intermittent running training were found. The results of this study showed that it is possible to

use some sided games for physically integrated training. The problem that coach has to solve

during small-sided games, is the control of the activity of the players by the choice of the

number of players, the presence of goalkeepers, the playing area, and game instructions.

In the last years, after the previous mentioned studies focused on the comparison of small-

sided games with classic intermittent running exercise for endurance training, some authors

try to understand if small-sided games were suitable to improve the performance in a

continuous aerobic or an intermittent test with directional changes (Dellal et al., 2012), speed-

endurance (Ade et al., 2014) or agility of soccer players (Chaouachi et al., 2014).

In the first study (Dellal et al., 2012) the authors tried to compare the effects of small-sided

games versus High Intermittent Training (HIT), on specific measures of physical

performance. Subjects were tested at the beginning and at the end of an experimental session

of 10 weeks with two different tests: a continuous aerobic running test (Vameval test) and an

intermittent test with change of directions (30-15 Intermittent Fitness Test). During the

experimental period, the subjects were divided into three groups: the small- sided games

group (SSGs) trained with 2vs2 and 1vs1 in fields of respectively 20x20m and 15x10m; the

HIT group trained with different type of intermittent running drills (30’’-30’’, 15’’-15’’, 10’’-

10’’); the third group was the control group. The main result of this study was that SSGs and

HIT group showed significantly improvement in the two test respect the control group that

had no changes. No significant differences were found between the two experimental groups

(SSGs vs. HIT).

In the second study, Ade et al. (2014) compared 4 types of training: 2 speed-endurance drills

(8 bouts of 30 seconds of maximal speed run with 120 seconds recovery; 8 bouts of 60

seconds of maximal speed run with 60 seconds recovery) and 2 small-sided games drills (8

games of 1vs1 and 2vs2 in a 27x18m pitch with minigoals, respectively for 30 and 60 seconds

with 120 and 60 seconds). The findings of this study demonstrated that physiological response

of soccer players during small-sided games training was lower compared with the equivalent

running drills. Differently, during small-sided games, the results showed a higher blood

lactate concentrations, probably due to the great number of accelerations and decelerations.

In the third study, Chaouachi et al. (2014) compared the effect on players agility and change

of direction ability of two type of training: small-sided games (1vs1, 2vs2 and 3vs3) and

multidirectional sprints training. The main finding of this study was the significant superior

23

effect of SSG practice on agility performance considered as the ability to provide a proper

COD according to an unpredicted external stimulus (Chaouachi et al., 2014).

The results of these studies just mentioned in this paragraph, were all similar. Indeed, no

studies reported a greater metabolic demand for the SSGs respect to the classic running

intermittent exercise, but the level of intensity of the two training methods was equal. In

particular the findings of these studies emphasized the fact that some SSGs with reduced

number of players and pitch dimensions, like 2vs2 and 3vs3, or with particular rules (i.e.

presence of the goalkeeper), in some cases exposed the players to a higher physiological

demands than intermittent running exercise.

Compared with the methods without the ball, those specific that reproduce game situations

could offer relevant advantages, allowing coaches to achieve conditioning target applied in a

technical and tactical context. However, the traditional parameters used to determine the

intensity of training load with methods without the ball (i.e. distances and times) have to be

changed in case of specific drills that reproduce the game situations. Therefore, new specific

aspects, as number of players, field dimensions, time of drill, time of recovery and rules of

play, need to be included in the periodization and training monitoring phases. With this goal,

two examples can be taken from the research of Tessitore et al (2006). First, if the ball is

immediately throw-in game when the goal is scored (application of modified rules) the

exercise will result more intense. Second, once fixed a number of players, reducing the

exercise-field dimensions, the exercise (play) intensity of players could increase to a certain

ratio field dimension/n. of players, while increasing the field dimensions the exercise intensity

over a certain ratio could decrease.

Thus, the use of specific drills that reproduce the game situations requires that these specific

training load parameters, as a result of scientific investigations, are previously fixed.

1.9 Small sided games in handball

In Handball, as in other team sports, the outcome of performance implies the integration of

technical, tactical, physical and psychological aspects. It is well established by Chaouachi et

al (2009) that improving aerobic fitness of handball players can increase their conditioning

performance. Moreover, Cardoso-Marques and Gonzalez-Badillo (2006) demonstrated the

24

impressive effect of detraining in elite handball players, underlining the importance of

endurance training for handball player.

In handball, although still a little, the use of specific drills for endurance training is becoming

an adopted practice. The main study investigating the application of SSGs in handball is that

of Bucheit, Lepretre, Behaegel, Millet, Cuvelier and Ahmaidi, (2009). In handball, as well in

other team sports, the intensity of this type of drills was very high and similar to the

physiological demands of competition. In the study of Bucheit et al. (2009) the authors point

of view start from the fact that, although technical skills, anthropometric characteristics and

muscle strength and power are the most important factors for successful participation in elite

levels of handball leagues, the importance of aerobic capacity should not be underestimated.

Indeed, during a match, players run about 4-6 km (Bucheit, 2005) at a mean intensity close to

80-90% of maximal heart rate (Loftin et al., 1996). Significant associations between maximal

oxygen uptake (VO2max) and playing level have also been shown in other studies (Rannou et

al., 2001; Gorostiaga et al., 2005).

To enhance aerobic fitness of handball players is often used the classic method of intermittent

running exercise; the aim of the research of Bucheit et al. (2009) was to compare the classic

methods of training with the use of sport-specific exercise. The players involved in this

research performed both the training methods scheduled by the experimental design: 1) a

classic intermittent running exercise, composed by an 8-min shuttle intermittent running

consisting in 15 seconds of effort interspersed with 15 seconds of passive recovery; 2) a sport-

specific exercise consisting in a 4-a-side match in a normal field composed by two

consecutive 225 seconds playing periods were carried out, separated by 30 seconds of passive

rest to reach similar total exercise duration than intermittent exercise (8 minutes). The results

showed that VO2peak and VO2 were similar in both training methods but, expressed as a

percentage of VO2max, the sport-specific group VO2peak was significantly higher than the

intermittent exercise group VO2peak. Mean heart rate and rate of perceived exertion were

similar for the sport-specific group and intermittent exercise group.

Thus the findings of Bucheit et al. (2009) underlined the fact that 4-a-side handball game can

be used as a specific alternative to intermittent running exercise for enhancing aerobic fitness

in handball players. In particular, compared to the intermittent exercise, playing small

handball games is associated with a lower anaerobic participation and lesser system stress

metabolite accumulation, which encourages its use during competition phase. Furthermore, by

25

the results of the initial tests, was emerged that cardiorespiratory responses during small

handball games are inversely related to fitness level, thus coaches are invited to add specific

rules to increase the activity of the fittest players.

Another study of Bucheit, Laursen, Kuhnle, Ruch, Renaud and Ahmaidi (2009b) investigated

not only the simple aspect of the analysis of SSGs in handball, but was focused on the

comparison of the effect of high-intensity interval training versus a specific game-based

handball training on handball performance parameters in youth handball players. The

experimental period was scheduled on 10 weeks and after this period the results of the tests

confirmed the trend of the previous studies in different discipline: the best time and the mean

time in Repeated Sprint Ability test were improved like the final velocity in the 30-15

Intermittent Fitness Test for both groups. Thus, from the findings of this study, is possible to

say that both intermittent running exercise and small-sided game methods are effective

training methods for adolescent handball players, but sport-specific training should be

considered as the preferred training methods due to its higher game-based specificity. One of

the last studies on small-sided games in handball was made in 2014 by Clemente and Rocha:

researchers investigated the heart rate responses of student during small-sided games. In this

research the small-sided games were set differently respect the previous studies: the “task”

consisted of scoring by having one offensive player catching a ball pass beyond the opponent

defensive line (Clemente & Rocha, 2014). The authors tested this “tasks” in six experimental

conditions: 2vs2, 3vs3 and 4vs4 each in two different field dimensions (1/8 of the regular

field - 10 x 7.5 metres and 2/8 of the regular field - 20 x 7.5 metres). Findings of this study

highlighted the highest heart rate values during 2vs2 drills in both of the field dimensions.

However, despite the studies of Bucheit et al. (2009a and 2009b) and Clemente and Rocha

(2014) about the effects of a traditional intermittent running exercise compared with a specific

4-a-sided game played on a regular field dimension, and the use of game-based training in

young players or students, there is a lack of knowledge regarding different exercise setting in

which the number of players, field dimensions, and exercise durations are modified.

In 2015, Moss and Twist, analyzed another type of “integrated” training in handball, called

“team sport simulation”. This study, investigated and compared two types of drills (LONG

and SHORT), that were composed by circuits of technical gesture like dribbling, shoots or

passes, and physical action like sprint, jumps and change of direction. One of the important

findings of this study was the detection of an average HR of 84% of HRmax, with a maximum

26

HR of 92% of HRmax. Authors concluded that shorter work (SHORT) appeared to provide a

practically meaningful preservation of sprinting performance, both during and immediately

after exercise when compared to longer work (LONG) (Moss & Twist, 2015).

The last study on small-sided games in handball was the research of Iacono, Eliakim &

Meckel (2015) focused on the comparison of one type of small-sided games in handball

(3vs3) with the High-Intensity Intermittent Training (HIIT). Small-sided games were 5 ×

different time duration (range 2’25’’-3’10’’) of 3vs3 in a 20×20m court dimensions, with

always 1’ of recovery between the series. The HIIT program consisted of 12- to 16-minute

intermittent running of 15-second activity over 40-m shuttles interspersed by 15 seconds of

passive walking recovery. The results of this study underlined the efficiency of both training

program for the improvement of aerobic capabilities and supra-maximal intermittent

performance. In particular, small-sided games training was more effective for the

improvement of anaerobic and strength performances compared with HIIT.

27

2. Topic and Problem identification

The subject of this research is the analysis of SSG’s in a sport like handball, where there is a

lack of scientific literature about this problem and where the training methodology are in

some case not update respect other discipline like soccer or rugby. The problem that rises

from the application of SSG’s is if this training tools, that reproduces technical and tactical

element of the match, may reflect this also in the physiological aspects, leading to an increase

of the endurance capacity of handball players. This problem, already investigated in the

research of Buchheit et al. (2009), isn’t the only problem of the wide field of application of

small sided-games. Handball coach and physical trainer ask to have some tools to change the

load and effort of this SSG’s, with the aim of change the physical capacity to train, like it is

possible to do in the exercise without ball (vary the speed of run, insert of change of direction,

etc.). Thus the survey of the change in load and effort of handball players in response to the

change of number of players, or field dimensions in SSG’s, as already done for other sport

like in the studies of Tessitore et al. (2006), Sampaio et al. (2009) and Foster et al. (2010), can

answer this practical question.

3. Hypothesis and Objectives

The aim of this project is to analyse both load and effort demands of game-based drills in

handball, emphasizing the differences obtained with changes in the number of players and

field dimensions. In particular we construct four basic objectives:

1. Establish whether statistically significant differences occur in extent and intensity of cyclic

activities among 3-a-side drills with different space and number of players, among 4-a-side

drills with different space and number of players.

2. Establish whether statistically significant differences occur in relative heart rate among 3-a-

side drills with different space and number of players, among 4-a-side drills with different

space and number of players and among 3-a-side and 4-a-side drills.

3. Establish whether statistically significant differences occur in extent and intensity of cyclic

activities among 3-a-side and 4-a-side drills

4. Establish whether statistically significant differences occur in relative heart rate among 3-a-

side and 4-a-side drills

In accordance with the aims of the research we formatted 12 hypotheses:

28

H01: Among 3-a-side drills there are no statistical significant differences in distances covered

(amount of cyclic activities) by players during the game.

H02: Among 3-a-side drills there are no statistical significant differences in intensity of cyclic

activities performed by players during the game

H03: Among the 3-a-side drills there are no statistical significant differences in frequency of

acyclic activities performed by players during game

H04: Among the 3-a-side drills there are no statistical significant differences in relative heart

rate and RPE values.

H05: Among 4-a-side drills there are no statistical significant differences in distances covered

(amount of cyclic activities) by players during the game.

H06: Among 4-a-side drills there are no statistical significant differences in intensity of cyclic

activities performed by players during the game

H07: Among the 4-a-side drills there are no statistical significant differences in frequency of

acyclic activities performed by players during game

H08: Among the 4-a-side drills there are no statistical significant differences in relative heart

rate and RPE values.

H09: There are no statistical significant differences in distances covered (amount of cyclic

activities) by players between 3-a-side and 4-a-side drills.

H010: There is no statistically significant difference in intensity of cyclic activities performed

by the players between 3-a-side and 4-a-side drills.

H011: There is no statistically significant difference in frequency of acyclic activities

performed by players between 3-a-side and 4-a-side drills.

H012: There is no statistical difference in relative heart rate data recorded and RPE values

between 3-a-side and 4-a-side drills.

29

4. Methods

4.1 Sample description

The subjects who participated to this study were 8 players of the Lazio Pallamano, an Italian

A1 league team (Second division). Before the beginning of the experimental period every

players signed a written consensus and they can stop with the experiment in any moment.

During all the experimental sessions, the subject had to be health; the procedure of every

session was explained to the subjects before the beginning of each experimental session and

they had to agree with all the procedures.

4.2 Parameters

Cyclic movements were recorded as an amount of running (and/or walking) and intensity of

running (and/or walking). Intensity of running was divided into four speed classes according

to their speed (Table 2):

Table 2

Cyclic Movements Analyzed

Variable Description of variable Unit

Distance (S) Total of all run and/or walked distances in the

match or in a half

m

First speed class (SC1) Total of run and/or walked distances while

running or walking; speed: up to 1.4 m/s

m/s

Second speed class (SC2) Total of run distances while running slowly;

speed: between 1.4 m/s and 3.4 m/s

m/s

Third speed class (SC3) Total of run distances while running fast;

speed: between 3.4 m/s and 5.2 m/s

m/s

Fourth speed class (SC4)

Total of run distances while sprinting; speed:

above 5.2 m/s

m/s

Average speed (AS) Average speed of walking or running m/s

30

The four speed classes were established following the example of previous scientific

researches in handball. In the studies of Pers et al. (2002), Šibila et al. (2004) and Pori et al.

(2005), the classification of speed of run in handball match was made with the same four

speed classes indicated in the upper table. Also in studies about other team sports like that of

basketball of Vuckovic et al (2010), the type of classification of speed was made in the same

way represent in the table above.

Regarding the acyclic activities, the different activities detected during the experimental

period were listed in the table below (Table 3).

Table 3

Chosen Parameters of Acyclic Activities

Variable Description of variable Unit

SH Shoots to goal from

different position

Number

PI Pistons movements toward

goal

Number

PA Passes Number

JU Jumps Number

ST Stopping attackers with

body and arms

Number

COD Change of direction Number

The experimental period was divided into two parts (Table 6). Between these two periods of

the research, some tests for the assessment of the sample were administered. The parameters

analyzed during this test, with the aim of understand in the best way the individual effort of

players during drills, were summarized in the Table 4.

31

Table 4

Chosen Parameters of Effort Measured by Tests

Variable Description of variable Unit

HR rest HR values in rest Beat/min

HR max Maximal HR values Beat/min

VO2max Maximal oxygen

consumption

ml*kg*min-1

Finally, to better understand the effort of players during the game, the variables described in

the table below were analyzed (Table 5).

