The modern computational social science incorporates the new approaches for studying of society [1]. Using the so-called digital footprints (recorded data about human actions: e-mail activity, mobile calls, purchases with credit cards etc.), it is possible to quantitatively analyse the individual and collective behavior patterns in order to get some new knowledge about the general `rules' which govern the society. Playing online games offer an example of well-documented collective human activities [2]. Here, we analyse the temporal characteristics of players behaviour in the free massive multiplayer online browser game. Having the data for more than 17,000 players, we build and analyse the distributions of interevent times between their consecutive actions on the amalgamated collective and individual levels. Some features of these distributions reflect the well-known real-life phenomena, such as circadian and weekly cycles or bursts of activity which follows the important events in the world. The peculiarities of different kinds of actions cause the differences between the corresponding interevent times distributions. The distinctions between dynamics of highly active players and whose with just small number of actions are shown as well. [1] Lazer D. et al., Computational Social Science, SCIENCE, 2009, vol. 323, 721-723. [2] Szell M., Thurner S., Measuring social dynamics in a massive multiplayer online game, Social Networks, 2012, vol. 32, 313-329.

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