Some interesting numbers came out earlier this week around ride hailing apps. As WBUR points out, the top three Massachusetts cities account for 70 percent of all ride hailing trips in the state. 

Still, with more than 1-million trips Newton ranks 5th, right behind Brookline, as a decent market for where trips begin. In all, according to the state’s numbers, 1,051,030 trips began in Newton and 1,073,900 ended here, that accounts for about 1.6 percent of the total state market. Here is now Newton breaks down: 

Number of Origin Trips1,051,030
Number of Destination Trips1,073,900
Origin Trips per Person12.34
Destination Trips per Person12.61

On a per-person basis, Newton’s ranking drops significantly. 

Another figure I found very interesting was the speed of travel. While the average ride in the state lasts for about 15.4 minutes, goes for 4.5 miles with a speed of 17.7 miles per hour, the fastest trips happen in the lower density areas of central and western mass, while the slowest are in Brookline, Cambridge, Somerville, Everett and Boston. You’d expect this given the increased traffic in the denser urban fabric. Those trips are between 14 and 16 mph. 

But Newton’s average speed is 22 mph. This could be because a lot of those trips are on the I-90 or I-95, or it could be that our traffic just isn’t all that bad. Waltham’s average speed was 23 mph, while Watertown’s is a slower 19 mph.

Age plays a significant role in ride hailing use, but density remains key. Watertown, with a lower percentage of 18-24 year-old riders (7 percent compared to 12 percent in Newton) but a higher rate of density (7.74 people per sq mile vs. 4.4 in Newton) has more origin rides per person. 

There’s a lot this doesn’t tell us. For example, it doesn’t tell us whether those rides were supplemental in getting people to and from the T, or if they’re full trips. It also doesn’t tell us how many people in each vehicle (though, the report suggests that a third of rides include more than one passenger) and it doesn’t tell us where in the city these rides are most common. This makes it difficult, for example, to use the information to create or improve bus routes or to put in ride hailing gathering points in high-use areas.

The whole report is worth a read.