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Statistical analyses of basketball team performance: understanding teams’ wins and losses according to a different index of ball possessions

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  • Jaime Sampaio
  • Manuel Janeira

Abstract

The aim of the present paper is to investigate the discriminatory power of game statistics between winning and losing teams in the Portuguese Professional Basketball League. Methodological issues concerning game rhythm contamination and data organization according to game type (regular season or play-off), game final outcome (win or loss), game location (home or away) and game final score differences are discussed. Archival data were obtained for the 1997-1998 and the 1998-1999 Portuguese Professional Basketball League seasons for (a) all 353 regular season home and away games and (b) all 56 play-off home and away games. Cluster analysis was conducted to establish, according to game final score differences, three different groups for the subsequent analysis (close games, with final score differences between 1 and 8 points; balanced games, with final score differences between 8 and 18 points and unbalanced games, with final score differences above 18 points). Afterwards, discriminant analysis was used to identify the game statistics that maximize mean differences between winning and losing teams according to previously defined factors (type, location, cluster groups). Obtained results allowed us to understand that in balanced and unbalanced games, losing teams performed poorly in all game statistics. In contrast, results from close games allowed us to identify different team performance profiles according to game type and location. Globally, regular season profile was best discriminated by successful free-throws, whereas play-offs profile was best discriminated by offensive rebounding. On the other hand, home wins were best discriminated by committed fouls whereas successful free-throws discriminated away wins. Coaches and players should be aware of these different profiles in order to increase specificity at the time of game planning and control.

Suggested Citation

  • Jaime Sampaio & Manuel Janeira, 2003. "Statistical analyses of basketball team performance: understanding teams’ wins and losses according to a different index of ball possessions," International Journal of Performance Analysis in Sport, Taylor & Francis Journals, vol. 3(1), pages 40-49, April.
    • Handle: RePEc:taf:rpanxx:v:3:y:2003:i:1:p:40-49
    DOI: 10.1080/24748668.2003.11868273
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    Cited by:

    1. Nikolaos Stavropoulos & Alexandra Papadopoulou & Pavlos Kolias, 2021. "Evaluating the Efficiency of Off-Ball Screens in Elite Basketball Teams via Second-Order Markov Modelling," Mathematics, MDPI, vol. 9(16), pages 1-13, August.
    2. Jeon, Gyuhyeon & Park, Juyong, 2021. "Characterizing patterns of scoring and ties in competitive sports," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 565(C).
    3. 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.
    4. Shaoliang Zhang & Miguel Ángel Gomez & Qing Yi & Rui Dong & Anthony Leicht & Alberto Lorenzo, 2020. "Modelling the Relationship between Match Outcome and Match Performances during the 2019 FIBA Basketball World Cup: A Quantile Regression Analysis," IJERPH, MDPI, vol. 17(16), pages 1-11, August.
    5. 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.
    6. Jaime Sampaio & Tim McGarry & Julio Calleja-González & Sergio Jiménez Sáiz & Xavi Schelling i del Alcázar & Mindaugas Balciunas, 2015. "Exploring Game Performance in the National Basketball Association Using Player Tracking Data," PLOS ONE, Public Library of Science, vol. 10(7), pages 1-14, July.
    7. Kęstutis Matulaitis & Tomas Bietkis, 2021. "Prediction of Offensive Possession Ends in Elite Basketball Teams," IJERPH, MDPI, vol. 18(3), pages 1-11, January.
    8. Nimai Parmar & Nic James & Mike Hughes & Huw Jones & Gary Hearne, 2017. "Team performance indicators that predict match outcome and points difference in professional rugby league," International Journal of Performance Analysis in Sport, Taylor & Francis Journals, vol. 17(6), pages 1044-1056, November.
    9. Zongpeng Zhai & Yongbo Guo & Yuanchang Li & Shaoliang Zhang & Hongyou Liu, 2020. "The Regional Differences in Game-Play Styles Considering Playing Position in the FIBA Female Continental Basketball Competitions," IJERPH, MDPI, vol. 17(16), pages 1-11, August.

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