Search engine for discovering works of Art, research articles, and books related to Art and Culture
Javascript must be enabled to continue!
Predicting Highlights in Badminton Matches: A Knowledge- Aware Model Analysis of Rally-by-Rally Statistics
View through CrossRef
Abstract
In the realm of sports analytics, predicting highlights in badminton matches plays a crucial role in enhancing fan engagement and broadcasting. This study introduces a Knowledge-Aware Model (KAM) that integrates domain-specific knowledge and data-driven techniques to predict game highlights. Analyzing an extensive dataset from the 2017 World Championships and the 2018 Thomas Cup, comprising over 5,180 individual rallies from 140 singles matches, the KAM considers serving and receiving zones, technical stroke nuances, total strokes, rally time and point outcomes. Comparative evaluations against baseline models and state-of-the-art approaches demonstrate the KAM's superiority, achieving an F1-score of 0.793. By combining comprehensive match statistics with rally-specific data, the KAM offers an innovative approach to predicting highlights, with implications extending beyond badminton to multimedia analysis and recommendation systems. This research presents a pivotal step towards more precise and engaging sports analytics.
Title: Predicting Highlights in Badminton Matches: A Knowledge- Aware Model Analysis of Rally-by-Rally Statistics
Description:
Abstract
In the realm of sports analytics, predicting highlights in badminton matches plays a crucial role in enhancing fan engagement and broadcasting.
This study introduces a Knowledge-Aware Model (KAM) that integrates domain-specific knowledge and data-driven techniques to predict game highlights.
Analyzing an extensive dataset from the 2017 World Championships and the 2018 Thomas Cup, comprising over 5,180 individual rallies from 140 singles matches, the KAM considers serving and receiving zones, technical stroke nuances, total strokes, rally time and point outcomes.
Comparative evaluations against baseline models and state-of-the-art approaches demonstrate the KAM's superiority, achieving an F1-score of 0.
793.
By combining comprehensive match statistics with rally-specific data, the KAM offers an innovative approach to predicting highlights, with implications extending beyond badminton to multimedia analysis and recommendation systems.
This research presents a pivotal step towards more precise and engaging sports analytics.
Related Results
Predictors of Statistics Anxiety Among Graduate Students in Saudi Arabia
Predictors of Statistics Anxiety Among Graduate Students in Saudi Arabia
Problem The problem addressed in this study is the anxiety experienced by graduate students toward statistics courses, which often causes students to delay taking statistics cours...
Identification of male’s badminton talents: A systematic review
Identification of male’s badminton talents: A systematic review
The exploration of athlete selection has posed a significant challenge for sports scientists over numerous years, representing a pivotal factor in the success of training endeavors...
Modeling performance evaluation in badminton sports: a fuzzy logic approach
Modeling performance evaluation in badminton sports: a fuzzy logic approach
Spectators and many young students have flocked to badminton matches in recent years. Badminton practice has received a lot of media coverage. The current state of badminton evalua...
Physiological Profiles of Malaysian Young Male Badminton Players, Archers and Non-athletes
Physiological Profiles of Malaysian Young Male Badminton Players, Archers and Non-athletes
Background: This study investigated physiological profiles of Malaysian young male badminton players, archers and non-athlete controls. Methods: Thirty-three young male participant...
Design of Badminton Technical Movement Recognition System Based on Improved Agnes Algorithm
Design of Badminton Technical Movement Recognition System Based on Improved Agnes Algorithm
The Badminton Technical Movement Recognition System is a technology-driven solution aimed at identifying and analyzing various technical movements performed by badminton players du...
Badminton Hawk-Eye Challenge: A Lightweight Badminton Detection Network Based on Feature Pyramid
Badminton Hawk-Eye Challenge: A Lightweight Badminton Detection Network Based on Feature Pyramid
Abstract
The utilization of Hawk-eye technology is a reliable method to ensure the fairness and precise while playing. However, due to the high hardware cost such an applic...
Badminton Smash Basic Training Model
Badminton Smash Basic Training Model
The purpose of the study. This study aims to develop a basic training model for badminton Smash in badminton athletes in West Kalimantan.
Materials and methods. The method used ...
Media-based agility training model of badminton games for students of universitas negeri jakarta badminton club
Media-based agility training model of badminton games for students of universitas negeri jakarta badminton club
Badminton athletes need agility to place the shuttlecock into an empty opponent's field so that the opponent finds it difficult to return the ball. So, the purpose of this study is...