Passing Path Predicts Shooting Outcome in Football

Author:

Cao Shun1

Affiliation:

1. University of Houston

Abstract

Abstract What determines the outcome of a shot (scored or unscored) in football (soccer)? Numerous studies have investigated various aspects of this question, including the skills and physical/mental state of the shooter or goalkeeper, the positional information of shots, as well as the attacking styles and defensive formations of the opposing team. However, a critical question has received limited attention: How does the passing path affect the outcome of a shot? In other words, do different paths of the ball before shooting significantly influence the result of shots occurred in the same location? This study aims to fill the gap in the literature by conducting qualitative studies using a dataset comprising 34,938 shots, along with passing paths from top-tier football leagues and international competitions such as the World Cup. Eighteen path features were extracted and applied to three different machine-learning models. The results indicate that the passing path, whether with or without the positional information of shots, can indeed predict shooting outcomes and reveal influential path features. Moreover, it suggests that taking quick actions to move the ball across areas with a high probability of scoring a goal can significantly increases the chance of a successful shot. Interestingly, certain path features that are commonly considered important for team performance, such as the distribution of passe among players and the overall path length, were found to be less significant for shooting outcomes. These findings enhance our understanding of the effective ball-passing and provide valuable insights into the critical factors for achieving successful shots in football games.

Publisher

Research Square Platform LLC

Reference66 articles.

1. Capturing complex, non-linear team behaviours during competitive football performance;Duarte R;J. Syst. Sci. Complex.,2013

2. Buldú, J.M., Busquets, J., Martínez, J.H., Herrera-Diestra, J.L., Echegoyen, I., Galeano, J. and Luque, J., 2018. Using network science to analyse football passing networks: Dynamics, space, time, and the multilayer nature of the game. Frontiers in psychology, 9, p.1900.

3. Applying graphs and complex networks to football metric interpretation;Arriaza-Ardiles E;Human movement science,2018

4. Bangsbo, J. and Peitersen, B., 2000. Soccer systems and strategies. Human Kinetics.

5. Science of winning soccer: Emergent pattern-forming dynamics in association football;Vilar L;Journal of systems science and complexity,2013

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3