In this paper, we analyze the shooting performance of basketball players by examining factors that may generate high-pressure game situations. Using play-by-play data from the Italian "Serie A2" Championship 2015/2016 to build the model, we validate the main results using data from the Olympic Basketball Tournament Rio 2016" to determine whether the identified relationships can be confirmed using data from players at a very different professional level. After a preliminary exploratory analysis, we (1) develop a multivariate model, based on the Classification And Regression Tree (CART) algorithm, to investigate how selected high-pressure situations, jointly considered, affect scoring probability, and propose new shooting performance measures; (2) investigate players' personal reactions to selected high-pressure game situations by introducing additional new measures, improving the indices currently used to measure the players' shooting performance. The results are interesting and easy to interpret with the aid of some insightful graphical representations. Our approach can be exploited by both scouts and coaches to understand important characteristics of players and, ultimately, to measure and enhance a team's performance.
Big data analytics to model scoring probability in basketball: the effect of shooting under high-pressure conditions
ZUCCOLOTTO, Paola;MANISERA, Marica;SANDRI, Marco
2018-01-01
Abstract
In this paper, we analyze the shooting performance of basketball players by examining factors that may generate high-pressure game situations. Using play-by-play data from the Italian "Serie A2" Championship 2015/2016 to build the model, we validate the main results using data from the Olympic Basketball Tournament Rio 2016" to determine whether the identified relationships can be confirmed using data from players at a very different professional level. After a preliminary exploratory analysis, we (1) develop a multivariate model, based on the Classification And Regression Tree (CART) algorithm, to investigate how selected high-pressure situations, jointly considered, affect scoring probability, and propose new shooting performance measures; (2) investigate players' personal reactions to selected high-pressure game situations by introducing additional new measures, improving the indices currently used to measure the players' shooting performance. The results are interesting and easy to interpret with the aid of some insightful graphical representations. Our approach can be exploited by both scouts and coaches to understand important characteristics of players and, ultimately, to measure and enhance a team's performance.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
