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2020 | OriginalPaper | Chapter

Routine Inspection: A Playbook for Corner Kicks

Authors : Laurie Shaw, Sudarshan Gopaladesikan

Published in: Machine Learning and Data Mining for Sports Analytics

Publisher: Springer International Publishing

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Abstract

 We present a set of tools for identifying and studying the offensive and defensive strategies used by football teams in corner kick situations: their corner playbooks. Drawing from methods in topic modelling, our tools classify corners based on the runs made by the attacking players, enabling us to identify the distinct corner routines used by individual teams and search tracking data to find corners that exhibit specific features of interest. We use a supervised machine learning approach to identify whether individual defenders are marking man-to-man or zonally and study the positioning of zonal defenders over many matches. We demonstrate how our methods can be used for opposition analysis by highlighting the offensive and defensive corner strategies used by teams in our data over the course of a season.

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next chapter How Data Availability Affects the Ability to Learn Good xG Models
Footnotes
1
Measuring positions one second after the first ball event helps to identify the target position of players aiming to reach a flick-on.
 
2
Our methodology does not identify the specific opponent a defender is man-marking.
 
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Metadata
Title
Routine Inspection: A Playbook for Corner Kicks
Authors
Laurie Shaw
Sudarshan Gopaladesikan
Copyright Year
2020
Book
Machine Learning and Data Mining for Sports Analytics

Print ISBN: 978-3-030-64911-1

Electronic ISBN: 978-3-030-64912-8

Copyright Year: 2020

DOI
https://doi.org/10.1007/978-3-030-64912-8_1

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