Action Valuation in Sports: A Survey
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Abstract (arXiv)
Action Valuation (AV) has emerged as a key topic in Sports Analytics, offering valuable insights by assigning scores to individual actions based on their contribution to desired outcomes. Despite a few surveys addressing related concepts such as Player Valuation, there is no comprehensive review dedicated to an in-depth analysis of AV across different sports. In this survey, we introduce a taxonomy with nine dimensions related to the AV task, encompassing data, methodological approaches, evaluation techniques, and practical applications. Through this analysis, we aim to identify the essential characteristics of effective AV methods, highlight existing gaps in research, and propose future directions for advancing the field.
Key facts. Cited by 2 papers in the map (data through 14 Oct 2026). Builds on 13 of its 58 references that are in the map. First posted on arXiv 8 Apr 2025.
Builds on
13 of 58 references.
References · 13
- 2019Multi-Agent Reinforcement Learning: A Selective Overview of Theories and Algorithmscited by 567
- 2018Actions Speak Louder Than Goals: Valuing Player Actions in Soccercited by 90
- 2023TacticAI: an AI assistant for football tacticscited by 44
- 2023VARS: Video Assistant Referee System for Automated Soccer Decision Making from Multiple Viewscited by 38
- 2024SoccerNet Game State Reconstruction: End-to-End Athlete Tracking and Identification on a Minimapcited by 34
- 2020A framework for the fine-grained evaluation of the instantaneous expected value of soccer possessionscited by 24
- 2018Deep Reinforcement Learning in Ice Hockey for Context-Aware Player Evaluationcited by 23
- 2022A Comprehensive Review of Computer Vision in Sports: Open Issues, Future Trends and Research Directionscited by 21
- 2021Evaluation of soccer team defense based on prediction models of ball recovery and being attacked: A pilot studycited by 17
- 2021What Happened Next? Using Deep Learning to Value Defensive Actions in Football Event-Datacited by 10
- 2023Action valuation of on- and off-ball soccer players based on multi-agent deep reinforcement learningcited by 10
- 2024Deep learning for action spotting in association football videoscited by 7
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Citing papers per year: 2026: 2.
2 papers.