Artificial Intelligence, Optimization, and Data Sciences in Sports

Edited by Maude J. Blondin (), Iztok Fister () and Panos M. Pardalos ()

in Springer Optimization and Its Applications from Springer, currently edited by Pardalos, Panos, Thai, My T. and Du, Ding-Zhu

Date: 2025
ISBN: 978-3-031-76047-1
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Chapters in this book:

Artificial Intelligence, Optimization, and Data Sciences in Sports: Editorial

Maude J. Blondin, Iztok Fister and Panos M. Pardalos

Machine Learning for Soccer Match Result Prediction

Rory Bunker, Calvin Yeung and Keisuke Fujii

Machine Learning for the Prediction of the Index of Effectiveness in Cycling

A. Torres, M. A. Yepez, G. Millour, F. Nougarou and F. Domingue

Machine Learning in Biomechanics: Key Applications and Limitations in Walking, Running and Sports Movements

Carlo Dindorf, Fabian Horst, Djordje Slijepčević, Bernhard Dumphart, Jonas Dully, Matthias Zeppelzauer, Brian Horsak and Michael Fröhlich

Artificial Intelligence and Machine Learning-Based Data Analytics for Sports: General Overview and NBA Case Study

Akemi Gálvez, Vei S. Chan, Sara Pérez-Carabaza and Andrés Iglesias

An Ecological Dynamics Approach to the Use of Artificial Intelligence and Machine Learning to Analyze Performance in Football

Sofia Ferreira, Daniel Carrilho and Duarte Araújo

A Supervised Learning Approach for Evaluating Football Performances

Stefania Corsaro, Giuseppina Dello Ioio, Vincenzo Di Sauro and Zelda Marino

Bridging Route-Based Cycling Training with Digital Twins

Alen Rajšp and Iztok Fister

Perspectives of Artificial Intelligence in Training and Exercise

Arnold Baca

A Fuzzy Model to Optimise the Football Rule Assuring Spectacle, Fair Play, Objectivity and Ethics

Jaime Gil-Lafuente and Domenico Marino

Physical Efficiency in Soccer: Relevance, Correlations, and Impacts Using AI Methods

Daniel Capanema, Adriano Alves, João Claudino and Adriano Pereira

A PageRank-Based Method for College Football Recruiting Rankings

Sergiy Butenko, Andrew Johnson, Erick Moreno-Centeno and Justin Yates

Applications of Improvements to the Pythagorean Won-Lost Expectation in Optimizing Rosters

Alexander F. Almeida, Kevin Dayaratna, Steven J. Miller and Andrew K. Yang

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DOI: 10.1007/978-3-031-76047-1

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