implementing the Expected Goal (xG) model to predict scores in soccer matches

Izzatul Umami, Deden Hardan Gautama, Heliza Rahmania Hatta

Abstract


Football is a sport that has the most fans in the world. What makes sebak patterns so popular are their uncertain and unpredictable results. There are many factors that affect the outcome of a football match, including strategy, skill, and even luck. Therefore, guessing the results of a soccer match is an interesting problem. All shots are grouped into sections on the playing field and theoretical goal scores are applied to each area. The factors analyzed are: distance of shot from goal and angle of shot in relation to goal. When calculating xG, it is recommended that the distance and angle of the shot are important. The combination of the two xG factors is better calculated than each variable only. In addition, this xG check has been able to relatively accurately identify the mid-table teams that score and concede goals.

Article Metrics

Abstract: 4252 Viewers PDF: 2877 Viewers

Keywords


xG model, a soccer match, distance, predict scores

Cite:

How to cite item

Full Text:

PDF


References


A. Rathke, “An examination of expected goals and shot efficiency in soccer,” J. Hum. Sport Exerc., vol. 12, no. Proc2, 2017, doi: 10.14198/jhse.2017.12.proc2.05.

P. Lucey, A. Bialkowski, M. Monfort, P. Carr, and I. Matthews, “‘Quality vs Quantity’: Improved Shot Prediction in Soccer using Strategic Features from Spatiotemporal Data,” Proc. 8th Annu. MIT Sloan Sport. Anal. Conf., pp. 1–9, 2014, [Online]. Available: http://www.sloansportsconference.com/?p=15790.

O. Hubáček, G. Šourek, and F. Železný, “Deep learning from spatial relations for soccer pass prediction,” CEUR Workshop Proc., vol. 2284, pp. 162–169, 2018.

L. Combining, A. Segmentationshape, A. For, R. Fruit, and D. M. W. Hannan, “a M Achine V Ision a Lgorithm Combining Adaptive,” 2017 IEEE Int. Conf. Power, Control. Signals Instrum. Eng., vol. XI, no. 2001, pp. 1–17, 2009.

H. M. Zawbaa, N. El-Bendary, A. E. Hassanien, and T. hoon Kim, “Event detection based approach for soccer video summarization using machine learning,” Int. J. Multimed. Ubiquitous Eng., vol. 7, no. 2, pp. 63–80, 2012.

B. M. Faria, L. P. Reis, N. Lau, and G. Castillo, “Machine Learning algorithms applied to the classification of robotic soccer formations and opponent teams,” 2010 IEEE Conf. Cybern. Intell. Syst. CIS 2010, pp. 344–349, 2010, doi: 10.1109/ICCIS.2010.5518540.

X. X. Xu et al., “Research on the optimal design of soccer robot based on the mechanical analysis,” Adv. Mater. Res., vol. 1049–1050, no. Mmebc, pp. 1033–1037, 2014, doi: 10.4028/www.scientific.net/AMR.1049-1050.1033.

F. da S. L. Cardoso, S. González-Víllora, J. Guilherme, and I. Teoldo, “Young Soccer Players With Higher Tactical Knowledge Display Lower Cognitive Effort,” Percept. Mot. Skills, vol. 126, no. 3, pp. 499–514, 2019, doi: 10.1177/0031512519826437.

D. Bao, H. Wang, B. Fang, and L. Li, “HfutEngine3D Soccer Simulation Team Description 2008,” Sci. Technol., 2008.

J. Carlos Núñez and B. Dagnino, “Exploring the application of soccer mathematical models to game generation on a simulated environment,” pp. 1–10, 2020, [Online]. Available: www.metrica-sports.com.

K. Pelechrinis and W. Winston, “A Skellam regression model for quantifying positional value in soccer,” J. Quant. Anal. Sport., pp. 1–31, 2021, doi: 10.1515/jqas-2019-0122.

H. Igarashi, K. Nakamura, and S. Ishihara, “Learning of soccer player agents using a policy gradient method: Coordination between kicker and receiver during free kicks,” Proc. Int. Jt. Conf. Neural Networks, no. 2, pp. 46–52, 2008, doi: 10.1109/IJCNN.2008.4633765.

B. Larrousse, “Improving decision making for shots,” StatsBomb Innov. Footb. Conf. 2019, pp. 1–15, 2019.

H. I. Ayman, “DEVELOPING A COOPERATIVE BEHAVIOR FOR MULTI AGENTS SYSTEM,” no. July, 2007.

J. Bu, S. Lao, and L. Bai, “Automatic line mark recognition and its application in camera calibration in soccer video,” Proc. - IEEE Int. Conf. Multimed. Expo, 2011, doi: 10.1109/ICME.2011.6012137.

M. Van Roy, P. Robberechts, T. Decroos, and J. Davis, “Valuing On-the-Ball Actions in Soccer: A Critical Comparison of xT and VAEP,” 2019, [Online]. Available: www.aaai.org.

J. H. Kim, “An Analysis of Comparison on Performances in Soccer Attacking-Third,” Korean J. Sport Sci., vol. 24, no. 4, pp. 653–661, 2013, doi: 10.24985/kjss.2013.24.4.653.

J. Fernández, L. Bornn, and D. Cervone, “A framework for the fine-grained evaluation of the instantaneous expected value of soccer possessions,” arXiv, 2020.

M. Lauer, S. Lange, and M. Riedmiller, “Calculating the perfect match: An efficient and accurate approach for robot self-localization,” Lect. Notes Comput. Sci. (including Subser. Lect. Notes Artif. Intell. Lect. Notes Bioinformatics), vol. 4020 LNAI, no. c, pp. 142–153, 2006, doi: 10.1007/11780519_13.

Y. Liu, Q. Huang, Q. Ye, and W. Gao, “A new method to calculate the camera focusing area and player position on playfield in soccer video,” Vis. Commun. Image Process. 2005, vol. 5960, p. 59604H, 2005, doi: 10.1117/12.632721.

A. N. Fitriana, K. Mutijarsa, and W. Adiprawita, “Color-based segmentation and feature detection for ball and goal post on mobile soccer robot game field,” 2016 Int. Conf. Inf. Technol. Syst. Innov. ICITSI 2016 - Proc., pp. 1–4, 2017, doi: 10.1109/ICITSI.2016.7858232.

C. Lago-Peñas, J. Lago-Ballesteros, and E. Rey, “Differences in performance indicators between winning and losing teams in the UEFA Champions League,” J. Hum. Kinet., vol. 27, no. 1, pp. 135–146, 2011, doi: 10.2478/v10078-011-0011-3.


Refbacks

  • There are currently no refbacks.


Barcode

IJIIS: International Journal of Informatics and Information Systems

ISSN:2579-7069 (Online)
Organized by:Departement of Information System, Universitas Amikom Purwokerto, Indonesia; Faculty of Computing and Information Science, Ain Shams University, Cairo, Egypt
Website:www.ijiis.org
Email:husniteja@uinjkt.ac.id (publication issues)
  taqwa@amikompurwokerto.ac.id (managing editor)
  contact@ijiis.org (technical & paper handling issues)

 This work is licensed under a Creative Commons Attribution-ShareAlike 4.0