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The Q-Pass Index: A Multifactorial IMUs-Based Tool to Assess Passing Skills in Basketball

Despite being a key sport-specific characteristic in performance, there is no practical tool to assess the quality of the pass in basketball. The aim of this study is to develop a tool (the quality-pass index or Q-Pass) able to deliver a quantitative, practical measure of passing skills quality base...

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Autores principales: Quílez-Maimón, Arturo, Rojas-Ruiz, Francisco Javier, Delgado-García, Gabriel, Courel-Ibáñez, Javier
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8271510/
https://www.ncbi.nlm.nih.gov/pubmed/34283154
http://dx.doi.org/10.3390/s21134601
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author Quílez-Maimón, Arturo
Rojas-Ruiz, Francisco Javier
Delgado-García, Gabriel
Courel-Ibáñez, Javier
author_facet Quílez-Maimón, Arturo
Rojas-Ruiz, Francisco Javier
Delgado-García, Gabriel
Courel-Ibáñez, Javier
author_sort Quílez-Maimón, Arturo
collection PubMed
description Despite being a key sport-specific characteristic in performance, there is no practical tool to assess the quality of the pass in basketball. The aim of this study is to develop a tool (the quality-pass index or Q-Pass) able to deliver a quantitative, practical measure of passing skills quality based on a combination of accuracy, execution time and pass pattern variability. Temporal, kinematics and performance parameters were analysed in five different types of passes (chest, bounce, crossover, between-the-leg and behind-the-back) using a field-based test, video cameras and body-worn inertial sensors (IMUs). Data from pass accuracy, time and angular velocity were collected and processed in a custom-built excel spreadsheet. The Q-pass index (0–100 score) resulted from the sum of the three factors. Data were collected from 16 young basketball players (age: 16 ± 2 years) with high (experienced) and low (novice) level of expertise. Reliability analyses found the Q-pass index as a reliable tool in both novice (CV from 4.3 to 9.3%) and experienced players (CV from 2.8 to 10.2%). Besides, important differences in the Q-pass index were found between players’ level (p < 0.05), with the experienced showing better scores in all passing situations: behind-the-back (ES = 1.91), bounce (ES = 0.82), between-the-legs (ES = 1.11), crossover (ES = 0.58) and chest (ES = 0.94). According to these findings, the Q-pass index was sensitive enough to identify the differences in passing skills between young players with different levels of expertise, providing a numbering score for each pass executed.
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spelling pubmed-82715102021-07-11 The Q-Pass Index: A Multifactorial IMUs-Based Tool to Assess Passing Skills in Basketball Quílez-Maimón, Arturo Rojas-Ruiz, Francisco Javier Delgado-García, Gabriel Courel-Ibáñez, Javier Sensors (Basel) Article Despite being a key sport-specific characteristic in performance, there is no practical tool to assess the quality of the pass in basketball. The aim of this study is to develop a tool (the quality-pass index or Q-Pass) able to deliver a quantitative, practical measure of passing skills quality based on a combination of accuracy, execution time and pass pattern variability. Temporal, kinematics and performance parameters were analysed in five different types of passes (chest, bounce, crossover, between-the-leg and behind-the-back) using a field-based test, video cameras and body-worn inertial sensors (IMUs). Data from pass accuracy, time and angular velocity were collected and processed in a custom-built excel spreadsheet. The Q-pass index (0–100 score) resulted from the sum of the three factors. Data were collected from 16 young basketball players (age: 16 ± 2 years) with high (experienced) and low (novice) level of expertise. Reliability analyses found the Q-pass index as a reliable tool in both novice (CV from 4.3 to 9.3%) and experienced players (CV from 2.8 to 10.2%). Besides, important differences in the Q-pass index were found between players’ level (p < 0.05), with the experienced showing better scores in all passing situations: behind-the-back (ES = 1.91), bounce (ES = 0.82), between-the-legs (ES = 1.11), crossover (ES = 0.58) and chest (ES = 0.94). According to these findings, the Q-pass index was sensitive enough to identify the differences in passing skills between young players with different levels of expertise, providing a numbering score for each pass executed. MDPI 2021-07-05 /pmc/articles/PMC8271510/ /pubmed/34283154 http://dx.doi.org/10.3390/s21134601 Text en © 2021 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
Quílez-Maimón, Arturo
Rojas-Ruiz, Francisco Javier
Delgado-García, Gabriel
Courel-Ibáñez, Javier
The Q-Pass Index: A Multifactorial IMUs-Based Tool to Assess Passing Skills in Basketball
title The Q-Pass Index: A Multifactorial IMUs-Based Tool to Assess Passing Skills in Basketball
title_full The Q-Pass Index: A Multifactorial IMUs-Based Tool to Assess Passing Skills in Basketball
title_fullStr The Q-Pass Index: A Multifactorial IMUs-Based Tool to Assess Passing Skills in Basketball
title_full_unstemmed The Q-Pass Index: A Multifactorial IMUs-Based Tool to Assess Passing Skills in Basketball
title_short The Q-Pass Index: A Multifactorial IMUs-Based Tool to Assess Passing Skills in Basketball
title_sort q-pass index: a multifactorial imus-based tool to assess passing skills in basketball
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8271510/
https://www.ncbi.nlm.nih.gov/pubmed/34283154
http://dx.doi.org/10.3390/s21134601
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