128
Views
1
CrossRef citations to date
0
Altmetric
Research Articles

Conversion index for running on different indoor track and field facility types

&
Pages 375-384 | Received 16 May 2017, Accepted 21 Jun 2017, Published online: 11 Jul 2017
 

Abstract

There are many variations of sizes for indoor running tracks, which have caused difficulty in setting fair and equitable qualifying standards for championship competitions. The aim of this study was to determine event- and gender-specific conversions by indoor track facility type for standard running events ranging from 200 to 5000 m. All performances for running events were obtained from 2010 to 2015 using the Track and Field Results Reporting System. Conversions between track types were determined as factor differences using a mixed modelling approach in SAS for gender and event separately. A total of 325,074 performances (162,176 male, 162,898 female) on 184 flat, 19 banked, 36 oversized and 21 undersized tracks were included in the analysis. All conversion standards with 90% confidence intervals for men and women presented were clear. For all events and both genders, converting from an undersized track to all other track types resulted in faster race times (conversion < 1.0), flat to banked and flat to oversized tracks also resulted in faster race times (conversion < 1.0) and banked and oversized to flat tracks resulted in slower race times (conversion > 1.0). Overall, there is a significant track effect between facility types for both genders and most facility types.

Log in via your institution

Log in to Taylor & Francis Online

PDF download + Online access

  • 48 hours access to article PDF & online version
  • Article PDF can be downloaded
  • Article PDF can be printed
USD 61.00 Add to cart

Issue Purchase

  • 30 days online access to complete issue
  • Article PDFs can be downloaded
  • Article PDFs can be printed
USD 204.00 Add to cart

* Local tax will be added as applicable

Related Research

People also read lists articles that other readers of this article have read.

Recommended articles lists articles that we recommend and is powered by our AI driven recommendation engine.

Cited by lists all citing articles based on Crossref citations.
Articles with the Crossref icon will open in a new tab.