Volume 3,Issue 7
The Application of Game Theory in Team Selection for FTC Robotics Competitions
The First Tech Challenge (FTC) adopts an "alliance vs. alliance" format as its core competition system. During the playoff stage, the top 8 teams (a number that may be adjusted to the top 6 depending on the competition specifications) are granted the autonomy to select their allies. However, this process is influenced by information asymmetry during the qualifying rounds, supply-demand mismatches in the mutual selection process, and the one-hour decision-making time constraint, rendering the traditional experience-driven selection model inefficient and risky. This paper utilizes data from the FTC competition Scouting system to deeply adapt classical game theory models to the team selection scenario. Simulation results demonstrate that, compared to traditional methods, game theory-driven selection enhances the average winning rate of alliances and reduces misselection rates, providing a scientific decision-making pathway for FTC team selection and offering practical references for the application of game theory in competitive sports.
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