Massive Christmas Day for Boris Bikes

Christmas Day this year recorded far and away the highest ever simultaneous usage of the Barclays Cycle Hire bikes, aka the Boris Bikes, probably meaning it was the biggest number of hires in a single day too. The lack of any Christmas Day tube or bus service in the capital is the obvious reason for the huge usage spike. Previous popular days for the were the four tube strikes in late 2010. Both these events can be seen in the graph above. There is a diamond for each day, showing the difference between the maximum number of bikes available at a point in the day (typically at around 3am), and the minimum available (typically around 4pm for weekends or 9am/6pm for weekdays). Christmas Day was the big jump on the far right of the graph. The jump is much bigger than for Christmas Day 2010, as that day was pretty cold and snowy and only especially hardened tourists would be using the bikes then.

The top days are (measured by maximum closed-system simultaneous usage, i.e. maximum number of Boris Bikes out of the docks and rolling around the streets in a single moment, assuming no removal or addition by the operator that day):

  • Sunday 25 December 2011 – 2065 (Christmas Day – no tubes or buses)
  • Sunday 2 October 2011 – 1795 (Late summer heatwave)
  • Thursday 3 February 2011 – 1791 (?)
  • Tuesday 15 March 2011 – 1649 (Likely false result – mass removal)
  • Saturday 1 October 2011 – 1627 (Late summer heatwave)

Actual total usage on each day is likely to be roughly proportional, and typically ~20 times the above numbers.

Note – please don’t read too much into the lowest usage days that appear on the graph. We’ve had quite a few power problems with our server room this year, and such low days may simply be when we were able to record little if any data. Large-scale bike removals and additions by the operator can also distort the results quite a bit, by perhaps up to 500 bikes a day. Mass additions to the system will depress the true result for that day, while mass removals can falsely inflate the numbers. It’s difficult to spot these, except by looking at the graph for the previous and following days, and comparing the max/min numbers.