Isn't his algorithm pretty bluntly designed to do this?

So I did my own analysis: I calculated the travel time from every address to every other address in Helsinki around 7:30-8:00am (about 30 billion searches total!). Then I calculated the (weighted) average travel time to anywhere in the city, using amount of jobs in the target area as weight.

That would seemingly bias towards centrally-located addresses (travel time & number of jobs), and his heat maps seem to show this. I believe you could pretty easily duplicate what he's doing with a few dozen randomly sampled routes. Or is there more to it?

My thought was to make the algorithm a bit less blunt by sampling routes that are relevant to your lifestyle.

Just might spice it up if you partition the bucket of all routes into spaces defined by your lifestyle too. It would be interesting to see what the best address in Helsinki is for hipsters. Or families. Or athletes. Or business people...

This is so cool because anyone who has moved has faced this problem.

"My only comment is in how you measure the value of an address." This. Having lived in the center (reddish area) and later also in southern Helsinki (bluish green), I strongly prefer the latter due to it's proximity to the sea and as it's way quieter area without busses, trams or general traffic. And judging by housing prices so do many others who live in the city.

Don't get me wrong. I found the map highly interesting but maybe in determining best places to live it's a bit of a stretch. There might more value here for businesses that aim to be easily reachable.