Are regional differences in basketball already established in under-18 games?

Abstract

Aims:

To identify regional differences in basketball games for under-age categories, this study analyzed game-related statistics of four continental championships for under-18 (U18) men.

Methods:

A total of 149 games from each continental championship for U18 men held in 2016 were analyzed. A one-way analysis of variance followed by a Bonferroni post hoc test was performed to assess differences in game-related statistics between the continents (Europe, Africa, America, Asia). A discriminant analysis was performed to identify game-related statistics which discriminate among the continents.

Results:

The U18 African championship, which was characterized by a high number of free throws, was clearly discriminated from any other U18 continental championship. Among the other U18 continental championships excluding the African championship, the biggest difference was observed between the European and the Asian championships. The U18 European championship was characterized by a low number of possessions and a high number of assists, whereas the U18 Asian championship was characterized by a high number of possessions and a low number of assists. Both possessions and assists showed high numbers in the U18 American championship.

Conclusion:

This study identified regional differences in basketball games among four continental championships for U18 men held in 2016. It is suggested that basketball games for under-age categories are played in a different manner in each region of the world. The information derived from this study will help players and coaches of under-age national teams prepare for international competitions.

Keywords:
basketball; continental difference; discriminant analysis; youth sports

Introduction

In basketball, game-related statistics, which reflect players’ behavior in the game, are recorded and summarized in a box score. In official games played under the rules of the International Basketball Federation (FIBA), the recording process is executed according to the regulations established by FIBA¹, which ensure intra- and inter-operator reliability². The FIBA regulations define eight game-related statistics: field goals, free throws, rebounds, turnovers, assists, steals, blocked shots, and fouls. Game-related statistics have been studied to scientifically illustrate the games in various categories: the Olympic Games for men^3,4,5 and women⁶, FIBA Basketball World Cup for men⁷, professional leagues for men^{8, 9,10} and women^11,12,13, and international tournaments for youth athletes^14,15. In addition, game-related statistics have been analyzed in various contexts such as effects of rule changes^16,17, age and sex differences^18,19, and relationship with physical fitness²⁰.

Although game-related statistics have been extensively studied, only a few studies have been performed focusing on regional differences in basketball^21,22,23. Ibáñez and colleagues have recently investigated regional differences among continental championships for senior men held in 2015 and reported that each continental championship has a specific performance profile²¹: Europe, a low number of possessions and a high number of assists; Africa, high numbers of free throws, rebounds, steals and fouls; America, a high number of field goal attempts; Asia, a high number of possessions and a low number of assists.

The previous findings of Ibáñez, González-Espinosa, Feu, García-Rubio²¹ would be useful for players and coaches of national teams preparing for international competitions. However, international competitions are held not only for senior but also for junior (under-age categories) players. Since junior games have been reported to show different characteristics compared to senior games^{18, 19}, it is uncertain that the regional differences observed among the continental championships for seniors are also observed for juniors. If regional differences among continental championships for juniors are dissimilar to those for seniors, the previous findings on seniors²¹ cannot be applied to juniors. Therefore, identifying regional differences in junior games would be of help for players and coaches of junior national teams to prepare for international competitions. In addition, investigating junior games would be valuable not only in terms of game preparations, but also in terms of long-term player development. Although scientific evidence related to long-term player development has been accumulating, it is still considered insufficient in the field of team sports²⁴. Since a single study cannot provide conclusive evidence due to the complex nature of player development in team sports, studies on junior players should be conducted from various perspectives. To the best of our knowledge, no studies have investigated regional differences in junior games. Therefore, to identify regional differences in basketball games for under-age categories, this study analyzed game-related statistics of four continental championships for under-18 (U18) men.

