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1. Introduction

    One of the most important investigation areas in Sport Sciences is related to the need of explain, predict or even to advance the athletes’ success. From their own experience, coaches believe that this success can be explained by the players’ technical skill quality observed during the game (Queiroz, 1986; Lorente, 1988; Brunet, 1988; Araújo, 1992; Salamanca, 1994). From this point, it seems important to confirm if the highest talented athletes from a technical skill analysis belong to better performance teams, as referred in the literature (Hopkins, 1977; Blaskovic & Milanovic, 1985; Brooks et al., 1987; Brandão, 1995). In other words, in those who have better final standings in a competition. On the other hand, it is also important to know if in lower age steps, which are related to early learning stages, the larger investment in training guided for the acquisition and development of the technical skill performance is justified and responsible for team different performance level.

    Therefore, the aims of this study are the following:

• To identify the degree of relationship between teams final standings and individual skill performance;

• To compare, from the point of view of individual skills, basketball players of different performance level. This second aim is related to the hypothesis that player’s sub-division is highly related to their technical skills.

2. Material and methods

    The sample comprises 246 Basketball players, 12 to 14 years old, belonging to 21 teams. They played official competitions of Porto Basketball Association. Teams were presented in 4 series of competition (SA, SB, SC and SD), of different performance levels, according to their standings in a preview tournament.

    Technical skills were evaluated according to Basketball Test Battery from AAPHERD (Kirkendall, 1987).

    The Analysis of Variance was used to compare the technical skill performance in the 4 series (SA, SB, SC and SD). Pearson Product-Moment Correlation and Linear Regression were used in order to examine the relationship between team final standings and their achievements in each of the technical indicators. The significance level was 5%.

3. Results

    The mean comparison of technical indicators in the 4 series of competition is expressed in Tables 3.1. and 3.2. (ANOVA of independent measures and following confirmations for the Scheffé F test, respectively).

Table 3.1. Results of mean comparison among the different series

Technical indicators	SA n=72	SB n=68	SC n=58	SD n=48	F	P
Pass	78.611 ± 9.293	69.162 ± 7.392	72.931± 6.8	64.729 ± 6.982	34.426	.0001*
Dribbling	17.479 ± 1.014	19.2 ± 1.78	18.305 ± 1.4	19.554 ± 1.796	23.986	.0001*
Shoot	35.083 ± 5.352	32.118 ± 5.346	31.069 ± 6.327	27.81 ± 7.124	14.753	.0001*
Defensive sliding	21.701 ± 2.465	23.184 ± 3.219	21.768 ± 2.154	23.253 ± 2.6	6.131	.0005*

* Significant statistically values for p < 0.05

    These results show significant differences among the series for all the technical indicators (Pass: F=34.426, p=0.0001; Dribbling: F=23.986, p=0.0001; Shoot: F=14.753, p=0.0001; Defensive Sliding: F=6.131, p=0.0005).

Table 3.2. Comparisons a posteriori (Scheffé F-test)

Technical indicators / Series	Pass		Dribbling		Shoot		Defensive sliding
	Average Difference	Scheffé f-test	Average Difference	Scheffé f-test	Average Difference	Scheffé f-test	Average Difference	Scheffé f-test
SA vs. SB	9.449	17.113*	-1.721	15.224*	2.966	2.88*	-1.433	3.392*
SA vs. SC	5.68	5.68*	-0.826	3.222*	4.014	4.847*	-0.068	0.007
SA vs. SD	13.882	30.415*	-2.075	18.229*	7.273	14.263*	-1.552	3.276*
SB vs. SC	-3.769	2.437	0.895	3.685*	1.049	0.322	1.366	2.757*
SB vs. SD	4.433	3.03*	-0.354	0.519	4.307	4.888*	-0.119	0.019
SC vs. SD	8.202	9.683*	-1.249	6.023*	3.259	2.611*	-1.484	2.733*

* Significant statistically values for p < 0.05

    The results of the comparison à posteriori (see Table 3.2.) are the following:

• Pass and Shoot are similar between SB vs. SC. For all the other pairs of comparisons it is evident the difference among the series;

• For the Dribbling, all the comparisons between series are different unless between SB vs. SD;

• The Defensive Sliding shows differences between SA vs. SB, SA vs. SD, SB vs. SC, and SC vs. SD.

    The Pearson Product-Moment Correlation (r) between technical indicators and team final standings, as well as the values of common variance (r2) for the same indicators, are expressed in Table 3.3.

Table 3.3. Correlation values and of common variance between the technical indicators and the final classification.

