TY - JOUR

T1 - The origins of goals in the German Bundesliga

AU - Anzer, Gabriel

AU - Bauer, Pascal

AU - Brefeld, Ulf

N1 - Publisher Copyright: © 2021 Informa UK Limited, trading as Taylor & Francis Group.

PY - 2021/11/17

Y1 - 2021/11/17

N2 - We propose to analyse the origin of goals in professional football (soccer) in a purely data-driven approach. Based on positional and event data of 3,457 goals from two seasons German Bundesliga and 2nd Bundesliga (2018/20,219 and 2019/2020), we devise a rich set of 37 features that can be extracted automatically and propose a hierarchical clustering approach to identify group structures. The results consist of 50 interpretable clusters revealing insights into scoring patterns. The hierarchical clustering found 8 alone standing clusters (penalties, direct free kicks, kick and rush, one-two’s, assisted by header, assisted by throw-in) and nine categories (e.g., corners) combining more granular patterns (e.g., five subcategories of corner-goals). We provide a thorough discussion of the clustering and show its relevance for practical applications in opponent analysis, player scouting and for long-term investigations. All stages of this work have been supported by professional analysts from clubs and federation.

AB - We propose to analyse the origin of goals in professional football (soccer) in a purely data-driven approach. Based on positional and event data of 3,457 goals from two seasons German Bundesliga and 2nd Bundesliga (2018/20,219 and 2019/2020), we devise a rich set of 37 features that can be extracted automatically and propose a hierarchical clustering approach to identify group structures. The results consist of 50 interpretable clusters revealing insights into scoring patterns. The hierarchical clustering found 8 alone standing clusters (penalties, direct free kicks, kick and rush, one-two’s, assisted by header, assisted by throw-in) and nine categories (e.g., corners) combining more granular patterns (e.g., five subcategories of corner-goals). We provide a thorough discussion of the clustering and show its relevance for practical applications in opponent analysis, player scouting and for long-term investigations. All stages of this work have been supported by professional analysts from clubs and federation.

KW - Sports analytics

KW - Professional football (Soccer)

KW - Hierarchical Clustering

KW - Tactical Analysis

KW - Business informatics

UR - http://www.scopus.com/inward/record.url?scp=85111431422&partnerID=8YFLogxK

U2 - 10.1080/02640414.2021.1943981

DO - 10.1080/02640414.2021.1943981

M3 - Journal articles

C2 - 34308758

VL - 39

SP - 2525

EP - 2544

JO - Journal of Sports Sciences

JF - Journal of Sports Sciences

SN - 0264-0414

IS - 22

ER -