Methods

Sample and Variables

Box scores of all the 149 games from each continental championship for U18 men held in 2016 (Table 1) were obtained from the official website of FIBA. In official games played under the rules of FIBA, game-related statistics are recorded according to the regulations established by FIBA¹, which ensure intra- and inter-operator reliability². In addition, a high level of inter-rater reliability has been repeatedly confirmed (kappa coefficient above 0.89)^4,17,21,25, so that official scores are treated as reliable in basketball studies^26,27. Game-related statistics of each game were analyzed separately for the winning and losing teams (298 cases were analyzed in total). The analyzed game-related statistics were as follows: 2- and 3-point field goals (successful and unsuccessful), free throws (successful and unsuccessful), defensive and offensive rebounds, assists, steals, turnovers, blocks and fouls committed. To eliminate the effect of game rhythm, the variables were normalized to 100 game ball possessions²⁸. Game ball possessions were calculated as an average of team ball possessions (TBP) of both teams²⁹. TBP was calculated from field goal attempts (FGA), offensive rebounds (ORB), turnovers (TO) and free throw attempts (FTA) using the following equation²⁹:

$TBP=FGA-ORB+TO+0.4\times FTA$

Table 1
Sample characteristics.

	Teams	Games	Cases
Europe	16	48	96
	(Bosnia and Herzegovina, Croatia, Finland, France, Germany, Greece, Israel, Italy, Latvia, Lithuania, Russia, Serbia, Slovenia, Spain, Sweden, Turkey)
Africa	11	39	78
	(Algeria, Angola, Cote d’Ivoire, Dem. Rep. of Congo, Egypt, Gabon, Mali, Republic of Benin, Rwanda, Tunisia, Uganda)
America	8	20	40
	(Argentina, Brazil, Canada, Chile, Dominican Republic, Puerto Rico, USA, Virgin Islands)
Asia	12	42	84
	(China, Chinese Taipei, India, Indonesia, Iran, Iraq, Japan, Kazakhstan, Korea, Lebanon, Philippines, Thailand)
Total	47	149	298

Statistical Analysis

Statistical analyses were performed with R version 3.3.0 for Windows³⁰. A one-way analysis of variance (ANOVA) followed by a Bonferroni post hoc test was performed to assess differences in each variable between the continents. Cohen’s d was calculated as an effect size and interpreted on the same basis as the study on the senior championships²¹ (d = 0.20 to 0.49, small effect; d = 0.50 to 0.79, medium effect; d ≥ 0.80, large effect). A discriminant analysis was performed using R code ‘candis’ (http://aoki2.si.gunma-u.ac.jp/R/src/candis.R) and ‘geneig’ (http://aoki2.si.gunma-u.ac.jp/R/src/geneig.R) to identify game-related statistics which discriminate between the continents. An absolute value of a structural coefficient (SC) greater than or equal to 0.30 was considered relevant for the discrimination²¹. Statistical significance was set at P < 0.05.

Results

Significant F-values were obtained for all variables except successful 2-point field goals and turnovers (Table 2). Most of the differences were found between the African and the other continental championships (Table 3). Large effect size differences between the African and the other continental championships were observed for unsuccessful free throws (vs. Europe and Asia), assists (vs. Europe and America), unsuccessful 2-point field goals (vs. America), defensive rebounds (vs. America), blocks (vs. America), team ball possessions (vs. Asia) and offensive rebounds (vs. Asia). Point difference and team ball possessions showed large effect size differences between the European and Asian championships. There were no large effect size differences between the European and American championships, and between the American and Asian championships. However, medium effect size differences were observed between the European and American championships (point difference, team ball possessions, unsuccessful 2-point field goals and blocks), and between the American and Asian championships (successful free throws and assists).

Table 2
Game-related statistics of each continental championship for U18 men.

