One of the most fundamental steps in any multistep sport program is to evaluate the player's performance, within different areas.1 Nevertheless, in team sports, performance is not simple to measure2 and selection is known to be as a complex process (often unstructured).3 In fact, the literature relations to sports expertise, has tended to be mono-disciplinary.

In team-handball, the study of the morphologic profile of successful athletes has been one of the issues most often addressed, and the differences between players from teams exhibiting different levels of performance4 are one of the main areas of study.

Also the physiology of team-handball (and fitness) is now better understood,5, 6 and it is known that modern team-handball incorporate acyclical patterns of movement (the intensity of exercises varies in a relatively unpredictable manner).7

About the interaction between expertise and individual movement patterns, it seems that random variability characterizes less experienced motor performance, whereas active functional variability may demonstrate expert motor performance.8 In other words, it seems that movement frequency rate (which is associated with the ability of ball manipulation) may significantly predict team-handball players’ performance.9 Nevertheless, the choice and the frequency of using a particular tactical option in attack did not guarantee efficiency (to score), and could be affected by the level of individual technical-tactical skills in low-quality teams.10 These findings suggested that the team-handball-specific skill evaluation could be useful as a selection indicator.3

In addition, the sport psychology literature, based on the idea that psychological attributes can contribute to athletic success, has incorporated since its inception, a great interest in the study of excellence.11 It seems that motivation,12 anxiety management and coping skills13 may play an important role in athletic development, but it is still difficult to determine strong psychological differences between elite athletes and their less successful counterparts.14

However, to move forward in the understanding of expertise a more multidisciplinary approach is needed. In accordance, we hypothesized that significant differences could be found among performance groups and the purposes of the present study were: (i) to describe and compare morphological, physiological, specific-skills and psychological attributes of team-handball players from two teams with different performances, and (ii) to identify the variables that differentiated between the successful and less-successful team-handball players.

Thirteen teams participated in the National Handball Professional Championship. A total of thirty-four team-handball players (age 23.4 ± 4.7 years), from two teams ranked (during the 1st half of the National Championship), i.e. (i) first (Successful; n = 18; age, 23.0 ± 3.8 years), and (ii) last place (i.e. thirteenth) (Less-Successful, n = 16, age 23.8 ± 5.6 years), were studied. The local Scientific and Ethical committees approved the experimental protocol. Before inclusion in the study, the objectives and procedures were explained to subjects, and written informed consent was obtained from them. All participants were tested during the competitive period, and measurements of each participant were undertaken according to four categories of variables, namely: morphological (proportionality, somatotype and body composition), physiological, team-handball-specific skills (technical skills and game intelligence) and psychological profiling.

A total of thirty-three anthropometric dimensions were obtained. The dimensions included five basic measures, nine skinfolds (mm), eight girths (cm), six breadths (cm) and five lengths (cm). The five basic measures were stature (cm), body mass (kg), sitting height (cm), armspan (cm), handspan (cm). The nine skinfolds were subscapular, triceps, biceps, chest, midaxillary, iliac crest, abdominal, front thigh and medial calf. The eight girths were head, arm (relaxed), arm (flexed and tensed), forearm (maximum), chest (mesosternale), waist (minimum), thigh (mid-troch-tib. lat.) and calf (maximum). The six bone breadths were biacromial, transverse chest, A–P chest depth, biiliocristal, humerus and femur. The five lengths were acromiale-dactylion, acromiale-radiale, radiale-stylion, radiale-dactylion and midstylion-dactylion. Measurements included in the anthropometric profile were obtained following the protocol in Marfell-Jones et al.,15 with the exception of armspan (perpendicular distance between the longitudinal planes of the left and right dactyilon), handspan (the greater distance between the longitudinal planes of the 1st and 5th fingers), chest skinfold (the skinfold measurement was taken obliquely in the mean distance between the breast nipple and the axilla fold), midaxillary (measured horizontally in the level of xiphoid-sternal articulation over the midaxillary line), acromiale-dactylion length (the linear distance between the acromiale and dactylion sites) and radiale-dactylion length (the linear distance between the radiale and dactylion sites). Anthropometric measurements were obtained using portable measurement devices. Stature and heights were measured without shoes and head-covers, using a portable Anthropometer (GPM, Siber-Hegner, Zurich, Switzerland, 2008) calibrated to the nearest 0.1 cm. Body mass was measured with subjects wearing light clothing and without shoes, to the nearest 0.5 kg, using a scale (Secca model 761 7019009, Vogel & Halke, Hamburg, Germany, 2006) calibrated with known weights. Skinfold thickness was obtained using a skinfold caliper (Slim Guide, Rosscraft, Surrey, Canada, 2001), lengths and diameters using a large sliding caliper (GPM, Siber-Hegner, Zurich, Switzerland, 2008), girths using a flexible non-stretching steel (Model W606PM, Lufkin, TX, USA). All measures were collected by two technicians accredited by the International Society for the Advancement of Kinanthropometry (ISAK) with the levels 1 and 2 (the intra-observer technical errors of measurements were well below the accepted maximum for stature, skinfolds, breadths and girths). Measurements were gathered and used to evaluate proportionality, somatotype and body composition. The somatotype was determined according to Head-Carter anthropometric protocol16 and to evaluate body composition, the fractionation of body mass in five components (skin, adipose, bone, muscle and residual tissue masses) was used.17

