  In contrast to most scientific disciplines, sports science research has been
characterized by comparatively little effort investment in the development of
relevant phenomenological models. Scarcer yet is the application of said models
in practice. We present a framework which allows resistance training
practitioners to employ a recently proposed neuromuscular model in actual
training program design. The first novelty concerns the monitoring aspect of
coaching. A method for extracting training performance characteristics from
loosely constrained video sequences, effortlessly and with minimal human input,
using computer vision is described. The extracted data is subsequently used to
fit the underlying neuromuscular model. This is achieved by solving an inverse
dynamics problem corresponding to a particular exercise. Lastly, a computer
simulation of hypothetical training bouts, using athlete-specific capability
parameters, is used to predict the effected adaptation and changes in
performance. The software described here allows the practitioner to manipulate
hypothetical training parameters and immediately see their effect on predicted
adaptation for a specific athlete. Thus, this work presents a holistic view of
the monitoring-assessment-adjustment loop.
