I’m new to this forum. I am an Australian age-group triathlete who has been training and racing for over 30 years. I am also a triathlon coach and sports scientist.
I’m currently doing a PhD in sport science (in triathlon training load) at Deakin University, and I need your help as a participant in my latest research study.
ðŸŠâ€â™‚ï¸ðŸš´â€â™€ï¸ðŸƒâ€â™‚ï¸We’ve recently expanded our study on age-group triathlete training load to a target population of triathletes worldwide.
What’s in it for you?
👉 Do you want to benchmark your training against triathletes worldwide? Our aim is to gain insights from diverse training patterns across age groups and race distance preferences. Additionally, we’re developing an interactive web-based app for comparing training loads across different athlete groups once the research is complete.
👉 What’s involved?
Export and upload 6 months of your TrainingPeaks data (data will be anonymised and is compliant with international research ethics guidelines). Take a 10-minute survey to share your insights.
👉 Why Participate?
Help shape future training strategies for triathletes and coaches worldwide. Be part of groundbreaking research that could revolutionise the world of triathlon.
👉 Scan the QR code in the video (link below) or click this link - deakin.au/3Oef4sF - to learn more and join our global study!
Looks interesting - I’ll participate. A question, though. By choosing the last six months of data, you’ll get the end of the season + off season for northern hemisphere athletes. For southern hemisphere athletes, the data will be summer-fall, the height of competition. Does this potentially cause issues with combining the data? What about a single athlete interested in comparing their training with the ‘rest of the world’? Maybe have everyone upload a year’s worth of data, find the peak training volume month for each and then use that plus 2.5 months on either side of that month?
Looking forward to seeing the results - good luck!
For southern hemisphere athletes, the data will be summer-fall, the height of competition. Does this potentially cause issues with combining the data? What about a single athlete interested in comparing their training with the ‘rest of the world’? Maybe have everyone upload a year’s worth of data, find the peak training volume month for each and then use that plus 2.5 months on either side of that month?
Looking forward to seeing the results - good luck!
These are good questions you probably should factor into your model. There are going to be tons of variables for which you must control, but it is great that you have a great topic to study.
Thank you for your inquiry. We request a dataset from participants spanning six months from the past twelve months of training, with an emphasis on periods characterised by minimal breaks from training. It is acknowledged that athletes, even those situated within the same hemisphere, experience varying seasons based on their targeted races and locations. To accommodate this diversity, we have implemented a matrix allowing participants to designate which months correspond to specific phases of their training regimen (e.g., base, build, off-season, etc.). Our analysis endeavours to incorporate these nuances through the utilisation of diverse statistical methodologies.
We appreciate your kind sentiments regarding the study. Following the conclusion of our research, in addition to developing a complimentary web-based application, we intend to utilise platforms such as this to disseminate information regarding the publication of our study (provided it meets our expectations for publication, which we anticipate with reasonable confidence).
In responding to Giorgitd’s queries regarding the data, we will do as much as we can statistically to factor in the variability of the season phase of the data uploaded. The exciting part of this research is that we are looking at actual training data, not asking athletes to provide us with an overview of their training based on memory.
However, as you point out, this also presents challenges and we will need to take care with our analysis.
Thanks for the compliment, re topic. I hope you and your fellow athletes will take part.
