Theoretical and Natural Science

- The Open Access Proceedings Series for Conferences


Theoretical and Natural Science

Vol. 28, 26 December 2023


Open Access | Article

Judging Messi’s and Ronaldo’s scoring ability in different situations according to the model

Xinrui Chen * 1 , Yufei Tang 2
1 Univerity of California Davis
2 Stony Brook University

* Author to whom correspondence should be addressed.

Theoretical and Natural Science, Vol. 28, 123-128
Published 26 December 2023. © 2023 The Author(s). Published by EWA Publishing
This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Citation Xinrui Chen, Yufei Tang. Judging Messi’s and Ronaldo’s scoring ability in different situations according to the model. TNS (2023) Vol. 28: 123-128. DOI: 10.54254/2753-8818/28/20230374.

Abstract

In the past decade, two players have overshadowed others in soccer. Who is better, Lionel Messi or Cristiano Ronaldo, has been debated for over a decade. Unlike basketball, the low-scoring nature of soccer dictates that one usually cannot visually conclude the game. Most people discuss who shines in terms of statistics, but there is no way to know the goal-scoring preferences of either man. This paper explores the goal-scoring ability of the two men in different situations to prove who is more complete based on the goal-scoring records of the 2020-2021 season and the data required for expected goals (xG). The study results prove that Messi is more dominant with long-range shots, and Ronaldo scores goals in all visible ranges. This paper introduces a new method of comparing Messi and Ronaldo and uses it as an example to develop a comparison that applies to all players.

Keywords

Lionel Messi, Cristiano Ronaldo, Soccer, Numerical model

References

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3. Rathke, A. (2017). An examination of expected goals and shot efficiency in soccer. J. Hum. Sport Exer. 12, 514–529. doi: 10.14198/jhse.2017.12. Proc2.05

4. Alexander, Duncan. How Soccer Analytics Works. Penguin Random House, 2021.

5. Fernández, Javier, and Luke Bornn. “Wide Open Spaces: A Statistical Technique for Measuring Space Creation in Professional Soccer.” Journal of Quantitative Analysis in Sports, vol. 12, no. 3, 2016, pp. 139-150.

6. Ismael Gómez, et al. “Fitting Your Own Football XG Model · Dato Futbol.” DATO FUTBOL, 14 Apr. 2020, https://www.datofutbol.cl/xg-model/.

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Data Availability

The datasets used and/or analyzed during the current study will be available from the authors upon reasonable request.

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Volume Title
Proceedings of the 2023 International Conference on Mathematical Physics and Computational Simulation
ISBN (Print)
978-1-83558-261-9
ISBN (Online)
978-1-83558-262-6
Published Date
26 December 2023
Series
Theoretical and Natural Science
ISSN (Print)
2753-8818
ISSN (Online)
2753-8826
DOI
10.54254/2753-8818/28/20230374
Copyright
26 December 2023
Open Access
This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited

Copyright © 2023 EWA Publishing. Unless Otherwise Stated