all AI news
Evaluation of creating scoring opportunities for teammates in soccer via trajectory prediction. (arXiv:2206.01899v1 [cs.AI])
June 7, 2022, 1:10 a.m. | Masakiyo Teranishi, Kazushi Tsutsui, Kazuya Takeda, Keisuke Fujii
cs.LG updates on arXiv.org arxiv.org
Evaluating the individual movements for teammates in soccer players is
crucial for assessing teamwork, scouting, and fan engagement. It has been said
that players in a 90-min game do not have the ball for about 87 minutes on
average. However, it has remained difficult to evaluate an attacking player
without receiving the ball, and to reveal how movement contributes to the
creation of scoring opportunities for teammates. In this paper, we evaluate
players who create off-ball scoring opportunities by comparing …
More from arxiv.org / cs.LG updates on arXiv.org
Jobs in AI, ML, Big Data
Lead GNSS Data Scientist
@ Lurra Systems | Melbourne
Senior Machine Learning Engineer (MLOps)
@ Promaton | Remote, Europe
Lead Data Engineer
@ JPMorgan Chase & Co. | Jersey City, NJ, United States
Senior Machine Learning Engineer
@ TELUS | Vancouver, BC, CA
CT Technologist - Ambulatory Imaging - PRN
@ Duke University | Morriville, NC, US, 27560
BH Data Analyst
@ City of Philadelphia | Philadelphia, PA, United States