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What’s Next in Complex Networks? Capturing the Concept of Attacking Play in Invasive Team Sports

Overview of attention for article published in Sports Medicine, September 2017
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (86th percentile)

Mentioned by

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1 news outlet
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10 X users

Citations

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39 Dimensions

Readers on

mendeley
103 Mendeley
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1 CiteULike
Title
What’s Next in Complex Networks? Capturing the Concept of Attacking Play in Invasive Team Sports
Published in
Sports Medicine, September 2017
DOI 10.1007/s40279-017-0786-z
Pubmed ID
Authors

João Ramos, Rui J. Lopes, Duarte Araújo

Abstract

The evolution of performance analysis within sports sciences is tied to technology development and practitioner demands. However, how individual and collective patterns self-organize and interact in invasive team sports remains elusive. Social network analysis has been recently proposed to resolve some aspects of this problem, and has proven successful in capturing collective features resulting from the interactions between team members as well as a powerful communication tool. Despite these advances, some fundamental team sports concepts such as an attacking play have not been properly captured by the more common applications of social network analysis to team sports performance. In this article, we propose a novel approach to team sports performance centered on sport concepts, namely that of an attacking play. Network theory and tools including temporal and bipartite or multilayered networks were used to capture this concept. We put forward eight questions directly related to team performance to discuss how common pitfalls in the use of network tools for capturing sports concepts can be avoided. Some answers are advanced in an attempt to be more precise in the description of team dynamics and to uncover other metrics directly applied to sport concepts, such as the structure and dynamics of attacking plays. Finally, we propose that, at this stage of knowledge, it may be advantageous to build up from fundamental sport concepts toward complex network theory and tools, and not the other way around.

X Demographics

X Demographics

The data shown below were collected from the profiles of 10 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 103 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 103 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 16 16%
Student > Master 12 12%
Researcher 5 5%
Student > Doctoral Student 5 5%
Professor 5 5%
Other 22 21%
Unknown 38 37%
Readers by discipline Count As %
Sports and Recreations 37 36%
Social Sciences 6 6%
Computer Science 5 5%
Psychology 3 3%
Neuroscience 2 2%
Other 11 11%
Unknown 39 38%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 15. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 05 August 2019.
All research outputs
#2,077,585
of 23,002,898 outputs
Outputs from Sports Medicine
#1,373
of 2,711 outputs
Outputs of similar age
#38,894
of 289,792 outputs
Outputs of similar age from Sports Medicine
#30
of 37 outputs
Altmetric has tracked 23,002,898 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 90th percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 2,711 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 51.3. This one is in the 49th percentile – i.e., 49% of its peers scored the same or lower than it.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 289,792 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 86% of its contemporaries.
We're also able to compare this research output to 37 others from the same source and published within six weeks on either side of this one. This one is in the 18th percentile – i.e., 18% of its contemporaries scored the same or lower than it.