Before the physiological tests, performed a 20-min warm-up (incorporating a slow jog followed by static and dynamic stretching) prior to, and rested during the 10-min between tests (recovery period). Water breaks and extra rest time were allowed if needed. Each athlete was instructed and verbally encouraged to give his maximal effort.

Participants performed nine tests and fourteen variables were recorded for analysis. These included two speed tests: 30-m sprint and agility.18 All sprint times were recorded using electronic timing lights (Wireless Sprint System, BROWER Timing Systems, Salt Lake City, UT, USA) and the best scores (time; in s) were recorded for analysis. To determine lower body explosive strength, as reported in Bosco et al. protocol,19 the athletes performed four different vertical jumps (squat jump; countermovement jump; Abalakov jump; drop jump – 40 cm) on an Ergojump (Digitime 1000, Digitest, Jyvaskyla, Finland). Three trials were performed and the best trial was recorded for analysis (in m). To complement the aforesaid tests to determine the upper body explosive strength, the athletes performed three trials of two vertical jumps adapted to arms (i.e. squat jump adapted to arms; countermovement jump adapted to arms). To measure handgrip strength, the participants completed three trials (with each hand; in kgf), on a grip strength dynamometer (Jamar Hidraulic Hand Dynamometer, Sammons Preston, Bolingbrook, IL, USA).18 To measure back strength the participants completed three trials on a back muscle dynamometer (Takei n°1858, Tokyo, Japan).18 In all dynamometry measures, the best scores were recorded for analysis (in kgf). The abdominal strength (i.e. endurance) was assessed using the sit-up test (in 60 s), and the number of executions was recorded for analysis (#).18 To study the aerobic capacity, the participants performed the Cooper test18 and the estimated VO2max values (R = 0.90) were calculated using the Cooper test equation [VO2max = 22.351 × (distance; in m)/1000) − 11.288].20 To perform the Back-Saver Sit-and-Reach test, the participants completed three trials on a flex tester (AcuFlex, Novel Products Inc, Addison, IL, USA), as reported by the Cooper Institute for Aerobics Research.21 The best score was recorded for analysis (in cm).

According to Massuça et al. (in press), the scientific literature does not include validated tools to assess the technical and tactical proficiency of team-handball athletes. To achieve this purpose, two handball expert coaches evaluated (on a five-points Likert scale ranging from “very poor” – 1 to “excellent” – 5), during 2 training sessions, all participants using the grid suggested by Moreno,22 i.e.: (i) seven motor/technical skills dimensions (defensive displacements; types of marking; ability to retrieve balls; ability to escape the opponent; pass and reception; type of shots; one vs one); and (ii) four cognitive and game intelligence dimensions (ability to create and fill up spaces; offensive and defensive battle; defensive collaboration; ability to vary their actions).

All participants completed three psychological tests: (i) Task and Ego Orientation in Sport Questionnaire – TEOSQ; (ii) Sport Competition Anxiety Test - SCAT; and (iii) Inventory of Self-Perception – ICAC.

