Evidence map›Paper›PMID 38676261›Full record

ArticleSensors (Basel, Switzerland)2024

Characterization of Running Intensity in Canadian Football Based on Tactical Position.

Abdullah Zafar, Samuel Guay, Sophie-Andrée Vinet, Amélie Apinis-Deshaies, Raphaëlle Creniault, Géraldine Martens, François Prince, Louis De Beaumont

Open access · goldAbstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
1.4field-weighted citation impact, top 22% 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

1 citing paper in PubMed, 3 citations in OpenAlex.

  1. 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

8 authors at 2 institutions in 1 country.

Abdullah ZafarDepartment of Kinesiology, University of Waterloo, Waterloo, ON N2L 3G1, Canada.ORCID 0000-0002-7872-7715
Samuel GuayCentre de Recherche, Hôpital du Sacré-Cœur de Montréal, Montreal, QC H4J 1C5, Canada.
Sophie-Andrée VinetCentre de Recherche, Hôpital du Sacré-Cœur de Montréal, Montreal, QC H4J 1C5, Canada.
Amélie Apinis-DeshaiesCentre de Recherche, Hôpital du Sacré-Cœur de Montréal, Montreal, QC H4J 1C5, Canada.
Raphaëlle CreniaultCentre de Recherche, Hôpital du Sacré-Cœur de Montréal, Montreal, QC H4J 1C5, Canada.
Géraldine MartensCentre de Recherche, Hôpital du Sacré-Cœur de Montréal, Montreal, QC H4J 1C5, Canada.ORCID 0000-0001-7038-7165
François PrinceCentre de Recherche, Hôpital du Sacré-Cœur de Montréal, Montreal, QC H4J 1C5, Canada.ORCID 0000-0002-1650-7346
Louis De BeaumontCentre de Recherche, Hôpital du Sacré-Cœur de Montréal, Montreal, QC H4J 1C5, Canada.ORCID 0000-0003-4753-3499
Hôpital du Sacré-Cœur de Montréal · CAUniversity of Waterloo · CA

Funding

CSRD VA 1
6 · The paper itself

Abstract

This study aimed to use a data-driven approach to identify individualized speed thresholds to characterize running demands and athlete workload during games and practices in skill and linemen football players. Data were recorded from wearable sensors over 28 sessions from 30 male Canadian varsity football athletes, resulting in a total of 287 performances analyzed, including 137 games and 150 practices, using a global positioning system. Speed zones were identified for each performance by fitting a 5-dimensional Gaussian mixture model (GMM) corresponding to 5 running intensity zones from minimal (zone 1) to maximal (zone 5). Skill players had significantly higher (

Indexed as

AthletesRunningAdultAthletic PerformanceCanadaFootballGeographic Information SystemsHumansMaleSoccerYoung Adultgamegaussian mixture modelphysical performancetrainingwearable sensorsworkload

Identifiers

PMID38676261
PMCPMC11053679
OpenAlexW4395010193

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.