Article Text

Download PDFPDF
Improving the reporting of tennis injuries: the use of workload data as the denominator?
  1. Machar Reid1,
  2. Stuart J Cormack2,
  3. Rob Duffield3,
  4. Stephanie Kovalchik1,4,
  5. Miguel Crespo5,
  6. Babette Pluim6,
  7. Danielle T Gescheit1,2
  1. 1 Game Insight Group, Tennis Australia, Melbourne, Victoria, Australia
  2. 2 School of Exercise Science, Australian Catholic University, Sydney, New South Wales, Australia
  3. 3 Sport and Exercise Discipline Group, Faculty of Health, University of Technology Sydney, Ultimo, New South Wales, Australia
  4. 4 Institute of Sport, Exercise and Active Living, Victoria University, Melbourne, Victoria, Australia
  5. 5 Development Department, International Tennis Federation, London, UK
  6. 6 Dutch Tennis Federation, Amsterdam, Netherlands
  1. Correspondence to Dr Machar Reid, Tennis Australia, Melbourne, VIC 3121, Australia; Mreid{at}tennis.com.au

Statistics from Altmetric.com

Request Permissions

If you wish to reuse any or all of this article please use the link below which will take you to the Copyright Clearance Center’s RightsLink service. You will be able to get a quick price and instant permission to reuse the content in many different ways.

Discussion

Historically, epidemiology researchers have identified bespoke units of measurement to express each sport’s injury narrative. In 2009, respected industry professionals suggested that tennis injuries be reported per 1000 player-hours rather than athletic exposures (such as 1000 matches) due to large variations in the time component of such exposures.1 This goes some way to addressing the lack of uniformity in tennis injury data, which McCurdie et al 2 have identified as the most significant challenge to understanding injury in elite tennis. However, given the streams of data now available, it seems timely to revisit whether this recommended choice of exposure remains as pertinent as it once was.

Gescheit et al 3 recently highlighted how the choice of exposure can influence study conclusions. For example, when comparing female muscle injury rates using game exposures (strongly correlated to match duration) versus set exposures at the Australian Open between 2011 and 2016, they found 14% variation in the number of reported injuries …

View Full Text

Footnotes

  • Contributors All authors have contributed substantially to the conception, design and compilation of the work, and agree to be accountable to all aspects of it.

  • Funding This research received no specific grant from any funding agency in the public, commercial or not-for-profit sectors.

  • Competing interests None declared.

  • Provenance and peer review Not commissioned; externally peer reviewed.