Cargando…

Development and Validation of an Observational Game Analysis Tool with Artificial Intelligence for Handball: Handball.ai

Performance analysis based on artificial intelligence together with game-related statistical models aims to provide relevant information before, during and after a competition. Due to the evaluation of handball performance focusing mainly on the result and not on the analysis of the dynamics of the...

Descripción completa

Detalles Bibliográficos
Autores principales: Marquina, Moises, Lozano, Demetrio, García-Sánchez, Carlos, Sánchez-López, Sergio, de la Rubia, Alfonso
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10422213/
https://www.ncbi.nlm.nih.gov/pubmed/37571498
http://dx.doi.org/10.3390/s23156714
_version_ 1785089148997074944
author Marquina, Moises
Lozano, Demetrio
García-Sánchez, Carlos
Sánchez-López, Sergio
de la Rubia, Alfonso
author_facet Marquina, Moises
Lozano, Demetrio
García-Sánchez, Carlos
Sánchez-López, Sergio
de la Rubia, Alfonso
author_sort Marquina, Moises
collection PubMed
description Performance analysis based on artificial intelligence together with game-related statistical models aims to provide relevant information before, during and after a competition. Due to the evaluation of handball performance focusing mainly on the result and not on the analysis of the dynamics of the game pace through artificial intelligence, the aim of this study was to design and validate a specific handball instrument based on real-time observational methodology capable of identifying, quantifying, classifying and relating individual and collective tactical behaviours during the game. First, an instrument validation by an expert panel was performed. Ten experts answered a questionnaire regarding the relevance and appropriateness of each variable presented. Subsequently, data were validated by two observers (1.5 and 2 years of handball observational analysis experience) recruited to analyse a Champions League match. Instrument validity showed a high accordance degree among experts (Cohen’s kappa index (k) = 0.889). For both automatic and manual variables, a very good intra- ((automatic: Cronbach’s alpha (α) = 0.984; intra-class correlation coefficient (ICC) = 0.970; k = 0.917) (manual: α = 0.959; ICC = 0.923; k = 0.858)) and inter-observer ((automatic: α = 0.976; ICC = 0.961; k = 0.874) (manual: α = 0.959; ICC = 0.923; k = 0.831) consistency and reliability was found. These results show a high degree of instrument validity, reliability and accuracy providing handball coaches, analysts, and researchers a novel tool to improve handball performance.
format Online
Article
Text
id pubmed-10422213
institution National Center for Biotechnology Information
language English
publishDate 2023
publisher MDPI
record_format MEDLINE/PubMed
spelling pubmed-104222132023-08-13 Development and Validation of an Observational Game Analysis Tool with Artificial Intelligence for Handball: Handball.ai Marquina, Moises Lozano, Demetrio García-Sánchez, Carlos Sánchez-López, Sergio de la Rubia, Alfonso Sensors (Basel) Article Performance analysis based on artificial intelligence together with game-related statistical models aims to provide relevant information before, during and after a competition. Due to the evaluation of handball performance focusing mainly on the result and not on the analysis of the dynamics of the game pace through artificial intelligence, the aim of this study was to design and validate a specific handball instrument based on real-time observational methodology capable of identifying, quantifying, classifying and relating individual and collective tactical behaviours during the game. First, an instrument validation by an expert panel was performed. Ten experts answered a questionnaire regarding the relevance and appropriateness of each variable presented. Subsequently, data were validated by two observers (1.5 and 2 years of handball observational analysis experience) recruited to analyse a Champions League match. Instrument validity showed a high accordance degree among experts (Cohen’s kappa index (k) = 0.889). For both automatic and manual variables, a very good intra- ((automatic: Cronbach’s alpha (α) = 0.984; intra-class correlation coefficient (ICC) = 0.970; k = 0.917) (manual: α = 0.959; ICC = 0.923; k = 0.858)) and inter-observer ((automatic: α = 0.976; ICC = 0.961; k = 0.874) (manual: α = 0.959; ICC = 0.923; k = 0.831) consistency and reliability was found. These results show a high degree of instrument validity, reliability and accuracy providing handball coaches, analysts, and researchers a novel tool to improve handball performance. MDPI 2023-07-27 /pmc/articles/PMC10422213/ /pubmed/37571498 http://dx.doi.org/10.3390/s23156714 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Marquina, Moises
Lozano, Demetrio
García-Sánchez, Carlos
Sánchez-López, Sergio
de la Rubia, Alfonso
Development and Validation of an Observational Game Analysis Tool with Artificial Intelligence for Handball: Handball.ai
title Development and Validation of an Observational Game Analysis Tool with Artificial Intelligence for Handball: Handball.ai
title_full Development and Validation of an Observational Game Analysis Tool with Artificial Intelligence for Handball: Handball.ai
title_fullStr Development and Validation of an Observational Game Analysis Tool with Artificial Intelligence for Handball: Handball.ai
title_full_unstemmed Development and Validation of an Observational Game Analysis Tool with Artificial Intelligence for Handball: Handball.ai
title_short Development and Validation of an Observational Game Analysis Tool with Artificial Intelligence for Handball: Handball.ai
title_sort development and validation of an observational game analysis tool with artificial intelligence for handball: handball.ai
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10422213/
https://www.ncbi.nlm.nih.gov/pubmed/37571498
http://dx.doi.org/10.3390/s23156714
work_keys_str_mv AT marquinamoises developmentandvalidationofanobservationalgameanalysistoolwithartificialintelligenceforhandballhandballai
AT lozanodemetrio developmentandvalidationofanobservationalgameanalysistoolwithartificialintelligenceforhandballhandballai
AT garciasanchezcarlos developmentandvalidationofanobservationalgameanalysistoolwithartificialintelligenceforhandballhandballai
AT sanchezlopezsergio developmentandvalidationofanobservationalgameanalysistoolwithartificialintelligenceforhandballhandballai
AT delarubiaalfonso developmentandvalidationofanobservationalgameanalysistoolwithartificialintelligenceforhandballhandballai