Expected passes
نویسندگان
چکیده
Abstract Passes are by far football’s (soccer) most frequent event, yet surprisingly little meaningful research has been devoted to quantify them. With the increase in availability of so-called positional data, describing positioning players and ball at every moment game, our work aims determine difficulty pass calculating its success probability based on surrounding circumstances. As experts will agree, not all passes equal difficulty, however, traditional metrics count them as such. we can how well execute passes, assess their risk profile, even compute completion probabilities for hypothetical combining physical machine learning models. Our model uses first 0.4 seconds a trajectory movement vectors predict intended target with an accuracy $$93.0\%$$ 93.0 % successful $$72.0\%$$ 72.0 unsuccessful much higher than any previously published work. extreme gradient boosting then likelihood towards identified area under curve (AUC) $$93.4\%$$ 93.4 . Finally, discuss several potential applications, like player scouting or evaluating decisions.
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ژورنال
عنوان ژورنال: Data Mining and Knowledge Discovery
سال: 2022
ISSN: ['1573-756X', '1384-5810']
DOI: https://doi.org/10.1007/s10618-021-00810-3