  This paper explores multi-entry strategies for betting pools related to
single-elimination tournaments. In such betting pools, participants select
winners of games, and their respective score is a weighted sum of the number of
correct selections. Most betting pools have a top-heavy payoff structure, so
the paper focuses on strategies that maximize the expected score of the
best-performing entry. There is no known closed-formula expression for the
estimation of this metric, so the paper investigates the challenges associated
with the estimation and the optimization of multi-entry solutions. We present
an exact dynamic programming approach for calculating the maximum expected
score of any given fixed solution, which is exponential in the number of
entries. We explore the structural properties of the problem to develop several
solution techniques. In particular, by extracting insights from the solutions
produced by one of our algorithms, we design a simple yet effective
problem-specific heuristic that was the best-performing technique in our
experiments, which were based on real-world data extracted from recent March
Madness tournaments. In particular, our results show that the best 100-entry
solution identified by our heuristic had a 2.2% likelihood of winning a $1
million prize in a real-world betting pool.