Table 5

Chosen parameters of effort during the game

Variable Description of variable Unit

HR abs Absolute HR values during the game Beat/min

HR rel 5 Relative HR values during the game below

50% of maximal effort

%

HR rel 5-7 Relative HR values during the game between

50% and 70% of maximal effort

%

HR rel 7-9 Relative HR values during the game between

70% and 90% of maximal effort

%

HR rel 9 Relative HR values during the game over 90%

of maximal effort

%

The choice of using this type of classification for heart rate is made on the basis of previous

studies on the analysis of effort in handball. In particular the study of Pori and Šibila (2006)

about the analysis of high-intensity large-scale movements in team handball, and the doctoral

thesis of Bon (2001) about the quantified evaluation of loading and monitoring of heart rate of

handball players in a match.

32

4.3 Experimental procedures

The literary review highlighted the lack of research on particular handball drills for the

development of the specific endurance. In particular, unlike other team sports, there is a total

absence of studies on the variation of effort for handball players in response to the variation of

some parameters of the drills like field dimensions, number of players or change of rules.

Thus the drills that were analysed in this research are:

- the 3-a-side in a field of 24mx12m (approximately 36sqm for players);

- the 3-a-side in a field of 30mx15m (approximately 56sqm for player);

- the 3-a-side in a field of 32mx16m (approximately 64sqm for player);

- the 4-a-side in a field of 24mx12m (approximately 28sqm for player);

- the 4-a-side in a field of 30mx15m (approximately 45sqm for player);

- the 4-a-side in a field of 32mx16m (approximately 51sqm for player).

During the 3-a-side drills the defence in front of the goalkeeper was a zone-defence that

reproduced the central part of an hypothetic 5-1 defence with the back center and two half

defenders, without the front center defender; the opponent held the position of left, right and

central backcourts independently of their real role.

During the 4-a-side drills the defence in front of the goalkeeper was a zone defence that

reproduced the central part of an hypothetic 5-1 defence with the back and front center

defender and the two half defender; the opponent held the position of left, right and central

backcourts and of pivot.

The floor lines that were marked on the field are represented in figure 1 and 2 with the

dislocation of the players in each of two types of drills: the line of six meters was semicircular

and the line of seven meters was marked in normal way like in the regular field.

33

Figure 1. Example of dislocation of players in 4-a-side drills. This figure shows how the

players normally play during the 4vs4 drills, in the roles of central, left and right back, and

pivot.

Figure 2. Example of dislocation of players in 3-a-side drills. This figure shows how the

players normally play during the 3vs3 drills, in the roles of central, left and right back.

34

The rules of the drills were the same of the normal handball with the exception of:

1) throw-in after a goal was immediately made by the goalkeepers from their 6-m area, and the

investigator was always available to immediately replace the ball when it was thrown out of

the playing area (Buchheit et al., 2009),

2) the 2-min exclusions were not present, but the referee only sanctioned “normal” faults.

The drills lasted for 8 minutes and during this time the substitution of player was forbidden to

the aim of have the same players in game for all the drill. In the case of an injury the player

was immediately substitutes by another but his physiological data will not calculate for the

general assessment of the load of the drill.

The referee of all the drills will be always the same: an official referee of the FIGH (Italian

handball federation).

The experimental period was divided into two parts of about 6 weeks (Table 6): during the

first were taken the data on 3vs3, during the second were taken the data on 4vs4; thus the

experimental period lasted about 4 months, for a total of twelve experimental sessions, plus

two sessions for tests that were made in the period between the two experimental parts. All

the experimental sessions were scheduled at the same time of the day, (on a Tuesday once

every weeks during normal training) to avoid any effect of circadian rhythms on the measured

variables (Drust, Waterhouse, Atkinson, Edwards & Reilly, 2005).

In each experimental session were taken data about only one type of drill with one series of

eight minute. In this way for each type of drill will be taken data two times.

To decide which players had to play in the 3vs3 drills, a draw was made before each training

session due to randomize the drills participants.

Before each experimental session every player had to wear the specific vest to support the

GPS unit and the heart rate belt (Figure 3); during this procedure an assistant signed on a

specific table, the number of GPS unit with its relative player name and the time of start of the

activity of GPS unit. After this procedure the players performed a standardized warm-up that

includes the warm-up for the goalkeepers, for a total duration of twenty minutes.

Before start the first drill, the assistant noted the time of start and end of the drill. At the end

of each drill every player had to look at the Borg scale and tell to the assistant the personal

value for the drill just ended.

35

Figure 3. GPS equipments. This figure illustrates the package of the GPSorts with the GPS

units, and the specific vest to support them.

Table 6

Schedule of All the Experimental Sessions

3vs3 Test 4vs4

First week 24x12 (1) --- ---

Second week 24x12 (2) --- ---

Third week 30x15 (1) --- ---

Fourth week 30x15 (2) --- ---

Fifth week 32x16 (1) --- ---

Sixth week 32x16 (2) --- ---

Seventh Week --- First session ---

Eighth week --- Second session ---

Ninth week --- --- 24x12 (1)

Tenth week --- --- 24x12 (2)

Eleventh week --- --- 30x15 (1)

Twelfth week --- --- 30x15 (2)

Thirteenth week --- --- 32x16 (1)

Fourteenth week --- --- 32x16 (2)

36

To evaluate in the better way the load and effort of the players during the various types of

drills, the following survey were made:

Match Analysis

To provide valuable information on the overall demands of team-sport competition, time-

motion analysis was made. All the drills were recorded by means of video cameras

positioned at a side of the pitch. The images were analyzed for counting of the number of

acyclic movements previous mentioned. By means of a SPI elite GPS system (GPSports), the

cyclic movements were categorized as: 1) total of all run and/or walked distances in the drills;

2) total of run and/or walked distances while running or walking: speed up to 1.4 m/s; 3) total

of run distances while running slowly: speed between 1.4 m/s and 3.4 m/s; 4) total of run

distances while running fast: speed between 3.4 m/s and 5.2 m/s 5) total of run distances

while sprinting: speed above 5.2 m/s; 6) average speed of walking or running; 7) maximal

speed during the drills.

In literature are not reported researches in the handball environment in which the amount and

the intensity of cyclic movements are calculated thanks to the SPI elite GPS System. This is

probably due to the fact that being handball a discipline indoor, for many years was preferred

the use of fixed camera system for the acquisition of data about cyclic movements. In this

research there was no obstruction to the signal of the GPS device within the handball court, as

it was merely covered by a plastic sheet (Figure 4).

The portability and the more simplicity of the GPS system, led to an increase of utilization of

this technology for the assessment of load and effort in team-sports. Many studies have been

focused on the validity and reliability of the GPS System, and a comparison between these

new technologies with the fixed camera system. In the analysis made by Duffield, Reid,

Baker and Spratford (2009), the comparison of GPS system with a 22 camera VICON motion

analysis system reported that for measuring athlete movement patterns at slow or moderate

speeds and for a long distance, GPS technology has acceptable inter-unit reliability and

accuracy for distance measured; as the speed of movement increases there is and

underestimation of total distance covered and of peak of speed. Also the other studies on this

topic obtained the same results: Petersen, Pyne, Portus and Dawson (2009) and Jennings,

Cormack, Coutts, Boyd and Aughey (2010) underlined the fact that the results of their studies

showed that the GPS devices have an acceptable level of accuracy and reliability for total

37

distance and peak speeds during high-intensity intermittent exercise, but may not be provide

reliable measures for higher intensity activities.

On the basis of the studies previous mentioned many authors used the GPS system to their

goal: Castellano and Camasichana (2010) made a motion analysis and an heart rate evaluation

of beach soccer, Brewer, Dawson, Heasma, Stewart and Cormack (2010) compared the

movement pattern of elite and sub-elite Australian football games, Macutkiewicz and

Sunderland (2011) used the GPS to evaluate activity profiles of elite women hockey players

during match play.

Figure 4. Handball court covered by a plastic sheet. This figure illustrates the court where the

experimental sessions were made; the plastic sheet permits the passage of the GPS signal

without obstacle.

Before the experimental period, a GPS signal test with a preliminary study was made. We

detected heart rate and gps signal during a single 3vs3 drill. The successive analysis of the

data underlined no interruption in the transmission of the gps signal. Furthermore, before the

experimental period, we tested the signal of the GPS in all the court area. Once the GPS unit

is on (Figure 5), if the signal is good, the top green light blinks and then remains fix for the

rest of the session. If there is no GPS signal, the lower red light blinks.

38

Figure 5. GPS unit. 1=Good signal light; 2=No signal light; 3=power button

Heart rate measurements (HR)

To evaluate the player’s efforts, HR was recorded with SPI elite GPS system (GPSports)

during the entire exercises with a sampling frequency of 1/15 sec. The intensity of effort

subsequently was calculated in relation to the estimated HRmax obtained during the field test.

To indicate the physical load imposed on athletes during the drills analyzed, was used the

follows way : the subjects minimum HR (surveyed in the morning in the bed of 5 consecutive

days), together with the maximum HR obtained from the 30-15IFT, was put in the Karvonen

formula (HR(%)=[100*(HR-HRmin)]/[HRmax-HRmin]) to calculate the relative effort (Duarte,

Araújo, Fernandes, Travassos, Folgado, Diniz & Davids, 2010). The reference scale was the

follows : <50%, 50%-70%, 70%-90% and >90% of the relative HR. Then, the percentage of

time (s) spent in each activity categories will be calculated for subsequent statistical analysis.

1

2

3

39

Subjective ratings

The Borg’s scales of perceived exertion (RPE), was administered (Figure 6). Therefore, at the

end of the experimental session, subjects were asked to evaluate the intensity by means of a

10-point likert scale (Borg’s scale CR10), ranging from “noting at all” (0 pt) to “very, very

hard” (10 pt). Scores will be recorded to the nearest 0.5.

Figure 6. Rate of Perceived Exertion’s scale of Borg

The utilization of the modified Borg’s scale, instead of the classic Borg’s scale 6-20 (Borg,

1998), is supported by the scientific literature already published on SSG’s. Authors like

Impellizzeri et al (2006), Rampinini et al (2007), Coutts et al (2009), Fanchini et al (2011)

used for the evaluation of effort of adult players during small sided-games in soccer the CR10

scale of Borg. Only two studies on the application of specific-drills on soccer used the 6-20

40

Borg’s Rate of perceived exertion scale, but the subjects of the researches were young players

(Hill-Haas, Roswell, Coutts & Dawson, 2008; Hill-Haas, Dawson, Coutts & Roswell, 2009).

Moreover in the only research in the scientific literature about the use of SSG’s in handball,

the study of Buchheit et al. (2009), is administered the CR10 scale of Borg to evaluate the

effort of handball players. Thus, for the above mentioned reasons, and for the reliability and

validity of the CR10 scale respect to the 6-20, in this research was used the CR10 scale to

assess the effort of handball players during handball SSG’s.

In some of the previous research focused on performance in team sport, another tool to

evaluate the effort of players was the blood lactate accumulation. In our study, we didn’t use

this method for 2 main reasons:

1) the difficulties to have the presence of a doctor during each experimental session

(mandatory for this type of exam)

2) the influence of high intensity activities during handball match or training on blood

lactate accumulation; for example if we made the sampling procedure at the end of the

8 min drill, the blood lactate value could be very heterogeneous not due to real

differences in players fitness but for the influence of the last 1 minute activity of each

player. (high intensity action in the last minute could increase the blood lactate

accumulation value)

4.4 Sample evaluations

To define in the better way the sample of handball players that participated to this study and

their fundamental characteristics, according to their age, the following test protocols were

applied:

Anthropometric evaluations

Anthropometric measurements were made to ascertain the participants’ height (cm), body

mass (kg), body mass index (kg/m2), and percentage of body fat by means of skinfold

thickness evaluations. The specific skinfolds were the triceps, subscapular, suprailiac,

abdominal, axillary, thigh and pectoral and they were measured three times each by means of

a Lange calliper (Cambridge Scientific Instruments, Cambridge, MD). The Jackson and

41

Pollock formula for men (1978) was used to calculate the individual’s percentage of total

body fat relatively to the age.

Maximal heart rate evaluation (30-15 Intermittent Fitness Test - 30-15IFT)

The test consists of 30s runs and 15s rests, the latter can be either walking or standing on the

spot. The running velocity (loading) increases with each repetition and the subjects perform

the test until exhaustion and/or until they can cope with the increasing loading. The running

velocity (pace) is dictated by a sound signal according to which the subjects orient themselves

as it resounds at the beginning of every 30s of loading, at every line on the handball court

(thus informing the subjects whether they are lagging behind or running ahead of the required

velocity and can therefore accelerate or decelerate) and at the end of every 30s of loading. The

sound signals differ accordingly (Figure 7).

Figure 7. Scheme of the 30-15 IFT lines

The initial velocity is 8 km/h and grows by 0.5 km/h with every repetition. The subjects run

for as long as they are able to keep up with the velocity dictated by the sound signals. The test

is completed when they are unable to reach the selected line on the court three consecutive

times (or 3m of the tolerance zone in front of the line). The final result is the last velocity

which the subject ran in accordance with the described rules (Maximal Aerobic Velocity or

42

MAV). The maximal absolute obtained hart rate by this test should serve to calculate the

relative hart rate.

We decided to use only a field test and not a laboratory test. The main reason of this choice

was the difficulty of semi-professional players to reach the laboratory, and the not possibility

of plan all the test sessions with the presence of a doctor (mandatory for a maximal laboratory

test).

Jump evaluations

Counter movement jump (CMJ) was evaluated by means of an optical acquisition system

(Optojump, Microgate, Udine, Italy). During tests the effect of the arm swings was minimized

requesting the athletes to keep their hands on their hips (Figure 8). Two trials with a 5-minute

recovery period between trials were allowed to the players and the receiving of verbal

encouragement was allowed too. Thus, their best performance was used for statistical

analysis.

Figure 8. Example of Jumps evaluation with the Optojump

43

Sprint evaluations

The time of twenty-meter sprints (20 m) was measured by means of a dual infrared reflex

photoelectric cells system (Polifemo, Microgate, Udine, Italy) (Figure 9). The “start” and

“end” photoelectric cells were positioned 20 meters apart and the first timing gate was

positioned at 0.5 m from the starting. The test was filmed to evaluate the correct executions.

Prior to the test, players made a 15-minute standardized warm-up period during which they

carried out jogging, technical exercises of moderate intensity, and stretching. For each test

two trials with a 5-minute recovery period between trials were allowed to the players and the

receiving of verbal encouragement was allowed too. Thus, their best performance was used

for statistical analysis.

Figure 9. Microgate Photoelectric cells system

Repeated sprint ability evaluation (RSA)

To evaluate the player’s repeated sprint ability the 40-m Maximal Shuttle-run Test (MST)

reported in the study of Glaister, Hauck, Abraham, Merry, Beaver, Woods and McInnes,

44

(2009), with the use of photoelectric cells, was administered. In the 40-m MST, which

consisted of 8 × 40-m shuttles interspersed with 20 s recovery intervals, subjects were

required to run between two lines placed 20-m apart, with the start/finish line (and the

photocells) placed at the midpoint of the course (Figure 10). On instruction, each subject

sprinted 10 m from the start/finish line to the end of the course, turn 180°, sprint 20-m to the

other end of the course, turn 180°, and sprint 10-m back through the start/finish line. Subjects

were instructed to place at least one foot over the line at the end of each shuttle, the adherence

of which was monitored to ensure full compliance.

