Using Uber Data To Avoid Sausage Fests

A neuroscientist working for Uber (the GPS-based personal taxi service) has compiled and analyzed its in-house data (your secrets are safe with them, they promise) and uncovered some interesting rider patterns in San Franswishco. Of particular interest to players on the make is the data that shows where in a city the girls are going out at night.

We used Rapleaf’s Name to Gender API to assess the likelihood of a rider’s gender given their name, only accepting a match if the probability was >= 95%. So someone with the name of Leslie remains unclassified because there’s only a 94.1% chance the name is from a female, whereas a boy named Sue would be misclassified as female with a 99.2% probability.

Any deviations above this line means that a neighborhood has more women taking rides into it than what we would expect given the number of men that take rides there. Deviations below that line are places where we see more men than we would expect given the number of women (actually, technically, places where we see fewer women than we would predict given the number of men).

What’s the gist?

– There are 35% more women in the Marina and 47% more women in Pac Heights on weekend nights than expected.

– Conversely, there are 23% more men in SoMa, 16% more in the Castro, and 14% more in the Financial District.

So if you’re looking for a guy, head to SoMa on a Friday night. If you’re looking for a lady, check out the Marina or Pac Heights!

This is the kind of information that is invaluable to PUAs. (Or really to any normal red-blooded man who wants to go to where the girls are, and not to where the sausage fests gather.)

I suppose you’d need some way to get your greasy mitts on Uber user data to geolocate the certified fresh sex ratios, unless an enterprising matrix hacker could design an app that pilfers such data for personal use.

Something like this would only work for a short while, as long as supply is limited. Once enough men get a hold of this dame data you have maybe a few hours before the sweaty hordes descend upon your vaghalla. And then the women leave.

And why do the women leave when too many men show up? Aren’t they there to meet men? That is a seeming paradox of female behavior that I will explain for you:

One, women don’t like to be reminded of their beauty ranking among other women. An audience of a few men zeroing in on the hottest three girls is bearable because it can be rationalized as happenstance. But a small army of men all gawking at the same three hotties is dispiriting to the lesser ladies.

Two, women don’t like to be around men stinking of sex-hungry desperation. They prefer the company, tangential or otherwise, of men who act as if they have their choice of the litter. And venues where the sex ratio is favorable to men tends to prime those men with the right proper attitude of choosiness that women love. A venue teeming with try-hard men ten strong to every one halfway-decent woman has the opposite effect on those women: It repulses them.

Three, women start to feel a little insecure when the testosterone reaches critical mass. Most notably, they begin to fear closing time solicitations from sloppy drunks. If the number of sloppy drunks exceeds the number of sober men and fat cockblock friends, it could be a real challenge to leave the place without a scene erupting.

Four, women subconsciously assess a place full of men as the sort of place that doesn’t attract ALPHA men. After all, an alpha male will know where to go, and where he goes is NOT where every other guy goes. Women intuitively grasp this unspoken rule of nightlife, and will compensate by heading to female-friendly venues that are also hot spots for smart (and efficient) alpha males.

1 comment / Add your comment below

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