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Discriminating Factors between Successful and Unsuccessful Teams: A Case Study in Elite Youth Olympic Basketball Games

Author

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  • Koh Koon Teck

    (Nanyang Technological University)

  • John Wang

    (Nanyang Technological University)

  • Mallett Clifford

    (The University of Queensland)

Abstract

Archival data was gathered from the FIBA33 games during the 1st inaugural Youth Olympic Games held in Singapore. Data collected from 70 basketball games played by boys from 20 participating countries were gathered for analysis. Analysis of game-related statistics and FIBA33 final rankings differentiated successful from unsuccessful teams. Ninety-five percent of the cases were correctly classified using discriminant analysis and in the cross-validation (leave-one-out method) the correct re-classification was 75 percent. Data triangulated from interviews and field notes were used to determine key factors contributing to team's success in the FIBA33 games. Results of the present study showed that players from the top 10 successful teams could be differentiated from those in the bottom 10 unsuccessful teams. The determining factors were taller, had better shooting percentages, played aggressively (i.e., recorded more team fouls and the ability to draw fouls on opponents during games). Coaches can use these results to improve player's recruitment process, reinforce the importance of fundamental skills such as shooting, individual offensive and defensive concepts under different game situations during trainings.

Suggested Citation

  • Koh Koon Teck & John Wang & Mallett Clifford, 2011. "Discriminating Factors between Successful and Unsuccessful Teams: A Case Study in Elite Youth Olympic Basketball Games," Journal of Quantitative Analysis in Sports, De Gruyter, vol. 7(3), pages 1-15, July.
    • Handle: RePEc:bpj:jqsprt:v:7:y:2011:i:3:n:21
    DOI: 10.2202/1559-0410.1346
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    Cited by:

    1. Alessandro Chessa & Pierpaolo D’Urso & Livia Giovanni & Vincenzina Vitale & Alfonso Gebbia, 2023. "Complex networks for community detection of basketball players," Annals of Operations Research, Springer, vol. 325(1), pages 363-389, June.
    2. Paola Zuccolotto & Marco Sandri & Marica Manisera, 2023. "Spatial performance analysis in basketball with CART, random forest and extremely randomized trees," Annals of Operations Research, Springer, vol. 325(1), pages 495-519, June.
    3. Paola Zuccolotto & Marco Sandri & Marica Manisera, 2021. "Spatial Performance Indicators and Graphs in Basketball," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 156(2), pages 725-738, August.

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