The TEOSQ, a trait-based version of Duda,23 provided a measure of motivational orientation. The exploratory factor analysis done, with a subsample of adult male handball athletes (n = 203) from the Portuguese (European) cultural context, supported: (i) the hypothesized theoretical model of two factors (Bartlett's Test of Sphericity: χ2 = 628.992, df = 78, P < 0.001; KMO = 0.754; GFI = 0.927; AGFI = 0.874; RMSR* = 0.040), and (ii) a satisfactory internal consistency (Cronbach's alpha coefficients being 0.70 and 0.77 for the task and ego orientation subscales, respectively). Subjects must respond to 13 items concerning success in sport, which are preceded by the statement “I feel most successful in sport. Responses to each item are measured on a five-point Likert scale ranging from “strongly disagree”1 to “strongly agree”5 and the intensity of agreement or disagreement with each item reflects: or a possible task orientation (e.g. “I learn a new skill by trying hard”) or an ego orientation (e.g. “I can do better than my team mates”). Both, task and ego orientations were calculated.

The SCAT is a 15-item scale that is used to measure competitive trait anxiety in adults. Ten of the above mention items make up the scale; five are spurious items (1, 4, 7, 10, and 13) included solely to reduce response bias. Items are measured on a 3-point scale, from “Hardly Ever”1 to “Often”.3 Scores range from 10 to 30, and higher scores indicate higher competitive trait anxiety. Sample items include, e.g. “Before I compete I worry about not performing well” and “Before I compete I get a queasy feeling in my stomach”. The psychometric properties of this scale have been extensively evaluated.24 Item-total correlations range from 0.60 to 0.82. Internal consistency ranges from 0.95 to 0.97 and mean test-retest reliability is 0.77. Martens et al.24 reported that high SCAT scores were related to high competitive state anxiety in competitive situations and that SCAT scores predicted competitive state anxiety better than coaches’ ratings.

The ICAC is a subjective scale of self-assessment. To fill the scale subjects must respond to 20 items concerning self-perception. Responses to each item are measured on a five-point Likert scale ranging from “Disagree”1 to “Very much agree”.5 Higher scores indicate higher self-concept. According to Vaz-Serra,25 this instrument has good internal consistency (Spearman–Brown coefficient = 0.791 for a sample of 920 participants) and high temporal stability (test–retest = 0.838, for an interval of 4 weeks). An exploratory factor analysis supports the theoretical model of six factors25: (i) Social acceptance/rejection (e.g. “I’m usually well accepted by others”; α = 0.76); (ii) Self-efficacy (e.g. “I often give up my job when I meet difficulties”; α = 0.70); (iii) Psychological maturity (e.g. “Tend to be frank and express my opinions”; α = 0.72); (iv) Impulsivity-activity (e.g. “I am a person who really like doing what I want”; α = 0.71). However, because the fifth and sixth factors had a mixed nature23 were not considered in this study.

All calculations were performed using the Statistical Package for the Social Sciences (SPSS Inc, version 17.0, Chicago, Illinois). Descriptive and comparative data are presented, and group data are expressed as mean and standard deviation (SD) for all dependent variables. Variables were checked for normality. Successful and Less-Successful groups were compared on each variable of interest using multivariate (Non-Parametric MANOVA) and univariate (Non-Parametric ANOVA) analysis of variance. The stepwise discriminant function analysis was used for all data sets to determine which combination of measures best discriminated between the two groups of players. Finally, in a multidisciplinary approach, all selected variables were analyzed together, using the stepwise discriminant function, to determine which combination of measures best discriminated between the two groups of success. For all analyses, 5% was adopted as the significance level.

As previously mentioned, measurements for each participant were undertaken within to four categories, i.e. morphological, physiological, handball-specific skills and psychological profile, related variables.

No significant differences were indicated, using MANOVA, in anthropometric measures (¿ = 0.06, F31,2 = 9.948) and specially as regards girth measures (¿ = 0.776, F8,25 = 0.901) and breath mesures (¿ = 0.789, F6,27 = 1.205). However, the MANOVA showed significant difference between groups in what concerns basic measures (¿ = 0.614, F4,29 = 4.563, P < 0.01), skinfolds measures (¿ = 0.348, F9,24 = 4.995, P < 0.01) and length measures (¿ = 0.714, F4,29 = 2.903, P < 0.05). ANOVA showed significant differences between groups in stature, sitting height and suprailiac skinfold. Discriminant analysis showed that a combination of five variables could successfully discriminated between groups (coefficient: stature = −1.738; chest skinfold = −1.740; iliac crest skinfold = 1.005; biiliocristal breath = 1.234; radiale-dactylion length = 1.514). The described function (¿ = 0.165, χ2(5) = 53.080, P < 0.001) explained 100% of anthropometric variance. MANOVA showed significant differences in somatotype components (¿ = 0.763, F3,30 = 3.108, P < 0.05) specificaly in endomorphy (ANOVA). In fact, discriminant analysis showed that endomorphy (coefficient = 1.000) successfully discriminated the two groups; 61.8% of original grouped cases were correctly classified (¿ = 0.830, χ2(1) = 5.886, P < 0.05). Nevertheless, no significant differences were observed in the study of body composition (¿ = 0.752, F5,28 = 1.846) (Table 1).

