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The success rate of a basketball shot may be higher at locations where a player makes more shots. For a marked spatial point process, this means that the mark and the intensity are associated. We propose a Bayesian joint model for the mark…

Applications · Statistics 2023-02-02 Jieying Jiao , Guanyu Hu , Jun Yan

Basketball shot charts provide valuable information regarding local patterns of in-game performance to coaches, players, sports analysts, and statisticians. The spatial patterns of where shots were attempted and whether the shots were…

Methodology · Statistics 2025-03-05 Jiahao Cao , Qingpo Cai , Lance A. Waller , DeMarc A. Hickson , Guanyu Hu , Jian Kang

We propose a Bayesian nonparametric matrix clustering approach to analyze the latent heterogeneity structure in the shot selection data collected from professional basketball players in the National Basketball Association (NBA). The…

Methodology · Statistics 2020-10-19 Fan Yin , Guanyu Hu , Weining Shen

Basketball shot location data provide valuable summary information regarding players to coaches, sports analysts, fans, statisticians, as well as players themselves. Represented by spatial points, such data are naturally analyzed with…

Methodology · Statistics 2020-11-24 Fan Yin , Jieying Jiao , Guanyu Hu , Jun Yan

Basketball analytics has significantly advanced our understanding of the game, with shot selection emerging as a critical factor in both individual and team performance. With the advent of player tracking technologies, a wealth of granular…

Applications · Statistics 2025-03-12 Jiahao Cao , Hou-Cheng Yang , Guanyu Hu

In this paper, we propose a shot percentage distribution strategy among the players of a basketball team to maximize the score that can be achieved by them. The approach is based on the concepts of game theory related to network flow.

Computer Science and Game Theory · Computer Science 2023-10-03 Aditya Singh

Shooting location is a core indicator of offensive style in invasion sports. Existing basketball shot-chart analyses often use spatial information for descriptive visualization, location-based efficiency modeling, or clustering players into…

Methodology · Statistics 2026-03-26 Kazuhiro Yamada , Keisuke Fujii

In this paper, we propose two novel basketball metrics: ``expected points'' for team-based comparisons and ``expected points above average (EPAA)'' as a player-evaluation tool. Established within the Bayesian hierarchical model framework,…

Other Statistics · Statistics 2025-08-05 Benjamin Williams , Erin M. Schliep , Bailey Fosdick , Ryan Elmore

We develop a machine learning approach to represent and analyze the underlying spatial structure that governs shot selection among professional basketball players in the NBA. Typically, NBA players are discussed and compared in an…

Machine Learning · Statistics 2014-01-09 Andrew Miller , Luke Bornn , Ryan Adams , Kirk Goldsberry

Every shot in basketball has an opportunity cost; one player's shot eliminates all potential opportunities from their teammates for that play. For this reason, player-shot efficiency should ultimately be considered relative to the lineup.…

Applications · Statistics 2021-04-19 Nathan Sandholtz , Jacob Mortensen , Luke Bornn

This paper develops metrics from a social network perspective that are directly translatable to the outcome of a basketball game. We extend a state-of-the-art multi-resolution stochastic process approach to modeling basketball by modeling…

Applications · Statistics 2019-10-01 Fan Bu , Sonia Xu , Katherine Heller , Alexander Volfovsky

We propose a multidimensional tensor clustering approach for studying how professional basketball players' shooting patterns vary over court locations and game time. Unlike most existing methods that only study continuous-valued tensors or…

Methodology · Statistics 2022-05-23 Guanyu Hu , Yishu Xue , Weining Shen

In this paper, we develop a group learning approach to analyze the underlying heterogeneity structure of shot selection among professional basketball players in the NBA. We propose a mixture of finite mixtures (MFM) model to capture the…

Applications · Statistics 2020-10-21 Guanyu Hu , Hou-Cheng Yang , Yishu Xue

Traditional NBA player evaluation metrics are based on scoring differential or some pace-adjusted linear combination of box score statistics like points, rebounds, assists, etc. These measures treat performances with the outcome of the game…

Applications · Statistics 2023-09-21 Sameer K. Deshpande , Shane T. Jensen

I address the difficult challenge of measuring the relative influence of competing basketball game strategies, and I apply my analysis to plays resulting in three-point shots. I use a glut of SportVU player tracking data from over 600 NBA…

Applications · Statistics 2017-03-22 Bradley A. Sliz

Motivated by the goal of evaluating real-time forecasts of home team win probabilities in the National Basketball Association, we develop new tools for measuring the quality of continuously updated probabilistic forecasts. This includes…

Methodology · Statistics 2020-10-05 Chi-Kuang Yeh , Gregory Rice , Joel A. Dubin

In recent years, analytics has started to revolutionize the game of basketball: quantitative analyses of the game inform team strategy, management of player health and fitness, and how teams draft, sign, and trade players. In this review,…

Applications · Statistics 2020-07-22 Zachary Terner , Alexander Franks

Batting average is one of the principle performance measures for an individual baseball player. It is natural to statistically model this as a binomial-variable proportion, with a given (observed) number of qualifying attempts (called…

Applications · Statistics 2008-12-18 Lawrence D. Brown

For professional basketball, finding valuable and suitable players is the key to building a winning team. To deal with such challenges, basketball managers, scouts and coaches are increasingly turning to analytics. Objective evaluation of…

Applications · Statistics 2016-07-26 Lu Xin , Mu Zhu , Hugh Chipman

The underlying physics of basketball shooting seems to be a straightforward example of the Newtonian mechanics that can easily be traced by numerical methods. However, a human basketball player does not make use of all the possible…

Popular Physics · Physics 2016-10-25 Byeong June Min
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