FirstPersonScience: Quantifying Psychophysics for First Person Shooter Tasks
This provides a tool for esports players, coaches, and analysts to make data-driven decisions, though it is incremental as it applies existing experimental methods to a new domain.
The authors tackled the need for quantitative tools in esports research by developing FirstPersonScience, a software application for designing controlled experiments in First Person Shooter games, and validated it with latency analysis and a case study showing training effects.
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.