Score contribution per author:
α: calibrated so average coauthorship-adjusted count equals average raw count
We consider a model where two players compete for n items having different common values in a Blotto game. Players must decide how to allocate their common budgets across all n items. The winner of each item is determined stochastically using a lottery mechanism which yields a unique equilibrium in pure strategies. We analyze behavior under two competing payoff objectives found in the Blotto games literature that have not been previously compared: (i) players aim to maximize their total expected payoff and (ii) players maximize the probability of winning a majority value of all n items. We report results from an experiment where subjects face both payoff objectives and we find support for the differing theoretical predictions.