10 meters start/finish line

20 meters

10 meters

Figure 10. Scheme of Glaister et al. Repeated Sprint Ability Test.

The best time and the mean time of the eight shuttle-sprints were recorded; furthermore the

fatigue time was calculated as the difference between the best and the worst sprint time.

4.5 Statistical analysis

The statistical package SPSS (17.0) was used for the analysis. Data was presented as mean

values and standard deviations of frequency of occurrence (%); statistical significance was set

at an alpha level of P=0.05. Before the study, the Kolmogorov test was applied to test the

normal distribution of the data.

To verify differences among the heart rate classes and cyclic movements (speed classes) in

the three different field dimensions, two multivariate analysis of variance (MANOVA) for

repeated-measures were applied, considering the heart rate classes in the first and the speed

classes in the second as within factor. For each heart rate class a further MANOVA for

45

repeated measures was be made to verify differences among 3-a-side and 4-a side drill in each

of three field dimension. For statistical tests that used multiple comparisons, post-hoc Fisher

protected least significant difference comparisons with Bonferroni corrections was used.

To verify differences among RPE values in the three difference field dimensions ANOVA for

repeated measures was applied and post-hoc comparisons were performed by means of

Tukey’s test.

Non parametric statistics (i.e., Chi-square and Mann-Whitney U tests) was used to analyse

frequencies of occurrence of observed variables or data set that do not meet the criteria of the

normal distribution. This group of variables was composed by the acyclic movements of the

match analysis.

To provide meaningful analysis for significant comparisons from small groups, the Cohen’s

effect sizes (ES) between groups was also calculated. An ES < 0.2 was considered trivial,

from 0.3 to 0.6 small, <1.2 moderate and >1.2 large. In order to avoid Type I statistical errors

univariate effects within MANOVAs was examined only if the overall MANOVA was

significant. In order to control for assumptions which must be met in this kind of analyses the

Levene’s test for homogeneity of variance and the Mauchly's test for the sphericity, were

performed.

46

5. Results

The results of this study were divided into 4 different section that are listed below:

1) Sample assessment: all the data about the evaluations of subjects anthropometric

characteristics, Maximal Heart rate, jump and sprint capacity, Repeated Sprint Ability.

2) Analyses of load and effort in the 3vs3 SSG’s: all the results found during the 3vs3

SSG’s experimental sessions (cyclic and acyclic movements, match analysis, heart rate and

RPE values).

3) Analyses of load and effort in the 4vs4 SSG’s: all the results found during the 4vs4

SSG’s experimental sessions (cyclic and acyclic movements, match analysis, heart rate and

RPE values).

4) Analysis of load and effort of the 3vs3 compared to the 4vs4 SSG’s: all the results

found comparing the 3vs3 to the 4vs4 SSG’s

5.1 Sample assessment

Anthropometric evaluations

The anthropometric measures of the sample are showed in the table below (Table 7). The

average age of the subjects was 29±4 (range 24-33) years and their average height and weight

was respectively of 183.75±8.22 cm and 84.50±9.56 kg.

Table 7

Sample’s Anthropometric Measures

Subjects Age (years) Weight

(kg)

Height (cm) Body mass

index

Fat mass (%)

1 27 73 182 22.04 10.58

2 33 78 178 24.62 15.65

3 24 90 186 26.01 15.92

4 29 95 200 23.75 20.91

5 30 84 185 24.54 13.50

6 29 78 173 26.06 14.06

7 37 100 188 28.29 22.07

8 27 78 178 24.62 12.96

Average 29.50±4.00 84.5±9.56 183.75±8.22 24.99±1.85 15.71±3.95

47

Maximal heart rate evaluation (30-15 Intermittent Fitness Test - 30-15IFT)

The heart rate evaluation made on the sample of this study by the administration of the 30-15

IFT, highlighted the results reported in the Table 8. The average HR rest and max were

respectively of 51±7 and 182±8 bpm. The average MAV was of 18.94±1.15 km/h and lead to

an average VO2max of 53.48 ± 3.31 ml*kg*min-1

.

Table 8

Sample’s Heart rate and VO2 max evaluation

Subjects HR rest

(bpm)

HR max

(bpm)

MAV

(km/h)

VO2 max

(ml*kg*min-1

)

1 54 176 17.5 49.25

2 54 199 19.5 56.71

3 61 180 19 51.44

4 54 178 17.5 49.03

5 41 180 19.5 55.29

6 44 186 20 56.46

7 45 173 18 52.73

8 54 185 20.5 56.91

Average 51±7 182±8 18.94±1.15 53.48±3.31

Jump and sprint evaluations

The results of the assessment of the CMJ and the 20-meters sprint are reported in the Table 9.

The average eight of jump during the CMJ test was of 33.16±2.32 cm and the average time on

the 20-meters sprint was of 3.34±0.17 sec.

Repeated sprint ability evaluation (RSA)

The evaluation of the RSA of the subjects was made by the administration of the Glaister test

(2009). The results are showed in the Table 10 and underlined an average sprint time of

9.29±0.24 sec with a fatigue time of 0.68±0.60 sec.

48

Table 9

Sample’s Jumps and Sprint Evaluation

Subjects CMJ (cm) 20-m Sprint (sec)

1 32.50 3.07

2 36.70 3.27

3 33.60 3.45

4 34.80 3.52

5 32.50 3.34

6 31.00 3.29

7 29.40 3.57

8 34.80 3.19

Average 33.16±2.32 3.34±0.17

Table 10

Sample’s RSA Evaluation

Subjects Best (sec) Worst (sec) Mean (sec) Fatigue time (sec)

1 8.50 10.59 9.53 2.09

2 9.04 9.38 9.23 0.34

3 8.94 9.64 9.27 0.70

4 9.20 9.60 9.46 0.40

5 8.97 9.68 9.27 0.71

6 9.05 9.31 9.20 0.26

7 9.38 9.66 9.55 0.28

8 8.35 9.02 8.81 0.67

Average 8.93±0.34 9.61±0.46 9.29±0.24 0.68±0.60

5.2 Analyses of load and effort in the 3vs3 SSG’s

The results concerning cyclic movements are presented in Table 11. The total distance

travelled by players during SSG’s increased significantly in parallel with the increasing

dimensions of the court (p<0.05; large ES).

49

As showed in the table below, the greatest average distance travelled by players during SSG

was of 1095.0±113.0m, observed during the drill in the largest court (32×16m). In the other

two experimental conditions, the average distance covered by players was 980.0±73.5m and

885.2±66.7 m respectively observed with the 30×15m and 24×12m court dimensions.

Table 11

Total distances covered in each experimental condition of the 3vs3

Court dimensions Total distances (m)

24×12m 885.2±66.7

30×15m 980.0±73.5*

32×16m 1095.0±113.0*#

Note. *=Significant difference vs. 24x12m (p<0.05; large ES), #=Significant difference vs.

30x15m (p<0.05; large ES)

The results of distance covered by players in the four speed zones are reported in Table 12.

Statistical analysis highlighted substantial differences between the 24×12m and the 30×15m

court in the first, second and third speed zones (p<0.05; moderate ES). With the 30×15m

court, players covered more distance in the second and third speed zones compared with

24×12m court. However, players covered less distance in the first speed zone with the

30×15m court compared with the 24×12m one. Statistical differences were also found

between the 24×12m and 32×16m court in the second and third speed zones (p<0.05;

moderate ES): with the greatest pitch dimensions (32×16m), players covered more distance in

the second and third speed zones in comparison to the smallest one (24×12m). There were no

substantial differences in the fourth speed zone for all of the experimental conditions.

Table 12

Distances Covered in the Four Speed Zones in Each Experimental Condition of the 3vs3

Court dimensions 1stspeed zone

(m)

2nd

speed zone

(m)

3rd

speed zone

(m)

4th

speed zone

(m)

24×12m 267.0±25.0 526.7±30.8 85.2±46.1 0.4±1.0

30×15m 219.9±22.7* 633.9±65.0* 155.5±71.0* 6.2±11.1

32×16m 230.0±30.5 669.8±80.4* 205.8±77.5* 27.9±35.9

Note. *=Significant difference vs. relative 24x12m (p<0.05; moderate ES)

50

There was no significant effect of court dimension on acyclic activities (Table 13).

Table 13

Acyclic Activities in Each Experimental Condition of the 3vs3

Court dimensions Actions Shoots Passes SABA PM Jumps COD

24×12m 34±1 58±5 71±6 15±3 8±2 11±2 7±3

30×15m 29±1 49±3 65±6 4±1 6±1 8±2 6±3

32×16m 28±2 48±4 72±4 6±1 3±1 8±3 4±2

Note. SABA=Stopping attackers with body and arms, PM=Pistons movements toward goal,

COD=Changes of direction.

Finally, there was no effect of court dimension on HR (Table 14)

Table 14

Time Spent in the Heart Rate Zones in Each Experimental Condition of the 3vs3

Court

dimensions

<50% HRrel

(% time)

50%-70% HRrel

(% time)

70%-90% HRrel

(% time)

>90% HRrel

(% time)

24×12m 0.6±0.9 5.0±4.4 40.8±27.4 53.7±31.6

30×15m 2.7±1.1 9.5±9.8 65.1±23.3 22.7±27.7

32×16m 0.6±1.1 3.4±1.6 47.1±37.8 48.9±39.3

Note. HRrel=relative Heart Rate calculated by the Karvonen Formula

The RPE values found during the 32×16m drill were significantly higher compared with the

drill on the 24×12m court (p<0.05; large ES). There was no other significant difference in

RPE (Table 15).

Table 15

Rating of Perceived Exertion’s Values in Each Experimental Condition of the 3vs3

Court dimensions RPE values

24×12m 6.3±0.5

30×15m 7.7±0.8

32×16m 8.2±1.0*

Note. RPE=Rate of Perceived Exertion, *=Significant difference vs. 24x12m (p<0.05; large

ES)

51

5.2 Analyses of load and effort in the 4vs4 SSG’s

The results of the distance covered analysis are shown in the Table 16. The only statistical

difference was found between the data obtained during the 4vs4 in the 30×15m and the

24×12m: distance covered by players increased parallel with the court dimensions only

passing by the small court (24×12m) to the medium court (30×15m) (from 948.1±64.5m to

1087.2±92.0m), but not from the medium court to the large one (32×16m) (1079.8±90.6m).

Table 16

Total Distances Covered in Each Experimental Condition of the 4vs4

Court dimensions Total distances (m)

24×12m 948.1±64.5

30×15m 1087.2±92.0*

32×16m 1079.8±90.6

Note. *=Significant difference vs. 24x12m (p<0.05; large ES).

The results of distance covered by players in the four speed zones are reported in Table 17.

Statistical analysis highlighted substantial differences between the 24×12, and the 30×15m

court in the first and third (p<0.05; moderate ES) speed zones. With the 24×12m court,

players covered more distance in the first but less distance in the third speed zone (p<0.05;

moderate ES). Statistical differences were also found between the 32×16m court and the

24×12m one; with larger court dimension, players covered less distance in the first speed zone

but more distance in the third speed zone (p<0.05; moderate ES).

There were no substantial differences in the second and fourth speed zone for all of the

experimental conditions.

Table 17

Distances Covered in the Four Speed Zones in Each Experimental Condition of the 4vs4

Court

dimensions

1stspeed zone

(m)

2nd

speed zone

(m)

3rd

speed zone

(m)

4th

speed zone

(m)

24×12m 227.3±20.1 613.4±66.6 114.1±52.3 3.9±5.9

30×15m 212.0±27.7* 618.6±40.3 242.9±75.0* 19.6±25.4

32×16m 176.3±42.9* 635.1±98.0 289.5±75.2* 13.9±11.1

Note. *=Significant difference vs. relative 24x12m (p<0.05; moderate ES).

52

There was no significant effect of court dimension on acyclic activities (Table 18).

Table 18

Acyclic Activities in Each Experimental Condition of the 4vs4

Court dimensions Actions Shoots Passes SABA PM Jumps COD

24×12m 32±2 46±2 78±8 5±1 4±2 6±2 3±2

30×15m 27±1 41±4 75±10 5±1 3±1 6±2 2±2

32×16m 26±2 41±5 74±13 3±2 2±1 5±2 2±1

Note. SABA=Stopping attackers with body and arms, PM=Pistons movements toward goal,

COD=Changes of direction.

Finally, there was no effect of court dimension on HR and RPE values (Tables 19-20).

Table 19

Time Spent in Heart Rate Zones in Each Experimental Condition of the 4vs4

Court

dimensions

<50% HRrel

(% time)

50%-70% HRrel

(% time)

70%-90% HRrel

(% time)

>90% HRrel

(% time)

24×12m 0.9±0.7 3.0±1.0 40.0±26.4 56.1±27.7

30×15m 4.2±3.3 3.9±1.8 47.7±32.8 44.1±33.6

32×16m 3.3±1.9 4.7±3.5 59.1±35.3 32.9±38.7

Note. HRrel=relative Heart Rate calculated by the Karvonen Formula.

Table 20

Rating of Perceived Exertion’s Values in Each Experimental Condition of the 4vs4

Court dimensions RPE values

24×12m 7.7±1.0

30×15m 8.2±1.2

32×16m 7.3±1.2

Note. RPE=Rate of Perceived Exertion

53

5.4 Analysis of load and effort of the 3vs3 compared to the 4vs4 SSG’s

The univariate statistical analysis used to compare the total distance covered by players

during 3vs3 respect to the 4vs4, did not underlined significant differences (Table 21).

Table 21

Total Distances Covered During the 3vs3 Compared With the 4vs4

Court dimensions 3vs3 total distances (m) 4vs4 total distances (m)

24×12m 885.2±66.7 948.1±64.5

30×15m 980.0±73.5

1087.2±92.0

32×16m 1095.0±113.0

1079.8±90.6

The multivariate analysis of the distance covered by players in the four speed zones during

3vs3 compared to the 4vs4, showed that only in the 3rd

zones there were significant

differences. Players covered more distances running between 3.4 and 5.2 m/s during the 4vs4

drill respect the 3vs3 one. No differences were found for the other speed zones. (Table 22).

Finally, no differences were found between 3vs3 and 4vs4 conditions regarding the match

analysis and effort’s assessment by HR and RPE survey.

54

Table 22

Distances Covered in the Four Speed Zones During 3vs3 Compared With 4vs4

1st

speed zone (m) 2nd

speed zone (m) 3rd

speed zone (m) 4th

speed zone (m)

3vs3 4vs4 3vs3 4vs4 3vs3 4vs4 3vs3 4vs4

24×12 267.0±25.0 227.3±20.1 526.7±30.8 613.4±66.6 85.2±46.1 114.1±52.3* 0.4±1.0 3.9±5.9

30×15 219.9±22.7 212.0±27.7 633.9±65.0 618.6±40.3 155.5±71.0 242.9±75.0* 6.2±11.1 19.6±25.4

32×16 230.0±30.5 176.3±42.9 669.8±80.4 635.1±98.0 205.8±77.5 289.5±75.2* 27.9±35.9 13.9±11.1

Note. *=Significant difference between the 4vs4 value vs. relative 3vs3 value (p<0.05; moderate ES)

55

6. Discussion

6.1 Sample analysis

To better understand the findings of this research, first of all we should compare our sample

of handball players with the top elite athletes of this sport. Eight amateur players (age 29±4

years) belonging to an Italian Serie A1 league team (second tier championship in Europe)

were recruited to participate in this study. Players had at least six years of experience in

handball training (four times per-week) and competitions; they also took part in national

championships at the time of the investigation. Analyzing the anthropometric characteristics

of the sample, and comparing them with those of the elite handball players, we can confirm

the non-professional level of the sample: the table below shows the anthropometric

characteristics of our sample compared with those detected by the previous studies on this

topic (Table 23).