	Europe			Africa			America			Asia			ANOVA
	Mean	SD		Mean	SD		Mean	SD		Mean	SD		F	P
PTS	71.7	11.9		69.5	20.1		71.6	15.0		77.0	17.9		3.08	0.03
PD	10.5	8.0		23.9	24.6		17.4	12.3		24.3	19.1		12.37	< 0.01
TBP	76.4	5.5		75.7	10.7		80.7	8.2		82.7	6.0		15.57	< 0.01
S2P	25.2	5.3		26.5	10.0		23.4	7.7		26.8	9.1		2.01	0.11
U2P	28.7	7.0		26.3	7.7		33.5	8.9		31.1	8.2		9.36	< 0.01
S3P	9.0	4.1		6.9	4.1		8.0	3.8		8.4	3.9		3.9	< 0.01
U3P	22.8	6.5		19.0	7.4		21.8	6.4		22.3	7.5		4.87	< 0.01
SFT	16.6	6.9		18.8	9.7		18.0	6.7		14.2	6.2		5.48	< 0.01
UFT	7.9	3.8		14.8	8.0		9.6	4.9		8.7	4.4		26.12	< 0.01
DRB	36.5	6.9		31.7	9.0		39.2	6.5		35.8	8.9		9.27	< 0.01
ORB	17.7	6.1		13.8	7.0		19.2	6.9		20.2	6.9		13.29	< 0.01
AST	20.1	5.9		13.4	6.9		19.3	6.3		15.3	6.2		19.83	< 0.01
STL	11.4	3.6		7.8	6.0		10.9	4.3		11.8	5.3		11.13	< 0.01
TO	22.2	5.1		21.7	7.3		21.5	6.3		22.4	6.3		0.33	0.81
BLK	3.6	2.2		3.1	2.7		5.4	3.0		4.5	2.8		8.73	< 0.01
FC	25.8	5.2		28.4	8.9		24.7	7.1		23.8	6.0		6.59	< 0.01

• PTS, points scored; PD, point difference; TBP, team ball possessions; S2P, successful 2-point field goals; U2P, unsuccessful 2-point field goals; S3P, successful 3-point field goals; U3P, unsuccessful 3-point field goals; SFT, successful free throws; UFT, unsuccessful free throws; DRB, defensive rebounds; ORB, offensive rebounds; AST, assists; STL, steals; TO, turnovers; BLK, blocks; FC, fouls committed. Significant P-values are shown in bold (P < 0.05).

Table 3
Results of post hoc comparison between each continental championship for U18 men.

	EU-AF			EU-AM			EU-AS			AF-AM			AF-AS			AM-AS
	P	d		P	d		P	d		P	d		P	d		P	d
PTS	1.00	0.13		1.00	0.01		0.18	0.36		1.00	0.11		0.02	0.40		0.52	0.32
PD	< 0.01	0.77		0.23	0.72		< 0.01	0.96		0.31	0.31		1.00	0.01		0.24	0.40
TBP	1.00	0.09		0.02	0.68		< 0.01	1.10		< 0.01	0.51		< 0.01	0.82		1.00	0.29
S2P	1.00	0.17		1.00	0.30		1.00	0.22		0.28	0.34		1.00	0.03		0.17	0.40
U2P	0.25	0.33		< 0.01	0.63		0.26	0.31		< 0.01	0.89		< 0.01	0.60		0.65	0.29
S3P	< 0.01	0.50		1.00	0.24		1.00	0.14		0.99	0.27		0.12	0.37		1.00	0.10
U3P	< 0.01	0.55		1.00	0.15		1.00	0.07		0.22	0.40		0.02	0.45		1.00	0.07
SFT	0.33	0.27		1.00	0.21		0.22	0.36		1.00	0.09		< 0.01	0.57		0.06	0.60
UFT	< 0.01	1.14		0.71	0.39		1.00	0.19		< 0.01	0.74		< 0.01	0.96		1.00	0.18
DRB	< 0.01	0.61		0.40	0.41		1.00	0.09		< 0.01	0.92		< 0.01	0.46		0.15	0.42
ORB	< 0.01	0.59		1.00	0.23		0.08	0.39		< 0.01	0.77		< 0.01	0.92		1.00	0.15
AST	< 0.01	1.05		1.00	0.13		< 0.01	0.79		< 0.01	0.88		0.34	0.29		< 0.01	0.64
STL	< 0.01	0.75		1.00	0.13		1.00	0.08		< 0.01	0.57		< 0.01	0.71		1.00	0.17
TO	1.00	0.08		1.00	0.14		1.00	0.03		1.00	0.04		1.00	0.11		1.00	0.15
BLK	0.99	0.23		< 0.01	0.71		0.12	0.37		< 0.01	0.81		< 0.01	0.54		0.65	0.28
FC	0.09	0.36		1.00	0.20		0.26	0.37		0.03	0.44		< 0.01	0.61		1.00	0.14

