QPass: a Merit-based Evaluation of Soccer Passes
August 08, 2016 Β· Declared Dead Β· π arXiv.org
"No code URL or promise found in abstract"
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Authors
Laszlo Gyarmati, Rade Stanojevic
arXiv ID
1608.03532
Category
cs.AI: Artificial Intelligence
Cross-listed
stat.AP,
stat.ML
Citations
28
Venue
arXiv.org
Last Checked
4 months ago
Abstract
Quantitative analysis of soccer players' passing ability focuses on descriptive statistics without considering the players' real contribution to the passing and ball possession strategy of their team. Which player is able to help the build-up of an attack, or to maintain the possession of the ball? We introduce a novel methodology called QPass to answer questions like these quantitatively. Based on the analysis of an entire season, we rank the players based on the intrinsic value of their passes using QPass. We derive an album of pass trajectories for different gaming styles. Our methodology reveals a quite counterintuitive paradigm: losing the ball possession could lead to better chances to win a game.
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