Spatial tracking data are used in sport analytics to study the players’ position during the game in order to evaluate game strategies, players’ roles, performance, also in prospect. From the broad fields of statistics, mathematics, information science and computer science it is possible to draw theories and methods useful to produce innovative results based on speed, distance, players’ separation trajectories. In basketball, spatial tracking data can be combined with play-by-play data, joining results on spatial movements to team performance. In this paper, using tracking data from basketball, we study the spatial pattern of players on the court in order to contribute to the literature of data mining methods for tracking data analysis in sports, with the final objective of suggesting new game strategies to improve team performance.

(2019). Basketball Analytics Using Spatial Tracking Data . Retrieved from http://hdl.handle.net/10446/228013

Basketball Analytics Using Spatial Tracking Data

Metulini, Rodolfo;
2019-01-01

Abstract

Spatial tracking data are used in sport analytics to study the players’ position during the game in order to evaluate game strategies, players’ roles, performance, also in prospect. From the broad fields of statistics, mathematics, information science and computer science it is possible to draw theories and methods useful to produce innovative results based on speed, distance, players’ separation trajectories. In basketball, spatial tracking data can be combined with play-by-play data, joining results on spatial movements to team performance. In this paper, using tracking data from basketball, we study the spatial pattern of players on the court in order to contribute to the literature of data mining methods for tracking data analysis in sports, with the final objective of suggesting new game strategies to improve team performance.
2019
Inglese
New Statistical Developments in Data Science
Petrucci, Alessandra; Racioppi; Filomena; Verde, Rosanna
978-3-030-21158-5
288
305
318
cartaceo
online
Switzerland
Cham
Springer Nature
SIS 2017: Convegno della Società Italiana di Statistica, Florence, Italy, 28-30 June 2017
Florence (Italy)
28-30 June 2017
Settore SECS-S/02 - Statistica per La Ricerca Sperimentale e Tecnologica
Sport science; performance analysis; players’ position; players’ trajectories; convex hulls; cluster analysis
info:eu-repo/semantics/conferenceObject
3
Manisera, Marica; Metulini, Rodolfo; Zuccolotto, Paola
1.4 Contributi in atti di convegno - Contributions in conference proceedings::1.4.01 Contributi in atti di convegno - Conference presentations
reserved
Non definito
273
(2019). Basketball Analytics Using Spatial Tracking Data . Retrieved from http://hdl.handle.net/10446/228013
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