Football Player Substitution Analysis using NLP and Survival Analysis

Title

Football Player Substitution Analysis using NLP and Survival Analysis

Creator

Bera A.; Joshi S.; Nair A.M.

Description

Football player substitution is extremely significant in situations where the team is down by goals or attempting to retain a lead that can add value to the team's performance. However, substituting players based on their prior performance would not assist the squad in making good decisions. In one of the papers, they used an inverse gaussian hazard model to determine the survival rate of players. However, the main issue arises when players do not give their all due to their mental state, which plays a critical role during the game. Furthermore, most of the research papers relied solely on past performance of players and various analyses, which was insufficient. This study discovered that the player's mindset should be mentally stable and competitive which is also very crucial during the match by reading various research articles. Hence, this study proposes a framework which comprises of two models, namely Survival Analysis (Kaplan-Meier Fitter) and Natural Language Processing (Sentimental Analysis). Sentimental Analysis would hel p in determining a player's mindset before the match and Kaplan-Meier Fitter is used to find out the survival rate of player's performance based on several factors like goal scored, passing accuracy etc. which would allow the team to make better informed decisions. Comparison of these two models would yield the best results for substitute players on the bench on the basis of their past performance and their mental health which will allow them to make team management to make better judgments. 2023 IEEE.

Source

Proceedings - 5th International Conference on Smart Systems and Inventive Technology, ICSSIT 2023, pp. 753-757.

Date

2023-01-01

Publisher

Institute of Electrical and Electronics Engineers Inc.

Subject

Kaplan-Meier Fitter; Natural language Processing; player analysis; player comparison.; Sentimental analysis; Survival Analysis; team's performance

Coverage

Bera A., Deemed to Be University, Department of Data Science Christ, Pune, India; Joshi S., Deemed to Be University, Department of Data Science Christ, Pune, India; Nair A.M., Deemed to Be University, Department of Data Science Christ, Pune, India

Rights

Restricted Access

Relation

ISBN: 978-166547467-2

Format

Online

Language

English

Type

Conference paper

Identifier

https://doi.org/10.1109/ICSSIT55814.2023.10061118

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