Enhancing Auto-Generated Baseball Highlights via Win Probability and Bias Injection Method

The automatic generation of sports highlight videos is emerging in both the sports entertainment domain and research community. Earlier methods for generating highlights rely on visual-audio cues or contextual cues, so they may not capture the overall flow of the game well. In this paper, we propose a technique based on Win Probability Added (WPA), an empirical sabermetric baseball statistic, to generate baseball highlights that can better reflect in-game dynamics. Additionally, we introduce methods for generating “biased” highlights toward one team by systematically manipulating WPAs. Through a mixed-method user study with 43 baseball enthusiasts, we found that participants evaluated WPA-based highlights more favorably than existing AI highlights. For (un)favorably biased highlights, the game result (win/loss) was the most dominating factor in user perception, but bias directions and strengths also had nuanced effects on them. Our work contributes to the development of automated tools for generating customized sports highlights.