• EU, Europe; AF, Africa; AM, America; AS, Asia; PTS, points scored; PD, point difference; TBP, team ball possessions; S2P, successful 2-point field goals; U2P, unsuccessful 2-point field goals; S3P, successful 3-point field goals; U3P, unsuccessful 3-point field goals; SFT, successful free throws; UFT, unsuccessful free throws; DRB, defensive rebounds; ORB, offensive rebounds; AST, assists; STL, steals; TO, turnovers; BLK, blocks; FC, fouls committed. P < 0.05 and d ≥ 0.80 are shown in bold.

Classification results of the discriminant analysis are shown in Table 4. The total correct classification rate was 70.8%. Three significant functions were obtained from the analysis (Table 5 and Figure 1). The African championship was discriminated from the other continental championships by unsuccessful free throws, defensive rebounds, offensive rebounds, assists and steals (Function 1). The European championship was discriminated from the Asian championship by ball possessions and assists (Function 2), and from the American championship by unsuccessful 2-point field goals, unsuccessful free throws and blocks (Function 3).

Table 4
Classification results of discriminant analysis.

		Predicted				Total
		Region	EU	AF	AM	AS
Original	Count	EU	75	7	2	12	96
		AF	8	54	0	16	78
		AM	11	1	18	10	40
		AS	14	3	3	64	84
	Percentage	EU	78.1	7.3	2.1	12.5	100
		AF	10.3	69.2	0	20.5	100
		AM	27.5	2.5	45.0	25.0	100
		AS	16.7	3.6	3.6	76.2	100

• EU, Europe; AF, Africa; AM, America; AS, Asia.
• Correct classifications are shown in bold.

Table 5
Discriminant functions with structural coefficients (SC) for each variable.

	Function 1	Function 2	Function 3
Eigenvalue	0.88	0.46	0.15
Wilks' Lambda	0.32	0.59	0.87
Chi-square	332.2	151.0	41.2
Canonical correlation	0.68	0.56	0.37
Proportion of trace (%)	58.6	31.1	10.3
P	< 0.01	< 0.01	< 0.01
Team ball possessions	0.24	0.46	0.24
Successful 2-point field goals	-0.08	0.14	-0.19
Unsuccessful 2-point field goals	0.28	0.14	0.35
Successful 3-point field goals	0.18	-0.04	-0.25
Unsuccessful 3-point field goals	0.22	-0.01	-0.19
Successful free throws	-0.15	-0.23	0.27
Unsuccessful free throws	-0.52	0.00	0.44
Defensive rebounds	0.32	-0.06	0.18
Offensive rebounds	0.35	0.24	-0.02
Assists	0.37	-0.42	-0.14
Steals	0.34	0.09	-0.24
Turnovers	0.02	0.04	-0.12
Blocks	0.25	0.16	0.40
Fouls committed	-0.24	-0.19	0.01

• |SC| ≥ 0.30 was considered relevant for discrimination (shown in bold).

Figure 1
Territorial map of discriminant functions 1 and 2. AF, Africa; AM, America; AS, Asia; EU, Europe. Abbreviations plotted inside the figure indicate group centroids.

Discussion

To identify regional differences in basketball games for under-age categories, this study analyzed game-related statistics of four continental championships for U18 men held in 2016. Significant differences were found among the continental championships, suggesting that basketball games for under-age categories are played in a different manner in each region of the world.

