Trajectory Prediction Model for Crossing-Based Target Selection

2019 ◽  
Author(s):  
Hao Zhang ◽  
Jin Huang ◽  
Feng Tian
Keyword(s):  
Prediction Model ◽  
Target Selection ◽  
Trajectory Prediction

scholarly journals Trajectory prediction model for crossing-based target selection

2019 ◽  
Vol 1 (3) ◽  
pp. 330-340
Author(s):  
Hao ZHANG ◽  
Jin HUANG ◽  
Feng TIAN ◽  
Guozhong DAI ◽  
Hongan WANG
Keyword(s):  
Prediction Model ◽  
Target Selection ◽  
Trajectory Prediction

scholarly journals Rating Player Actions in Soccer

2021 ◽  
Vol 3 ◽  
Author(s):  
Uwe Dick ◽  
Maryam Tavakol ◽  
Ulf Brefeld
Keyword(s):  
Neural Network ◽  
Prediction Model ◽  
Recurrent Neural Network ◽  
Performance Indicators ◽  
Data Driven ◽  
Tracking Data ◽  
Trajectory Prediction ◽  
Study Approach

We present a data-driven model that rates actions of the player in soccer with respect to their contribution to ball possession phases. This study approach consists of two interconnected parts: (i) a trajectory prediction model that is learned from real tracking data and predicts movements of players and (ii) a prediction model for the outcome of a ball possession phase. Interactions between players and a ball are captured by a graph recurrent neural network (GRNN) and we show empirically that the network reliably predicts both, player trajectories as well as outcomes of ball possession phases. We derive a set of aggregated performance indicators to compare players with respect to. to their contribution to the success of their team.

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