We begin our women’s edition of the “holistic Kona analysis” with swim trivia. The women’s champion hasn’t come out of the water any better than 4th place in the last five years in Kona (Mirinda Carfrae has been comfortable emerging in 8th place in her last two victories). Conversely, the fastest women’s swimmer hasn’t finished higher than 3rd overall (Leanda Cave, 2011).
This all seems deserving of a big “so what.” After all, Sebastian Kienle is no Aquaman either, being the 9th man onto the bike before charging to the win. However, digging a little deeper into the numbers reveals that the swim is a more potent factor in the women’s race than in the men’s. The standard deviation between swim splits for the ten fastest men in Kona over the last five years is 1:24. For the ten fastest women it’s been 4:24.
In other words, the women spread out significantly more than the men in the water. Kienle had to make up 3 minutes and 24 seconds to take the race leader. Carfrae had to bridge a gap of 5:24. That’s hardly where anyone wants to start their day on the bike. It’s therefore an interesting final point that the correlation factor relating women’s swim splits to overall race time suggests it’s not an important element to the race, but that it does correlate more than 2.5 times more strongly than the men’s swim splits.
Just to illustrate, we represent the trends in men’s and women’s swim splits over time, with the scale equalized on both graphs to show the difference.
What it all boils down to is that the women’s swim is a lot “looser” than the men’s race, and so while it still doesn’t make a giant impact on the final outcome, the potential exists that it could. Whereas the men have more or less equalized the swim stage by settling into a level of consistent but perhaps mediocre technique, the women’s race is more varied and could be described as a less consistent group where the greater variance in training allows those with greater athleticism on the road to make up for a lack of finesse in the water.
If one of those seven women in front of Carfrae could elevate their running game, they could turn a hard day for her into a payday for themselves. Consider how unique and important this is. For years athletes have heard that “every second counts” in the context of aerodynamics on the bike. But for the pro women there is an extraordinary opportunity unavailable to the men to capitalize on minutes gained in the water.
Exactly how to capitalize on those minutes is the $120,000 question. Just as with the men, the bike seems like a good place to start. Bike split correlates more strongly with overall finish time than any other factor. The women’s trend is just slightly weaker than the men, with R and R2 values of 0.91 and 0.83, respectively, compared to the men’s 0.92 and 0.85.
Another fascinating divergence between men and women occurs on the run. The men’s R and R2 values were both 0.73. For the women, they are 0.8 and 0.65. This means that the trend itself is steeper, yet it’s a less reliable predictor of overall time. The graphic below makes it a little more intuitive.
There is a significant concentration of people beneath the red trend line, meaning that the model would have predicted them to take longer to finish the race based on their run split. The likely explanation is that they put serious time on the bike. All the blue dots above the line indicate someone who ran a great marathon but didn’t have quite the swim/bike combination to match.
That brings us to the final analysis of “White’s Ratio” for the women. Remember from our last installment on the men’s race that this is the bike split divided by the run split. For the top men in the last five years it was 1.58 with a high degree of variability. The ratio for the last five men’s champions was 1.59. First, the graph of the women’s correlation.
And our calculated ratio is 1.63. However, for women’s champions, the average ratio is 1.74. That’s a strong indicator that the winners are making their money on the run (a larger ratio means either an unusually slow bike split or unusually fast run), which once again breaks from trends we see in the men’s race (champions and the other top-10 finishers with similar ratios) and also contradicts our statistical data. I have a couple of conspiracy theories hypotheses about the cause.
The first is physiological. Men and women are different. Runners and cyclists are different. It could be that women are somehow more suited to run than bike, compared to males. That would mean a woman who makes the run her specialty discipline has chosen the “superior weapon.”
There could be more limitations for women in terms of muscle mass and ability to produce power on the bike than there are for running endurance. There may also be differences between women and men in terms of how many calories they can put through their system over time.
The second is more about the dynamics of air and race rules. Women have complained for years that age-group males riding up into their ranks plays havoc with their performance. We’ve already discussed how the top men are never truly unattended on the course and the possible influence race officials and media may exert on bike performance. It’s possible that the extra traffic slows all women down, so that top women aren’t able to ride at their full potential. That could be especially true for the champions since they aren’t the first ones onto the bike.
The third could be a broader and more ambiguous issue attached to the general plight of women in sports. In the swim, bike and run we see significantly more variability in the women’s race than in the men’s. The key to the evolution of consistency seems to be money. As pro men acquired bigger and better sponsors over the years, they could spend more time training and recovering than working a second job.
It goes without saying that pro women in all sports make less money than their male counterparts. That applies to triathlon, too. In a sport where there’s not that much money to begin with, it could mean that the unseen difference between first and tenth place in Kona is a massive divide between haves and have-nots.
So once again, questions produce answers that lead to more questions. The biggest revelation here is that the Ironwoman is a distinct and unique race from the Ironman. The swim matters more. The bike/run dynamics are more volatile. And there are potentially a host of factors involved that the men don’t have to deal with. We’ve heard from industry experts and a few professionals, but they’ve all been males up to this point. We invite our women readers to respond and offer any insight or opinion they might have.
If you enjoyed this analysis of Ironman statistics – women, check out Part 1 (overall performance) and Part 2 (swim) and Part 3 (bike) and Part 4 (bike power) and Part 5 (run) and Part 6 (bike aerodynamics) and Part 7 (putting it all together – men).
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