Table 1. Descriptive statistics of morphological characteristics (proportionality, somatotype and body composition) for Successful and Less-Successful team-handball groups (mean (SD)), and independent samples comparisons.

The mean difference is: not significant (NS).

* P < 0.05.

** P < 0.01.

The MANOVA showed significant groups difference on physiological characteristics (¿ = 0.306, F14,19 = 3.085, P < 0.05). Univariate ANOVA showed that there were significant differences between groups for 30-m sprint, sit-ups, handgrip strength (right and left) and back strength. Discriminant analysis showed that the standing vertical jump (coefficient = 0.876) was more discriminant than the variables 30-m sprint (coefficient = 0.789), sit-ups (coefficient = −0.774) or the right handgrip task (coefficient = 0.584). Moreover, the function (¿ = 0.354, χ2(4) = 31.127, P < 0.001) explain 88.2% of physiological variance (Table 2).

Table 2. Descriptive statistics of physiological characteristics for Successful and Less-Successful team-handball groups (mean (SD)), and independent samples comparisons.

SJ, Standing vertical jump; CMJ, countermovement vertical jump; ABK, Abalakov jump; DJ40, drop jump from 40-cm; SJA, standing vertical jump adapted to arms; CMJA, countermovement vertical jump adapted to arms.

The mean difference is: not significant (NS)

* P < 0.05.

** P < 0.01.

The MANOVA indicated no significant differences between groups in technical skills evaluation (¿ = 0.761, F7,26 = 1.164). However, the ability to retrieve balls was significantly different when using the univariate ANOVA. Furthermore, the discriminant analysis (¿ = 0.882, χ2(1) = 3.949, P < 0.05) showed that the ability to retrieve balls (coefficient = 1.000) could discriminate between groups and explained 73.5% of the technical skills variance. Considering tactical variables, the MANOVA showed that there was no difference between groups in what concerns the four game intelligence variables taken into account (¿ = 0.923, F4,29 = 0.604, P > 0.05), confirmed via ANOVA (Table 3).

Table 3. Descriptive statistics of specific skills scores of Successful and Less-Successful team-handball groups (mean (SD)), and independent samples comparisons.

The mean difference is: not significant (NS).

* P < 0.05.

Performances in the three psychological tests (questionnaires) were similar between groups, and no significant differences were observed when using MANOVA (¿ = 0.642, F8,25 = 1.742, P > 0.05), in fact, the univariate ANOVA confirmed that the studied variables were not significantly different between groups (Table 4).

Table 4. Descriptive statistics of psychological characteristics for Successful and Less-Successful team-handball groups (mean (SD)), and independent samples comparisons.

The mean difference is not significant (NS).

Using all the previous significant and discriminant variables, a new stepwise discriminant function analysis showed that one function (¿ = 0.200, χ2(6) = 46.603, P < 0.001), with a combination of six variables, could successfully discriminate the groups studied (Successful = −1.827; Less-Successful = 2.055) and explained 94.1% of variance (cumulative). Moreover, the variables classification showed that the 30-m sprint time was the variable that best differentiated between groups followed by stature, the the ability to vary their actions, the performance on standing vertical jump, on handgrip (right) and on sit-ups (Table 5).

Table 5. Stepwise discriminant analysis (standardized canonical discriminant function coefficients, eigenvalues and variance) for Successful and Less-Successful team-handball groups.

The main purpose of the present study was to identify the variables that can distinguish between successful and less-successful team-handball athletes.

Our results showed that the successful team-handball athletes possessed a balanced mesomorph and the less-successful athletes had an endomorphic mesomorph somatotype. Moreover, significant differences between groups were observed as concerns the endomorphy category. This category successfully discriminated the two groups (explained 61.8% of variance). Also five anthropometric measures successfully discriminated between the two groups studied, namely: stature, chest skinfold, suprailiac skinfold, biiliocristal breath and radiale-dactylion length.

