  Tasks of different nature and difficulty levels are a part of people's lives.
In this context, there is a scientific interest in the relationship between the
difficulty of the task and the persistence need to accomplish it. Despite the
generality of this problem, some tasks can be simulated in the form of games.
In this way, we employ data from a large online platform, called Steam, to
analyze games and the performance of their players. More specifically, we
investigated persistence in completing tasks based on the proportion of players
who accomplished game achievements. Overall, we present five major findings.
First, the probability distribution for the number of achievements is
log-normal distribution. Second, the distribution of game players also follows
a log-normal. Third, most games require neither a very high degree of
persistence nor a very low one. Fourth, players also prefer games that demand a
certain intermediate persistence. Fifth, the proportion of players as a
function of the number of achievements declines approximately exponentially. As
both the log-normal and the exponential functions are memoryless, they are
mathematical forms that describe random effects arising from the nature of the
system. Therefore our first two findings describe random processes of
fragmenting achievements and players while the last three provide a
quantitative measure of the human preference in the pursuit of challenging,
achievable, and justifiable tasks.
