Factorized Point Process Intensities: A Spatial Analysis of Professional Basketball

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 heuristic, imprecise manner that relies on unmeasured intuitions about player behavior. This makes it difficult to draw comparisons between players and make accurate player specific predictions. Modeling shot attempt data as a point process, we create a low dimensional representation of offensive player types in the NBA. Using non-negative matrix factorization (NMF), an unsupervised dimensionality reduction technique, we show that a low-rank spatial decomposition summarizes the shooting habits of NBA players. The spatial representations discovered by the algorithm correspond to intuitive descriptions of NBA player types, and can be used to model other spatial effects, such as shooting accuracy.Engineering and Applied Science

Considerations in Design of Transition Behaviors for Dynamic Thematic Maps

Maps provide a means for visual communication of spatial information. The success of this communication process largely rests on the design and symbolization choices made by the cartographer. For static mapmaking we have seen substantial research in how our design decisions can influence the legibility of the map’s message, however, we have limited knowledge about how dynamic maps communicate most effectively. Commonly, dynamic maps communicate spatiotemporal information by 1) displaying known data at discrete points in time and 2) employing cartographic transitions that depict changes that occur between these points. Since these transitions are a part of the communication process, we investigate how three common principles of static map design (visual variables, level of measurement, and classed vs. unclassed data representations) relate to cartographic transitions and their abilities to congruently and coherently represent temporal change in dynamic phenomena. In this review we find that many principles for static map design are less than reliable in a dynamic environment; the principles of static map symbolization and design do not always appear to be effective or congruent graphical representations of change. Through the review it becomes apparent that we are in need of additional research in the communication effectiveness of dynamic thematic maps. We conclude by identifying several research areas that we believe are key to developing research-based best practices for communicating about dynamic geographic processes

Considerations in Design of Transition Behaviors for Dynamic Thematic Maps

Maps provide a means for visual communication of spatial information. The success of this communication process largely rests on the design and symbolization choices made by the cartographer. For static mapmaking we have seen substantial research in how our design decisions can influence the legibility of the map’s message, however, we have limited knowledge about how dynamic maps communicate most effectively. Commonly, dynamic maps communicate spatiotemporal information by 1) displaying known data at discrete points in time and 2) employing cartographic transitions that depict changes that occur between these points. Since these transitions are a part of the communication process, we investigate how three common principles of static map design (visual variables, level of measurement, and classed vs. unclassed data representations) relate to cartographic transitions and their abilities to congruently and coherently represent temporal change in dynamic phenomena. In this review we find that many principles for static map design are less than reliable in a dynamic environment; the principles of static map symbolization and design do not always appear to be effective or congruent graphical representations of change. Through the review it becomes apparent that we are in need of additional research in the communication effectiveness of dynamic thematic maps. We conclude by identifying several research areas that we believe are key to developing research-based best practices for communicating about dynamic geographic processes