Those from a running background may be aware of the WAVA method of adjusting run times to account for gender and age. This is often used in running clubs to provide a handicapping system so that they can see who did best for their age and gender, levelling the playing field so there is a means of comparing all times equally. It can offer great encouragement to all and a bit of extra friendly rivalry to motivate better performances.
So I thought I’d see what we could do for triathlon. It’s a much trickier problem, with so many variables, and I couldn’t find any published or accepted methods. But I thought it would be fun and interesting to see how we might get some kind of measure, so here goes…
I looked at the results from the ITU World Sprint Triathlon championships in the Gold Coast, taking the best time in each age group to see how they compared. Apart from a couple of anomalies the data was consistent. Age plays its part as you might expect. But up to the age of 40 the performances remain little affected. The age groups 40-49 shows the first signs of the slippery slope,when the mind is still willing but the body starts to say “hold on”. Its downhill from there: yet remarkably steady and consistent between both genders with times only doubled by the time you reach 80. It is also apparent that the best female times are around 10% longer than the equivalent male age group.
I’ve taken the data and have plotted below the correction factor you would have to apply to the times to make them all the same. That is to say make the winning 80 year old equal to the winning 20 year old (essentially what WAVA does for runners). In all cases I’ve based the calculation on a male 25-29, arguably at the top of their game. I’ve had to smooth the plots a little and rounded one or two factors for consistency.
Now I’m not going to claim this is definitive – it’s based on the results from a single event, and a race that permits drafting. However, I thought it would be fun to see how it would influence the club championship results if one used this as handicapping data. I’ve removed names to protect the innocent! (times are in minutes)
As expected the positions for older athletes and females have improved: maybe that helps show to them just how well they are doing for their age and gender, and give some more encouragement to keep up the good work. I’m sorry for the fit young men who find they have fallen down the rankings, you are just going to have to work that bit harder next time out! But it also shows that our first and second placed triathletes are deserved winners regardless of any handicapping system. We all need to commit to our training if we are to challenge them.
As I’ve said earlier you should take these figures with a pinch of salt: they are not definitive. But it could be a bit of fun to use to compare yourself with other club members and get a bit of banter going with a post race beer.