Evidence map›Paper›PMID 35009866›Full record

ArticleSensors (Basel, Switzerland)2022

Individualization of Intensity Thresholds on External Workload Demands in Women's Basketball by K-Means Clustering: Differences Based on the Competitive Level.

Sergio J Ibáñez, Carlos D Gómez-Carmona, David Mancha-Triguero

Open access · goldAbstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
17citing papers in PubMed, 2 pooled it
5.0field-weighted citation impact, top 4% of its field
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

17 citing papers in PubMed, 2 syntheses or guidelines pooled it, 30 citations in OpenAlex.

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  17. Physical Fitness as a Predictor of Performance during Competition in Professional Women's Basketball Players.International journal of environmental research and public health · 2023
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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

3 authors at 2 institutions in 1 country.

Sergio J IbáñezResearch Group in Optimization of Training and Sports Performance (GOERD), Didactics of Body Expression, Music and Plastic Department, Sport Science Faculty, University of Extremadura, 10005 Caceres, Spain.ORCID 0000-0001-6009-4086
Carlos D Gómez-CarmonaResearch Group in Optimization of Training and Sports Performance (GOERD), Didactics of Body Expression, Music and Plastic Department, Sport Science Faculty, University of Extremadura, 10005 Caceres, Spain.ORCID 0000-0002-4084-8124
David Mancha-TrigueroResearch Group in Optimization of Training and Sports Performance (GOERD), Didactics of Body Expression, Music and Plastic Department, Sport Science Faculty, University of Extremadura, 10005 Caceres, Spain.
Universidad de Extremadura · ESUniversidad San Pablo CEU · ES

Funding

The author Carlos D. Gómez Carmona was supported by a grant from the Spanish Ministry of Education, Culture, and Sport FPU17/00407This study was co-funded by the Regional Department of Economy and Infrastructure of the Government of Extremadura (Spain) through the European Funds of Regional Development of the European Union GR18170This study was co-funded by the Spanish National Agency of Investigation through the project "Scientific and Technological Support to analyze the Training Workload of Basketball teams ac-cording to sex, level of the players and season period" PID2019-106614GB-I00
6 · The paper itself

Abstract

In previous studies found in the literature speed (SP), acceleration (ACC), deceleration (DEC), and impact (IMP) zones have been created according to arbitrary thresholds without considering the specific workload profile of the players (e.g., sex, competitive level, sport discipline). The use of statistical methods based on raw data could be considered as an alternative to be able to individualize these thresholds. The study purposes were to: (a) individualize SP, ACC, DEC, and IMP zones in two female professional basketball teams; (b) characterize the external workload profile of 5 vs. 5 during training sessions; and (c) compare the external workload according to the competitive level (first vs. second division). Two basketball teams were recorded during a 15-day preseason microcycle using inertial devices with ultra-wideband indoor tracking technology and microsensors. The zones of external workload variables (speed, acceleration, deceleration, impacts) were categorized through k-means clusters. Competitive level differences were analyzed with Mann-Whitney's U test and with Cohen's d effect size. Five zones were categorized in speed (<2.31, 2.31-5.33, 5.34-9.32, 9.33-13.12, 13.13-17.08 km/h), acceleration (<0.50, 0.50-1.60, 1.61-2.87, 2.88-4.25, 4.26-6.71 m/s

Indexed as

Athletic PerformanceBasketballAccelerationCluster AnalysisFemaleHumansWorkloadimpactsk-means clusterspeedteam sportstechnology

Identifiers

PMID35009866
PMCPMC8749797
OpenAlexW4206573419

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.