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Sports analytics—Evaluation of basketball players and team performance
V Sarlis, C Tjortjis - Information Systems, 2020 - Elsevier
Given the recent trend in Data Science (DS) and Sports Analytics, an opportunity has arisen
for utilizing Machine Learning (ML) and Data Mining (DM) techniques in sports. This paper …
for utilizing Machine Learning (ML) and Data Mining (DM) techniques in sports. This paper …
Big ideas in sports analytics and statistical tools for their investigation
Sports analytics—broadly defined as the pursuit of improvement in athletic performance
through the analysis of data—has expanded its footprint both in the professional sports …
through the analysis of data—has expanded its footprint both in the professional sports …
Actions speak louder than goals: Valuing player actions in soccer
Assessing the impact of the individual actions performed by soccer players during games is
a crucial aspect of the player recruitment process. Unfortunately, most traditional metrics fall …
a crucial aspect of the player recruitment process. Unfortunately, most traditional metrics fall …
[PDF][PDF] Decomposing the immeasurable sport: A deep learning expected possession value framework for soccer
What is the right way to think about analytics in soccer? Is the sport about measured events
such as passes and goals, possession percentages and traveled distance, or even more …
such as passes and goals, possession percentages and traveled distance, or even more …
Deep soccer analytics: learning an action-value function for evaluating soccer players
Given the large pitch, numerous players, limited player turnovers, and sparse scoring,
soccer is arguably the most challenging to analyze of all the major team sports. In this work …
soccer is arguably the most challenging to analyze of all the major team sports. In this work …
Methodology and evaluation in sports analytics: challenges, approaches, and lessons learned
There has been an explosion of data collected about sports. Because such data is extremely
rich and complex, machine learning is increasingly being used to extract actionable insights …
rich and complex, machine learning is increasingly being used to extract actionable insights …
Exploring game dynamics in padel: Implications for assessment and training
Courel-Ibáñez, J, Sánchez-Alcaraz Martinez, BJ, and Muñoz Marín, D. Exploring game
dynamics in padel: implications for assessment and training. J Strength Cond Res 33 (7) …
dynamics in padel: implications for assessment and training. J Strength Cond Res 33 (7) …
Artificial intelligence for team sports: a survey
The sports domain presents a number of significant computational challenges for artificial
intelligence (AI) and machine learning (ML). In this paper, we explore the techniques that …
intelligence (AI) and machine learning (ML). In this paper, we explore the techniques that …
[PDF][PDF] quality vs quantity: Improved shot prediction in soccer using strategic features from spatiotemporal data
In this paper, we present a method which accurately estimates the likelihood of chances in
soccer using strategic features from an entire season of player and ball tracking data taken …
soccer using strategic features from an entire season of player and ball tracking data taken …
Large-scale analysis of soccer matches using spatiotemporal tracking data
Although the collection of player and ball tracking data is fast becoming the norm in
professional sports, large-scale mining of such spatiotemporal data has yet to surface. In this …
professional sports, large-scale mining of such spatiotemporal data has yet to surface. In this …