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Comparison of player perceptions to mechanical measurements of third generation synthetic turf football surfaces

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posted on 2023-01-17, 08:37 authored by David Cole, Paul FlemingPaul Fleming, Jonathan RobertsJonathan Roberts, David James, Mickael Benetti, Katharina Wistel, Johsan Billingham, Steph ForresterSteph Forrester
Mechanical testing of synthetic turf football surfaces is considered essential to ensure player performance and safety. However, it remains unknown how well the mechanical outputs reflect player perceptions of these surfaces. The first objective of this study was to investigate the agreement between the outputs from the Rotational Traction Tester and the Advanced Artificial Athlete with player perceptions across a range of controlled third generation turf football surfaces. The second objective was to identify the modifications to the Rotational Traction Tester and the Advanced Artificial Athlete configurations and output variables that give the strongest agreement with player perceptions. An indoor test area containing ten third generation turf surfaces with controlled hardness and traction properties was constructed. Each surface was tested using the Advanced Artificial Athlete and Rotational Traction Tester in their current configuration and in several modified configurations aimed at better replicating the player–surface interaction. Using a trained panel paired comparisons technique, 18 University footballers (11 males and 7 females) identified differences in the surfaces based on four sensory attributes Movement Speed, Slip, Leg Shock and Give. Results indicated strong agreement (correlation coefficients between 0.7 and 1.0) across several Rotational Traction Tester and Advanced Artificial Athlete testing configurations and output variables with player perceptions. It is recommended that the current Rotational Traction Tester is improved through added instrumentation to allow surface stiffness to be evaluated (the rate of generation of traction resistance). It is further recommended that the Advanced Artificial Athlete adopts a new algorithm to improve the accuracy of the surface’s Vertical Deformation and Energy Restitution, and the number of drops is reduced from three to one.

Funding

Fédération Internationale de Football Association

History

School

  • Architecture, Building and Civil Engineering
  • Mechanical, Electrical and Manufacturing Engineering

Published in

Sports Engineering

Volume

26

Issue

1

Publisher

Springer Science and Business Media

Version

  • VoR (Version of Record)

Rights holder

© The Author(s)

Publisher statement

This is an Open Access article published by Springer Nature and is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The version of record of this article, first published in Sports Engineering, is available online at Publisher’s website: https://doi.org/10.1007/s12283-022-00398-x

Acceptance date

2022-12-23

Publication date

2023-01-15

Copyright date

2023

ISSN

1369-7072

eISSN

1460-2687

Language

  • en

Depositor

Dr Steph Forrester. Deposit date: 16 January 2023

Article number

5

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