Table 23

Comparison of Sample Anthropometric Characteristics With Those of Elite Handball Players

(Ghobadi et al., 2013)

Characteristic Sample References values

Height (cm) 183.7 ± 8.2 190.1 ± 6.8

Weight (kg) 84.5 ± 9.6 92.4 ± 9.8

BMI 25.0 ± 1.85 25.5 ±2.1

Fat mass (% of body weight) 15.7 ±3.9 10.5 ± 5.5 % – 18.1 ± 3.8 %

If we compare our sample’s height and weight values with those of the study of Ghobadi et al.

(2013) about all the players involved in the 2013 Men’s Handball World Championship, the

only differences that we can underline is the greater mean height and weight of the elite

players. Our data about BMI and fat mass of handball players, comply with the mean values

of the handball players who took part to the 2013 Men’s Handball World Championship.

If we compare the main physiological characteristics of our sample with those of the elite

handball players detected in the previous studies, we do not find great differences: the mean

VO2max of our subjects was 53.5 ± 3.3 ml*kg*min-1

and the HRmax reached during exhaustive

incremental endurance test was 182 ± 8 bpm; the previous studies that investigated these

physiological characteristics of handball players, found values of VO2max that range from

56

52.8 ± 5.5 ml*kg*min-1

(Chaouachi et al. 2009) to 58.7 ± 0.9 ml*kg*min-1

(Rannou et al.,

2001) and the HRmax reached during incremental endurance test from 191 ± 8 bpm (Sporis et

al., 2010) to 194 ± 5 bpm (Kruger et al., 2013). The only difference in the physiological

values of our sample respect the other studies, is the HRmax reached during the endurance test:

being the HRmax largely affected by the age, probably this little differences in the bpm is due

to the higher mean age of our sample (29.5 ± 4.0 years) respect to the two studies used for the

comparison (26.4 ± 3.8 years, Sporis et al., 2010; 25.9 ± 3.8 years, Kruger et al., 2013).

Finally, comparing the jump and sprint performance of our subjects to the elite players, the

non-professional level of the sample is confirmed. Indeed, the Countermovement Jumps’s

(CMJ) height values found by previous studies on top elite handball players, ranges from 35.9

± 5.3 to 43.9 ± 6.0 cm (Nikolaidis et al., 2015; Michalsik et al., 2014), while in our research

the mean value of CMJ height was 33.2 ± 2.3 cm. Furthermore, the data about time in 20-

meters sprint of the subjects of this research, is higher than those of Haugen et al., (2014): 3.3

± 0.2 sec vs. 2.8 ± 0.1 sec. The differences in all the physical and physiological characteristics

analyzed of our players respect to elite ones are summarized in the table below (Table 24).

Table 24

Differences in the Physical and Physiological Characteristics Between Sample of This

Research and Other Studies

Characteristic Sample References values

Height (cm) 183.7 ± 8.2 190.1 ± 6.8

Weight (kg) 84.5 ± 9.6 92.4 ± 9.8

BMI 25.0 ± 1.85 25.5 ±2.1

Fat mass (% of body weight) 15.7 ±3.9 10.5 ± 5.5 – 18.1 ± 3.8

VO2max (ml*kg*min-1

) 53.5 ± 3.3 52.8 ± 5.5 – 57.0 ± 4.1

HRmax (bpm) 182 ± 8 191 ± 8 – 194 ± 5

CMJ (cm) 33.2 ± 2.3 35.9 ± 5.3 – 43.9 ± 6.0

20-m sprint (sec) 3.3 ± 0.2 2.8 ± 0.1

6.2 3vs3 small-sided handball games

The results from this study about 3vs3 small-sided handball games indicated that the size of

the court affects load and effort of players during the handball SSG’s. In general, almost all of

57

the parameters increased in parallel with the increase in court dimensions. Moreover, the

results can help us to describe the main characteristics of SSG’s in handball, with respect to

load and effort of players.

The values of the total distance travelled during the games significantly differed between the

24×12m and 32×16m courts. Indeed, the distance covered by players increased parallel with

the court dimension (Figure 11).

Figure 11. Total distances covered in each experimental condition (court dimension) of the

3vs3 Small-sided handball games. ⃰ =Significant difference vs. 24x12m (p<0.05; large ES)

#=Significant difference vs. 30x15m (p<0.05; large ES)

As expected, with the increasing of the court dimensions, there was also an increase of the

cyclic activities. For the comparison of the present findings, I used the variable “distance

covered per minute”. The total distance covered per minute in this research was 110.7 m.min-

1 in a game with a 24×12m court, 122.5 m.min-1 in a game with 30×15m court and 136.9

m.min-1 on the 32×16m court. These values are much higher than the values obtained in a

match on normal handball court. The normal values vary from 79.8m.min-1 (Bon, 2001) to

87.5m.min-1 (Pori et al., 2009). However, the data is similar to the data obtained in the soccer

SSG’s (Barbero-Alvarez et al., 2007; Pereira Da Silva, Kirkendall & Leite De Barros Neto,

2007). It is obvious that the short duration of the games and the reduced number of players in

0

200

400

600

800

1000

1200

24x12 30x15 32x16

Tota

l dis

tan

ce (

m)

#

58

SSG’s allow participants to perform a relatively high amount of cyclic movements in a short

period. This kind of argument is also supported by the data obtained by Buchheit (Buchheit,

et al., 2009b). Players covered in average 154m/min in the 4vs4 handball game on the regular

court in 2×225sec periods. This means there was more space per player than there was in the

previous research and, as a consequence, there was a greater amount of distance covered. As

there were different match analysis systems being applied in these studies, any comparisons

of the results should be done with caution (Randers, Mujika, Hewitt, Santisteban,

Bischoff, Solano, Zubillaga, Peltola, Krustrup & Mohr, 2010).

When analysing cyclic movements divided into the four speed zones, we observed a small

amount of fast running and sprinting, (in the highest speed zone). This might be due to the

fact that with less space available for each player, players lack the possibility of accelerating

and increasing their running speed; indeed, data regarding distance covered by the players in

the 2nd and 3rd speed zones (run and fast run) has grown with the increasing of court

dimensions (24×12m vs. 32×16m court) (Figure 12). Similar data were reported also from a

soccer SSG’s study (Castellano & Casamichana, 2010).

We determined there were no statistical differences occurring among the acyclic activities,

during games on all three court dimensions. However, even though not statistically

significant, differences occurred in the number of stopping attackers with body and arms

(defensive actions) (medium phi ES=0.33). The greater occurrence of these actions was in the

game with 24×12m court compared with the 32×16m court. As there was an increase in the

defensive activities on a smaller SSG’s court, this can be considered as a consequence of the

smaller area per player, which causes a greater proximity to the opponents and hence higher

probability for physical contact. In comparison with the data provided by Póvoas et al. (2012),

during a normal handball game, our data revealed a higher number of jumps per minute

[9±2.9 (1.12/min) vs. 16.8±6.14 (0.28/min)]. In soccer (Tessitore et al., 2006; Kelly & Drust,

2009) very few differences in acyclic activities, such as passing, receiving, dribbling

interceptions and headings, were found in response to change of court dimensions. However,

Kelly and Drust (2009) found a high number of tackles and shots with a smaller court. The

increasing number of tackles on the smaller SSG’s court has been attributed to the previous

factors, i.e. the smaller area per player gives the opportunity for more body contact. Even if I

could not confirm these significant differences amongst all of the three courts in regards to

shots, it is interesting that in handball SSG’s, players also execute more shots during a game

59

on a smaller court. This can be justified by proximity of goals, which can lead the players to

make more frequent attempts to goal (Aguiar et al., 2012).

Figure 12. Distances covered in the four speed zones in each experimental condition of the

3vs3 small-sided handball games; *=Significant difference vs. relative 24x12m speed zone

(p<0.05; moderate ES).

There was no effect of court dimensions on HR. In other cases, such as studies of rugby

(Gabbett et al., 2012a) and soccer (Aroso et al., 2004; Da Silva et al., 2011; Köklü et al.,

2011; Rampinini et al., 2007) some differences were observed. These studies highlighted the

increase of distance covered and HR values of the players parallel with the increase of court

dimensions. Only two studies, to the author’s knowledge, found an inverse trend with the HR

values that increased with the decrease of the court dimensions (Katis & Kellis, 2009;

Tessitore et al., 2006). As with our research, there were two other studies that found no

difference with the changes of court dimensions. This was probably due to the age of the

subject being low (Jones & Drust, 2007) and to the limited sampling (Kelly & Drust, 2009).

Furthermore, we have to consider that HR is only a partial measure of load, and sometimes it

may not be sufficiently sensitive to differences in actual metabolic demands, especially in

handball SSG (Buchheit et al., 2009b).

0

100

200

300

400

500

600

700

800

0 - 1.4 1.4 - 3.4 3.4 - 5.2 >5.2

Dis

tan

ce (

m)

Speed zones (m/s)

24x12

30x15

32x16

60

During the eight-minute SSG’s, the players reached near to maximal HR (>90% of HRmax) for

42 ± 12% of total time (Figure 13). This data underlines the high intensity of the SSG’s drills

in comparison with a normal match. Indeed, the study of Póvoas et al. (2011), showed that

during handball matches, the players effective mean HR (considering only the effective time

spent by the players on the field) is around 82 ± 9.3 % of HRmax. Comparing our data with the

relative HR found by Kruger et al., (2013), in the different playing positions (85.2 ± 5.8 % for

wings, 86.4 ± 1.8 % for backs and 83.4 ± 1.0 % of HRmax for pivots), the high intensity of

SSG’s analyzed in our study is confirmed. Furthermore, during the matches, the players HR

are “only” for the 10% of the 1st half and for the 4% of 2nd half above 90% of HRmax (Póvoas

et al., 2012). In longer bouts of SSG’s, (10 or 15 minutes), the players might be forced to

reduce the intensity of playing to achieve a more normal match intensity.

Figure 13. Time spent in the different Heart Rate zones in each experimental condition of the

3vs3 small-sided handball games

Obviously a comparison between data showed by this research and handball player’s HR

values during the normal match, should be made with caution. As previous studies revealed,

during team sports players adopt pacing strategies; this can modify the HR activities over a

longer period as in an entire match (Aughey, 2009; Mugglestone, Morris, Saunders

& Sunderland, 2013; Gabbett, Walker B. & Walker, S., et al., 2015; Sampson et al., 2015).

0

10

20

30

40

50

60

70

80

90

100

<50% 50-70% 70-90% >90%

% o

f to

tal d

rill

tim

e

Heart rate zones (% HRmax)

24x12

30x15

32x16

61

Certainly the high HR values found were due to the high amount of “distance covered per

minute”, high incidence of jumps, change of direction and consequent stops after high

intensity actions (typical handball actions). If we consider that exercising >85% HRmax might

be enough to improve maximal cardiovascular function, and in turn, VO2max and the

anaerobic threshold (Helgerud, Engen, Wisloff & Hoff, 2001; Impellizzeri et al., 2006), the

SSG’s used here may be useful for improving the aerobic endurance of the handball players.

Another important comparison of our HR data could be done with the previous two studies on

small-sided handball games (Buchheit et al., 2009b; Iacono et al., 2015). The data emerged

from these two studies underlined a higher impact of small-sided games on the handball

player’s HR mean values: 92.3% of HRmax (range 89.0 - 95.6% of HRmax) in the study of

Buchheit et al. (2009) and from 91.6% to 93.1% of HRmax in the study of Iacono et al. (2015).

We can compare these data with our HR values of the 3vs3 with 32×16 court dimension,

where the space available for each players (64sqm) are similar with those of Buchheit et al.

(80sqm) and Iacono et al. (66sqm). During our 3vs3, the Heart Rate’s players were higher

than 90% of HRmax for about 33% of the drill time (about 160’’). The experimental protocol

of the two previous studies was based on different small-sided games bout with different

duration: from 145’’ (Iacono et al., 2015) to 225’’ (Buchheit et al’, 2009b). Thus, the total

time passed with HR values higher than 90% of HRmax of our players are completely

comparable with the drills duration of the two previous research. Obviously, our players had

to adopt pacing strategies to cope with a 8-min duration drill respect the 2×225’’ with 30’’ of

passive rest of Buchheit et al. (2009b) and the 5×145’’-190’’ with 1’ of passive rest of Iacono

et al. (2015).

The further analysis of effort using the RPE scale showed a greater value for the 32×16m

court drill compared with the 24×12m. These differences underlined a general increase of

values with the increase of the court dimensions (Figure 14). Similar results were also

reported in two studies of SSG’s in soccer, i.e. the lower RPE values corresponded to the

smaller court (Rampini et al., 2007; Castellano & Casamichana, 2010). The increasing of the

RPE with the increasing of space available for each player, without the same trend

emphasized by the HR, was also found by a rugby study by Kennett et al., (2012). Probably,

the observed dissociation between RPE and HR could be related to greater variability of RPE

compared with HR (Hill-Haas et al., 2008). The RPE also have a multifunctional nature,

62

which is mediated not only by physiological but also by psychological factors (Borg et al.,

1987; Morgan, 1994).

Figure 14. Rating of perceived exertion’s values (RPE) in each experimental condition of the

3vs3 small-sided handball games; *=Significant difference vs. 24x12m (p<0.05; large ES)

Finally, comparing our results with those of Buchheit et al. (2009b), we found a higher values

of RPE on the 32×16 court (the only that was similar to the abovementioned study for single

player’s pitch space). This difference (8.2±1 vs. 6.3±0.5), could be due to the brief rest of 30

seconds inserted in the study of Buchheit, which allowed players to recover. Nevertheless,

comparisons between these two studies have to be made carefully, because of the differences

in the experimental procedures.

6.3 4vs4 small-sided handball games

Analysing the results of this study about 4vs4 handball SSG’s, the first aspect that emerges is

that the trend highlighted during the 3vs3 survey, is confirmed for almost all parameters.

Indeed, this part of the research, like the first one on 3vs3 SSG’s, underlined the fact that the

parameters analyzed increased in parallel with the increase of court dimensions.

First of all, the data about total distance covered by players during 4vs4 confirmed that with

more space available, players covered more distance. In particular, statistical differences

0

1

2

3

4

5

6

7

8

9

10

24x12 30x15 32x16

RP

E va

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s

63

appear between data of 4vs4 played on the 24x12m and 4vs4 played on the 30x15m pitch

dimensions (Figure 15).

Figure 15. Total distances covered in each experimental condition (court dimension) of the

4vs4 Small-sided handball games; ⃰ =Significant difference vs. 24x12m (p<0.05; large ES).

Like for the 3vs3 analysis, for the comparison of the 4vs4 findings, we used the variable

“distance covered per minute”. The total distance covered per minute during the 4vs4

experimental sessions was 118.5 m.min-1 in a game with a 24×12m court, 135.9 m.min-1 in a

game with 30×15m court and 135.0 m.min-1 on the 32×16m court.

