Change is Hard: Consistent Player Behavior Across Games with Conflicting Incentives

2026-03-17

AI Summary

This study investigates whether players adapt their behavioral strategies when faced with conflicting incentive structures across games, focusing on League of Legends—which emphasizes mastery—and Teamfight Tactics, which rewards flexibility. Leveraging behavioral logs from 4,830 players who completed at least 50 matches in both games, the research achieves the first cross-game tracking of the same player cohort, effectively mitigating self-selection bias. Through large-scale behavioral analysis and cross-game modeling, the findings reveal a high degree of individual behavioral consistency, suggesting that personal agency is a stronger predictor of behavior across contexts than game-specific structural incentives. These results challenge assumptions rooted in environmental determinism and offer novel insights for behavioral intervention and game design.

Technology Category

• Game Theory and Economic Paradigms: Behavioral Game Theory
• Multiagent Systems: Mechanism Design
• Cognitive Modeling & Cognitive Systems: Adaptive Behavior

Application Category

• User Modeling, Personalization and Recommendation: Studies of user behavior, including longitudinal effects of personalized systems
• Economics, Online Markets and Human Computation: Incentives in network design for Web infrastructures and ecosystems
• Responsible Web: Machine-in-the-loop, human agency and autonomy

Abstract

This paper examines how player flexibility -- a player's willingness to engage in a breadth of options or specialize -- manifests across two gaming environments: League of Legends (League) and Teamfight Tactics (TFT). We analyze the gameplay decisions of 4,830 players who have played at least 50 competitive games in both titles and explore cross-game dynamics of behavior retention and consistency. Our work introduces a novel cross-game analysis that tracks the same players' behavior across two different environments, reducing self-selection bias. Our findings reveal that while games incentivize different behaviors (specialization in League versus flexibility in TFT) for performance-based success, players exhibit consistent behavior across platforms. This study contributes to long-standing debate about agency versus structure, showing individual agency may be more predictive of cross-platform behavior than game-imposed structure in competitive settings. These insights offer implications for game developers, designers and researchers interested in building systems to promote behavior change.

Problem

• player behavior consistency
• cross-game analysis
• behavioral flexibility
• specialization
• conflicting incentives

Innovation

• cross-game analysis
• behavior consistency
• player flexibility
• self-selection bias
• agency vs structure