While you're at it normalize success at giving birth based on the fraction of men to attempt it.
Why would that matter? They're not running as a group; if you're the fastest then you win. This isn't a probabilistic thing. Lots of slow men crowding the starting line isn't going to impact who finishes first.
I pulled up the most recent Ironman race; there were 5 men for every woman in the competition. So I'm using that as a rule of the thumb. But the same logic applies to any population imbalance at the top of the funnel.
I made no such assumption.
If you pull runner speeds from any distribution, and label 90% of those numbers "male" and 10% "female", 90% of the time the highest speed will be labelled "male".
Even if you are pulling the female runner speeds from a slightly faster distribution, if most of the people running are men then men will still win most of the time.
Failing to normalize by the population sizes at the start of the race is a blatant mathematical error. Until you fix it your argument is flawed and if you don't fix it you're willfully wrong.
You literally wrote "all else equal" in your comment.
> pull runner speeds from any distribution
Not true. If I pick a distribution of elite women and non-athlete men, all of the top finishers will be women. You're assuming speeds are normally distributed; they are not.
Where is this data that you're citing here? It doesn't line up with any data I've seen, nor with my extensive experience in amateur racing. Most races are won by the same small group of elite runners. The size of the field is immaterial as the majority of racers have no chance of winning.
Normalizing for population size might make sense if you actually had to beat everyone independently. Fortunately, you're only racing the person in first so everyone else can be safely ignored.
Put another way, if Michael Phelps is racing he's going to win. You can only win by beating him, the rest of the field doesn't matter.
>>You literally wrote "all else equal" in your comment.
That's different from the assumption that all competitors are equally likely to win.
>You're assuming speeds are normally distributed
No. Any distribution will work.
>Where is this data that you're citing here?
I didn't say anything about data. I said your argument has a blatant mathematical flaw. You said "why would it matter" in response to "if 90% of the competitors [are men]". It absolutely matters. Even if you do turn out to be correct about women being worse at this sport, you are only right in the broken clock sense.
>Put another way, if Michael Phelps is racing he's going to win. You can only win by beating him, the rest of the field doesn't matter.
The people who show up to the race are coming out of some distribution. Michael Phelps isn't showing up to every race. The probability that you win the race comes down to how fast you are vs. the max of n samples from the distribution of runners.
The list of the winner of some annual marathon is a really shitty piece of evidence. Out of all the racers and times taken, it gives us data on exactly one of them. It is especially useless to try and breakdown running ability by demographic because it doesn't even tell us how much data we have on each demographic of interest.
If you don't see why just citing the list of marathon winners fails to reject the hypothesis that women and men are about equal at ultra-marathons, then you don't understand what makes for a good data-supported argument.
If you're a data nerd and a runner armed with this knowledge, it will have occurred to you to wonder if distance (in time) from the winner is correlated with gender and field size. It is not. Thus, you're proposing that we "normalize" for something which is shown to not have an effect on who wins a race.
> at this distance.
~~All the distances in those tables are significantly longer than the 50k this article was about.~~
Edit: Ah, I missed it due to the weird order - but my original point stands, there is no point in ignoring part of someone's comment when trying to rebut them.
Let´s say you had a bunch of computers, and somebody had told you a certain type always ran slowly, so you never used them for anything fast, and even put them on slower connections, because of that. And then one day, you discovered if you connected them up to faster links, they ran faster.
You now have a larger number of faster computers. As with computers, so with society, it´s not a zero sum game.
1. Men generally tend to be faster than women
2. Women generally tend to be better at long-endurance than men
But this is for the average case and not the professional case, where men tend to dominate anyway.
https://blog.mapmyrun.com/are-women-better-than-men-at-long-...
Are there any facts that back up this claim?
50k is barely over marathon distance, and there is a huge difference between woman and men on marathon distance (~2:01 for men vs ~2:15 for woman (10% slower).
I don't know of any longer distance running event in which such a gap doesn't actually increase. That is, the larger the distance, the slower woman actually become relatively to men.
At the far end, for example, for the Spartathlon (https://en.wikipedia.org/wiki/Spartathlon), the fastest men complete the distance in around ~21 hours while the fastest woman takes ~24 hours (13% slower). If you look at the times of the top 3 males and woman of each year, most years top 3 mens finish in ~<24 hours, while women are at ~<31 hours.
It might be interesting to visualize the gap per year vs the temperature. There are some studies about how heat affects the running performance of men and woman in marathon distance races, but not so much for long distance races (https://insights.ovid.com/article/00005768-200703000-00012). IIRC (don't take me for this), heat affects slower runners more independently of sex.
This is 31 miles, which is not much longer than a standard 26.2 mile marathon. Marathons have a lot of competition, so we can see how top athletes compare, and there the record is 2:01 for men vs 2:15 for women. What you're saying is for much longer races.
I believe there’s a wall at about 20 miles, too.
~20 miles is the distance that a "median" person can run before muscle glycogen is depleted and less efficient energy-production mechanisms must take up the slack. The size (and duration) of one's muscle glycogen stores depends on many factors, including the physical size of muscles, efficiency of reintroduction of liver glycogen, training status, running economy, GI effectiveness vs stress, and many others.
Interestingly enough, in longer ultras one gets the chance to conquer the "wall," recover, and then hit it all over again, maybe several times.
https://en.wikipedia.org/wiki/Hour_record
men: 55 km
women: 48 km
People keep repeating this idea throughout thread but as user geargrinder posted earlier, the difference at the ~days level is pretty big, at least in ultra running. For example [1]:
1000 miles Records
Men: Yiannis Kouros - 10 d + 10:30:35
Women: Sandy Barwick - 12 d + 14:38:40
I had also heard - and believed - the idea that women were roughly equal at ultra distances but seeing the tables posted by geargrinder has been a massive revelation to the contrary for me. Is there some other proof that indeed backs the claim that women are roughly equal at large distances, or is this a total urban legend?
[1] https://ultrarunning.com/featured/ultrarunning-magazine-all-...
The people who regularly win RAAM (race across america) are the masochists who are able to combine peak athletic performance and 2.5 hours of sleep a night for a week.
Obviously something else much longer than 1 hour, with as many variables removed would be a better comparison. I don't think a traditional road race would work, since there's too many variables about team/pack strategy, the peloton, breakaways, etc. But possibly a 2 or 3 hour solo time trial on the same course.
https://www.nytimes.com/2018/12/05/sports/courtney-dauwalter...
I would guess there's a sweet spot in distance where the finish times in men and women are closer, but considering testosterone helps with muscle recovery and creating red blood cells, I don't think it would be a multi day distance.