Question

One minimax theorem not described in the linked file is Yao's application of the Von Neumann result to lower bounds for algorithms. The elegant idea is that in order to prove a lower bound on the behavior of a randomized algorithm over worst-case inputs, it is sufficient to instead analyze the behavior of a fixed algorithm over a carefully chosen distribution of inputs. Thinking of algorithms as columns and inputs as rows, the connection becomes a bit clearer.