Comparing these values obtained during 4vs4 SSG’s with those of normal handball match

(from 79.8m.min-1, Bon, 2001, to 87.5m.min-1, Pori et al., 2009), we can assure that during

these type of drills, players have to covered more distance per minute respect to an handball

match played on regular court. Other than regular court handball match, we can compare data

obtained during 4vs4 with the only previous study on handball that reproduce similar

experimental situation (Buchheit et al., 2009b). In this study, the author analyzed 2x225sec

periods of 4vs4 on normal handball court; one of the results was a distance covered per

minute by the players of 154m/min that, compared with our results, underlined once again the

increased of cyclic movement parallel with the increase of space available for each player.

Also in this case, like for the 3vs3 results, it is very important make any comparisons of data

0

200

400

600

800

1000

1200

24x12 30x15 32x16

Tota

l dis

tan

ce (

m)

64

with caution (Randers et al., 2010). Different match analysis systems applied could led to

different results.

Data about cyclic movements divided into the four speed zones, highlighted the fact that

during 4vs4, with the increasing of space available, the distance covered by players running

(3.4-5.2m/s) increases (Figure 16). Indeed, statistical differences were found in the third speed

zones between 24x12m and 30x15m court dimensions, and between 24x12m and 32x16m

court dimensions. Another data that emerges from the research on 4vs4 is that in the 24x12m

court dimensions, player covered more distances in the first speed zone (walking or standing

still); this means that, not being any differences in the second and fourth speed zones, the less

distance covered by players running (third speed zone) during 4vs4 in the 24x12m court

dimensions is “replaced” from more distance walking or standing still (first speed zone). This

trend, highlighted by the analysis of cyclic movements divided into the four speed zones, is

confirmed by the previous study on 3vs3 small-sided-handball games and also from a soccer

SSG’s study (Castellano & Casamichana, 2010).

Figure 16. Distances covered in the four speed zones in each experimental condition of the

4vs4 small-sided handball games; *=Significant difference vs. relative 24x12m (p<0.05;

moderate ES)

0

100

200

300

400

500

600

700

800

0-1.4 1.4-3.4 3.4-5.2 >5.2

Dis

tan

ce (

m)

Speed Zones (m/s)

24x12

30x15

32x16

* *

* *

65

Differently, no statistical differences were found during the analysis of acyclic movements.

Technical parameters like number of passes, shoots, actions, pistons movements, defensive

actions, and physical parameters like number of jumps and changes of direction, didn’t

change in response to different court dimensions. Other studies showed this trend also in

others sports: Tessitore et al. (2006), Kelly and Drust, (2009) found very few differences in

acyclic activities, such as passing, receiving, dribbling interceptions and headings, in response

to change of court dimensions.

No statistical differences were found also in the analysis of HR during 4vs4 handball small

sided games (Figure 17).

Figure 17. Time spent in the different Heart Rate zones in each experimental condition of the

4vs4 small-sided handball games.

Other two researches like this one, found no differences in HR values during small sided

games in response to different court dimensions (Jones & Drust, 2007; Kelly & Drust, 2009).

Probably this trend is due to the same reasons: we have to consider that HR is only a partial

measure of load, and sometimes it may not be sufficiently sensitive to differences in actual

metabolic demands, especially in handball SSG (Buchheit et al., 2009b); this fact, joint with

the limited sampling of the study and the great variability of the HR measures, were probably

0

10

20

30

40

50

60

70

80

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<50% 50-70% 70-90% >90%

% o

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Heart rate zones (%HRmax)

24x12

30x15

32x16

66

the reasons of the results obtained in this part of the research on 4vs4 small-sided-handball

games. However, like in the 3vs3 analysis, we have to consider very interesting the average

data emerges from the HR survey: the players reached near to maximal HR (>90% of HRmax)

for 44%±11% of total time (Figure 17); this data, compared with a normal match (82%±9.3%

of HRmax) underlined another time the high intensity of 4vs4 handball small sided games.

Obviously, comparing normal match data with the data of this research on 8-min bouts of

4vs4, we have to be careful because of pacing strategy that players adopt in all the team sports

(Aughey, 2009; Mugglestone et al., 2013; Gabbett et al., 2015; Sampson et al., 2015).

The further analysis of effort of players during 4vs4 small-sided-handball games confirmed

the trend of HR values, showing no statistical differences in the RPE values among the three

different court dimensions.(Figure 18).

Figure 18. Rating of perceived exertion’s values (RPE) in each experimental condition of the

4vs4 small-sided handball games.

Comparing our results with those of Buchheit et al. (2009b), we found higher values of RPE

even thought players during our study had less space available respect to the research of

Buchheit. This difference (7.7±0.4 vs. 6.3±0.5), could be due to the brief rest of 30 seconds

inserted in the study of Buchheit, which allowed players to recover.

0

1

2

3

4

5

6

7

8

9

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24x12 30x15 32x16

RP

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67

6.4 Comparison of the two type of small-sided-handball games

Other then the analysis of load and effort of 3vs3 and 4vs4 small-sided-handball games, one

of the aims of this research was the comparison of these two type of drills. Fixed the court

dimensions, with the increase of number of players and consequent decrease of space

available for each players, our expectations were to find statistical difference between the

parameters analyzed. The trend that emerged from the results was different.

Starting from the cyclic movements, the complex analysis for the comparison of the two type

of drills, doesn’t found statistically significant differences in the total distance covered by

players during the 8-min drill (Figure 19). No studies on handball were made about

differences in SSG’s with different space available for each player. Thanks to the analysis of

the study of Buchheit (2009b) on 4vs4 played in normal court, we deduced, by the

comparison with our study on 3vs3 and 4vs4 small-sided-handball games, that distance

covered by players increased parallel to the space available.

Figure 19. Comparison of total distance covered by players during 3vs3 and 4vs4 small-sided

handball games.

Probably the little difference of space available for each player between the 3vs3 and 4vs4

drills was not enough to create statistical differences among these two experimental condition.

Indeed the differences in space available were of 8sqm in the 24x12m drill, 11sqm in the

0

200

400

600

800

1000

1200

1400

24x12 30x15 32x16

Tota

l dis

tan

ce (

m)

3vs3

4vs4

68

30x15m drill and 13sqm in the 32x16m drill. The singles analysis of 3vs3 and 4vs4 confirmed

this aspect: statistical differences in total distance covered were found only where the

difference in space available for each player was 17sqm (24x12m vs. 30x15m in the 4vs4

drill), 20sqm (24x12m vs. 30x15m in the 3vs3 drill) or 28sqm (24x12m vs. 32x16m in the

3vs3 drill). In the study of Buchheit (2009b), the space available for each player was 80sqm,

so the differences with our experimental condition range from 16sqm to 52sqm. Being

difficult a comparison of two different study, with two different experimental procedure, an

interesting future study could be a comparison of two small-sided-handball games where the

space available for each player differs of more than 50sqm.

The multivariate analysis of the distance covered by players in the four speed zones during

3vs3 compared to the 4vs4, showed that only in the 3rd

zones there were significant

differences. Players covered more distances running between 3.4 and 5.2 m/s during the 4vs4

drill respect the 3vs3 one. No differences were found for the other speed zones. (Figure 20).

Figure 20. Distance covered in the four speed zones during 3vs3 compared to 4vs4;

*=Significant difference vs. relative 3vs3 court dimensions (p<0.05; moderate ES)

0

100

200

300

400

500

600

700

800

3 vs 3 4 vs 4 3 vs 3 4 vs 4 3 vs 3 4 vs 4

24x12 30x15 32x16

Dis

tan

ce (

m)

Speed 1.4

Speed 3.4

Speed 5.2

Speed max *

*

*

69

This data about statistical differences in the third speed zones between 3vs3 and 4vs4 in all

experimental condition (court dimensions), could means that to vary the distance covered

running by players, needs only 8sqm of difference in the court dimensions. The interesting

data is that, contrary to expectations, less space for each player led to more distance covered

running by players.

The reason of this inverse trend respect to the single analysis of 3vs3 is probably due to the

role of the fourth player added in the 4vs4 drills respect to the 3vs3 ones. Indeed, the fourth

player was a pivot that, playing on the six meters line, doesn’t “steal” space to others players.

Furthermore, having a pivot in the opponent defence, other players during counterattack can

pass him the ball and run more easily.

The analysis of acyclic movements did not showed statistically significance differences

(Table 25).

Table 25.

Acyclic Activities in 3vs3 Comparing With 4vs4 Condition

24x12m 30x15m 32x16m

3vs3 4vs4 3vs3 4vs4 3vs3 4vs4

Action 34±1 36±1 30±1 26±0 30±1 28±1

Passes 72±9 69±5 67±9 79±16 72±4 9±4

SABA 16±1 6±0 4±1 6±1 5±1 2±1

PM 10±3 3±1 7±1 4±2 3±1 2±1

Jumps 12±2 6±2 8±3 7±4 8±3 7±2

COD 8±3 3±2 5±3 3±2 4±2 2±1

Note. SABA=Stopping attackers with body and arms, PM=Pistons movements toward goal,

COD=Changes of direction.

70

Our expectations, as in the 3vs3 and 4vs4 individual analysis, were that with less space

available for each player, parameters like defensive actions and changes of direction were

increased. Indeed a consequence of the smaller area per player, should be a greater proximity

to the opponents and hence higher probability for physical contact and changes of direction.

Furthermore, with one more player for each team in the 4vs4 respect to the 3vs3, we thought

to find greater number of passes during the drill. The no statistical differences found in the

two experimental conditions is probably due to the low number of count for some parameters

like defensive actions (stopping attackers with body and arms) and pistons movements

towards goal; this distribution of data had created some issues during the statistical analysis

with Chi-square test. So, like for the separate analysis of 3vs3 and 4vs4, also comparing the

two type of drills, seems that the modification of space available for each players doesn’t

influence the number of technical parameters or physical activity like jumps and changes of

direction.

The final comparison that we made between the effort of players during 3vs3 and 4vs4 small-

sided handball games, did not highlighted statistical differences. Specifically, the HR values

did not differ in the two experimental conditions (Figure 21).

Figure 21. Heart Rate values during 3vs3 compared to 4vs4 small-sided handball games.

0

10

20

30

40

50

60

70

80

90

100

3 vs 3 4 vs 4 3 vs 3 4 vs 4 3 vs 3 4 vs 4

24x12 30x15 32x16

% o

f to

tal d

rill

tim

e

HR 50

HR 70

HR 90

HR 100

71

Also in this case, like in the single analysis of 3vs3 and 4vs4, the great variability of HR

values and the little sample dimension, led to a big standard deviation in the data of this part

of the study.

Finally, the analysis of Rate of Perceived Exertion’s values, underlined a different trend

respect to the separate analysis of the two type of drills. Indeed, as long as in the analysis of

3vs3 and 4vs4 the RPE values increased significantly parallel with the space available for

each players, in the comparison of 3vs3 with 4vs4, this trend did not appear (Figure 22).

Figure 22. Rating of perceived exertion’s values during 3vs3 compared to 4vs4 small-sided

handball games.

The fact that, with less space available in the 4vs4 respect to the 3vs3, were not found lower

RPE values, was probably due to the little difference of space available for each player in the

two experimental condition (8-17sqm vs. 20-37sqm). Furthermore, once again, the fourth

player added in the 4vs4 respect to the 3vs3, was a pivot: this role normally plays on the 6-

meter line so he did not “steal” so much court space to the others players.

0

1

2

3

4

5

6

7

8

9

10

3 vs 3 4 vs 4 3 vs 3 4 vs 4 3 vs 3 4 vs 4

24x12 30x15 32x12

RP

E va

lue

s

72

7. Conclusion

7.1 Conclusions and practical implications

With the aim of understand in the best way the various results obtained from this study, we’ll

analyse the Hypothesis made at the beginning of this research:

H01: Among 3-a-side drills there are no statistical significant differences in distances covered

(amount of cyclic activities) by players during the game.

H02: Among 3-a-side drills there are no statistical significant differences in intensity of cyclic

activities performed by players during the game

H03: Among the 3-a-side drills there are no statistical significant differences in frequency of

acyclic activities performed by players during game

H04: Among the 3-a-side drills there are no statistical significant differences in relative heart

rate and RPE values.

Except for the H03 and the H04, that was only partially disproved, the other two null

Hypothesis were rejected. Indeed, our study underlined direct relationship between space

available for each player during 3vs3 small-sided handball games and distance covered by

players, RPE values and distance covered running by players.

H05: Among 4-a-side drills there are no statistical significant differences in distances covered

(amount of cyclic activities) by players during the game.

H06: Among 4-a-side drills there are no statistical significant differences in intensity of cyclic

activities performed by players during the game

H07: Among the 4-a-side drills there are no statistical significant differences in frequency of

acyclic activities performed by players during game

73

H08: Among the 4-a-side drills there are no statistical significant differences in relative heart

rate and RPE values.

Like for the 3vs3 analysis, also in the 4vs4 survey the H07 about acyclic activities was not

disproved and the H05 and the H06 were rejected, showing the same direct relationship

between space available for each player and the above parameters of cyclic activities.

Differently from the 3vs3 analysis, in the 4vs4 experimental condition, the H08 was totally not

disproved because no differences were found in the three different court dimension’s drills in

the HR and RPE values.

H09: There are no statistical significant differences in distances covered (amount of cyclic

activities) by players between 3-a-side and 4-a-side drills.

H010: There is no statistically significant difference in intensity of cyclic activities performed

by the players between 3-a-side and 4-a-side drills.

H011: There is no statistically significant difference in frequency of acyclic activities

performed by players between 3-a-side and 4-a-side drills.

H012: There is no statistical difference in relative heart rate data recorded and RPE values

between 3-a-side and 4-a-side drills.

The final part of this research, with the last four null Hypothesis, underlined the fact that little

differences in the space available for each player during small-sided handball games, does not

influence load and effort of players. Indeed, only the H010 was refused while the other three

null Hypothesis were not rejected. Furthermore, regarding the H010, statistical differences

were found only for the third speed zones, with more distances covered running by players

during 4vs4 respect to the 3vs3 drills. As already mentioned, this no finding of differences

between 3vs3 and 4vs4 is probably due to two reasons:

1) Differences in space available for each players (8-17sqm), was not so much to find statistical

differences between the two experimental condition; in the singles analysis of 3vs3 and 4vs4,

differences in space available differed from 20 to 37sqm.

74

2) The fourth player added to the 4vs4 respect to the 3vs3 was a pivot: this role, playing on the

six-meter line, does not “steal” so much space of the other players, minimizing in this way

differences in space available for each player between the 3vs3 and 4vs4

On the basis of previous discussion, we can conclude that findings emerged from the first of

this research (separate analysis of 3vs3 and 4vs4), regarding the load and effort to which the

handball players were exposed during the SSG’s drills, are certainly helpful for handball

coaches and athletic trainers wishing to use specific training methods. The high ratio of cyclic

activity per minute and the high HR values recorded make this type of drills extremely useful

for aerobic power training. The presence of a large number of jumps makes the SSG’s, in

particular on the 24×12m court, useful also for training jump ability in fatigue condition. The

little space available for the players might limit the expressions of high speed of run, so it is

also advisable to use the regular handball court to do the SSG’s, with the aim of allowing

players to express their maximum speed. Furthermore, because of the great number of

defensive activities, the 24×12m court SSG’s might be useful in developing the 1vs1 skill of

handball players. Considering the great amount of shooting for goals reported, SSG’s with all

the three court dimensions are useful in developing the goal making ability of handball

players in circumstances of general fatigue.

