Literature DB >> 17165413

Discriminative game-related statistics between basketball starters and nonstarters when related to team quality and game outcome.

Jaime Sampaio1, Sergio Ibáñez, Alberto Lorenzo, Miguel Gómez.   

Abstract

The aim of the present paper was to examine the differences in game-related statistics between basketball players who are selected for the starting five of the team (starters) and those who are not (nonstarters) when related to game outcome (winning and losing) and team quality (best teams, teams classified for the playoffs; and worst teams, teams who miss playoff classification). Archival data were gathered for all 2002-2003 regular season games from the Portuguese Professional League (N = 156). Discriminant analysis was used to identify the game-related statistics that differentiate between starters and nonstarters and interpreted by the examination of the structure coefficients (SC). When the best teams won the games, results described differences between starters and nonstarters with an emphasis on defensive rebounds (SC = .32), assists (SC = .32) and committed fouls (SC = -.68). When the worst teams won the games, results described differences between starters and nonstarters with an emphasis on 2-point field goals successful (SC = .47) and unsuccessful (SC = .48), defensive rebounds (SC =.39), successful free throws (SC =.32), and committed fouls (SC = -.55). An also important finding was that, in best teams, the nonstarters' performance was worse in the games that the team lost, whereas in worst teams, it was the starters' performance that was worse in the games that the team lost.

Mesh:

Year:  2006        PMID: 17165413     DOI: 10.2466/pms.103.2.486-494

Source DB:  PubMed          Journal:  Percept Mot Skills        ISSN: 0031-5125


  8 in total

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2.  Effects of Consecutive Basketball Games on the Game-Related Statistics that Discriminate Winner and Losing Teams.

Authors:  Sergio J Ibáñez; Javier García; Sebastian Feu; Alberto Lorenzo; Jaime Sampaio
Journal:  J Sports Sci Med       Date:  2009-09-01       Impact factor: 2.988

3.  Explaining Match Outcome During The Men's Basketball Tournament at The Olympic Games.

Authors:  Anthony S Leicht; Miguel A Gómez; Carl T Woods
Journal:  J Sports Sci Med       Date:  2017-12-01       Impact factor: 2.988

4.  Game Related Statistics Discriminating Between Starters and Nonstarters Players in Women'S National Basketball Association League (WNBA).

Authors:  Miguel-Ángel Gòmez; Alberto Lorenzo; Enrique Ortega; Jaime Sampaio; Sergio-José Ibàñez
Journal:  J Sports Sci Med       Date:  2009-06-01       Impact factor: 2.988

5.  Team Performance Indicators Explain Outcome during Women's Basketball Matches at the Olympic Games.

Authors:  Anthony S Leicht; Miguel A Gomez; Carl T Woods
Journal:  Sports (Basel)       Date:  2017-12-17

6.  Scoring Strategies Differentiating between Winning and Losing Teams during FIBA EuroBasket Women 2017.

Authors:  Daniele Conte; Inga Lukonaitiene
Journal:  Sports (Basel)       Date:  2018-05-29

7.  The Differences in the Performance Profiles Between Native and Foreign Players in the Chinese Basketball Association.

Authors:  Xing Wang; Bin Han; Shaoliang Zhang; Liqing Zhang; Alberto Lorenzo Calvo; Miguel-Ángel Gomez
Journal:  Front Psychol       Date:  2022-01-31

8.  Game statistics that discriminate winning and losing at the NBA level of basketball competition.

Authors:  Dimitrije Cabarkapa; Michael A Deane; Andrew C Fry; Grant T Jones; Damjana V Cabarkapa; Nicolas M Philipp; Daniel Yu
Journal:  PLoS One       Date:  2022-08-19       Impact factor: 3.752

  8 in total

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