Automatic Identification and Analysis of Basketball Plays: NBA On-Ball Screens

Andrew Yu; Sun Sunnie Chung

doi:10.1109/BCD.2019.8885163

Automatic Identification and Analysis of Basketball Plays: NBA On-Ball Screens

Andrew Yu
, Sun Sunnie Chung

Computer Science

The Behrend College
Cleveland State University

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

4 Scopus citations

Abstract

In this study, we present methodologies to process big data in complex multimedia forms for sports analytics. Sports analytics is the management and analysis of data collected from sports games to quantify past results and predict future outcomes. In basketball, the on-ball screen is a dynamic offensive strategy that involves the movement of multiple players and the ball to create an effective shot attempt. It is a fundamental play employed by all teams in the National Basketball Association (NBA), the highest level of competition for basketball. The analysis of a basketball team and its strategies must first include the identification of such plays. With the presence of sophisticated data collection and analysis tools, this paper proposes methodologies to extract, transform, and analyze player motion-tracking data in NBA games to automatically identify the presence of on-ball screens, with 90% sensitivity, an 8% improvement on existing literature.

Original language	English
Title of host publication	Proceedings - 2019 IEEE/ACIS 4th International Conference on Big Data, Cloud Computing, and Data Science, BCD 2019
Editors	Motoi Iwashita, Atsushi Shimoda, Prajak Chertchom
Place of Publication	usa
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	29-34
Number of pages	6
ISBN (Electronic)	9781728108865
DOIs	https://doi.org/10.1109/BCD.2019.8885163
State	Published - May 1 2019
Event	4th IEEE/ACIS International Conference on Big Data, Cloud Computing, and Data Science, BCD 2019 - Honolulu, United States Duration: May 29 2019 → May 31 2019

Conference

Conference	4th IEEE/ACIS International Conference on Big Data, Cloud Computing, and Data Science, BCD 2019
Country/Territory	United States
City	Honolulu
Period	05/29/19 → 05/31/19

Keywords

Big data analytics
Big data processing
NBA game analysis
Sports analytics

Access to Document

10.1109/BCD.2019.8885163

Cite this

Yu, A., & Chung, S. S. (2019). Automatic Identification and Analysis of Basketball Plays: NBA On-Ball Screens. In M. Iwashita, A. Shimoda, & P. Chertchom (Eds.), Proceedings - 2019 IEEE/ACIS 4th International Conference on Big Data, Cloud Computing, and Data Science, BCD 2019 (pp. 29-34). Article 8885163 Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/BCD.2019.8885163

Yu, Andrew ; Chung, Sun Sunnie. / Automatic Identification and Analysis of Basketball Plays: NBA On-Ball Screens. Proceedings - 2019 IEEE/ACIS 4th International Conference on Big Data, Cloud Computing, and Data Science, BCD 2019. editor / Motoi Iwashita ; Atsushi Shimoda ; Prajak Chertchom. usa : Institute of Electrical and Electronics Engineers Inc., 2019. pp. 29-34

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abstract = "In this study, we present methodologies to process big data in complex multimedia forms for sports analytics. Sports analytics is the management and analysis of data collected from sports games to quantify past results and predict future outcomes. In basketball, the on-ball screen is a dynamic offensive strategy that involves the movement of multiple players and the ball to create an effective shot attempt. It is a fundamental play employed by all teams in the National Basketball Association (NBA), the highest level of competition for basketball. The analysis of a basketball team and its strategies must first include the identification of such plays. With the presence of sophisticated data collection and analysis tools, this paper proposes methodologies to extract, transform, and analyze player motion-tracking data in NBA games to automatically identify the presence of on-ball screens, with 90\% sensitivity, an 8\% improvement on existing literature.",

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Yu, A & Chung, SS 2019, Automatic Identification and Analysis of Basketball Plays: NBA On-Ball Screens. in M Iwashita, A Shimoda & P Chertchom (eds), Proceedings - 2019 IEEE/ACIS 4th International Conference on Big Data, Cloud Computing, and Data Science, BCD 2019., 8885163, Institute of Electrical and Electronics Engineers Inc., usa, pp. 29-34, 4th IEEE/ACIS International Conference on Big Data, Cloud Computing, and Data Science, BCD 2019, Honolulu, United States, 05/29/19. https://doi.org/10.1109/BCD.2019.8885163

Automatic Identification and Analysis of Basketball Plays: NBA On-Ball Screens. / Yu, Andrew; Chung, Sun Sunnie.
Proceedings - 2019 IEEE/ACIS 4th International Conference on Big Data, Cloud Computing, and Data Science, BCD 2019. ed. / Motoi Iwashita; Atsushi Shimoda; Prajak Chertchom. usa: Institute of Electrical and Electronics Engineers Inc., 2019. p. 29-34 8885163.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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N2 - In this study, we present methodologies to process big data in complex multimedia forms for sports analytics. Sports analytics is the management and analysis of data collected from sports games to quantify past results and predict future outcomes. In basketball, the on-ball screen is a dynamic offensive strategy that involves the movement of multiple players and the ball to create an effective shot attempt. It is a fundamental play employed by all teams in the National Basketball Association (NBA), the highest level of competition for basketball. The analysis of a basketball team and its strategies must first include the identification of such plays. With the presence of sophisticated data collection and analysis tools, this paper proposes methodologies to extract, transform, and analyze player motion-tracking data in NBA games to automatically identify the presence of on-ball screens, with 90% sensitivity, an 8% improvement on existing literature.

AB - In this study, we present methodologies to process big data in complex multimedia forms for sports analytics. Sports analytics is the management and analysis of data collected from sports games to quantify past results and predict future outcomes. In basketball, the on-ball screen is a dynamic offensive strategy that involves the movement of multiple players and the ball to create an effective shot attempt. It is a fundamental play employed by all teams in the National Basketball Association (NBA), the highest level of competition for basketball. The analysis of a basketball team and its strategies must first include the identification of such plays. With the presence of sophisticated data collection and analysis tools, this paper proposes methodologies to extract, transform, and analyze player motion-tracking data in NBA games to automatically identify the presence of on-ball screens, with 90% sensitivity, an 8% improvement on existing literature.

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Yu A, Chung SS. Automatic Identification and Analysis of Basketball Plays: NBA On-Ball Screens. In Iwashita M, Shimoda A, Chertchom P, editors, Proceedings - 2019 IEEE/ACIS 4th International Conference on Big Data, Cloud Computing, and Data Science, BCD 2019. usa: Institute of Electrical and Electronics Engineers Inc. 2019. p. 29-34. 8885163 doi: 10.1109/BCD.2019.8885163

Automatic Identification and Analysis of Basketball Plays: NBA On-Ball Screens

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