Analysing the comparison of the two small-sided handball games the most important findings

was that little differences in the court dimensions does not influence the parameters

investigated of load and effort of players. This means that if coach, on the basis of the goal of

the training session, wants to vary the training stimulus, he have to modify the space available

for each players of more than 20sqm.

7.2 New relevant findings

This study was the first that investigated differences in two type of small-sided handball

games by the means of a GPS technology. For this reason, two particular findings are

important for the scientific community: data about total distance covered by players, and data

about distance covered by players in the four speed zone. The analysis of cyclic activities

underlined for both the drills (3vs3 and 4vs4) significant differences in total distance covered

by players in the 3 experimental condition (3 court dimensions). Thus, the first relevant

75

finding of this study is that more space available for each players, led to an increase in the

total distance covered (table 11 and 16).

Table 11

Total distances covered in each experimental condition of the 3vs3

Court dimensions Total distances (m)

24×12m 885.2±66.7

30×15m 980.0±73.5*

32×16m 1095.0±113.0*#

Note. *=Significant difference vs. 24x12m (p<0.05; large ES), #=Significant difference vs.

30x15m (p<0.05; large ES)

Table 16

Total Distances Covered in Each Experimental Condition of the 4vs4

Court dimensions Total distances (m)

24×12m 948.1±64.5

30×15m 1087.2±92.0*

32×16m 1079.8±90.6

Note. *=Significant difference vs. 24x12m (p<0.05; large ES).

Furthermore, the analysis of distance covered by players in the different four speed zones,

highlighted the fact that, in particular during 3vs3, more space available led to more distance

covered running (table 12 and 17).

Table 12

Distances Covered in the Four Speed Zones in Each Experimental Condition of the 3vs3

Court dimensions 1stspeed zone

(m)

2nd

speed zone

(m)

3rd

speed zone

(m)

4th

speed zone

(m)

24×12m 267.0±25.0 526.7±30.8 85.2±46.1 0.4±1.0

30×15m 219.9±22.7* 633.9±65.0* 155.5±71.0* 6.2±11.1

32×16m 230.0±30.5 669.8±80.4* 205.8±77.5* 27.9±35.9

Note. *=Significant difference vs. relative 24x12m (p<0.05; moderate ES)

76

Table 17

Distances Covered in the Four Speed Zones in Each Experimental Condition of the 4vs4

Court

dimensions

1stspeed zone

(m)

2nd

speed zone

(m)

3rd

speed zone

(m)

4th

speed zone

(m)

24×12m 227.3±20.1 613.4±66.6 114.1±52.3 3.9±5.9

30×15m 212.0±27.7* 618.6±40.3 242.9±75.0* 19.6±25.4

32×16m 176.3±42.9* 635.1±98.0 289.5±75.2* 13.9±11.1

Note. *=Significant difference vs. relative 24x12m (p<0.05; moderate ES).

For the first time, thanks to the results of this study, we were able to understand what should

be the differences in space available for each player to induce change in load and effort of

handball players during small-sided games: differences of 13 sqm or less do not led to

changes in load and effort of handball players; instead, differences of 17 sqm or more, could

induce changes in the load and effort of handball players.

Another important aspect that has to be underlined in this study is the importance of Small-

Sided games training for professional adult handball players. Is a common practice in the

team sport world, adopt small-sided games as a training stimulus, only with youth athletes.

Many times, with adult players, non-specific training methods as intermittent running

exercise, are preferred. Indeed, the great part of researches on small-sided handball games

previous mentioned (Buchheit et al., 2009a; Buchheit et al., 2009b; Clemente & Rocha, 2014;

Moss & Twist, 2015), were made on youth athletes or high school students.

Concluding, in this study was emphasized the high intensity of small-sided handball games

that, joint with the specific stimulus of play handball in different court dimensions, makes

these type of drill very useful also for professional adult handball players.

7.3 Proposals for further researches and views for the future

Starting from the interesting findings of this research, future studies could be focused on the

same parameters with a bigger sample dimensions. Indeed, the limit of this study was

certainly the sample, because the low number of subjects influenced the successive statistical

analysis. Studies with more subjects could normalize the results, with the consequent

possibility of underline new differences between the experimental conditions.

77

Interesting new studies, as already done for other team sports, could be focused on differences

in load and effort of players in response to different rules during small-sided handball games

(i.e. dribbling not allowed). Another parameters that was not considered in this study is the

encouragement of the coach during drills: the study of Rampinini et al. (2007) demonstrated

that coach encouragement during small-sided soccer drills can modify the effort of players.

No studies on handball were made on this particular modification of small-sided-games but

could be very interesting investigate the modification of load and effort of players in response

to the coach encouragement in a close environment like the handball court.

Regarding the space available for each player, future studies could try to understand the size

limits of court dimensions during small-sided handball games: maybe with too large court

dimensions, the effort of players may start to decrease so it could be very interesting

understand if there is this size limit. Also the tactical aspects of the role of the players

engaged during small-sided handball games, could be investigated: maybe the presence of the

pivot instead of one wing, could influence some parameters of load and effort of handball

players.

Finally, being nowadays the SSG’s one of the most used tools to increased handball players

fitness capacity, future studies could be interested on a comparison of this training method

with the non-specific running drills.

78

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Ključne besede: rokomet; obremenitve in napor; prirejene igre; video analiza; globalni sistem

pozicioniranja (GPS).

Matteo Corvino

ANALIZA OBREMENITVE IN NAPORA ROKOMETAŠEV PRI PRIREJENIH IGRAH

GLEDE NA PROSTOR IN ŠTEVILO IGRALCEV

POVZETEK

Cilji. Namen raziskave je bil ugotoviti vpliv treh različnih dimenzij igrišča na razlike, ki

nastanejo v nekaterih pokazateljih napora in obremenitve igralcev rokometa kadar igrajo tekme s

prirejenimi pravili na manjšem prostoru v razmerju igralcev 3 proti 3 in 4 proti 4 z vratarjem.

Metode. Vzorec merjencev je sestavljalo osem moških amaterskih rokometašev (28 ± 3 leta,

razpon 24–33 let). Po posebej pripravljenem protokolu so odigrali 8-minutne rokometne tekme

na treh različno velikih igriščih. V enem eksperimentalnem primeru so bile ekipe sestavljene iz

treh igralcev v polju in vratarja (3 proti 3), v drugem primeru pa iz štirih igralcev v polju in

vratarja (4 proti 4). Vsaka tekma s predvidenim številom igralcev je bila na posameznem igrišču

v določenem časovnem sosledju odigrana dva-krat (skupaj je bilo odigranih 12 tekem).

Dimenzije igrišč so znašale 12×24m za manjše, 30×15m za srednje in 32×16m za večje igrišče.

S pomočjo naprave za globalni sistem pozicioniranja - GPS (SPI pro elite 15hz, GPSports) ter s

pomočjo video analize, merilcev srčnega utripa in posebnega vprašalnika so bile zabeležene

naslednje skupine parametrov: ciklična in aciklična gibanja, srčni utrip ter ocena zaznanega

napora.

Rezultati. Pri analizi skupno opravljene razdalje smo na tekmah 3 proti 3 ugotovili značilne

razlike med vsemi tremi igrišči (p<0.05; velik ES). Na tekmah 4 proti 4 pa se je značilna razlika

pojavila samo med igriščema dimenzij 24×12m in 30×15m (p<0.05; velik ES). Pri analizi

opravljenih razdalij v štirih hitrostnih območjih (0-1,4 m/s; 1,4-3,4 m/s; 3,4-5,2 m/s; >5,2 m/s) so

bile ugotovljene značilne razlike v naslednjih eksperimentalnih pogojih: na tekmah z razmerjem

igralcev 3 proti 3 so igralci na igrišču dimenzij 30×15m v primerjavi z igriščem 24×12m opravili

manjšo razdaljo v prvem hitrostnem območju in večjo razdaljo v drugem in tretjem hitrostnih

območjih (p<0,05; srednji ES). Značilne razlike so bile pri igri 3 proti 3 ugotovljene tudi pri

primerjavi igre na igriščih dimenzij 24×12m glede na igrišče 32×16m: igralci so opravili večjo

razdaljo na igrišču 32×16m v drugem in tretjem hitrostnem območju (p<0.05; srednji ES).

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Podobni rezultati so bili zabeleženi tudi na tekmah z razmerjem igralcev 4 proti 4. V teh

eksperimentalnih pogojih so na igrišču dimenzij 24×12m igralci dosegli značilno višje vrednosti

opravljenih razdalij v prvem hitrostnem razredu in značilno nižje vrednosti v tretjem hitrostnem

razredu v primerjavi s tekmami odigranimi na igriščih drugih dveh dimenzij (p<0.05; srednji

ES). Na osnovi dobljenih podatkov pa ni bilo možno potrditi statistično značilnega vpliva

različnih dimenzij igrišča na frekvenco pojavljanja tehnično-taktičnih elementov (število

moštvenih akcij, podaj, strelov, zaletov proti vratom in obrambnih akcij), specifičnih rokometnih

skokov, sprememb smeri gibanja in na frekvenco srca v različnih območjih napora. Ta

ugotovitev velja tako za igro 3 proti 3 kot za igro 4 proti 4. Ocena stopnje zaznanega napora je

bila na tekmah 3 proti 3 značilno višja na igrišču 32×16m v primerjavi z igriščem 24×12m

(p<0,05; veliki ES). Na tekmah z večjim številom igralcev (4 proti 4) pa dimenzija igrišča ni

imela značilnega vpliva na oceno zaznanega napora (RPE). Primerjava podatkov dobljenih na

tekmah v obeh eksperimentalnih pogojih (3 proti 3 in 4 proti 4) na igriščih vseh treh dimenzij je

pokazala, da ni značilnih razlik v skupni opravljeni razdaliji. Značilne razlike pa so se pokazale v

tretjem hitrostem razredu, kjer je bila višja vrednost dosežena pri igri 4 proti 4 na vseh treh

igriščih (p<0.05; srednji ES). Ni pa bilo značilnih razlik v frekvenci pojavljanja tehnično-

taktičnih elementov, v specifičnih rokometnih skokih, spremembah smeri gibanja, v frekvenci

srčnega utripa in v oceni zaznanega napora (RPE).

Zaključki. - Naše ugotovitve kažejo, da se s spreminjanjem dimenzij igrišča pri prirejenih

rokometnih igrah glede na prostor in število igralcev, spremenijo tudi nekateri prametri, ki

odražajo napor in obremenitev igralcev. Zato se takšne igre lahko ciljno uporabljajo pri treningu

rokometašev.

Ključne besede: rokomet; obremenitve in napor; prirejene igre; video analiza; globalni sistem

pozicioniranja (GPS).

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Matteo Corvino

ANALIZA OBREMENITVE IN NAPORA ROKOMETAŠEV PRI PRIREJENIH IGRAH

GLEDE NA PROSTOR IN ŠTEVILO IGRALCEV

9. OBSEŽEN POVZETEK V SLOVENŠČINI

9.1 UVOD

V devetdesetih letih prešnjega stoletja se je, skladno s trendi v nekaterih drugih športnih igrah,

začel pospešeni razvoj raziskovalnega dela na področju proučevanja različnih vidikov

rokometne igre in treninga. Predvsem pojav novih tehnologij je omogočal večjo natančnost in

zanesljivost pridobljenih podatkov ter s tem tudi višjo stopnjo uporabnosti v praksi. Tako se je

povečalo število raziskav, ki so obravnavale frekvenco pojavljanja različnih strukturnih prvin

igre ter različne vidike obremenitev in napora rokometašev med igro. Nove tehnologije so, ob

klasičnem zbiranju podatkov o naporu igralcev med tekmo (npr. frekvenca srčnega utripa in

vsebnost laktata v krvi), dovoljevale tudi hkratno zbiranje podatkov o tem kakšne razdalje in

ob kakšnih htrostih pretečejo in prehodijo igralci med igro. Tako je bila leta 2002 v

mednarodnem prostoru objavljena prva raziskava, ki je obravnavala obremenitve rokometašev

(količina opravljenih razdalij v različnih hitrostnih razredih) z natančno in zanesljivo

računalniško in video tehnologijo (Perš idr., 2002). Avtorji so na modelni tekmi izmerili

povprečje pretečenih in prehojenih razdalij, ki je znašala 4800 m in sicer je znašal delež

sprintov (hitrost >5.2 m/s) 7% igralnega časa, delež hitrega teka (hitrost 5.2<3.0 m/s) je znašal

25% igralnega časa, 31% je bilo počasnega teka (hitrost 3.0<1.4) in 37% hoje ali stanja na

mestu (hitrost <1.4m/s). Omenjeni študiji so sledile mnoge druge v katerih so avtorji s

pomočjo video in računalniške tehnologije analizirali taktične in tehnične vidike rokometne

igre ter obremenitve igralcev med tekmo (Moncef idr., 2011; Bilge, 2012; Oliveira idr., 2012;

Gutiérrez Aguilar idr., 2012; Póvoas idr., 2012; Gutiérrez in Ruiz, 2013; Manchado idr.,

2013; Michalsik idr., 2014a; Michalsik in Aagaard, 2014; Karcher in Buchheit, 2014; Póvoas

idr., 2014a; Póvoas idr., 2014b; Michalsik idr., 2014b; Krüger idr., 2014; Wagner idr., 2014;

Michalsik in Aagaard, 2015; Michalsik idr., 2015a; Michalsik idr., 2015b). Glede na to, da je

rokomet šport, ki je sestavljen iz visoko intenzivnih akcij prepletenih z obdobji manj

intenzivnih akcij in relativnega počitka so raziskovalci tudi skušali preučiti metabolične

zahteve rokometne igre. Pri tem so se osredotočali predvsem na meritve frekvence srčnega

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utripa in pa na vsebnost laktata v krvi pri igralcih med rokometnimi tekmami. Kljub mnogim

omejitvam, ki so bile predvsem metodološke narave so raziskovalci opravili v zadnjih letih na

tem področju velik napredek. Tako je izmeril Póvoas (2009) v svoji študiji izvedeni na

igralcih vrhunskih portugalskih moštev povprečno vrednost vsebnosti laktata v krvi 4.2 ± 2

(razpon 1.6–8.6) mmol.l-1 v prvem polčasu in 3.1 ± 1.8 (razpon 1.3–8.4) mmol.l-1 v drugem

polčasu. Drugi raziskovalci so se osredotočali predvsem na meritve vsebnosti laktata v krvi ob

koncu polčasa in ob koncu tekme. Tako je bila pri danskih vrhunskih igralcih izmerjena ob

koncu tekme vrednost 4.8 ± 1.9 mmol.l-1 (Michalsik idr., 2014b), pri mladih tunizijskih

igralcih pa 8.3 ± 0.9 mmol.l-1 (Chelly idr., 2011). V mnogih raziskavah so se avtorji

osredotočali na merjenje frekvence srčnega utripa med tekmo in skušali na podlagi teh

podatkov sklepati na metabolične procese v rokometašev organizmu. Tako je bilo na osnovi

razmerja med frekvenco srca in sprejemom kisika (FS/VO2) ugotovljen povprečen sprejem

kisika pri igralcih med tekmo v vrednosti 70.9 ± 6% (Michalsik idr., 2014b), 71 ± 6% (Srhoj

idr., 2002) in 74 ± 10% (Póvoas, 2009) maksimalnega sprejema kisika (VO2max). Z

neposredna analizo frekvence srca so Póvoas idr. (2011) ugotovili, da so igralci med tekmo

dosegali povprečne vrednosti 82 ± 9.3 % maksimalne frekvence srca (FSmax). V še novejši

raziskavi je Kruger s sodelavci (2013) analiziral FS pri igralcih med tekmo glede na igralna

mesta. Ugotovitve kažejo značilne razlike med igralci, ki igrajo na različnih igralnih mestih –

krila (85.2 ± 5.8 %) in zunanji igralci (86.4 ± 1.8 %) so v primerjavi s pivoti (83.4 ± 1.0 %)

dosegali višje vrednosti FSmax.

