In this study we identified a low-dimensional representation of control mechanisms in throwing motions from a variety of subjects and target distances. The control representation was identified at the kinematic level in task and joint spaces respectively, and at the muscle activation level usingt he theory of muscle synergies. Representative features of throwing motions in all of these spaces were chosen to be investigated. Features were extracted using factorization and clustering techniques from the muscle data of unexperienced subjects (with different morphologies and physical conditions) during a series of throwing tasks. Two synergy extraction methods were tested to assess their consistency. For the task features, the degrees of freedom (DoF) and the muscles under study, the results can be summarized as: 1) a control representation across subjects consisting of only two synergies at the activation level and of representative features in the task and joint spaces, 2) a reduction of control redundancy (since the number of synergies are less than the number of actions to be controlled), 3) links between the synergies triggering intensity and the throwing distance, and finally 4) consistency of the extraction methods. Such results are useful to better represent mechanisms hidden behind such dynamical motions, and could offer a promising control representation for synthesizing motions with muscle-driven characters.