Version 1
: Received: 24 May 2021 / Approved: 25 May 2021 / Online: 25 May 2021 (15:33:19 CEST)
How to cite:
Kollár, A. Football analytics for better betting: Pitch partitioning, possession sequences, expected goal model and player evaluation on Dawson model. Preprints2021, 2021050619. https://doi.org/10.20944/preprints202105.0619.v1
Kollár, A. Football analytics for better betting: Pitch partitioning, possession sequences, expected goal model and player evaluation on Dawson model. Preprints 2021, 2021050619. https://doi.org/10.20944/preprints202105.0619.v1
Kollár, A. Football analytics for better betting: Pitch partitioning, possession sequences, expected goal model and player evaluation on Dawson model. Preprints2021, 2021050619. https://doi.org/10.20944/preprints202105.0619.v1
APA Style
Kollár, A. (2021). Football analytics for better betting: Pitch partitioning, possession sequences, expected goal model and player evaluation on Dawson model. Preprints. https://doi.org/10.20944/preprints202105.0619.v1
Chicago/Turabian Style
Kollár, A. 2021 "Football analytics for better betting: Pitch partitioning, possession sequences, expected goal model and player evaluation on Dawson model" Preprints. https://doi.org/10.20944/preprints202105.0619.v1
Abstract
One of the most significant developments in the sports world over the last two decades has been the use of mathematical methods in conjunction with the massive amounts of data now available to analyze performances, identify trends and patterns, and forecast results. Football analytics has advanced significantly in recent years and continues to evolve as it becomes a more recognized and integral part of the game. Football analytics is also used to forecast game outcomes, allowing bettors to make educated guesses. This article describes mathematical concepts related to football analytics that enable a better betting strategies. We explain how the pitch is partitioned into different zones and we define possession sequences. Furthermore, we explain what an expected goals model is and which expected goals model we use in this research. Furthermore, we define two general characteristics of a player evaluation method, each corresponding to one of the equations of the Dawson model. Based on these characteristics, we describe the developments of several general approaches for evaluating players in the context of the Dawson model.
Keywords
Betting, Dawson model, Football, xG, Pitch partitioning, possession sequences, expected goal model and player evaluation
Subject
Business, Economics and Management, Finance
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
