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Game related statistics which discriminate between winning and losing under-16 male basketball games

机译:与比赛相关的统计数据,用于区分16岁以下男篮比赛的成败

摘要

The aim of the present study was to identify the game-related statistics which discriminate between winning and losing teams in under-16 years old male basketball games. The sample gathered all 122 games in the 2004 and 2005 Under-16 European Championships. The game-related statistics analysed were the free-throws (both successful and unsuccessful), 2- and 3-points field-goals (both successful and unsuccessful) offensive and defensive rebounds, blocks, assists, fouls, turnovers and steals. The winning teams exhibited lower ball possessions per game and better offensive and defensive efficacy coefficients than the losing teams. Results from discriminant analysis were statistically significant and allowed to emphasize several structure coefficients (SC). In close games (final score differences below 9 points), the discriminant variables were the turnovers (SC = -0.47) and the assists (SC = 0.33). In balanced games (final score differences between 10 and 29 points), the variables that discriminated between the groups were the successful 2-point field-goals (SC = -0.34) and defensive rebounds (SC = -0. 36); and in unbalanced games (final score differences above 30 points) the variables that best discriminated both groups were the successful 2-point field-goals (SC = 0.37). These results allowed understanding that these players' specific characteristics result in a different game-related statistical profile and helped to point out the importance of the perceptive and decision making process in practice and in competition
机译:本研究的目的是确定与游戏相关的统计数据,以区分16岁以下未成年男子篮球比赛的胜负队伍。样本收集了2004年和2005年16岁以下欧洲锦标赛的所有122场比赛。所分析的与游戏相关的统计数据是罚球(成功和失败),2分和3分得分(进攻和防守),篮板,盖帽,助攻,犯规,失误和抢断。与失败的球队相比,获胜的球队每场比赛的控球率更低,进攻和防守效率系数更高。判别分析的结果具有统计学意义,并且可以强调几个结构系数(SC)。在近距离比赛(最终得分差异低于9分)中,判别变量为失误(SC = -0.47)和助攻(SC = 0.33)。在平衡游戏中(最终得分差在10到29分之间),区分组的变量是成功的2分球得分(SC = -0.34)和防守篮板(SC = -0。36);在不平衡的比赛中(最终得分差异超过30分),最能区分两组的变量是成功的2分实地进球(SC = 0.37)。这些结果有助于理解这些玩家的特定特征会导致与游戏相关的统计数据有所不同,并有助于指出感知和决策过程在实践和竞争中的重要性。

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