Technical indicators	r	p	r²
Pass	0.741	.000	55%
Dribbling	0.641	0.001	41%
Shoot	0.722	.000	52%
Defensive sliding	0.219	0.341	4,8%

    The strongest relationship with the team final standings were established by the Pass (r=0.741) and Shoot (r=0.722). Moderated correlation was registered between the Dribbling and team final standings (r=0.641). The lowest value of correlation was observed for Defensive Sliding (r=0.219, p>0.05).

    The study of the regression between technical indicators and team final standings are presented in Pictures 3.1., 3.2., 3.3. and 3.4.

Picture 3.1. Relationship between Pass and team final standings.

Picture 3.2. Relationship between Dribbling and team final standings.

Picture 3.3. Relationship between Shoot and team final standings.

Picture 3.4. Relationship between Defensive Sliding and team final standings.

    Pass had the highest value of common variance (55%) followed by the Shoot (52%) and the Dribbling (41%). The lowest value of common variance was registered for the Defensive Sliding (4,8%).

4. Discussion

    The study of the association between team final standings and the performance is a central subject in sport. In Basketball, this subject has been treated with some depth, namely in the recent studies of Hoffman et al. (1996) and Lidor & Arnon (1997). These authors appealed to indicators focused in the game and variables related to conditioning and coach's opinion. Though, in the domain of young Basketball players, the idea is to improve athletes' basic skill qualities. Based upon this methodological strategy, does it make sense to say that highly technical skill athlete plays in the better performance teams? In fact, our results confirm this idea. Generally speaking, the players with best results in technical skill evaluation play for better teams (SA), in contrast with those with the worst results who plays in lowest performance teams (SD). Another purpose of this investigation was to examine the relationship between 4 technical skills and the team final standings. Based on our results it can be concluded that Pass, Dribbling and Shoot explain 55%, 41% and 52% respectively, of the team final standings variation. This association values contrast sharply with the association value between the final classification and the Defensive sliding (4,8%).

    For the coaches, the significance of these results allow to solidify the idea of the largest importance of the Individual Offensive indicators face to the Individual Defensive Technique, in the strict domain of Basketball performance for youth players. Ultimately, it is possible to say that technical skill performance is one of the best measures of success for the player and for the team, and definitely a better chance for success is to endow these young athletes with "tools" of the game focused mainly on Individual Offensive Technical Skills.

5. Conclusions

    From the results of our study it is possible to present the following conclusions:

• There is a strong relationship between offensive technical indicators (Pass, Dribbling and Shooting) and team final standings;

• The results present important criterion-referenced values for pre-selection purposes in this age group.

References

• Araújo, J. (1992): Basquetebol - Preparação Técnica e Táctica, FPB e Associações Regionais de Basquetebol, Lisboa

• Kirkendall, D.; Grubber, J.; Johnson, R. (1987): Measurement and Evaluation for Physical Educators, Human Kinetics Publishers Inc., Champaign, Illinois.

• Lorente, J.R. (1998): La Logica Interna del Baloncesto Desde el Punto de Vista Practico. Revista CLINIC. Ano XI, nº 41, AEEB, pp. 21-24.

• Moreno, J. H. (1988): Baloncesto - Iniciación y Entrenamiento, Barcelona, Ed. Paidotribo.

• Queiroz, C. (1986); Estrutura e organização dos exercícios de treino em Futebol. FPF 1989

• Salamanca, J. (1994): El Modelo teorico en el Aprendizaje de la Tecnica en Baloncesto.. Revista CLINIC. Ano VII, nº 26, AEEB, pp. 5-6.

• Brandão, E. (1995): A performance em Basquetebol: um estudo multivariado no escalão de cadetes masculinos. . Dissertação apresentada no âmbito do mestrado em Ciências do Desporto, na área do Desporto de Crianças e Jovens, FCDEF- Universidade do Porto.

• Brooks, M. A. et al (1987): Relationship of specific and nonspecific variables to successful Basketball performance among high school players.. Perceptual and Motor Skills. N.º 64, 823-827.

• Blaskovic, M.; Milanovic, D. (1985): The Relationship Between Situational-Motoric Dimentions and performance in Basketball, in Teaching Team Sports. CONI, Roma

• Hoffman, J. R.; Tenenbaum, G.; Maresh, C.; Kraemer, W. (1996): Relationship between athletic Performance tests and playing time in elite college Basketball players.. Journal of Strength and Conditioning Research, Vol. 10, n.º 2, 67-71

• Hopkins, D. R. (1977): Factor Analysis of Selected Basketball Skill Tests.. The Research Quarterly, Volume 48, nº3, pp. 535-540

• Lidor, R.; Arnon, M. (1997): Correlational relationships between technical variables and final placing of basketball teams.. Coaching and Sport Science Journal, pp. 39-47.

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