Igre na zmanjšanem prostoru in z manjšim številom igralcev

Igre na zmanjšanem proostoru in z manjšim številom igralcev so v zadnjem obdobju v

številnih športnih igrah postale zelo pomembne. Uporabljajo se lahko tako v smislu uvajanja

začetnikov v športne igre (otrokom se igra približa glede na njihove razvojne značilnosti) kot

tudi v smislu razvoja različnih sposobnosti in znanj pri odraslih igralcih. Še posebej velik

razvoj so tovrstne igre dosegle v nogometu in ragbiju, pa tudi v košarki, odbojki in kriketu.

Mnogi raziskovalci so v preteklosti ugotavljali pozitivne učinke prilagoditve igre v smislu

zmanjšanja prostora igranja in števila igralcev ter tudi prilagoditve nekaterih drugih pravil kot

so čas trajanja igre, odmor med posameznimi igrami, cilj zadevanja, itd. (Platt idr., 2001;

Tessitore idr., 2006; Jones in Drust, 2007; Rampinini idr.; Hill-Haas idr. 2011; Gabbet idr.,

2012; Gabbet idr., 2012a; Casamichana idr., 2014; Clemente idr., 2014; Halouani et al., 2014;

Harrison et al., 2014; Hoffman idr., 2014; Campos-Vazquez et al., 2014; Johnston et al.,

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2014; Köklü et al., 2015; Sampson idr.., 2015). Podoben proces lahko zasledimo tudi v

rokometu. Čeprav z nekaj zamude glede na nogomet se je razvoj prirejenih iger, ki so

ohranjale osnovne značilnosti rokometa zelo razširil. Hkrati pa so ta razvoj spremljale številne

raziskave, ki so skušale ovrednotiti pomen njihov pomen iz različnih vidikov. Pri tem je

potrebno posebej izpostaviti raziskavi v kateri so Buccheit idr. (2009 in 2009a) na osnovi

dobljenih rezultatov potrdili tezo, da je možno z prirejenimi igrami dosegati podobne učinke

na fiziološkem nivoju kot z generičnim intervalnim treningom. Ob tem pa trening s pomočjo

prirejenih iger vsebuje specifiko vsebine rokometa saj pomaga igralcem tudi pri

izpopolnjevanju tehničnih in taktičnih znanj. To avtorji izpostavljajo kot veliko prednost. Do

podobnih rezultatov so prišli tudi Clemente in Rocha (2014) ter Moss in Twist (2015).

Navedena dejstva so bila razlog, da smo se odločili za raziskavo o vplivu različnih velikosti

igrišča in števila igralcev v prirejenih igrah na spremembe v obremenitvi in naporu

rokometašev med igro. S tako dobljenimi rezultati smo želeli omogočiti trenerjem v praksi

bolj natančen uvid v možnosti ciljne manipulacije z določenimi parametri pri igranju

prirejenih igre.

9.2 CILJI IN HIPOTEZE

Namen raziskave je bil ugotoviti vpliv treh različnih dimenzij igrišča na razlike, ki nastanejo

v nekaterih pokazateljih napora in obremenitve igralcev rokometa kadar igrajo tekme s

prirejenimi pravili na manjšem prostoru v razmerju igralcev 3 proti 3 in 4 proti 4 z vratarjem.

Oblikovali smo štiri osnovne cilje:

1. Ugotoviti ali obstajajo statistično značilne razlike v obsegu in intenzivnosti cikličnih gibanj

igralcev na tekmah s prirejenimi pravili na manjšem prostoru različnih dimenzij v razmerju

igralcev 3 proti 3 in 4 proti 4 z vratarjem.

2. Ugotoviti ali obstajajo statistično značilne razlike v relativni frekvenci srca med tekmami s

prirejenimi pravili na manjšem prostoru različnih dimenzij v razmerju igralcev 3 proti 3 in 4

proti 4 z vratarjem.

3. Ugotoviti ali obstajajo statistično značilne razlike v obsegu in intenzivnosti cikličnih gibanj

igralcev na tekmah s številom igralcev 3 proti 3 glede na tekme odigrane z razmerjem igralcev

4 proti 4 na igriščih različnih dimenzij.

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4. Ugotoviti ali obstajajo statistično značilne razlike v relativni frekvenci srca med tekmami s

številom igralcev 3 proti 3 glede na tekme odigrane z razmerjem igralcev 4 proti 4 na igriščih

različnih dimenzij.

V skladu s Cilji raziskave smo postavili 12 ničelnih hipotez.

9.3 METODE DELA

Preizkušanci

Vzorec merjencev je sestavljalo osem moških amaterskih rokometašev (28 ± 3 leta, razpon

24–33 let) članov kluba Lazio Pallamano, ki je v času trajanja eksperimenta igral v italijanski

ligi A1 (2.liga). Med meritvami so morali biti igralci popolnoma zdravi in nepoškodovani. Vsi

so bili pred začetkom meritev seznanjeni z eksperimentalnim postopkom. Vsak igralec je

moral podpisati pisno izjavo, da je seznanjen z zahtevami in cilji eksperimentalnega postopka,

z morebitnimi tveganji in s prostovoljnim sodelovanjem pri nalogi.

Spremenljivke

V vzorec spremenljivk smo zajeli spremenljivke s področja obremenitev igralca med tekmo

(obseg in intenzivnost cikličnih gibanj, frekvenca pojavljanja acikličnih aktivnosti oz.

tehnično-taktičnih elementov) kot tudi nekatere spremenljivke, ki opisujejo fiziološke

odgovore organizma na obremenitev med igro (absolutne in relativne vrednosti frekvence

srca, subjektivna ocena napora).

Ciklična gibanja igralcev med tekmo so bila beležena kot obseg in intenzivnost vseh

pretečenih in/ali prehojenih razdalij na celotni tekmi. Intenzivnost cikličnih gibanj pa je bila

razdeljena na štiri hitrostne razrede: 1HR – opravljene razdalje v hitrosti do 1,4 m/s; 2HR -

opravljene razdalje v hitrosti od 1,4 do 3,4 m/s; 3HR - opravljene razdalje v hitrosti od 3,4 do

5,2 m/s; 4HR - opravljene razdalje v hitrosti nad 5,2 m/s (Bon, 2001; Pori idr., 2005). Izbrane

aciklične aktivnosti so bile naslednje: streli proti vratom z različnih igralnih mest in

položajev, zaleti proti vratom, podaje, skoki, zaustavljanje in izrivanje nasprotnika in

spremembe smeri gibanja.

Izmed fizioloških spremenljivk so bile v vzorec zajete naslednje spremenljivke: vrednosti FS

v mirovanju, najvišja dosežena vrednost FS v terenskem testu »30-15 IFT« (Buccheit, 2005),

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absolutne vrednosti FS med tekmami, relativne vrednosti FS med tekmo pod 50 % največjega

napora, relativne vrednosti FS med tekmo med 50 in 70 % največjega napora, relativne

vrednosti FS med tekmo med 70 in 90 % največjega napora in relativne vrednosti FS med

tekmo nad 90 % največjega napora. Te spremenljivke so bile izračunane na podlagi formule

po Karvonenu (Duarte idr., 2010).

Za ocenjevanje subjektivno doživetega napora igralcev med tekmami smo uporabili Borgovo

skalo CR10 (Borg, 1998), kjer so bile ocene v razponu od «sploh nič« do »zelo, zelo dosti«.

Potek in organizacija meritev

V raziskavi so bile analizirane igre v naslednjih eksperimentalnih pogojih:

- igra 3 proti 3 na igrišču dimenzij 24mx12m (cca. 30m2 na igralca);

- igra 3 proti 3 na igrišču dimenzij 30mx15m (cca. 57m2 na igralca);

- igra 3 proti 3 na igrišču dimenzij 32mx16m (cca. 67m2 na igralca);

- igra 4 proti 4 na igrišču dimenzij 24mx12m (cca. 22m2 na igralca);

- igra 4 proti 4 na igrišču dimenzij 30mx15m (cca. 42m2 na igralca);

- igra 4 proti 4 na igrišču dimenzij 32mx16m (cca. 50m2 na igralca).

Tekme so bile odigrane s consko obrambo s prirejenimi pravili glede začetnega meta in

disciplinskih kazni. Sodniki so bili uradni sodniki Italijanske rokometne zveze. Posamezna

igra je v eni enoti trajala 8 minut in se je tokom eksperimetalnega obdobja ponovila dvakrat.

Tekme so bile odigrane enkrat tedensko ob torkih, en teden igra 3 proti 3 in naslednji 4 proti

4. Tako je bilo skupaj odigrano 12 tekem, celoteno eksperimentalno obdobje pa je trajalo 4

mesece. V to obdobje sta vključeni tudi dve enoti meritev različnih uporabljenih testov.

Pred vsako eksperimentalno enoto oz. tekmo so si merjenci nadeli posebno oblačilo, ki je

omogočalo nošenje GPS naprave in oddajnika za merjenje FS (SPI pro elite 15hz, GPSports).

S pomočjo te naprave so se beležili premiki igralcev v xy ravnini. Pred začetkom igranja so

merjenci opravili standardizirano ogrevanje v trajanju 20 minut. Takoj po koncu vsake igre so

morali igralci merilcu povedati osebno oceno napora glede na Borgovo skalo. Tekme so bile

posnete tudi s posebno kamero, ki je kasneje omogočala ugotavljanje frekvence pojavljanja

acikličnih aktivnosti.

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Metode obdelave podatkov

Za nadaljnjo statistično analizo smo uporabili statitični programski paket SPSS – 17.0

(Chicago, U.S.A.). Najprej smo za vse uporabljene spremenljivke izračunali osnovno opisno

statistiko in normalnost porazdelitve podatkov s pomočjo testa Kolmogorov-Smirnov.

Statistično značilne razlike so bile sprejete ob petodstotni napaki alfa. Za določitev razlik med

opravljenimi cikličnimi aktivnostmi ter med vrednostmi FS v določenem območju igrami v

razmerju igralcev 3 proti 3 in 4 proti 4 je bila uporabljena multivariantna analiza variance

(MANOVA) za ponovljene meritve. Za določitev posameznih razlik pa je bil uporabljen

Fisherjev post-hoc test z Bonfferonijevo korekcijo.

9.4 REZULTATI

Rezultati so prikazani v treh deli. Najpej je analizirana igra 3 proti 3 glede tekme odigrane na

igriščih vseh treh dimenzij. V drugem delu na enak način predstavljamo rezultate dobljene na

tekmah z razmerjem igralcev 4 proti 4. Na koncu pa je opravljena še primerjava med tekmami

v obeh eksperimentalnih pogojih glede na število igralcev – torej tekme 3 proti 3 v primerjavi

s tekmami 4 proti 4.

Analiza obremenitve in napora na tekmah z razmerjem igralcev 3 proti 3

Skupna razdalja, ki so jo igralci med tekmo prehodili in pretekli se je povečala z naraščanjem

dimenzij igrišča.

Tabela 1

Razlike v celotni opravljeni razdalji na vseh treh dimenzijah igrišča pri igri 3 proti 3

Igrišče Celotna razdalja (m)

24×12m 885.2±66.7

30×15m 980.0±73.5*

32×16m 1095.0±113.0*#

* - značilna razlika v primerjavi z igriščem 24x12m (p<0.05; velik ES).

# - značilna razlika v primerjavi z igriščem 30x15m (p<0.05; velik ES).

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Pri analizi skupno opravljene razdalje smo na tekmah 3 proti 3 ugotovili značilne razlike med

vsemi tremi igrišči (p<0.05; velik ES).

Tabela 2

Razlike v razdalijah opravljenih v štirih hitrostnih območjih na vseh treh dimenzijah igrišča

pri igri 3 proti 3

Igrišče 1HR (m) 2HR (m) 3HR (m) 4HR (m)

24×12m 267.0±25.0 526.7±30.8 85.2±46.1 0.4±1.0

30×15m 219.9±22.7* 633.9±65.0* 155.5±71.0* 6.2±11.1

32×16m 230.0±30.5 669.8±80.4* 205.8±77.5* 27.9±35.9

Legenda: 1HR – hitrost 0-1,4 m/s; 2HR – hitrost 1,4-3,4 m/s; 3HR – hitrost 3,4-5,2 m/s; 4HR

- hitrost >5,2 m/s

* - značilna razlika v primerjavi z igriščem 24x12m (p<0.05; srednji ES).

Pri analizi opravljenih razdalij v štirih hitrostnih območjih na tekmah z razmerjem igralcev 3

proti 3 smo ugotovili, da so igralci na igrišču dimenzij 30×15m v primerjavi z igriščem

24×12m opravili manjšo razdaljo v prvem hitrostnem območju in večjo razdaljo v drugem in

tretjem hitrostnih območju (p<0,05; srednji ES). Značilne razlike so bile pri igri 3 proti 3

ugotovljene tudi pri primerjavi igre na igriščih dimenzij 24×12m glede na igrišče 32×16m:

igralci so opravili večjo razdaljo na igrišču 32×16m v drugem in tretjem hitrostnem območju

(p<0.05; srednji ES).

Table 3

Razlike v frekvenci pojavljanja acikličnih aktivnosti pri igri 3 proti 3 na vseh treh dimenzijah

igrišča

Igrišče Akcije Streli Podaje ZNRT Zaleti Skoki SSG

24×12m 34±1 58±5 71±6 15±3 8±2 11±2 7±3

30×15m 29±1 49±3 65±6 4±1 6±1 8±2 6±3

32×16m 28±2 48±4 72±4 6±1 3±1 8±3 4±2

Legenda: ZNRT - zaustavljanje napadalcev z rokami in telesom; SSG - Spremembe smeri

gibanja

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Na osnovi dobljenih podatkov ni bilo možno potrditi statistično značilnega vpliva različnih

dimenzij igrišča na frekvenco pojavljanja acikličnih aktivnosti pri igri v razmerju igralcev 3

proti 3 (Tabela 3).

Tabela 4

Delež časa, ki so ga igralci med igro 3 proti 3 preživeli v različnih območjih napora

določenega z relativno frekvenco srca

Igrišče <50% FSrel

(% časa)

50%-70% FSrel

(% časa)

70%-90% FSrel

(% časa)

>90% FSrel

(% časa)

24×12m 0.6±0.9 5.0±4.4 40.8±27.4 53.7±31.6

30×15m 2.7±1.1 9.5±9.8 65.1±23.3 22.7±27.7

32×16m 0.6±1.1 3.4±1.6 47.1±37.8 48.9±39.3

Kot je razvidno iz Tabele 4 nismo mogli potrditi statistično značilnega vpliva različnih

dimenzij igrišča na frekvenco srca v različnih območjih napora pri igri 3 proti 3.

