What makes an action sequence enjoyable to watch?

Jean-Peïc Chou1, Kristine Zheng2, Junyi Chu2, Maneesh Agrawala1, Judith E. Fan1,2

1Department of Computer Science, Stanford University

2Department of Psychology, Stanford University

Abstract

People often seek out ways to watch others perform complex action sequences (e.g., sports). What makes some sequences more enjoyable to watch than others? We generated 24 video clips of gameplay from a Flappy Bird-style video game. Clips varied in difficulty (how often players succeeded on average) and in moment-to-moment uncertainty (how likely the player was to crash at any given step). Participants (N=864) rated each video on one of three dimensions: how much they enjoyed it, how difficult the level appeared, or how dangerous the player's trajectory appeared. We found that participants preferred videos where the player seemed to be completing more difficult obstacle courses, but dangerousness did not predict enjoyment ratings. These findings show how procedurally generated stimuli can isolate the factors that affect how enjoyable an action sequence is to watch.

Example Video

Map Difficulty Score

Map difficulty estimates how likely simulated agents are to fail on an obstacle course, averaged across agents with different sensorimotor abilities.

Dangerousness Score

Dangerousness estimates players' moment-to-moment susceptibility to imminent failure, with higher scores reflecting smaller margins for error along the trajectory.

Loading dangerousness graph...

Results

Participants showed moderate agreement in enjoyment ratings across the 24 videos, with mean ratings ranging from 51.4 to 70.3. Enjoyment varied smoothly across stimuli rather than splitting into distinct groups, with disagreement expressed mainly as spread around each video's mean.

Figure 2: Distribution of enjoyment ratings

Dangerousness and map difficulty ratings closely tracked model-based estimates from agent simulations (r = 0.79 and r = 0.64). Difficulty judgments were also associated with dangerousness, suggesting that viewers used both obstacle layout and trajectory-level cues when judging how hard a course appeared.

Figure 3: Ratings and model-based estimates

Videos rated as more difficult were also rated as more enjoyable (r = 0.68), whereas dangerousness showed no consistent relationship with enjoyment. Mixed-effects models indicate that difficulty ratings account for much of the explainable variance in enjoyment, while dangerousness does not add significant predictive power.

Figure 4: Enjoyment ratings and model fits