Rating Player Actions in Soccer
Research output: Journal contributions › Journal articles › Research › peer-review
Standard
Rating Player Actions in Soccer. / Dick, Uwe; Tavakol, Maryam; Brefeld, Ulf.
In: Frontiers in Sports and Active Living, Vol. 3, 682986, 15.07.2021.Research output: Journal contributions › Journal articles › Research › peer-review
Harvard
APA
Vancouver
Bibtex
}
RIS
TY - JOUR
T1 - Rating Player Actions in Soccer
AU - Dick, Uwe
AU - Tavakol, Maryam
AU - Brefeld, Ulf
N1 - This publication was funded by the Open Access Publication Fund of Leuphana University Lüneburg.
PY - 2021/7/15
Y1 - 2021/7/15
N2 - 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.
AB - 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.
KW - graph networks
KW - soccer
KW - sports analytics
KW - trajectory data
KW - trajectory prediction
KW - Informatics
KW - Business informatics
UR - http://www.scopus.com/inward/record.url?scp=85124574199&partnerID=8YFLogxK
U2 - 10.3389/fspor.2021.682986
DO - 10.3389/fspor.2021.682986
M3 - Journal articles
C2 - 34337404
AN - SCOPUS:85124574199
VL - 3
JO - Frontiers in Sports and Active Living
JF - Frontiers in Sports and Active Living
SN - 2642-9367
M1 - 682986
ER -