When we collect vital data from exercisers by putting wireless sensor nodes to them, the reliability of the wireless data collection is dependent on the position of node on the body of exerciser, therefore, in order to determine the suitable body position, it is essential to evaluate the data collection performances by changing the body positions of nodes in experiments involving human subjects. However, their fair comparison is problematic, because the experiments have no repeatability, that is, we cannot evaluate the performances for multiple body positions in an experiment at the same time. In this paper, we predict the performances by a software network simulator. Using two main functions such as a channel state function and a mobility function, the network simulator can repeatedly generate the same channel and mobility conditions for nodes. Numerical result obtained by the network simulator shows that when collecting vital data from twenty two footballers in a game, among three body position such as waist, forearm and calf, the forearm position gives the highest data collection rate and the predicted data collection rates agree well with the ones obtained by an experiment involving real subjects.