Seated-Shot-Put Equipment in Para Athletics—A Review and Presentation of Data From the Tokyo 2020 Paralympic Games

in Adapted Physical Activity Quarterly

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Connor J.M. Holdback School of Mechanical Engineering, University of Adelaide, Adelaide, SA, Australia

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https://orcid.org/0000-0003-2334-0414 *
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Rony Ibrahim Department of Physical Education, Qatar University, Doha, Qatar

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https://orcid.org/0000-0003-2481-9726
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David S. Haydon South Australian Sports Institute, Kidman Park, SA, Australia
Athletics Australia, Adelaide, SA, Australia

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Ross A. Pinder School of Mechanical Engineering, University of Adelaide, Adelaide, SA, Australia
Paralympic Innovation, Paralympics Australia, Kidman Park, SA, Australia

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https://orcid.org/0000-0002-0879-8948
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Paul N. Grimshaw School of Mechanical Engineering, University of Adelaide, Adelaide, SA, Australia
College of Health and Life Sciences, Hamad Bin Khalifa University, Doha, Qatar

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https://orcid.org/0000-0002-3359-1375
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Richard M. Kelso School of Mechanical Engineering, University of Adelaide, Adelaide, SA, Australia

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https://orcid.org/0000-0002-5783-9232
DOI:
https://doi.org/10.1123/apaq.2022-0168
Keywords:
seated throwing; biomechanics; sport engineering; impairment; disability
First Published Online:
01 Jun 2023
In Print:
Ahead of Print
Page Range:
1–18
Restricted access

This research provides a review of seated shot put alongside new data from the Tokyo 2020 Paralympic Games with the aim to understand the latest trends in equipment within a recently established rule set and how key equipment variables may impact performance for athletes in different classifications. First, a review of the literature found that the throwing pole is a key equipment aid that is not well understood, in part due to limitations in testing design. New data from the 2020 Paralympic Games showed inconsistent trends for the use of the throwing pole among athletes, particularly in transitionary classes (F33–34 and F54–55). A two-way analysis of variance found a main effect of classification on performance (p < .001), as well as an interaction effect between pole use and classification on performance (p < .05). Notably, pole users are seen to perform better than non–pole users in Class F32 (p < .05).

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