Competitors’ experiences of prior interactions shape patterns of rivalry over time. However, mechanisms that in uence learning from competitive experience remain largely unexamined. We develop a computational model of dyadic rivalry to examine how time delays in competitors’ feedback in uence their learning. Time delays are inevitable because the process of executing competitive moves takes time, and the market’s responses unfold gradually. We analyze how these lags impact learning and, subsequently, rms’ competitive behavior, industry pro ts, and performance heterogeneity. In line with the extant learning literature, our ndings reveal that time delays hinder learning from experience. However, this counterintuitively increases rivals’ pro ts by reducing their investments in costly head-to-head competition. Time delays also engender performance heterogeneity by causing rivals’ paths of competitive behavior to diverge.