The burst of video production appeals for new browsing frameworks. Chiefly in sports, TV companies have years of recorded match archives to exploit and sports fans are looking for replay, summary or collection of events. In this work, we design a new multi-resolution motion feature for video abstraction. This descriptor is based on optical flow singularities tracked along the video. We use these singlets in order to detect zooms, slow-motions and salient moments in soccer games and finally to produce an automatic summarization of a game. We produce a database for soccer video summarization composed of 4 soccer matches from HDTV games for the FIFA world cup 2014 annotated with goals, fouls, corners and salient moments to make a summary. We correctly detect 88.2% of saliant moments using this database. To highlight the generalization of our approach, we test our system on the final game of the handball world championship 2015 without any retraining, refining or adaptation.