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Prediction of Offensive Possession Ends in Elite Basketball Teams

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  • Kęstutis Matulaitis

    (Department of Coaching Science, Lithuanian Sports University, Sporto 6, 44221 Kaunas, Lithuania)

  • Tomas Bietkis

    (Department of Coaching Science, Lithuanian Sports University, Sporto 6, 44221 Kaunas, Lithuania)

Abstract

In basketball, the end of the ball possession has been described as one of the most important determinants of successful offensive play by a team. The present study aimed to: (i) investigate outcomes according to the play types of ends of the ball possession; (ii) find the most efficient ball possessions during the game; (iii) predict most efficient ends of the ball possession by time in an elite basketball competition. The sample was composed of 38,640 situations of ends of the ball possession from 240 games of the 2017–2018 regular season of the men’s Euroleague that were quantitatively analyzed. According to the results, the predictive model can be used in modern basketball. The most efficient ends of the ball possession are the 2-point field goals on the fast break (78.2%), cuts (64.8%), pick and roll (P&R) screener (61.5%), and transition and offensive rebound (57.4%) situations. This information allows a better collective understanding of basketball, and it could be a great tool to use for coaches to prove which tactical solutions are to be considered when improving offense and defense strategies. It also contributes to the design of precise practice tasks of the coach that improve the game.

Suggested Citation

  • Kęstutis Matulaitis & Tomas Bietkis, 2021. "Prediction of Offensive Possession Ends in Elite Basketball Teams," IJERPH, MDPI, vol. 18(3), pages 1-11, January.
  • Handle: RePEc:gam:jijerp:v:18:y:2021:i:3:p:1083-:d:487220
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    1. Tsamourtzis Evangelos & Karypidis Alexandros & Athanasiou Nikolaos, 2005. "Analysis of fast breaks in basketball," International Journal of Performance Analysis in Sport, Taylor & Francis Journals, vol. 5(2), pages 17-22, November.
    2. Kubatko Justin & Oliver Dean & Pelton Kevin & Rosenbaum Dan T, 2007. "A Starting Point for Analyzing Basketball Statistics," Journal of Quantitative Analysis in Sports, De Gruyter, vol. 3(3), pages 1-24, July.
    3. 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.
    4. Jorge Lorenzo Calvo & Alejandro Menéndez García & Archit Navandar, 2017. "Analysis of mismatch after ball screens in Spanish professional basketball," International Journal of Performance Analysis in Sport, Taylor & Francis Journals, vol. 17(4), pages 555-562, July.
    5. 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.
    6. Daniel Cervone & Alex D’Amour & Luke Bornn & Kirk Goldsberry, 2016. "A Multiresolution Stochastic Process Model for Predicting Basketball Possession Outcomes," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 111(514), pages 585-599, April.
    7. Miguel-Angel Gomez & Enrique Ortega & Gareth Jones, 2016. "Investigation of the impact of ‘fouling out’ on teams’ performance in elite basketball," International Journal of Performance Analysis in Sport, Taylor & Francis Journals, vol. 16(3), pages 983-994, December.
    8. L. Lamas & D. De Rose Junior & F. Santana & E. Rostaiser & L. Negretti & C. Ugrinowitsch, 2011. "Space creation dynamics in basketball offence: validation and evaluation of elite teams," International Journal of Performance Analysis in Sport, Taylor & Francis Journals, vol. 11(1), pages 71-84, April.
    9. Eric Luis Uhlmann & Christopher M Barnes, 2014. "Selfish Play Increases during High-Stakes NBA Games and Is Rewarded with More Lucrative Contracts," PLOS ONE, Public Library of Science, vol. 9(4), pages 1-5, April.
    10. 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.
    11. Gemma Robinson & Peter O’Donoghue, 2007. "A weighted kappa statistic for reliability testing in performance analysis of sport," International Journal of Performance Analysis in Sport, Taylor & Francis Journals, vol. 7(1), pages 12-19, January.
    12. A. Vaquera & J.V. García-Tormo & M.A. Gómez Ruano & J.C Morante, 2016. "An exploration of ball screen effectiveness on elite basketball teams," International Journal of Performance Analysis in Sport, Taylor & Francis Journals, vol. 16(2), pages 475-485, August.
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    2. Yasin Akinci, 2023. "Examining the Differences Between Playoff Teams and Non-Playoff Teams in Men’s Euroleague; Play-Type Statistics Perspective," SAGE Open, , vol. 13(4), pages 21582440231, December.

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