Spor çizelgelemede çekicilik

The attractiveness of a football match or tournament is often explained by the uncertainty of outcome hypothesis (UOH), which suggests that spectator interest increases as the unpredictability of match outcomes increases. In sports leagues, this is heavily influenced by competitive balance, which means how evenly matched the teams are. This thesis explores methods to enhance the attractiveness of football league scheduling by using advanced mathematical models and performance metrics. Traditional round-robin structures and rating methods are analyzed, and two scheduling models are proposed to improve match pairings. The first model introduces a new metric, competitive difference, and incorporates it within a proposed mathematical model aimed at increasing match-level uncertainty and enhancing seasonal unpredictability. Tests conducted on simulated and actual results from the Big Five European leagues showed a 39\% average increase in competitive matches across all leagues and a delayed determination of the champion in four of the five leagues. In addition, we identified best-case and potential worst-case scenarios, highlighting the significant impact of match results on the model's performance. The second model implements a dynamic scheduling approach inspired by online algorithms, adjusting match pairings at specific intervals (periods) based on updated team ratings (e.g., Elo and point rating systems). Results show that dynamic scheduling can provide additional competitive improvements over static schedules under specific arrangements. Together, these models address both practical scheduling challenges and the economic impacts of league structures on spectator engagement.