The U18 African championship was clearly discriminated from any other U18 continental championship. The U18 African championship was characterized by a high number of free throws. As free throws are awarded when the opposing team commits a foul, a high number of free throws reflect a high number of fouls. In fact, the number of fouls committed in the U18 African championship was the largest among the U18 continental championships. These results were in line with previously reported findings in the senior championship²¹. However, a difference between the U18 and the senior was also observed in the African championships. The number of steals in the African championship was the largest among the senior championships but the smallest among the U18 championships. Although a definitive conclusion cannot be made from a simple comparison between the two studies, it can be assumed that the U18 players often commit fouls when trying to steal the ball because of inadequate skills and lack of experience. A high number of fouls and/or steals would be a result of an aggressive and physical style of play, and the style of play may already be established in U18 games in Africa.

Among the other U18 continental championships excluding the African championship, the biggest difference was observed between the European and the Asian championships. The U18 European championship was characterized by a low number of possessions and a high number of assists. It has been demonstrated that the number of assists increases with age¹⁸. In fact, the number of assists in the U18 European championship was less than that in the senior European championship²¹ (20.1 vs. 28.1). However, the European championship showed the highest number in assists in each category of the U18 and senior continental championships. Assists have been considered as an indicator of well-organized offense, and the importance of assists has been repeatedly shown in previous studies on leagues and tournaments in Europe^{15, 26,31}. It is suggested that the style of European basketball is already established in U18 games.

In contrast to the European championship, the U18 Asian championship was characterized by a high number of possessions and a low number of assists. These results were also consistent with previously reported findings in the senior championship²¹. A high number of possessions indicates that the game pace was fast, and a low number of assists indicates that many points were scored after individual actions. In addition, Ibáñez and colleagues²¹ have pointed out that the number of possessions is related to how close or one-sided the game is, citing previous studies by Sampaio and colleagues^{26, 28}. In fact, the mean point difference between winning and losing teams in the Asian championship was the largest among the senior and U18 continental championships.

The results of discriminant analysis showed that the correct classification rate for the U18 American championship was low (45.0%) compared to the other continental championships (Europe, 78.1%; Africa, 69.2%; Asia, 76.2%). In the U18 American championship, 27.5% of the cases were misclassified into the European championship, and 25.0% of the cases were misclassified into the Asian championship. These results indicate that the homogeneity of the American championship is lower than that of the other continental championships, and some of the cases have similar characteristics to the European championship, whereas other cases have similar characteristics to the Asian championship. Nevertheless, some characteristics specific to the American championship could be found from this study. As mentioned above, the U18 European championship was characterized by a low number of possessions and a high number of assists, whereas the U18 Asian championship was characterized by a high number of possessions and a low number of assists. In contrast, both possessions and assists showed high numbers in the U18 American championship. It is likely that although the game pace in the U18 American championship was faster than that in the U18 European championship, the offense in the U18 American championship was better organized than that in the U18 Asian championship.

This study is not without limitations. Since all the data were obtained from box scores, specific elements of the game such as types of offense^32,33, screens^34,35 and timeouts^36,37 were not analyzed in this study. In addition, future studies should also be conducted on women’s games. Although women’s games show different characteristics compared to men’s games^18,19, few studies have focused on regional differences in women’s basketball.

Conclusion

This study identified regional differences in basketball games among four continental championships for U18 men held in 2016. It is suggested that basketball games for under-age categories are played in a different manner in each region of the world. From a practical standpoint, the information derived from this study will help players and coaches of under-age national teams prepare for international competitions. In international competitions, in contrast to domestic leagues, it is necessary to play games against relatively unfamiliar teams in a short period of time. Although detailed information about opponent teams can only be obtained through specific scouting of each opponent, basic information about opponent teams can be obtained from this study based on the continent to which each opponent belongs.

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  Gómez MA, Jimenez S, Navarro R, Lago-Penas C, Sampaio J. Effects of coaches' timeouts on basketball teams' offensive and defensive performances according to momentary differences in score and game period. Eur J Sport Sci. 2011;11(5):303-8.
• ³⁷
  Sampaio J, Lago-Penas C, Gómez MA. Brief exploration of short and mid-term timeout effects on basketball scoring according to situational variables. Eur J Sport Sci. 2013;13(1):25-30.

Publication Dates

• Publication in this collection
  2018

History

• Received
  29 Mar 2018
• Accepted
  02 June 2018