Influence of relative Quality and experience in female single tennis match performance using cluster and discriminant analysis

Due to the fast growth of advanced technology, the volume of sports data has increased, which has led to researchers' interest in studying the tennis data set. Tennis is an example of an individual sport where the opponent's skills and anticipation are just as significant as the player...

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Published in:AIP Conference Proceedings
Main Author: Husain N.C.; Abidin A.W.Z.; Rosdi K.M.; Nasruddin Z.A.; Ismail H.
Format: Conference paper
Language:English
Published: American Institute of Physics 2024
Online Access:https://www.scopus.com/inward/record.uri?eid=2-s2.0-85203121656&doi=10.1063%2f5.0225405&partnerID=40&md5=6e57709b2b8e2f54e0cf453123a4ea9b
id 2-s2.0-85203121656
spelling 2-s2.0-85203121656
Husain N.C.; Abidin A.W.Z.; Rosdi K.M.; Nasruddin Z.A.; Ismail H.
Influence of relative Quality and experience in female single tennis match performance using cluster and discriminant analysis
2024
AIP Conference Proceedings
3123
1
10.1063/5.0225405
https://www.scopus.com/inward/record.uri?eid=2-s2.0-85203121656&doi=10.1063%2f5.0225405&partnerID=40&md5=6e57709b2b8e2f54e0cf453123a4ea9b
Due to the fast growth of advanced technology, the volume of sports data has increased, which has led to researchers' interest in studying the tennis data set. Tennis is an example of an individual sport where the opponent's skills and anticipation are just as significant as the player's personal qualities and abilities in determining the outcome of a match. Winning is greatly influenced by the experience as well as the comparative talent of the opponents. Hence, this study has two aims: first, to calculate the Relative Quality of each player and then classify the similar patterns of the female single players' performance based on their experience and Relative Quality, and second, to determine which weightings of the variables best discriminate between winners and losers for each cluster. The match statistics for four 2018 Grand Slam main-draw women's singles matches were collected from separate official tournament websites: the Australian Open, the French Open, Wimbledon, and the US Open, which consist of 1016 observations. The methods used in this study are hierarchical-based clustering analysis, which groups the players based on these two attributes, and discriminant analysis, which governs which attributes are best to discriminate among the winners and losers for each of the four clusters. Based on the cluster analysis results, four clusters were identified and designated as LEHRQ, LELRQ, HEHRQ, and HEHRQ. The outcome of the discriminant analysis shows that the performance of a tennis player is most likely reliant on holding their serve and remaining powerful to break their opponent's serve. Moreover, there are variations in the components among clusters. Identifying to which group a player belongs provides valuable assistance to both players and coaches in optimizing their training strategies and augmenting their performance by refining their serving and return abilities. © 2024 Author(s).
American Institute of Physics
0094243X
English
Conference paper

author Husain N.C.; Abidin A.W.Z.; Rosdi K.M.; Nasruddin Z.A.; Ismail H.
spellingShingle Husain N.C.; Abidin A.W.Z.; Rosdi K.M.; Nasruddin Z.A.; Ismail H.
Influence of relative Quality and experience in female single tennis match performance using cluster and discriminant analysis
author_facet Husain N.C.; Abidin A.W.Z.; Rosdi K.M.; Nasruddin Z.A.; Ismail H.
author_sort Husain N.C.; Abidin A.W.Z.; Rosdi K.M.; Nasruddin Z.A.; Ismail H.
title Influence of relative Quality and experience in female single tennis match performance using cluster and discriminant analysis
title_short Influence of relative Quality and experience in female single tennis match performance using cluster and discriminant analysis
title_full Influence of relative Quality and experience in female single tennis match performance using cluster and discriminant analysis
title_fullStr Influence of relative Quality and experience in female single tennis match performance using cluster and discriminant analysis
title_full_unstemmed Influence of relative Quality and experience in female single tennis match performance using cluster and discriminant analysis
title_sort Influence of relative Quality and experience in female single tennis match performance using cluster and discriminant analysis
publishDate 2024
container_title AIP Conference Proceedings
container_volume 3123
container_issue 1
doi_str_mv 10.1063/5.0225405
url https://www.scopus.com/inward/record.uri?eid=2-s2.0-85203121656&doi=10.1063%2f5.0225405&partnerID=40&md5=6e57709b2b8e2f54e0cf453123a4ea9b
description Due to the fast growth of advanced technology, the volume of sports data has increased, which has led to researchers' interest in studying the tennis data set. Tennis is an example of an individual sport where the opponent's skills and anticipation are just as significant as the player's personal qualities and abilities in determining the outcome of a match. Winning is greatly influenced by the experience as well as the comparative talent of the opponents. Hence, this study has two aims: first, to calculate the Relative Quality of each player and then classify the similar patterns of the female single players' performance based on their experience and Relative Quality, and second, to determine which weightings of the variables best discriminate between winners and losers for each cluster. The match statistics for four 2018 Grand Slam main-draw women's singles matches were collected from separate official tournament websites: the Australian Open, the French Open, Wimbledon, and the US Open, which consist of 1016 observations. The methods used in this study are hierarchical-based clustering analysis, which groups the players based on these two attributes, and discriminant analysis, which governs which attributes are best to discriminate among the winners and losers for each of the four clusters. Based on the cluster analysis results, four clusters were identified and designated as LEHRQ, LELRQ, HEHRQ, and HEHRQ. The outcome of the discriminant analysis shows that the performance of a tennis player is most likely reliant on holding their serve and remaining powerful to break their opponent's serve. Moreover, there are variations in the components among clusters. Identifying to which group a player belongs provides valuable assistance to both players and coaches in optimizing their training strategies and augmenting their performance by refining their serving and return abilities. © 2024 Author(s).
publisher American Institute of Physics
issn 0094243X
language English
format Conference paper
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