Many activities require people to choose actions and guide movement in a way that takes into account the effects of fatigue on performance. Most people are familiar with the importance of pacing during long-duration, continuous activities, such as running a race or hiking a mountain. Pacing, however, is also important during short-duration tasks that are performed repeatedly, such as when playing a sport. In many sports and real-world activities that involve repeatedly intercepting moving targets, humans and other animals must be selective about which targets to pursue. Chasing targets that are moving too quickly to catch is futile. Even catchable targets may sometimes be best left to get away if, for example, the energetic costs of interception would leave the actor in a state of fatigue and unable to pursue the next target. To investigate how actors take all of these factors into account we conducted two experiments. Both of which instructed subjects to use a steering wheel and foot pedal to catch cylindrical targets in a virtual environment before they escaped into a forest on the edge of an open field. The objective was to catch as many targets as possible in the time allotted for each block. However, sprinting after every target led to poor performance because the farther subjects depressed the foot pedal, the more quickly they lost energy. This reduced the speed at which they were capable of moving and lengthened the time they needed to rest in order to once again catch faster targets. In the first experiment we found that subjects were more likely to pursue targets when their energy level at the beginning of the trial was higher, revealing that they were sensitive to their changing energy levels on a trial by trial basis. The data also suggest that subjects were able to anticipate how their action capabilities diminished when they chased targets and how this would affect their ability to catch the target on the current trial and in the near future. This led us to construct several manipulations of the energy function. These conditions are (1) baseline -- the same as that from experiment 1, (2) no carry over -- where energy does not carry over from one trial to the next, and (3) fixed energy -- where energy stays constant. The analyses for this second experiment are ongoing.