According to literature, body mass is determinant for performance, in the throwing events.2 However, in this study, there is a small difference in body mass, between the groups, that can be confirmed by the small differences in muscle and bone mass although the successful group are significantly taller.

According to Ziv and Lidor,5 team-handball is a dynamic team sport characterized by a high capacity to develop force level, great level of agility and flexibility. Nevertheless, significant differences between groups were observed in five physiological evaluations, i.e. the successful team-handball athletes recorded (i) higher values for sit-ups, (ii) faster times over the 30-m sprint, and (iii) lower values on dynamometry tests (handgrip and back strength) and in standing vertical jump. Was also observed that the averages of VO2max were not different in the two performance groups, but unlike the results of Alexander and Boreskie26 results (VO2max: world champion, 53.1 ml kg−1 min−1; non-world champion, 55.2 ml kg−1 min−1), less-successful team-handball athletes had a superior VO2max to successful ones. Furthermore, although Delamarche et al.27 has reached the conclusion that the maximal aerobic power and capacity are prerequisites to the achievement of excellence in team-handball (age 18–21 years), and more recently Gorostiaga et al.28 concluded that endurance capacity does not seem to be a limiting factor for elite performance in team-handball. In fact, our results suggest that team-handball players may not need to have an extraordinary aerobic capacity, but they must possess a reasonably high level aerobic capacity.

However, marked individual differences were observed among elite team-handball players in four physiological variables (that successfully discriminated between the two groups), namely: the standing vertical jump, the 30-m sprint, the sit ups and the right handgrip strength; which highlights the physical demands of the game. These results suggested that leg power is an essential component for success in athletic performance.29, 30 In other words, it seems that muscle mass and power are attributes to excellence in team-handball players.28

In general, morphologic and physiological attributes do have an important role on the all process of training evaluation, and physiological profiling can generate a useful database against which talented groups may be compared (explaining 88.2% of variance).

We are aware that the coach evaluation (team-handball-specific skills) is subjective and more or less dependent on the knowledge of the expert's assessment. Nevertheless, the ability to retrieve balls allows to discriminate successful and less-successful team-handball athletes (explain 73.5% of variance). Considering the game intelligence profile and psychological variables no significant difference was observed between groups. In fact, psychological profiles were similar. However, no research was found in literature that had compared the motivational orientation, anxiety and self-perception of professional male team-handball players of successful and less-successful handball teams.

Finally, multivariate statistical analysis techniques revealed that the two studied groups could be discriminated on the basis of six variables, and the most discriminating was the performance on the 30-m sprint test (i.e. time), followed by the standing vertical jump (height), the right handgrip strength, the abdominal resistance (sit-ups), the stature and the technical ability to vary their actions. These results agree partially with the results observed (i) in elite female team-handball players9; and (ii) in young team-handball players.3 In fact, it seems that in youth team-handball players, the skill test could be a good indicator to provide coaches with relevant information in the selection process. Nevertheless, we observed that (in adult male team-handball athletes) the determinants of success are multidisciplinary. In other words, our results suggested that the anthropometric (stature), physiological (standing vertical jump, right handgrip, sit ups) and cognitive and game intelligence (ability to vary their actions) profiles must be considered e training programs and in the selection process.

The battery test designed for this investigation was multidisciplinary in the sense that it embraced morphologic, physiological, handball-specific skills and psychological measures, which could be gathered in training conditions and did not require formal laboratory evaluations. The test battery proved to be of practical significance in so far as it successfully discriminated between groups of success and less-successful team-handball athletes. Moreover, performances on the 30-m sprint test, the standing vertical jump, the right handgrip strength, the sit-ups test, stature, and the ability of a player to vary their actions appear to be the strongest predictors of success in team-handball. Despite this multidisciplinary approach to success in team-handball is innovative, the small sample size weakens the study. In accordance, the next step would be (i) to examine the validity of discriminant variables (as predictors) in a large sample of adult team-handball players, (ii) to establish whether the new protocol proves useful in discriminating between successful handball players, and (iii) to establish baseline reference data for the development of perceptual training programs and talent identification of potential elite male team-handball players.

The authors declare that they have no competing interests.

Acknowledgements

The authors thank the athletes who participated in this study.

No funding received for this work.

Received 8 March 2013

Accepted 11 June 2013

Corresponding author. luis.massuca@ulusofona.pt