2017
DOI: 10.1016/j.cag.2017.08.006
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Visual soccer match analysis using spatiotemporal positions of players

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Cited by 28 publications
(31 citation statements)
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“…Shorter trajectories (trails) also aim at reducing visual clutter, and are used in sports when entities are simultaneously moving such as during boat races [BC16], soccer games [AAB*16] (see Figure ), or swimming races [CM16]. Trajectories are often used as visual signatures of phases of play [MLM*17, PVF13b]. These small multiples can represent segmented and abstracted sports events, such as football catches [Tim17], which then act as small visual summaries of particular game events.…”
Section: Visualization By Type: Tracking Datamentioning
confidence: 99%
“…Shorter trajectories (trails) also aim at reducing visual clutter, and are used in sports when entities are simultaneously moving such as during boat races [BC16], soccer games [AAB*16] (see Figure ), or swimming races [CM16]. Trajectories are often used as visual signatures of phases of play [MLM*17, PVF13b]. These small multiples can represent segmented and abstracted sports events, such as football catches [Tim17], which then act as small visual summaries of particular game events.…”
Section: Visualization By Type: Tracking Datamentioning
confidence: 99%
“…It has been demonstrated that they can be successfully applied to various problem domains. [4][5][6][7] Fundamentally important is the interaction with graphical data representations, which supports integrating the human capability of recognizing visual patterns (inference capability) and a user's knowledge about the data analysis process. Visual analytics solutions assist users in creating adequate mental models of complex data, supporting the perception of global characteristics and identification of local behavior through user-driven exploration.…”
Section: Introductionmentioning
confidence: 99%
“…Our approach bears similarity to the one adopted by Machado et al (2017), who present visual designs based on pixel-oriented layouts, called Player Attribute Heatmap (PAH), to summarize a soccer match using as input players positions over time. The PAH visualization, illustrated in Figure 16, is a matrix display of the player positions during part of the match (often a half-time), conveying how player positions and tactical schemes change along the match.…”
Section: Exploratory Visualization Of Multivariate Time Seriesmentioning
confidence: 99%
“…Normalized time series line graphs of the variables can also be inspected, with lines colored according to its variable's cluster. This view is associated with an array showing the corresponding matrix values, simulating a timeline, as shown in Figure 42, our version of the temporal pixel-oriented layout proposed by Machado et al (2017). These views facilitate identifying common patterns between values in different time windows.…”
Section: Variable Correlation Matrixmentioning
confidence: 99%
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