  In the emerging field of esports research, there is an increasing demand for
quantitative results that can be used by players, coaches and analysts to make
decisions and present meaningful commentary for spectators. We present
FirstPersonScience, a software application intended to fill this need in the
esports community by allowing scientists to design carefully controlled
experiments and capture accurate results in the First Person Shooter esports
genre. An experiment designer can control a variety of parameters including
target motion, weapon configuration, 3D scene, frame rate, and latency.
Furthermore, we validate this application through careful end-to-end latency
analysis and provide a case study showing how it can be used to demonstrate the
training effect of one user given repeated task performance.