Tabela 5

Razlike v vrednostih ocen zaznanega napora (RPE) med igro 3 proti 3

Igrišče RPE vrednosti

24×12m 6.3±0.5

30×15m 7.7±0.8

32×16m 8.2±1.0*

* - značilna razlika v primerjavi z igriščem dimenzij 24x12m (p<0.05; velik ES)

Ocena stopnje zaznanega napora je bila na tekmah 3 proti 3 značilno višja na igrišču 32×16m

v primerjavi z igriščem 24×12m (p<0,05; veliki ES). Ostale razlike pa niso bile značilne

(Tabela 5).

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Analiza obremenitve in napora na tekmah z razmerjem igralcev 4 proti 4

Za razliko od igre v razmerju igralcev 3 proti 3 je prišlo v igri 4 proti 4 do zmanjšanja

prehojenih in pretečenih razdalij na igrišču dimenzij 32×16m v primerjavi z igriščem dimenzij

30×15m. Razlika pa je bila zelo majhna.

Tabela 6

Razlike v celotni opravljeni razdalji na vseh treh dimenzijah igrišča pri igri 4 proti 4

Igrišče Celotna razdalja (m)

24×12m 948.1±64.5

30×15m 1087.2±92.0*

32×16m 1079.8±90.6

* - značilna razlika v primerjavi z igriščem 24x12m (p<0.05; velik ES).

Pri analizi skupno opravljene razdalje smo na tekmah 4 proti 4 ugotovili značilne razlike med

igriščem dimenzij 24×12m v primerjavi z igriščem 30×15m (p<0.05; velik ES) (Tabela 6).

Tabela 7

Razlike v razdalijah opravljenih v štirih hitrostnih območjih na vseh treh dimenzijah igrišča

pri igri 4 proti 4

Igrišče 1HR (m) 2HR (m) 3HR (m) 4HR (m)

24×12m 227.3±20.1 613.4±66.6 114.1±52.3 3.9±5.9

30×15m 212.0±27.7* 618.6±40.3 242.9±75.0* 19.6±25.4

32×16m 176.3±42.9* 635.1±98.0 289.5±75.2* 13.9±11.1

Legenda: 1HR – hitrost 0-1,4 m/s; 2HR – hitrost 1,4-3,4 m/s; 3HR – hitrost 3,4-5,2 m/s; 4HR

- hitrost >5,2 m/s, * - značilna razlika v primerjavi z igriščem 24x12m (p<0.05; srednji ES).

Pri analizi opravljenih razdalij v štirih hitrostnih območjih na tekmah z razmerjem igralcev 4

proti 4 smo ugotovili, da so igralci na igrišču dimenzij 24×12m dosegli značilno višje

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vrednosti opravljenih razdalij v prvem hitrostnem razredu in značilno nižje vrednosti v tretjem

hitrostnem razredu v primerjavi s tekmami odigranimi na igriščih drugih dveh dimenzij

(p<0.05; srednji ES) (Tabela 7).

Tabela 8

Razlike v frekvenci pojavljanja acikličnih aktivnosti pri igri 4 proti 4 na vseh treh dimenzijah

igrišča

Igrišče Akcije Streli Podaje ZNRT Zaleti Skoki SSG

24×12m 32±2 46±2 78±8 5±1 4±2 6±2 3±2

30×15m 27±1 41±4 75±10 5±1 3±1 6±2 2±2

32×16m 26±2 41±5 74±13 3±2 2±1 5±2 2±1

Legenda: ZNRT - zaustavljanje napadalcev z rokami in telesom; SSG - Spremembe smeri

gibanja.

Na osnovi dobljenih podatkov ni bilo možno potrditi statistično značilnega vpliva različnih

dimenzij igrišča na frekvenco pojavljanja acikličnih aktivnosti pri igri v razmerju igralcev 4

proti 4 (Tabela 8).

Tabela 9

Delež časa, ki so ga igralci med igro 4 proti 4 preživeli v različnih območjih napora

določenega z relativno frekvenco srca

Igrišče <50% FSrel

(% časa)

50%-70% FSrel

(% časa)

70%-90% FSrel

(% časa)

>90% FSrel

(% časa)

24×12m 0.9±0.7 3.0±1.0 40.0±26.4 56.1±27.7

30×15m 4.2±3.3 3.9±1.8 47.7±32.8 44.1±33.6

32×16m 3.3±1.9 4.7±3.5 59.1±35.3 32.9±38.7

Kot je razvidno iz Tabele 9 nismo mogli potrditi statistično značilnega vpliva različnih

dimenzij igrišča na frekvenco srca v različnih območjih napora pri igri 4 proti 4.

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Tabela 10

Razlike v vrednostih ocen zaznanega napora (RPE) med igro 4 proti 4

Igrišče RPE vrednosti

24×12m 7.7±1.0

30×15m 8.2±1.2

32×16m 7.3±1.2

Kot je razvidno iz Tabele 10 se tudi ocena stopnje zaznanega napora na tekmah 3 proti 3 ni

značilno razlikovala glede na igro na igriščih različnih dimenzijje (Tabela 10).

Analiza obremenitve in napora na tekmah z razmerjem igralcev 3 proti 3 v primerjavi z

tekmami odigranimi v razmerju igralcev 4 proti 4

Skupna razdalja, ki so jo igralci med tekmo prehodili in pretekli se je povečala z naraščanjem

dimenzij igrišča v obeh eksperimentalnih pogojih – tako pri igranju 3 proti 3 kot pri igri 4

proti 4. Edina izjema je bila zabeležena pri igri 4 proti 4 kjer je prišlo do majhnega

zmanjšanja povprečno opravljenih razdalij med igriščem 30×15m v primerjavi z igriščem

32×16m (Tabela 11).

Tabela 11

Razlike v celotni opravljeni razdalji na vseh treh dimenzijah igrišča pri igri 3 proti 3 v

primerjavi z igro 4 proti 4

Igrišče 3 proti 3 celotna razdalja (m) 4 proti 4 celotna razdalja (m)

24×12m 885.2±66.7 948.1±64.5

30×15m 980.0±73.5

1087.2±92.0

32×16m 1095.0±113.0

1079.8±90.6

Primerjava vseh prehojenih in pretečenih razdalij pri igri 3 proti 3 in igri 4 proti 4 ni pokazala

statistično značilnih razlik na nobenem izmed igrišč (Tabela 11).

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Tabela 12

Obseg razdalij prehojenih in pretečenih v štirih hitrostnih območjih pri igri 3 proti 3 v

primerjavi z igro 4 proti 4

1HR (m) 2HR (m) 3HR (m) 4HR (m)

3vs3 4vs4 3vs3 4vs4 3vs3 4vs4 3vs3 4vs4

24×12 267.0±25.0 227.3±20.1 526.7±30.8 613.4±66.6 85.2±46.1 114.1±52.3* 0.4±1.0 3.9±5.9

30×15 219.9±22.7 212.0±27.7 633.9±65.0 618.6±40.3 155.5±71.0 242.9±75.0* 6.2±11.1 19.6±25.4

32×16 230.0±30.5 176.3±42.9 669.8±80.4 635.1±98.0 205.8±77.5 289.5±75.2* 27.9±35.9 13.9±11.1

Legenda: HR – hitrostni razred.

* - Značilna razlika med igro 4 proti 4 v primerjavi z igro 3 proti 3 (p<0.05; srednji ES).

Tabela 13

Razlike v frekvenci pojavljanja acikličnih aktivnosti pri igri 3 proti 3 v primerjavi z igro 4

proti 4

24x12m 30x15m 32x16m

3vs3 4vs4 3vs3 4vs4 3vs3 4vs4

Akcije 34±1 36±1 30±1 26±0 30±1 28±1

Podaje 72±9 69±5 67±9 79±16 72±4 9±4

ZNRT 16±1 6±0 4±1 6±1 5±1 2±1

PM 10±3 3±1 7±1 4±2 3±1 2±1

Skoki 12±2 6±2 8±3 7±4 8±3 7±2

SSG 8±3 3±2 5±3 3±2 4±2 2±1

Legenda: ZNRT - zaustavljanje napadalcev z rokami in telesom; SSG - Spremembe smeri

gibanja

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9.5 RAZPRAVA

Rezultati raziskave kažejo, da imata različno število igralcev v posamezni ekipi in različne

dimenzije igrišča učinek na obremenitev in napor rokometašev pri igranju iger s prirejenimi

pravili. Pri igri 3 proti 3 je bilo zabeleženo naraščanje obsega cikličnih aktivnosti hkrati z

naraščanjem dimenzij igrišča. Pri igri 4 proti 4 pa sta rezultata dosežena pri igri na igrišču

30x15 in 32x16 zelo podobna (nekoliko višja je celo vrednost na manjšem igrišču). Kljub

temu lahko načeloma zaključimo, da se velikost igrišča odraža tudi na obsegu opravljenih

cikličnih aktivnosti. Za lažjo primerjavo smo uporabili tudi parameter “obseg cikličnih

aktivnosti na minuto”. Pri igri 3 proti 3 je bila na igrišču dimenzij 24×12m dosežena vrednost

110.7 m.min-1, na igrišču dimenzij 30×15m 122.5 m.min-1 in na največjem igrišču 136.9

m.min-1. Pri igri 4 proti 4 je vrednost na najmanjšem igrišču dimenzij 24×12m še nekoliko

višja in znaša 118.5 m.min-1. Vrednosti na drugih dveh igriščih pa sta skoraj identični - 135.9

m.min-1 in 135.0 m.min-1. Ti dve vrednosti sta zelo podobni vrednosti doseženi na največjem

igrišču pri igri 3 proti 3. Iz vidika uporabnosti analiziranih iger pa je zanimivo, da so vse

omenjene vrednosti višje kot tiste, ki so jih zabeležili raziskovalci na tekmah na normalnem

rokometnem igrišču in so varirale od 79.8m.min-1 (Bon, 2001) do 87.5m.min-1 (Pori idr.,

2009). So pa naši podatki primerljivi s tistimi, ki so jih pri nogometni igri na zmanjšanem

prostoru dobili Barbero-Alvarez idr. (2007) in Pereira idr. (2007). Po drugi strani pa so nižji

kot rezultati dobljeni v podobni raziskavi na rokometaših, kjer so igralci v povprečju prehodili

in pretekli 154m/min (Buchheit idr., 2009a). Iz te raiskave je tudi razvidno, da nekoliko krajše

trajanje igre z vmesnim odmorom (2×225sek.) in velika igralna površina (celotno rokometno

igrišče ob razmerju igralcev 4 proti 4) dovoljuje igralcem, da opravijo relativno velik obseg

cikličnih dejavnosti.

Ob analizi intenzivnosti cikličnih aktivnosti razdeljenih v štiri hitrostne razrede smo prišli do

ugotovitve, da igralci pri igrah na manjšem prostoru opravijo najmanjši obseg aktivnosti v

tretjem in četrtem HR (hiter tek in sprint). Se je pa delež teh dveh razredov povečeval hkrati s

povečevanjem velikosti igrišča tako pri igri 3 proti 3 kot pri igri 4 proti 4. Verjetno majhen

igralni prostor ne dovoljuje igralcem, da bi razvili dovolj veliko hitrost teka ker so razdalje

teka kratke. Do podobnih rezultatov so prišli tudi pri analizi malih iger pri nogometu

(Castellano in Casamichana, 2010).

Pri zabeleženi frekvenci acikličnih aktivnosti ni prišlo do značilnih razlik med tekmami

odigranimi na različno velikih igriščih tako v razmerju igralcev 3 proti 3 kot v razmerju

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igralcev 4 proti 4. Tudi pri proučevanju prirejenih nogometnih iger so raziskovalci prišli do

podobnih podatkov (Tessitore idr., 2006; Kelly in Drust, 2009).

V naši raziskavi pa nismo mogli potrditi statistično značilnega vpliva različnih dimenzij

igrišča na frekvenco srca v različnih območjih napora tako pri pri igri 3 proti 3 kot pri igri 4

proti 4. Če pa primerjamo naše podatke s podatki raziskave, ki jo je opravil Kruger idr. (2013)

na igralcih, ki so igrali normalne rokometne tekme (krila - 85.2 ± 5.8 % FSmax; zunanji igralci

- 86.4 ± 1.8 % FSmax; pivoti 83.4 ± 1.0 % FSmax) lahko ugotovimo, da so naši merjenci

dosegali zelo visoke vrednosti. Gotovo so visoke vrednosti FS zabeležene med tekmami

posledica velike količine opravljenih cikličnih aktivnosti na minuto, velike količine skokov,

sprememb smeri gibanja in specifičnih rokometnih akcij.

9.6 ZAKLJUČEK

Glede na dobljene podatke in opravljene primerjave ter razpravo lahko zaključimo, da so

prirejene igre glede prostora in števila igralcev uporabne kot trenažno sredstvo pri rokometu.

Tako parametri obremenitve in kot napora med posameznimi tekmami kažejo določene

razlike do katerih prihaja na podlagi različnega števila igralcev in velikosti igrišča. Visoko

razmerje cikličnih aktivnosti na minuto in izmerjene visoke vrednosti frekvence srca kažejo

na veliko vrednost analiziranih iger pri razvoju aerobne moči rokometašev. Prisotnost

velikega števila skokov še posebej v igri na igrišču dimenzij 24×12m omogoča tudi ugodne

učinke na razvoj specifične odrivne moči. Je pa majhno igrišče lahko problematično iz vidika

razvoja višjih hitrosti teka (sprinta) tako da igralci ne morejo razviti svojih najvišjih hitrosti

teka. Je pa tovrstna igra izredno koristna tudi zaradi prisotnosti velikega števila acikličnih

aktivnosti. Predvsem veliko število obrambnih aktivnosti (zaustavljanje nasprotnika z rokami

in telesom) kaže na možnost razvoja tehničnih in taktičnih znanj igralcev v igri 1 proti 1, ki je

pri rokometu zelo pomembna. Tudi veliko število strelov daje tem igram veliko vrednost, saj

je ob običajnem igranju rokometa število strelov na časovno enoto bistveno nižje. Rezultati

raziskave kažejo, da je večina značilnih razlik nastala med najmanjšim igriščem in ostalima

dvema igriščema. Medtem, kjer je bila razlika glede prostora na igralca najmanj 20m2

in več.

Podatki o obremenitvi in naporu igralcev na srednjem in največjem igrišču, ki se glede

prostora namenjenega posameznemu igralcu nista razlikovala več kot 10m2, so bili zelo

podobni in se niso značilno razlikovali. Iz tega izhaja eden izmed pomembnejših zaključkov

naše raziskave, ki je namenjen predvsem športni praksi. Če namreč trenerji želijo manipulirati

z malimi igrami z namenom, da bi dosegli različne cilje, morajo spreminjati razliko v prostoru

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na posameznega igralca najmanj za 20m2. Ta zaključek pa je pomemben tudi za raziskovalno

dejavnost na tem področju. Pri igriščih, ki se glede na relativno kvadraturo na posameznega

igralca ne razlikujejo dovolj, načeloma raziskovalci ne morejo pričakovati značilnih razlik v

parametrih obremenitve in napora.