A New Framework to Estimate Return on Investment for Player Salaries in the National Basketball Association

ABSTRACT An essential component of financial analysis is a comparison of realized returns. These calculations are straightforward when all cash flows have dollar values. Complexities arise if some flows are nonmonetary, however, such as on‐court basketball activities. To our knowledge, this problem remains open. We thus present the first known framework to estimate a return on investment for player salaries in the National Basketball Association (NBA). It is a flexible five‐part procedure that includes a novel player credit estimator, the Wealth Redistribution Merit Share (WRMS). The WRMS is a per‐game wealth redistribution estimator that allocates fractional performance‐based credit to players standardized and centered to uniformity. We show it is asymptotically unbiased to the natural share and simultaneously more robust. The per‐game approach allows for break‐even analysis between high‐performing players with frequent missed games and average‐performing players with consistent availability. The WRMS may be used to allocate revenue from a single game to each of its players. Using a player's salary as an initial investment, this creates a sequence of cash flows that may be evaluated using traditional financial analysis. We illustrate all methods with empirical estimates from the 2022–2023 NBA regular season. All data and replication code are made available.