An athletic game scheduling (AGS) problem can be formulated using 0-1 integer program with minor constraints and can be solved partially using traditional operations research methods. However, the constraints that each team and the league requested of the AGS scheduler make the problem no longer practical by typical operations research methods. In most real world problems, many constraints cannot be formulated into mathematical forms. We, therefore, developed heuristic algorithms that can generate reasonably good solutions in a short period. In this research, we propose two algorithms, multi echelon simulated annealing and multi echelon tabu search. In the beginning of the research, our research was concentrated on developing and defining general athletic game scheduling problems that can solve schedules for every athletic league with minor changes. We developed a schedule for year 2000 for the Southern League Baseball, an AA minor league. The procedures of this development process are provided. Finally, an A/B/C/D/E format is defined to determine the different types of AGS problems depending on these characteristics: the number of meetings between two teams, the number of divisions in the league, the availability of fixed time slots, and the number of teams in each division.