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Performance indicators that distinguish winning and losing teams in basketball

Author

Listed:
  • Gabor Csataljay
  • Peter O’Donoghue
  • Mike Hughes
  • Henriette Dancs

Abstract

To prepare a team for basketball games, to build up the best tactics, to make good decisions during a game, coaches need to know which elements of matches are the most crucial ones. Especially at close games where there is small difference between the performances of two teams. The main purpose of this study was to identify those critical performance indicators that most distinguish between winning and losing performances within matches. The statistical analysis of basketball games can lead to the identification of many significant performance indicators, not all of which can be analysed in real time. Therefore, a smaller subset of critical performance indicators can be identified by analysing close matches only. Data from 54 matches were gathered from the official score sheets of the European Basketball Championship 2007. Cluster analysis was used to classify the matches into three types such as tight games, balanced games and unbalanced games. There were 28 of these matches that were close matches where the differences between the two teams were 9 points or less. Wilcoxon signed ranks tests were used to compare 18 performance indicators between the winning and losing teams within each type of match. There were 13 significant performance indicators for the full set of matches. This was reduced to 6 critical performance indicators when only the close matches were considered. The analysis of tight matches explored that the winning teams had significantly less 3 point attempts (p<0.05) with higher shooting percentage (p<0.01). The number of successful free throws (p<0.01), the free throw percentage (p<0.001) and the number of defensive rebounds (p<0.01) also contributed to achieve a higher number of scored points and consequently determined success.

Suggested Citation

  • Gabor Csataljay & Peter O’Donoghue & Mike Hughes & Henriette Dancs, 2009. "Performance indicators that distinguish winning and losing teams in basketball," International Journal of Performance Analysis in Sport, Taylor & Francis Journals, vol. 9(1), pages 60-66, April.
  • Handle: RePEc:taf:rpanxx:v:9:y:2009:i:1:p:60-66
    DOI: 10.1080/24748668.2009.11868464
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    Cited by:

    1. Zoltan Boros & Kata Toth & Gergely Csurilla & Tamas Sterbenz, 2022. "A Comparison of 5v5 and 3x3 Men’s Basketball Regarding Shot Selection and Efficiency," IJERPH, MDPI, vol. 19(22), pages 1-12, November.
    2. Lorenzo Gasperi & Daniele Conte & Anthony Leicht & Miguel-Ángel Gómez-Ruano, 2020. "Game Related Statistics Discriminate National and Foreign Players According to Playing Position and Team Ability in the Women’s Basketball EuroLeague," IJERPH, MDPI, vol. 17(15), pages 1-10, July.
    3. Assanskiy, Artur & Shaposhnikov, Daniil & Tylkin, Igor & Vasiliev, Gleb, 2022. "Prove them wrong: Do professional athletes perform better when facing their former clubs?," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 98(C).
    4. Radivoj Mandić & Saša Jakovljević & Frane Erčulj & Erik Štrumbelj, 2019. "Trends in NBA and Euroleague basketball: Analysis and comparison of statistical data from 2000 to 2017," PLOS ONE, Public Library of Science, vol. 14(10), pages 1-17, October.
    5. Tomasz Zając & Kazimierz Mikołajec & Paweł Chmura & Marek Konefał & Michał Krzysztofik & Piotr Makar, 2023. "Long-Term Trends in Shooting Performance in the NBA: An Analysis of Two- and Three-Point Shooting across 40 Consecutive Seasons," IJERPH, MDPI, vol. 20(3), pages 1-12, January.
    6. Zsombor Zilinyi & Ágoston Nagy & Szilvia Borbély & Tamás Sterbenz, 2022. "Bounded Rationality and Heuristics: Do We Only Need to Score in Order to Win Individual Awards in Basketball?," IJERPH, MDPI, vol. 19(4), pages 1-9, February.

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