Public bike sharing schemes have spread all over the world in the last few years. For many of them, real-time data is readily available. This site brings this data together to make it readily accessible to the general public, providing real-time information and analysis.

It is hoped that this data will be of use to government and advocacy groups, aiding their efforts to understand the use of bike sharing schemes in our cities and make well-informed decisions about their expansion.

Data Sources & Methodology


The data presented on this site are a result of continuously polling third party real-time data APIs* over time and collecting the result. These APIs are provided by the vendors of bike sharing solutions, and are often used by developers to create useful smartphone apps for finding bikes and slots in realtime.

For each scheme, we collect real-time data once every minute.

*API, Application Programming Interface

Estimating Bikes In Transit

Most of the data on this site - available bikes, slots, station information, etc, is a function of simply polling the real-time data APIs. In the case of overall scheme statistics, it is likewise a simple exercise to determine the total number of bikes, slots, and the percentage of stations that are empty and full etc by totaling the figures for individual stations.

However, the figures for 'Bikes In Transit' are estimated by SchemeStats as follows:

In other words, assuming that there was a few minutes during the last 24 hour period whereby nobody was cycling, and that that period will thus have the maximum number of available bikes, we subtract the currently available bikes in the latest poll from that figure to estimate the bikes in circulation.

This is an imperfect figure and does not account for at least the following unknown variables:

  • Bikes removed from or added back into circulation due to maintenance
  • Bikes taken onto the back of the truck for redistribution


There are at least the following two known limitations to the data provided herein:

  • Data is only as accurate as that collected at polling time (every minute) from the provider
  • Data is only as granular as the polling interval. This means that events occuring between polls (i.e. bikes leaving and returning to stations) may be missed. For example, if two bikes are taken from a station and one returned in the space of a minute, station & scheme histories will simply count this as a decrease of one bike.


SchemeStats was created by Philip Lowney, a software developer from Wexford who lives in Dublin. SchemeStats is the result of an oft-discussed interest in creating an 'analytics for bikes' solution using skills gained in his career.

Feel free to connect via his LinkedIn account.

Cookie Policy

Last Updated: 14 June 2020

Cookie Overview

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