Automated Training Plan Generation for Athletes

In sports, athletes need detailed and individualised training plans for maintaining
and improving their skills in order to deliver their best performance in competitions.

This presents a considerable amount of effort and overhead for coaches, who not
only have to set realistic objectives, but also formulate extremely detailed training
plans. Automated Planning, which has already been successfully deployed in many
real-world applications such as space exploration, robotics, or manufacturing pro-
cesses, embodies a useful mechanism that can be exploited for generating training
plans for athletes.

In this thesis, we propose the use of automated-planning techniques for generating
individual physical preparation training plans, which consist of exercises the athlete
has to perform during training, given the athlete's current performance, the period
of time, and target performance that should be achieved. Our experimental analysis,
which considers general training of kickboxers, shows that apart of considerable less
planning time, training plans automatically generated by the proposed approach are
more detailed and individualised than plans prepared manually by a coach.