Evidence map›Paper›PMID 34283154›Full record

ArticleSensors (Basel, Switzerland)2021

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

Arturo Quílez-Maimón, Francisco Javier Rojas-Ruiz, Gabriel Delgado-García, Javier Courel-Ibáñez

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Article
  2. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Arturo Quílez-MaimónDepartment of Physical Education and Sport, Faculty of Sport Sciences, University of Granada, 18071 Granada, Spain.
Francisco Javier Rojas-RuizDepartment of Physical Education and Sport, Faculty of Sport Sciences, University of Granada, 18071 Granada, Spain.ORCID 0000-0001-9426-926X
Gabriel Delgado-GarcíaDepartment of Physical Education and Sport, Faculty of Sport Sciences, University of Granada, 18071 Granada, Spain.
Javier Courel-IbáñezDepartment of Physical Activity and Sport, Faculty of Sport Sciences, University of Murcia, 30720 Murcia, Spain.ORCID 0000-0003-2446-1875

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

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 (

Indexed as

Athletic PerformanceBasketballLegMotor SkillsReproducibility of Results3D analysisaccelerometerbiomechanicsgyroscopemotor controlteam sport

Identifiers

PMID34283154
PMCPMC8271510

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.