Research in developmental psychology has studied careers of prominent artists and scientists for decades, advocating the importance of chance for the successful unfolding of careers in various creative domains [1–4]. In recent years, the availability of big databases on scientific publications [5] and artistic records, from books to movies [6–8], has made it possible to test a number of previously suggested hypotheses on a large scale. For instance, in previous work [9, 10], the analysis of thousands of creative careers has shown that the biggest hit of an individual occurs randomly within an individual’s career, a finding named equal-odds-rule [3] or random impact rule [9]. This rule explains the variability in the occurrence of creative individuals’ best hits. Yet, career hits are not only the results of luck but also of other individual and team properties [11–17]. While previous literature suggests that luck and individual ability are both necessary to excel in art and science [18–21], a quantification of the role of luck across different creative domains is still lacking. In which creative fields are individuals more likely to go from rags to riches and vice-versa? How is the network position of an individual related to the occurrence of a career hit?

In this work, we quantify luck fluctuations in impact across creative careers from film, music, literature, and science, and create a framework to compare the broad observed differences in impact [7, 22]. Do these random fluctuations have the same magnitude across careers? To address this question, we build on the mathematical framework known as the Q-model proposed in Ref. [9] to untangle the impact into two components, one encoding fluctuation that can be interpreted as luck, and another depending only on the individual. We show that this model is consistent with the classical test theory [23], also known as the true score theory [24], stating that the measured value of a certain measurable attribute consists of the sum of its true – error-free – score, and a stochastic error term. We find that the value of such randomness varies depending on the creative fields. By comparing this stochastic term to the typical impact score associated with each artist and scientist, we identify creative domains where the impact of single creative products are the most exposed to luck and fluctuate the most within individual careers. The pronounced role of randomness in achieving success in creative careers is confirmed by the unpredictable relation between the position of an individual in her collaboration network, captured by a number of network measures, and the timing of the hit of her career. To carry out these analyses, we rely on a large-scale data set covering more than four million individuals from c. 1902 up until 2017.

The outline of this paper is the following. First, we test the validity of the requirements of the Q-model proposed in Ref. [9]. Second, we use the Q-model impact decomposition method to factor impact in creative careers. Third, we apply the classical test theory to quantify the role of luck within each field and discuss the observed differences across fields. Finally, we construct the collaboration network within each domain and compare the time of the best hit of creative individuals to the time at which they reach their highest score in network centrality.