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Toll-Free 866-264-7639

Divvy Safety In 2016: A Look At The Numbers

Chicago Divvy - cropped.jpg

As the deadly year in Chicago cycling continues, an important piece of the puzzle that needs to be considered is the Divvy system. Divvy - and ride-sharing in general - has been pronounced an exceptionally safe form of travel, and it seems that's actually the case. The first fatality on a Divvy bike, and possibly the first fatality in any ride-sharing system in the United States, did not occur until July 2016.

We decided to take a closer look at the numbers to see how many people use Divvy, how they use the system and who is using Divvy bikes so that we could put this fatality in proper context. To do this, we looked at Divvy statistics from 2015 (to get a full year's worth of data).

Divvy By The Numbers

In 2015, Divvy usage looked like this:

  • There were 3,183,438 total rides on Divvy bikes.
  • The average duration of these rides was 17 minutes.
  • The average age of all Divvy riders was 36.*

We also attempted to sort the data by gender, but found that the reported statistics were skewed well beyond a standard level of variance. For example, in the busiest period of the year, the data shows 50 percent of riders as male, 34 percent of riders as unknown and 16 percent of riders as female. Due to these data abnormalities, no concrete conclusions can be drawn (solely based on this data set) about the gender of Divvy riders.

What does this mean?

Thankfully, the data appears to confirm that Divvy is a safe means of transportation. While even one fatality is one too many, in the context of 3 million-plus rides in a year, the system has thus far been quite safe for riders. Despite this, Divvy riders should still exercise extreme caution because Chicago's streets are a dangerous place for cyclists on any type of bike.


*The data set does contain instances of blank age fields, as well as fields where people selected their birth year as being 1900 or a similar outlier year. However, there are not enough of these instances to move the average age more than one or two years (older or younger) when taken as part of a 3 million-plus rider data set.

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