  Recent studies in the science of success have shown that the highest-impact
works of scientists or artists happen randomly and uniformly over the
individual's career. Yet in certain artistic endeavours, such as acting in
films and TV, having a job is perhaps the most important achievement: success
is simply making a living. By analysing a large online database of information
related to films and television we are able to study the success of those
working in the entertainment industry. We first support our initial claim,
finding that two in three actors are "one-hit wonders". In addition we find
that, in agreement with previous works, activity is clustered in hot streaks,
and the percentage of careers where individuals are active is unpredictable.
However, we also discover that productivity in show business has a range of
distinctive features, which are predictable. We unveil the presence of a
rich-get-richer mechanism underlying the assignment of jobs, with a Zipf law
emerging for total productivity. We find that productivity tends to be highest
at the beginning of a career and that the location of the "annus mirabilis" --
the most productive year of an actor -- can indeed be predicted. Based on these
stylized signatures we then develop a machine learning method which predicts,
with up to 85% accuracy, whether the annus mirabilis of an actor has yet passed
or if better days are still to come. Finally, our analysis is performed on both
actors and actresses separately, and we reveal measurable and statistically
significant differences between these two groups across different metrics,
thereby providing compelling evidence of gender bias in show business.
